Climate variability and causes: from the perspective of the Tharaka people of eastern Kenya

NASA Astrophysics Data System (ADS)

Recha, Charles W.; Makokha, George L.; Shisanya, Chris A.

2017-12-01

The study assessed community understanding of climate variability in semi-arid Tharaka sub-county, Kenya. The study used four focus group discussions (FGD) ( N = 48) and a household survey ( N = 326) to obtain information from four agro-ecological zones (AEZs). The results were synthesized and descriptively presented. People in Tharaka sub-county are familiar with the term climate change and associate it with environmental degradation. There are, however, misconceptions and gaps in understanding the causes of climate change. There was a mismatch between community and individual perception of onset and cessation of rainfall—evidence that analysis of the impact of climate change should take into account the scale of interaction. To improve climate change knowledge, there is a need for climate change education by scientific institutions—to provide information on local climatic conditions and global and regional drivers of climate change to local communities.

Thermal barriers constrain microbial elevational range size via climate variability.

PubMed

Wang, Jianjun; Soininen, Janne

2017-08-01

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

Training NOAA Staff on Effective Communication Methods with Local Climate Users

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Mayes, B.

2011-12-01

Since 2002 NOAA National Weather Service (NWS) Climate Services Division (CSD) offered training opportunities to NWS staff. As a result of eight-year-long development of the training program, NWS offers three training courses and about 25 online distance learning modules covering various climate topics: climate data and observations, climate variability and change, NWS national and local climate products, their tools, skill, and interpretation. Leveraging climate information and expertise available at all NOAA line offices and partners allows delivery of the most advanced knowledge and is a very critical aspect of the training program. NWS challenges in providing local climate services includes effective communication techniques on provide highly technical scientific information to local users. Addressing this challenge requires well trained, climate-literate workforce at local level capable of communicating the NOAA climate products and services as well as provide climate-sensitive decision support. Trained NWS climate service personnel use proactive and reactive approaches and professional education methods in communicating climate variability and change information to local users. Both scientifically-unimpaired messages and amiable communication techniques such as story telling approach are important in developing an engaged dialog between the climate service providers and users. Several pilot projects NWS CSD conducted in the past year applied the NWS climate services training program to training events for NOAA technical user groups. The technical user groups included natural resources managers, engineers, hydrologists, and planners for transportation infrastructure. Training of professional user groups required tailoring the instructions to the potential applications of each group of users. Training technical user identified the following critical issues: (1) Knowledge of target audience expectations, initial knowledge status, and potential use of climate information; (2) Leveraging partnership with climate services providers; and, (3) Applying 3H training approach, where the first H stands for Head (trusted science), the second H stands for Heart (make it easy), and the third H for Hand (support with applications).

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.

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.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2018-06-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Local-scale changes in mean and heavy precipitation in Western Europe, climate change or internal variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma E.; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart J. J. M.

2017-09-01

High-resolution climate information provided by e.g. regional climate models (RCMs) is valuable for exploring the changing weather under global warming, and assessing the local impact of climate change. While there is generally more confidence in the representativeness of simulated processes at higher resolutions, internal variability of the climate system—`noise', intrinsic to the chaotic nature of atmospheric and oceanic processes—is larger at smaller spatial scales as well, limiting the predictability of the climate signal. To quantify the internal variability and robustly estimate the climate signal, large initial-condition ensembles of climate simulations conducted with a single model provide essential information. We analyze a regional downscaling of a 16-member initial-condition ensemble over western Europe and the Alps at 0.11° resolution, similar to the highest resolution EURO-CORDEX simulations. We examine the strength of the forced climate response (signal) in mean and extreme daily precipitation with respect to noise due to internal variability, and find robust small-scale geographical features in the forced response, indicating regional differences in changes in the probability of events. However, individual ensemble members provide only limited information on the forced climate response, even for high levels of global warming. Although the results are based on a single RCM-GCM chain, we believe that they have general value in providing insight in the fraction of the uncertainty in high-resolution climate information that is irreducible, and can assist in the correct interpretation of fine-scale information in multi-model ensembles in terms of a forced response and noise due to internal variability.

Associations between malaria and local and global climate variability in five regions in Papua New Guinea.

PubMed

Imai, Chisato; Cheong, Hae-Kwan; Kim, Ho; Honda, Yasushi; Eum, Jin-Hee; Kim, Clara T; Kim, Jin Seob; Kim, Yoonhee; Behera, Swadhin K; Hassan, Mohd Nasir; Nealon, Joshua; Chung, Hyenmi; Hashizume, Masahiro

2016-01-01

Malaria is a significant public health issue in Papua New Guinea (PNG) as the burden is among the highest in Asia and the Pacific region. Though PNG's vulnerability to climate change and sensitivity of malaria mosquitoes to weather are well-documented, there are few in-depth epidemiological studies conducted on the potential impacts of climate on malaria incidence in the country. This study explored what and how local weather and global climate variability impact on malaria incidence in five regions of PNG. Time series methods were applied to evaluate the associations of malaria incidence with weather and climate factors, respectively. Local weather factors including precipitation and temperature and global climate phenomena such as El Niño-Southern Oscillation (ENSO), the ENSO Modoki, the Southern Annular Mode, and the Indian Ocean Dipole were considered in analyses. The results showed that malaria incidence was associated with local weather factors in most regions but at the different lag times and in directions. Meanwhile, there were trends in associations with global climate factors by geographical locations of study sites. Overall heterogeneous associations suggest the importance of location-specific approaches in PNG not only for further investigations but also public health interventions in repose to the potential impacts arising from climate change.

Modeling Source Water TOC Using Hydroclimate Variables and Local Polynomial Regression.

PubMed

Samson, Carleigh C; Rajagopalan, Balaji; Summers, R Scott

2016-04-19

To control disinfection byproduct (DBP) formation in drinking water, an understanding of the source water total organic carbon (TOC) concentration variability can be critical. Previously, TOC concentrations in water treatment plant source waters have been modeled using streamflow data. However, the lack of streamflow data or unimpaired flow scenarios makes it difficult to model TOC. In addition, TOC variability under climate change further exacerbates the problem. Here we proposed a modeling approach based on local polynomial regression that uses climate, e.g. temperature, and land surface, e.g., soil moisture, variables as predictors of TOC concentration, obviating the need for streamflow. The local polynomial approach has the ability to capture non-Gaussian and nonlinear features that might be present in the relationships. The utility of the methodology is demonstrated using source water quality and climate data in three case study locations with surface source waters including river and reservoir sources. The models show good predictive skill in general at these locations, with lower skills at locations with the most anthropogenic influences in their streams. Source water TOC predictive models can provide water treatment utilities important information for making treatment decisions for DBP regulation compliance under future climate scenarios.

Extreme Events in China under Climate Change: Uncertainty and related impacts (CSSP-FOREX)

NASA Astrophysics Data System (ADS)

Leckebusch, Gregor C.; Befort, Daniel J.; Hodges, Kevin I.

2016-04-01

Suitable adaptation strategies or the timely initiation of related mitigation efforts in East Asia will strongly depend on robust and comprehensive information about future near-term as well as long-term potential changes in the climate system. Therefore, understanding the driving mechanisms associated with the East Asian climate is of major importance. The FOREX project (Fostering Regional Decision Making by the Assessment of Uncertainties of Future Regional Extremes and their Linkage to Global Climate System Variability for China and East Asia) focuses on the investigation of extreme wind and rainfall related events over Eastern Asia and their possible future changes. Here, analyses focus on the link between local extreme events and their driving weather systems. This includes the coupling between local rainfall extremes and tropical cyclones, the Meiyu frontal system, extra-tropical teleconnections and monsoonal activity. Furthermore, the relation between these driving weather systems and large-scale variability modes, e.g. NAO, PDO, ENSO is analysed. Thus, beside analysing future changes of local extreme events, the temporal variability of their driving weather systems and related large-scale variability modes will be assessed in current CMIP5 global model simulations to obtain more robust results. Beyond an overview of FOREX itself, first results regarding the link between local extremes and their steering weather systems based on observational and reanalysis data are shown. Special focus is laid on the contribution of monsoonal activity, tropical cyclones and the Meiyu frontal system on the inter-annual variability of the East Asian summer rainfall.

Changing precipitation in western Europe, climate change or natural variability?

NASA Astrophysics Data System (ADS)

Aalbers, Emma; Lenderink, Geert; van Meijgaard, Erik; van den Hurk, Bart

2017-04-01

Multi-model RCM-GCM ensembles provide high resolution climate projections, valuable for among others climate impact assessment studies. While the application of multiple models (both GCMs and RCMs) provides a certain robustness with respect to model uncertainty, the interpretation of differences between ensemble members - the combined result of model uncertainty and natural variability of the climate system - is not straightforward. Natural variability is intrinsic to the climate system, and a potentially large source of uncertainty in climate change projections, especially for projections on the local to regional scale. To quantify the natural variability and get a robust estimate of the forced climate change response (given a certain model and forcing scenario), large ensembles of climate model simulations of the same model provide essential information. While for global climate models (GCMs) a number of such large single model ensembles exists and have been analyzed, for regional climate models (RCMs) the number and size of single model ensembles is limited, and the predictability of the forced climate response at the local to regional scale is still rather uncertain. We present a regional downscaling of a 16-member single model ensemble over western Europe and the Alps at a resolution of 0.11 degrees (˜12km), similar to the highest resolution EURO-CORDEX simulations. This 16-member ensemble was generated by the GCM EC-EARTH, which was downscaled with the RCM RACMO for the period 1951-2100. This single model ensemble has been investigated in terms of the ensemble mean response (our estimate of the forced climate response), as well as the difference between the ensemble members, which measures natural variability. We focus on the response in seasonal mean and extreme precipitation (seasonal maxima and extremes with a return period up to 20 years) for the near to far future. For most precipitation indices we can reliably determine the climate change signal, given the applied model chain and forcing scenario. However, the analysis also shows how limited the information in single ensemble members is on the local scale forced climate response, even for high levels of global warming when the forced response has emerged from natural variability. Analysis and application of multi-model ensembles like EURO-CORDEX should go hand-in-hand with single model ensembles, like the one presented here, to be able to correctly interpret the fine-scale information in terms of a forced signal and random noise due to natural variability.

Vulnerability to climate change and adaptation strategies of local communities in Malawi: experiences of women fish-processing groups in the Lake Chilwa Basin

NASA Astrophysics Data System (ADS)

Jørstad, Hanne; Webersik, Christian

2016-12-01

In recent years, research on climate change and human security has received much attention among policy makers and academia alike. Communities in the Global South that rely on an intact resource base and struggle with poverty, existing inequalities and historical injustices will especially be affected by predicted changes in temperature and precipitation. The objective of this article is to better understand under what conditions local communities can adapt to anticipated impacts of climate change. The empirical part of the paper answers the question as to what extent local women engaged in fish processing in the Chilwa Basin in Malawi have experienced climate change and how they are affected by it. The article assesses an adaptation project designed to make those women more resilient to a warmer and more variable climate. The research results show that marketing and improving fish processing as strategies to adapt to climate change have their limitations. The study concludes that livelihood diversification can be a more effective strategy for Malawian women to adapt to a more variable and unpredictable climate rather than exclusively relying on a resource base that is threatened by climate change.

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.

How resilient are ecosystems in adapting to climate variability

NASA Astrophysics Data System (ADS)

Savenije, Hubert H. G.

2015-04-01

The conclusion often drawn in the media is that ecosystems may perish as a result of climate change. Although climatic trends may indeed lead to shifts in ecosystem composition, the challenge to adjust to climatic variability - even if there is no trend - is larger, particularly in semi-arid or topical climates where climatic variability is large compared to temperate climates. How do ecosystems buffer for climatic variability? The most powerful mechanism is to invest in root zone storage capacity, so as to guarantee access to water and nutrients during period of drought. This investment comes at a cost of having less energy available to invest in growth or formation of fruits. Ecosystems are expected to create sufficient buffer to overcome critical periods of drought, but not more than is necessary to survive or reproduce. Based on this concept, a methodology has been developed to estimate ecosystem root zone storage capacity at local, regional and global scale. These estimates correspond well with estimates made by combining soil and ecosystem information, but are more accurate and more detailed. The methodology shows that ecosystems have intrinsic capacity to adjust to climatic variability and hence have a high resilience to both climatic variability and climatic trends.

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.

Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change

PubMed Central

Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E.; Safeeq, Mohammad; Skaugset, Arne E.

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change. PMID:26295478

Local variability mediates vulnerability of trout populations to land use and climate change

USGS Publications Warehouse

Penaluna, Brooke E.; Dunham, Jason B.; Railsback, Steve F.; Arismendi, Ivan; Johnson, Sherri L.; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E.

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007–2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

Local Variability Mediates Vulnerability of Trout Populations to Land Use and Climate Change.

PubMed

Penaluna, Brooke E; Dunham, Jason B; Railsback, Steve F; Arismendi, Ivan; Johnson, Sherri L; Bilby, Robert E; Safeeq, Mohammad; Skaugset, Arne E

2015-01-01

Land use and climate change occur simultaneously around the globe. Fully understanding their separate and combined effects requires a mechanistic understanding at the local scale where their effects are ultimately realized. Here we applied an individual-based model of fish population dynamics to evaluate the role of local stream variability in modifying responses of Coastal Cutthroat Trout (Oncorhynchus clarkii clarkii) to scenarios simulating identical changes in temperature and stream flows linked to forest harvest, climate change, and their combined effects over six decades. We parameterized the model for four neighboring streams located in a forested headwater catchment in northwestern Oregon, USA with multi-year, daily measurements of stream temperature, flow, and turbidity (2007-2011), and field measurements of both instream habitat structure and three years of annual trout population estimates. Model simulations revealed that variability in habitat conditions among streams (depth, available habitat) mediated the effects of forest harvest and climate change. Net effects for most simulated trout responses were different from or less than the sum of their separate scenarios. In some cases, forest harvest countered the effects of climate change through increased summer flow. Climate change most strongly influenced trout (earlier fry emergence, reductions in biomass of older trout, increased biomass of young-of-year), but these changes did not consistently translate into reductions in biomass over time. Forest harvest, in contrast, produced fewer and less consistent responses in trout. Earlier fry emergence driven by climate change was the most consistent simulated response, whereas survival, growth, and biomass were inconsistent. Overall our findings indicate a host of local processes can strongly influence how populations respond to broad scale effects of land use and climate change.

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.

Modeling the effects of anthropogenic habitat change on savanna snake invasions into African rainforest.

PubMed

Freedman, Adam H; Buermann, Wolfgang; Lebreton, Matthew; Chirio, Laurent; Smith, Thomas B

2009-02-01

We used a species-distribution modeling approach, ground-based climate data sets, and newly available remote-sensing data on vegetation from the MODIS and Quick Scatterometer sensors to investigate the combined effects of human-caused habitat alterations and climate on potential invasions of rainforest by 3 savanna snake species in Cameroon, Central Africa: the night adder (Causus maculatus), olympic lined snake (Dromophis lineatus), and African house snake (Lamprophis fuliginosus). Models with contemporary climate variables and localities from native savanna habitats showed that the current climate in undisturbed rainforest was unsuitable for any of the snake species due to high precipitation. Limited availability of thermally suitable nest sites and mismatches between important life-history events and prey availability are a likely explanation for the predicted exclusion from undisturbed rainforest. Models with only MODIS-derived vegetation variables and savanna localities predicted invasion in disturbed areas within the rainforest zone, which suggests that human removal of forest cover creates suitable microhabitats that facilitate invasions into rainforest. Models with a combination of contemporary climate, MODIS- and Quick Scatterometer-derived vegetation variables, and forest and savanna localities predicted extensive invasion into rainforest caused by rainforest loss. In contrast, a projection of the present-day species-climate envelope on future climate suggested a reduction in invasion potential within the rainforest zone as a consequence of predicted increases in precipitation. These results emphasize that the combined responses of deforestation and climate change will likely be complex in tropical rainforest systems.

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.

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 Pacific Northwest's Climate Impacts Group: Climate Science in the Public Interest

NASA Astrophysics Data System (ADS)

Mantua, N.; Snover, A.

2006-12-01

Since its inception in 1995, the University of Washington's Climate Impacts Group (CIG) (funded under NOAA's Regional Integrated Science and Assessments (RISA) Program) has become the leader in exploring the impacts of climate variability and climate change on natural and human systems in the U.S. Pacific Northwest (PNW), specifically climate impacts on water, forest, fish and coastal resource systems. The CIG's research provides PNW planners, decision makers, resource managers, local media, and the general public with valuable knowledge of ways in which the region's key natural resources are vulnerable to changes in climate, and how this vulnerability can be reduced. The CIG engages in climate science in the public interest, conducting original research on the causes and consequences of climate variability and change for the PNW and developing forecasts and decision support tools to support the use of this information in federal, state, local, tribal, and private sector resource management decisions. The CIG's focus on the intersection of climate science and public policy has placed the CIG nationally at the forefront of regional climate impacts assessment and integrated analysis.

NOAA Climate Information and Tools for Decision Support Services

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Higgins, W.; Strager, C.; Horsfall, F. M.

2013-12-01

NOAA is an active participant of the Global Framework for Climate Services (GFCS) contributing data, information, analytical capabilities, forecasts, and decision support services to the Climate Services Partnership (CSP). These contributions emerge from NOAA's own climate services, which have evolved to respond to the urgent and growing need for reliable, trusted, transparent, and timely climate information across all sectors of the U.S. economy. Climate services not only enhance development opportunities in many regions, but also reduce vulnerability to climate change around the world. The NOAA contribution lies within the NOAA Climate Goal mission, which is focusing its efforts on four key climate priority areas: water, extremes, coastal inundation, and marine ecosystems. In order to make progress in these areas, NOAA is exploiting its fundamental capabilities, including foundational research to advance understanding of the Earth system, observations to preserve and build the climate data record and monitor changes in climate conditions, climate models to predict and project future climate across space and time scales, and the development and delivery of decision support services focused on risk management. NOAA's National Weather Services (NWS) is moving toward provision of Decision Support Services (DSS) as a part of the Roadmap on the way to achieving a Weather Ready National (WRN) strategy. Both short-term and long-term weather, water, and climate information are critical for DSS and emergency services and have been integrated into NWS in the form of pilot projects run by National and Regional Operations Centers (NOC and ROCs respectively) as well as several local offices. Local offices with pilot projects have been focusing their efforts on provision of timely and actionable guidance for specific tasks such as DSS in support of Coastal Environments and Integrated Environmental Studies. Climate information in DSS extends the concept of climate services to provision of information that will help guide long-term preparedness for severe weather events and extreme conditions as well as climate variability and change GFCS recently summarized examples of existing initiatives to advance provision of climate services in the 2012 publication Climate ExChange. In this publication, NWS introduced the new Local Climate Analysis Tool (LCAT), a tool that is used to conduct local climate studies that are needed to create efficient and reliable guidance for DSS. LCAT allows for analyzing trends in local climate variables and identifying local impacts of climate variability (e.g., ENSO) on weather and water conditions. In addition to LCAT, NWS, working in partnership with the North East Regional Climate center, released xmACIS version 2, a climate data mining tool, for NWS field operations. During this talk we will demonstrate LCAT and xmACIS as well as outline several examples of their application to DSS and its potential use for achieving GFCS goals. The examples include LCAT-based temperature analysis for energy decisions, guidance on weather and water events leading to increased algal blooms and red tide months in advance, local climate sensitivities to droughts, probabilities of hot/cold conditions and their potential impacts on agriculture and fish kills or fish stress.

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

Effects of local and regional climatic fluctuations on dengue outbreaks in southern Taiwan

PubMed Central

Chaves, Luis Fernando; Chen, Po-Jiang

2017-01-01

Background Southern Taiwan has been a hotspot for dengue fever transmission since 1998. During 2014 and 2015, Taiwan experienced unprecedented dengue outbreaks and the causes are poorly understood. This study aims to investigate the influence of regional and local climate conditions on the incidence of dengue fever in Taiwan, as well as to develop a climate-based model for future forecasting. Methodology/Principle findings Historical time-series data on dengue outbreaks in southern Taiwan from 1998 to 2015 were investigated. Local climate variables were analyzed using a distributed lag non-linear model (DLNM), and the model of best fit was used to predict dengue incidence between 2013 and 2015. The cross-wavelet coherence approach was used to evaluate the regional El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) effects on dengue incidence and local climate variables. The DLNM results highlighted the important non-linear and lag effects of minimum temperature and precipitation. Minimum temperature above 23°C or below 17°C can increase dengue incidence rate with lag effects of 10 to 15 weeks. Moderate to high precipitation can increase dengue incidence rates with a lag of 10 or 20 weeks. The model of best fit successfully predicted dengue transmission between 2013 and 2015. The prediction accuracy ranged from 0.7 to 0.9, depending on the number of weeks ahead of the prediction. ENSO and IOD were associated with nonstationary inter-annual patterns of dengue transmission. IOD had a greater impact on the seasonality of local climate conditions. Conclusions/Significance Our findings suggest that dengue transmission can be affected by regional and local climatic fluctuations in southern Taiwan. The climate-based model developed in this study can provide important information for dengue early warning systems in Taiwan. Local climate conditions might be influenced by ENSO and IOD, to result in unusual dengue outbreaks. PMID:28575035

Effects of local and regional climatic fluctuations on dengue outbreaks in southern Taiwan.

PubMed

Chuang, Ting-Wu; Chaves, Luis Fernando; Chen, Po-Jiang

2017-01-01

Southern Taiwan has been a hotspot for dengue fever transmission since 1998. During 2014 and 2015, Taiwan experienced unprecedented dengue outbreaks and the causes are poorly understood. This study aims to investigate the influence of regional and local climate conditions on the incidence of dengue fever in Taiwan, as well as to develop a climate-based model for future forecasting. Historical time-series data on dengue outbreaks in southern Taiwan from 1998 to 2015 were investigated. Local climate variables were analyzed using a distributed lag non-linear model (DLNM), and the model of best fit was used to predict dengue incidence between 2013 and 2015. The cross-wavelet coherence approach was used to evaluate the regional El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) effects on dengue incidence and local climate variables. The DLNM results highlighted the important non-linear and lag effects of minimum temperature and precipitation. Minimum temperature above 23°C or below 17°C can increase dengue incidence rate with lag effects of 10 to 15 weeks. Moderate to high precipitation can increase dengue incidence rates with a lag of 10 or 20 weeks. The model of best fit successfully predicted dengue transmission between 2013 and 2015. The prediction accuracy ranged from 0.7 to 0.9, depending on the number of weeks ahead of the prediction. ENSO and IOD were associated with nonstationary inter-annual patterns of dengue transmission. IOD had a greater impact on the seasonality of local climate conditions. Our findings suggest that dengue transmission can be affected by regional and local climatic fluctuations in southern Taiwan. The climate-based model developed in this study can provide important information for dengue early warning systems in Taiwan. Local climate conditions might be influenced by ENSO and IOD, to result in unusual dengue outbreaks.

Climatic extremes improve predictions of spatial patterns of tree species

USGS Publications Warehouse

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

2009-01-01

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

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

PubMed

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

2010-04-01

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

Impacts of El Niño Southern Oscillation and Indian Ocean Dipole on dengue incidence in Bangladesh

PubMed Central

Banu, Shahera; Guo, Yuming; Hu, Wenbiao; Dale, Pat; Mackenzie, John S.; Mengersen, Kerrie; Tong, Shilu

2015-01-01

Dengue dynamics are driven by complex interactions between hosts, vectors and viruses that are influenced by environmental and climatic factors. Several studies examined the role of El Niño Southern Oscillation (ENSO) in dengue incidence. However, the role of Indian Ocean Dipole (IOD), a coupled ocean atmosphere phenomenon in the Indian Ocean, which controls the summer monsoon rainfall in the Indian region, remains unexplored. Here, we examined the effects of ENSO and IOD on dengue incidence in Bangladesh. According to the wavelet coherence analysis, there was a very weak association between ENSO, IOD and dengue incidence, but a highly significant coherence between dengue incidence and local climate variables (temperature and rainfall). However, a distributed lag nonlinear model (DLNM) revealed that the association between dengue incidence and ENSO or IOD were comparatively stronger after adjustment for local climate variables, seasonality and trend. The estimated effects were nonlinear for both ENSO and IOD with higher relative risks at higher ENSO and IOD. The weak association between ENSO, IOD and dengue incidence might be driven by the stronger effects of local climate variables such as temperature and rainfall. Further research is required to disentangle these effects. PMID:26537857

Impacts of El Niño Southern Oscillation and Indian Ocean Dipole on dengue incidence in Bangladesh.

PubMed

Banu, Shahera; Guo, Yuming; Hu, Wenbiao; Dale, Pat; Mackenzie, John S; Mengersen, Kerrie; Tong, Shilu

2015-11-05

Dengue dynamics are driven by complex interactions between hosts, vectors and viruses that are influenced by environmental and climatic factors. Several studies examined the role of El Niño Southern Oscillation (ENSO) in dengue incidence. However, the role of Indian Ocean Dipole (IOD), a coupled ocean atmosphere phenomenon in the Indian Ocean, which controls the summer monsoon rainfall in the Indian region, remains unexplored. Here, we examined the effects of ENSO and IOD on dengue incidence in Bangladesh. According to the wavelet coherence analysis, there was a very weak association between ENSO, IOD and dengue incidence, but a highly significant coherence between dengue incidence and local climate variables (temperature and rainfall). However, a distributed lag nonlinear model (DLNM) revealed that the association between dengue incidence and ENSO or IOD were comparatively stronger after adjustment for local climate variables, seasonality and trend. The estimated effects were nonlinear for both ENSO and IOD with higher relative risks at higher ENSO and IOD. The weak association between ENSO, IOD and dengue incidence might be driven by the stronger effects of local climate variables such as temperature and rainfall. Further research is required to disentangle these effects.

The Portuguese Climate Portal

NASA Astrophysics Data System (ADS)

Gomes, Sandra; Deus, Ricardo; Nogueira, Miguel; Viterbo, Pedro; Miranda, Miguel; Antunes, Sílvia; Silva, Alvaro; Miranda, Pedro

2016-04-01

The Portuguese Local Warming Website (http://portaldoclima.pt) has been developed in order to support the society in Portugal in preparing for the adaptation to the ongoing and future effects of climate change. The climate portal provides systematic and easy access to authoritative scientific data ready to be used by a vast and diverse user community from different public and private sectors, key players and decision makers, but also to high school students, contributing to the increase in knowledge and awareness on climate change topics. A comprehensive set of regional climate variables and indicators are computed, explained and graphically presented. Variables and indicators were built in agreement with identified needs after consultation of the relevant social partners from different sectors, including agriculture, water resources, health, environment and energy and also in direct cooperation with the Portuguese National Strategy for Climate Change Adaptation (ENAAC) group. The visual interface allows the user to dynamically interact, explore, quickly analyze and compare, but also to download and import the data and graphics. The climate variables and indicators are computed from state-of-the-art regional climate model (RCM) simulations (e.g., CORDEX project), at high space-temporal detail, allowing to push the limits of the projections down to local administrative regions (NUTS3) and monthly or seasonal periods, promoting local adaptation strategies. The portal provides both historical data (observed and modelled for the 1971-2000 period) and future climate projections for different scenarios (modelled for the 2011-2100 period). A large effort was undertaken in order to quantify the impacts of the risk of extreme events, such as heavy rain and flooding, droughts, heat and cold waves, and fires. Furthermore the different climate scenarios and the ensemble of RCM models, with high temporal (daily) and spatial (~11km) detail, is taken advantage in order to quantify a plausible evolution of climate impacts and its uncertainties. Clear information on the data value and limitations is also provided. The portal is expected to become a reference tool for evaluation of impacts and vulnerabilities due to climate change, increased awareness and promotion of local adaptation and sustainable development in Portugal. The Portuguese Local Warming Website is part of the ADAPT programme, and is co-funded by the EEA financial mechanism and the Portuguese Carbon Fund.

THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE

PubMed Central

Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan

2015-01-01

Background: The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran’s universities. Methods: This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran’s public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. Results: of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran’s libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Conclusions: Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries. PMID:26622203

THE REGRESSION MODEL OF IRAN LIBRARIES ORGANIZATIONAL CLIMATE.

PubMed

Jahani, Mohammad Ali; Yaminfirooz, Mousa; Siamian, Hasan

2015-10-01

The purpose of this study was to drawing a regression model of organizational climate of central libraries of Iran's universities. This study is an applied research. The statistical population of this study consisted of 96 employees of the central libraries of Iran's public universities selected among the 117 universities affiliated to the Ministry of Health by Stratified Sampling method (510 people). Climate Qual localized questionnaire was used as research tools. For predicting the organizational climate pattern of the libraries is used from the multivariate linear regression and track diagram. of the 9 variables affecting organizational climate, 5 variables of innovation, teamwork, customer service, psychological safety and deep diversity play a major role in prediction of the organizational climate of Iran's libraries. The results also indicate that each of these variables with different coefficient have the power to predict organizational climate but the climate score of psychological safety (0.94) plays a very crucial role in predicting the organizational climate. Track diagram showed that five variables of teamwork, customer service, psychological safety, deep diversity and innovation directly effects on the organizational climate variable that contribution of the team work from this influence is more than any other variables. Of the indicator of the organizational climate of climateQual, the contribution of the team work from this influence is more than any other variables that reinforcement of teamwork in academic libraries can be more effective in improving the organizational climate of this type libraries.

Climate, Birth Weight, and Agricultural Livelihoods in Kenya and Mali

PubMed Central

Grace, Kathryn; Nawrotzki, Raphael J.

2018-01-01

Objectives. To examine an association between climate variability and birth weight in Mali and Kenya in relation to the local agricultural specialization. Methods. We combined health and sociodemographic data from the Demographic Health Surveys for Kenya (2008 and 2014) and Mali (2006 and 2012) with detailed data on precipitation, temperature, and vegetation. We analyzed the association between climate variability and birth weight by using multilevel regression models for the most common agricultural specializations: food cropping, cash cropping, and pastoralism. Results. There are differences in sensitivity to climate among different agricultural communities. An additional 100 millimeters of rainfall during the 12-month period before birth was associated with a 47-gram (P = .001) and 89-gram (P = .10) increase in birth weight for food croppers in Kenya and Mali, respectively. Every additional hot month in food-cropping communities in Kenya was associated with a 71-gram decrease in birth weight (P = .030), likely because of food croppers’ limited use of modern agricultural techniques. Overall, cash croppers are least sensitive to climate variability in both countries. Conclusions. Effective climate change adaptation strategies are essential for protecting and improving health outcomes and should be tailored to local households’ livelihood strategies. PMID:29072943

Climate variations of Central Asia on orbital to millennial timescales.

PubMed

Cheng, Hai; Spötl, Christoph; Breitenbach, Sebastian F M; Sinha, Ashish; Wassenburg, Jasper A; Jochum, Klaus Peter; Scholz, Denis; Li, Xianglei; Yi, Liang; Peng, Youbing; Lv, Yanbin; Zhang, Pingzhong; Votintseva, Antonina; Loginov, Vadim; Ning, Youfeng; Kathayat, Gayatri; Edwards, R Lawrence

2016-11-11

The extent to which climate variability in Central Asia is causally linked to large-scale changes in the Asian monsoon on varying timescales remains a longstanding question. Here we present precisely dated high-resolution speleothem oxygen-carbon isotope and trace element records of Central Asia's hydroclimate variability from Tonnel'naya cave, Uzbekistan, and Kesang cave, western China. On orbital timescales, the supra-regional climate variance, inferred from our oxygen isotope records, exhibits a precessional rhythm, punctuated by millennial-scale abrupt climate events, suggesting a close coupling with the Asian monsoon. However, the local hydroclimatic variability at both cave sites, inferred from carbon isotope and trace element records, shows climate variations that are distinctly different from their supra-regional modes. Particularly, hydroclimatic changes in both Tonnel'naya and Kesang areas during the Holocene lag behind the supra-regional climate variability by several thousand years. These observations may reconcile the apparent out-of-phase hydroclimatic variability, inferred from the Holocene lake proxy records, between Westerly Central Asia and Monsoon Asia.

Climate variations of Central Asia on orbital to millennial timescales

PubMed Central

Cheng, Hai; Spötl, Christoph; Breitenbach, Sebastian F. M.; Sinha, Ashish; Wassenburg, Jasper A.; Jochum, Klaus Peter; Scholz, Denis; Li, Xianglei; Yi, Liang; Peng, Youbing; Lv, Yanbin; Zhang, Pingzhong; Votintseva, Antonina; Loginov, Vadim; Ning, Youfeng; Kathayat, Gayatri; Edwards, R. Lawrence

2016-01-01

The extent to which climate variability in Central Asia is causally linked to large-scale changes in the Asian monsoon on varying timescales remains a longstanding question. Here we present precisely dated high-resolution speleothem oxygen-carbon isotope and trace element records of Central Asia’s hydroclimate variability from Tonnel’naya cave, Uzbekistan, and Kesang cave, western China. On orbital timescales, the supra-regional climate variance, inferred from our oxygen isotope records, exhibits a precessional rhythm, punctuated by millennial-scale abrupt climate events, suggesting a close coupling with the Asian monsoon. However, the local hydroclimatic variability at both cave sites, inferred from carbon isotope and trace element records, shows climate variations that are distinctly different from their supra-regional modes. Particularly, hydroclimatic changes in both Tonnel’naya and Kesang areas during the Holocene lag behind the supra-regional climate variability by several thousand years. These observations may reconcile the apparent out-of-phase hydroclimatic variability, inferred from the Holocene lake proxy records, between Westerly Central Asia and Monsoon Asia. PMID:27833133

Socioeconomic Drought in a Changing Climate: Modeling and Management

NASA Astrophysics Data System (ADS)

AghaKouchak, Amir; Mehran, Ali; Mazdiyasni, Omid

2016-04-01

Drought is typically defined based on meteorological, hydrological and land surface conditions. However, in many parts of the world, anthropogenic changes and water management practices have significantly altered local water availability. Socioeconomic drought refers to conditions whereby the available water supply cannot satisfy the human and environmental water needs. Surface water reservoirs provide resilience against local climate variability (e.g., droughts), and play a major role in regional water management. This presentation focuses on a framework for describing socioeconomic drought based on both water supply and demand information. We present a multivariate approach as a measure of socioeconomic drought, termed Multivariate Standardized Reliability and Resilience Index (MSRRI; Mehran et al., 2015). This model links the information on inflow and surface reservoir storage to water demand. MSRRI integrates a "top-down" and a "bottom-up" approach for describing socioeconomic drought. The "top-down" component describes processes that cannot be simply controlled or altered by local decision-makers and managers (e.g., precipitation, climate variability, climate change), whereas the "bottom-up" component focuses on the local resilience, and societal capacity to respond to droughts. The two components (termed, Inflow-Demand Reliability (IDR) indicator and Water Storage Resilience (WSR) indicator) are integrated using a nonparametric multivariate approach. We use this framework to assess the socioeconomic drought during the Australian Millennium Drought (1998-2010) and the 2011-2014 California Droughts. MSRRI provides additional information on socioeconomic drought onset, development and termination based on local resilience and human demand that cannot be obtained from the commonly used drought indicators. We show that MSRRI can be used for water management scenario analysis (e.g., local water availability based on different human water demands scenarios). Finally, we provide examples of using the proposed modeling framework for analyzing water availability in a changing climate considering local conditions. Reference: Mehran A., Mazdiyasni O., AghaKouchak A., 2015, A Hybrid Framework for Assessing Socioeconomic Drought: Linking Climate Variability, Local Resilience, and Demand, Journal of Geophysical Research, 120 (15), 7520-7533, doi: 10.1002/2015JD023147

Advances of NOAA Training Program in Climate Services

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.

2012-12-01

Since 2002, NOAA's National Weather Service (NWS) Climate Services Division (CSD) has offered numerous training opportunities to NWS staff. After eight-years of development, the training program offers three instructor-led courses and roughly 25 online (distance learning) modules covering various climate topics, such as: climate data and observations, climate variability and change, and NWS national / local climate products (tools, skill, and interpretation). Leveraging climate information and expertise available at all NOAA line offices and partners allows for the delivery of the most advanced knowledge and is a very critical aspect of the training program. The emerging NOAA Climate Service (NCS) requires a well-trained, climate-literate workforce at the local level capable of delivering NOAA's climate products and services as well as providing climate-sensitive decision support. NWS Weather Forecast Offices and River Forecast Centers presently serve as local outlets for the NCS climate services. Trained NWS climate service personnel use proactive and reactive approaches and professional education methods in communicating climate variability and change information to local users. Both scientifically-sound messages and amiable communication techniques are important in developing an engaged dialog between the climate service providers and users. Several pilot projects have been conducted by the NWS CSD this past year that apply the program's training lessons and expertise to specialized external user group training. The technical user groups included natural resources managers, engineers, hydrologists, and planners for transportation infrastructure. Training of professional user groups required tailoring instructions to the potential applications for each group of users. Training technical users identified the following critical issues: (1) knowledge of target audience expectations, initial knowledge status, and potential use of climate information; (2) leveraging partnership with climate services providers; and, (3) applying 3H training approach, where the first H stands for Head (trusted science), the second H stands for Heart (make it easy), and the third H for Hand (support with applications).

Geomorphic determinants of species composition of alpine tundra, Glacier National Park, U.S.A.

USGS Publications Warehouse

George P. Malanson,; Bengtson, Lindsey E.; Fagre, Daniel B.

2012-01-01

Because the distribution of alpine tundra is associated with spatially limited cold climates, global warming may threaten its local extent or existence. This notion has been challenged, however, based on observations of the diversity of alpine tundra in small areas primarily due to topographic variation. The importance of diversity in temperature or moisture conditions caused by topographic variation is an open question, and we extend this to geomorphology more generally. The extent to which geomorphic variation per se, based on relatively easily assessed indicators, can account for the variation in alpine tundra community composition is analyzed versus the inclusion of broad indicators of regional climate variation. Visual assessments of topography are quantified and reduced using principal components analysis (PCA). Observations of species cover are reduced using detrended correspondence analysis (DCA). A “best subsets” regression approach using the Akaike Information Criterion for selection of variables is compared to a simple stepwise regression with DCA scores as the dependent variable and scores on significant PCA axes plus more direct measures of topography as independent variables. Models with geographic coordinates (representing regional climate gradients) excluded explain almost as much variation in community composition as models with them included, although they are important contributors to the latter. The geomorphic variables in the model are those associated with local moisture differences such as snowbeds. The potential local variability of alpine tundra can be a buffer against climate change, but change in precipitation may be as important as change in temperature.

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

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.

The Distribution of Climate Change Public Opinion in Canada.

PubMed

Mildenberger, Matto; Howe, Peter; Lachapelle, Erick; Stokes, Leah; Marlon, Jennifer; Gravelle, Timothy

2016-01-01

While climate scientists have developed high resolution data sets on the distribution of climate risks, we still lack comparable data on the local distribution of public climate change opinions. This paper provides the first effort to estimate local climate and energy opinion variability outside the United States. Using a multi-level regression and post-stratification (MRP) approach, we estimate opinion in federal electoral districts and provinces. We demonstrate that a majority of the Canadian public consistently believes that climate change is happening. Belief in climate change's causes varies geographically, with more people attributing it to human activity in urban as opposed to rural areas. Most prominently, we find majority support for carbon cap and trade policy in every province and district. By contrast, support for carbon taxation is more heterogeneous. Compared to the distribution of US climate opinions, Canadians believe climate change is happening at higher levels. This new opinion data set will support climate policy analysis and climate policy decision making at national, provincial and local levels.

The Distribution of Climate Change Public Opinion in Canada

PubMed Central

Gravelle, Timothy

2016-01-01

While climate scientists have developed high resolution data sets on the distribution of climate risks, we still lack comparable data on the local distribution of public climate change opinions. This paper provides the first effort to estimate local climate and energy opinion variability outside the United States. Using a multi-level regression and post-stratification (MRP) approach, we estimate opinion in federal electoral districts and provinces. We demonstrate that a majority of the Canadian public consistently believes that climate change is happening. Belief in climate change’s causes varies geographically, with more people attributing it to human activity in urban as opposed to rural areas. Most prominently, we find majority support for carbon cap and trade policy in every province and district. By contrast, support for carbon taxation is more heterogeneous. Compared to the distribution of US climate opinions, Canadians believe climate change is happening at higher levels. This new opinion data set will support climate policy analysis and climate policy decision making at national, provincial and local levels. PMID:27486659

A data centred method to estimate and map how the local distribution of daily precipitation is changing

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nick

2014-05-01

Estimates of how our climate is changing are needed locally in order to inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles in distributions of variables such as daily temperature or precipitation. Here we focus on these local changes and on a method to transform daily observations of precipitation into patterns of local climate change. We develop a method[1] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes, to specifically address the challenges presented by daily precipitation data. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the relative amount of precipitation in those days. Our method is 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 how fast different quantiles of precipitation distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily precipitation from specific locations across Europe over the last 60 years. We treat geographical location and precipitation as independent variables and thus obtain as outputs the pattern of change at a given threshold of precipitation and with geographical location. This is model- independent, thus providing data of direct value in model calibration and assessment. Our results show regionally consistent patterns of systematic increase in precipitation on the wettest days, and of drying across all days which is of potential value in adaptation planning. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, 371 20120287; D. A. Stainforth, 2013, S. C. Chapman, N. W. Watkins, Mapping climate change in European temperature distributions, Environ. Res. Lett. 8, 034031 [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

Exploring Local Approaches to Communicating Global Climate Change Information

NASA Astrophysics Data System (ADS)

Stevermer, A. J.

2002-12-01

Expected future climate changes are often presented as a global problem, requiring a global solution. Although this statement is accurate, communicating climate change science and prospective solutions must begin at local levels, each with its own subset of complexities to be addressed. Scientific evaluation of local changes can be complicated by large variability occurring over small spatial scales; this variability hinders efforts both to analyze past local changes and to project future ones. The situation is further encumbered by challenges associated with scientific literacy in the U.S., as well as by pressing economic difficulties. For people facing real-life financial and other uncertainties, a projected ``1.4 to 5.8 degrees Celsius'' rise in global temperature is likely to remain only an abstract concept. Despite this lack of concreteness, recent surveys have found that most U.S. residents believe current global warming science, and an even greater number view the prospect of increased warming as at least a ``somewhat serious'' problem. People will often be able to speak of long-term climate changes in their area, whether observed changes in the amount of snow cover in winter, or in the duration of extreme heat periods in summer. This work will explore the benefits and difficulties of communicating climate change from a local, rather than global, perspective, and seek out possible strategies for making less abstract, more concrete, and most importantly, more understandable information available to the public.

Sensitivity of tree ring growth to local and large-scale climate variability in a region of Southeastern Brazil

NASA Astrophysics Data System (ADS)

Venegas-González, Alejandro; Chagas, Matheus Peres; Anholetto Júnior, Claudio Roberto; Alvares, Clayton Alcarde; Roig, Fidel Alejandro; Tomazello Filho, Mario

2016-01-01

We explored the relationship between tree growth in two tropical species and local and large-scale climate variability in Southeastern Brazil. Tree ring width chronologies of Tectona grandis (teak) and Pinus caribaea (Caribbean pine) trees were compared with local (Water Requirement Satisfaction Index—WRSI, Standardized Precipitation Index—SPI, and Palmer Drought Severity Index—PDSI) and large-scale climate indices that analyze the equatorial pacific sea surface temperature (Trans-Niño Index-TNI and Niño-3.4-N3.4) and atmospheric circulation variations in the Southern Hemisphere (Antarctic Oscillation-AAO). Teak trees showed positive correlation with three indices in the current summer and fall. A significant correlation between WRSI index and Caribbean pine was observed in the dry season preceding tree ring formation. The influence of large-scale climate patterns was observed only for TNI and AAO, where there was a radial growth reduction in months preceding the growing season with positive values of the TNI in teak trees and radial growth increase (decrease) during December (March) to February (May) of the previous (current) growing season with positive phase of the AAO in teak (Caribbean pine) trees. The development of a new dendroclimatological study in Southeastern Brazil sheds light to local and large-scale climate influence on tree growth in recent decades, contributing in future climate change studies.

[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.

Humans and seasonal climate variability threaten large-bodied coral reef fish with small ranges.

PubMed

Mellin, C; Mouillot, D; Kulbicki, M; McClanahan, T R; Vigliola, L; Bradshaw, C J A; Brainard, R E; Chabanet, P; Edgar, G J; Fordham, D A; Friedlander, A M; Parravicini, V; Sequeira, A M M; Stuart-Smith, R D; Wantiez, L; Caley, M J

2016-02-03

Coral reefs are among the most species-rich and threatened ecosystems on Earth, yet the extent to which human stressors determine species occurrences, compared with biogeography or environmental conditions, remains largely unknown. With ever-increasing human-mediated disturbances on these ecosystems, an important question is not only how many species can inhabit local communities, but also which biological traits determine species that can persist (or not) above particular disturbance thresholds. Here we show that human pressure and seasonal climate variability are disproportionately and negatively associated with the occurrence of large-bodied and geographically small-ranging fishes within local coral reef communities. These species are 67% less likely to occur where human impact and temperature seasonality exceed critical thresholds, such as in the marine biodiversity hotspot: the Coral Triangle. Our results identify the most sensitive species and critical thresholds of human and climatic stressors, providing opportunity for targeted conservation intervention to prevent local extinctions.

[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.

Assessing climate change impacts on water resources in remote mountain regions

NASA Astrophysics Data System (ADS)

Buytaert, Wouter; De Bièvre, Bert

2013-04-01

From a water resources perspective, remote mountain regions are often considered as a basket case. They are often regions where poverty is often interlocked with multiple threats to water supply, data scarcity, and high uncertainties. In these environments, it is paramount to generate locally relevant knowledge about water resources and how they impact local livelihoods. This is often problematic. Existing environmental data collection tends to be geographically biased towards more densely populated regions, and prioritized towards strategic economic activities. Data may also be locked behind institutional and technological barriers. These issues create a "knowledge trap" for data-poor regions, which is especially acute in remote and hard-to-reach mountain regions. We present lessons learned from a decade of water resources research in remote mountain regions of the Andes, Africa and South Asia. We review the entire tool chain of assessing climate change impacts on water resources, including the interrogation and downscaling of global circulation models, translating climate variables in water availability and access, and assessing local vulnerability. In global circulation models, mountain regions often stand out as regions of high uncertainties and lack of agreement of future trends. This is partly a technical artifact because of the different resolution and representation of mountain topography, but it also highlights fundamental uncertainties in climate impacts on mountain climate. This problem also affects downscaling efforts, because regional climate models should be run in very high spatial resolution to resolve local gradients, which is computationally very expensive. At the same time statistical downscaling methods may fail to find significant relations between local climate properties and synoptic processes. Further uncertainties are introduced when downscaled climate variables such as precipitation and temperature are to be translated in hydrologically relevant variables such as streamflow and groundwater recharge. Fundamental limitations in both the understanding of hydrological processes in mountain regions (e.g., glacier melt, wetland attenuation, groundwater flows) and in data availability introduce large uncertainties. Lastly, assessing access to water resources is a major challenge. Topographical gradients and barriers, as well as strong spatiotemporal variations in hydrological processes, makes it particularly difficult to assess which parts of the mountain population is most vulnerable to future perturbations of the water cycle.

Climate change: believing and seeing implies adapting.

PubMed

Blennow, Kristina; Persson, Johannes; Tomé, Margarida; Hanewinkel, Marc

2012-01-01

Knowledge of factors that trigger human response to climate change is crucial for effective climate change policy communication. Climate change has been claimed to have low salience as a risk issue because it cannot be directly experienced. Still, personal factors such as strength of belief in local effects of climate change have been shown to correlate strongly with responses to climate change and there is a growing literature on the hypothesis that personal experience of climate change (and/or its effects) explains responses to climate change. Here we provide, using survey data from 845 private forest owners operating in a wide range of bio-climatic as well as economic-social-political structures in a latitudinal gradient across Europe, the first evidence that the personal strength of belief and perception of local effects of climate change, highly significantly explain human responses to climate change. A logistic regression model was fitted to the two variables, estimating expected probabilities ranging from 0.07 (SD ± 0.01) to 0.81 (SD ± 0.03) for self-reported adaptive measures taken. Adding socio-demographic variables improved the fit, estimating expected probabilities ranging from 0.022 (SD ± 0.008) to 0.91 (SD ± 0.02). We conclude that to explain and predict adaptation to climate change, the combination of personal experience and belief must be considered.

Projecting the Local Impacts of Climate Change on a Central American Montane Avian Community

NASA Technical Reports Server (NTRS)

Gasner, Matthew R.; Jankowski, Jill E.; Ciecka, Anna L.; Kyle, Keiller O.; Rabenold, Kerry N.

2010-01-01

Significant changes in the climates of Central America are expected over the next century. Lowland rainforests harbor high alpha diversity on local scales (<1 km2), yet montane landscapes often support higher beta diversity on 10-100 km2 scales. Climate change will likely disrupt the altitudinal zonation of montane communities that produces such landscape diversity. Projections of biotic response to climate change have often used broad-scale modelling of geographical ranges, but understanding likely impacts on population viability is also necessary for anticipating local and global extinctions. We model species abundances and estimate range shifts for birds in the Tilaran Mountains of Costa Rica, asking whether projected changes in temperature and rainfall could be sufficient to imperil high-elevation endemics and whether these variables will likely impact communities similarly. We find that nearly half of 77 forest bird species can be expected to decline in the next century. Almost half of species projected to decline are endemic to Central America, and seven of eight species projected to become locally extinct are endemic to the highlands of Costa Rica and Panam . Logistic-regression modelling of distributions and similarity in projections produced by temperature and rainfall models suggest that changes in both variables will be important. Although these projections are probably conservative because they do not explicitly incorporate biological or climate variable interactions, they provide a starting point for incorporating more realistic biological complexity into community-change models. Prudent conservation planning for tropical mountains should focus on regions with room for altitudinal reorganization of communities comprised of ecological specialists.

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

USDA-ARS?s Scientific Manuscript database

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

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

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.

2015-01-01

The effect of anthropogenic climate change on organisms will likely be related to climate change exposure and velocity at local and regional scales. However, common methods to estimate climate change exposure and velocity ignore important components of climate that are known to affect the ecology and evolution of organisms.We develop a novel index of climate change (climate overlap) that simultaneously estimates changes in the means, variation and correlation between multiple weather variables. Specifically, we estimate the overlap between multivariate normal probability distributions representing historical and current or projected future climates. We provide methods for estimating the statistical significance of climate overlap values and methods to estimate velocity using climate overlap.We show that climates have changed significantly across 80% of the continental United States in the last 32 years and that much of this change is due to changes in the variation and correlation between weather variables (two statistics that are rarely incorporated into climate change studies). We also show that projected future temperatures are predicted to be locally novel (<1·5% overlap) across most of the global land surface and that exposure is likely to be highest in areas with low historical climate variation. Last, we show that accounting for changes in the variation and correlation between multiple weather variables can dramatically affect velocity estimates; mean velocity estimates in the continental United States were between 3·1 and 19·0 km yr−1when estimated using climate overlap compared to 1·4 km yr−1 when estimated using traditional methods.Our results suggest that accounting for changes in the means, variation and correlation between multiple weather variables can dramatically affect estimates of climate change exposure and velocity. These climate components are known to affect the ecology and evolution of organisms, but are ignored by most measures of climate change. We conclude with a set of future directions and recommend future work to determine which measures of climate change exposure and velocity are most related to biological responses to climate change.

Effects of Global Change on U.S. Urban Areas: Vulnerabilities, Impacts, and Adaptation

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Wilbanks, Thomas J.; Kirshen, Paul; Romero-Lnkao, Patricia; Rosenzweig, Cynthia; Ruth, Matthias; Solecki, William; Tarr, Joel

2007-01-01

Human settlements, both large and small, are where the vast majority of people on the Earth live. Expansion of cities both in population and areal extent, is a relentless process that will accelerate in the 21st century. As a consequence of urban growth both in the United States and around the globe, it is important to develop an understanding of how urbanization will affect the local and regional environment. Of equal importance, however, is the assessment of how cities will be impacted by the looming prospects of global climate change and climate variability. The potential impacts of climate change and variability has recently been annunciated by the IPCC's "Climate Change 2007" report. Moreover, the U.S. Climate Change Science Program (CCSP) is preparing a series of "Synthesis and Assessment Products" (SAPs) reports to support informed discussion and decision making regarding climate change and variability by policy matters, resource managers, stakeholders, the media, and the general public. We are authors on a SAP describing the effects of global climate change on human settlements. This paper will present the elements of our SAP report that relate to what vulnerabilities and impacts will occur, what adaptation responses may take place, and what possible effects on settlement patterns and characteristics will potentially arise, on human settlements in the U.S. as a result of climate change and climate variability. We will also present some recommendations about what should be done to further research on how climate change and variability will impact human settlements in the U.S., as well as how to engage government officials, policy and decision makers, and the general public in understanding the implications of climate change and variability on the local and regional levels. Additionally, we wish to explore how technology such as remote sensing data coupled with modeling, can be employed as synthesis tools for deriving insight across a spectrum of impacts (e.g. public health, urban planning for mitigation strategies) on how cities can cope and adapt to climate change and variability. This latter point parallels the concepts and ideas presented in the U.S. National Academy of Sciences, Decadal Survey report on "Earth Science Applications from Space: National Imperatives for the Next Decade and Beyond" wherein the analysis of the impacts of climate change and variability, human health, and land use change are listed as key areas for development of future Earth observing remote sensing systems.

Assessing the Effects of Climate Variability on Orange Yield in Florida to Reduce Production Forecast Errors

NASA Astrophysics Data System (ADS)

Concha Larrauri, P.

2015-12-01

Orange production in Florida has experienced a decline over the past decade. Hurricanes in 2004 and 2005 greatly affected production, almost to the same degree as strong freezes that occurred in the 1980's. The spread of the citrus greening disease after the hurricanes has also contributed to a reduction in orange production in Florida. The occurrence of hurricanes and diseases cannot easily be predicted but the additional effects of climate on orange yield can be studied and incorporated into existing production forecasts that are based on physical surveys, such as the October Citrus forecast issued every year by the USDA. Specific climate variables ocurring before and after the October forecast is issued can have impacts on flowering, orange drop rates, growth, and maturation, and can contribute to the forecast error. Here we present a methodology to incorporate local climate variables to predict the USDA's orange production forecast error, and we study the local effects of climate on yield in different counties in Florida. This information can aid farmers to gain an insight on what is to be expected during the orange production cycle, and can help supply chain managers to better plan their strategy.

Local-scale topoclimate effects on treeline elevations: a country-wide investigation of New Zealand's southern beech treelines.

PubMed

Case, Bradley S; Buckley, Hannah L

2015-01-01

Although treeline elevations are limited globally by growing season temperature, at regional scales treelines frequently deviate below their climatic limit. The cause of these deviations relate to a host of climatic, disturbance, and geomorphic factors that operate at multiple scales. The ability to disentangle the relative effects of these factors is currently hampered by the lack of reliable topoclimatic data, which describe how regional climatic characteristics are modified by topographic effects in mountain areas. In this study we present an analysis of the combined effects of local- and regional-scale factors on southern beech treeline elevation variability at 28 study areas across New Zealand. We apply a mesoscale atmospheric model to generate local-scale (200 m) meteorological data at these treelines and, from these data, we derive a set of topoclimatic indices that reflect possible detrimental and ameliorative influences on tree physiological functioning. Principal components analysis of meteorological data revealed geographic structure in how study areas were situated in multivariate space along gradients of topoclimate. Random forest and conditional inference tree modelling enabled us to tease apart the relative effects of 17 explanatory factors on local-scale treeline elevation variability. Overall, modelling explained about 50% of the variation in treeline elevation variability across the 28 study areas, with local landform and topoclimatic effects generally outweighing those from regional-scale factors across the 28 study areas. Further, the nature of the relationships between treeline elevation variability and the explanatory variables were complex, frequently non-linear, and consistent with the treeline literature. To our knowledge, this is the first study where model-generated meteorological data, and derived topoclimatic indices, have been developed and applied to explain treeline variation. Our results demonstrate the potential of such an approach for ecological research in mountainous environments.

Local-scale topoclimate effects on treeline elevations: a country-wide investigation of New Zealand’s southern beech treelines

PubMed Central

Buckley, Hannah L.

2015-01-01

Although treeline elevations are limited globally by growing season temperature, at regional scales treelines frequently deviate below their climatic limit. The cause of these deviations relate to a host of climatic, disturbance, and geomorphic factors that operate at multiple scales. The ability to disentangle the relative effects of these factors is currently hampered by the lack of reliable topoclimatic data, which describe how regional climatic characteristics are modified by topographic effects in mountain areas. In this study we present an analysis of the combined effects of local- and regional-scale factors on southern beech treeline elevation variability at 28 study areas across New Zealand. We apply a mesoscale atmospheric model to generate local-scale (200 m) meteorological data at these treelines and, from these data, we derive a set of topoclimatic indices that reflect possible detrimental and ameliorative influences on tree physiological functioning. Principal components analysis of meteorological data revealed geographic structure in how study areas were situated in multivariate space along gradients of topoclimate. Random forest and conditional inference tree modelling enabled us to tease apart the relative effects of 17 explanatory factors on local-scale treeline elevation variability. Overall, modelling explained about 50% of the variation in treeline elevation variability across the 28 study areas, with local landform and topoclimatic effects generally outweighing those from regional-scale factors across the 28 study areas. Further, the nature of the relationships between treeline elevation variability and the explanatory variables were complex, frequently non-linear, and consistent with the treeline literature. To our knowledge, this is the first study where model-generated meteorological data, and derived topoclimatic indices, have been developed and applied to explain treeline variation. Our results demonstrate the potential of such an approach for ecological research in mountainous environments. PMID:26528407

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 Variability and Human Migration in the Netherlands, 1865–1937

PubMed Central

Jennings, Julia A.; Gray, Clark L.

2014-01-01

Human migration is frequently cited as a potential social outcome of climate change and variability, and these effects are often assumed to be stronger in the past when economies were less developed and markets more localized. Yet, few studies have used historical data to test the relationship between climate and migration directly. In addition, the results of recent studies that link demographic and climate data are not consistent with conventional narratives of displacement responses. Using longitudinal individual-level demographic data from the Historical Sample of the Netherlands (HSN) and climate data that cover the same period, we examine the effects of climate variability on migration using event history models. Only internal moves in the later period and for certain social groups are associated with negative climate conditions, and the strength and direction of the observed effects change over time. International moves decrease with extreme rainfall, suggesting that the complex relationships between climate and migration that have been observed for contemporary populations extend into the nineteenth century. PMID:25937689

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Olive flowering phenology variation between different cultivars in Spain and Italy: modeling analysis

NASA Astrophysics Data System (ADS)

Garcia-Mozo, H.; Orlandi, F.; Galan, C.; Fornaciari, M.; Romano, B.; Ruiz, L.; Diaz de La Guardia, C.; Trigo, M. M.; Chuine, I.

2009-03-01

Phenology data are sensitive data to identify how plants are adapted to local climate and how they respond to climatic changes. Modeling flowering phenology allows us to identify the meteorological variables determining the reproductive cycle. Phenology of temperate of woody plants is assumed to be locally adapted to climate. Nevertheless, recent research shows that local adaptation may not be an important constraint in predicting phenological responses. We analyzed variations in flowering dates of Olea europaea L. at different sites of Spain and Italy, testing for a genetic differentiation of flowering phenology among olive varieties to estimate whether local modeling is necessary for olive or not. We build models for the onset and peak dates flowering in different sites of Andalusia and Puglia. Process-based phenological models using temperature as input variable and photoperiod as the threshold date to start temperature accumulation were developed to predict both dates. Our results confirm and update previous results that indicated an advance in olive onset dates. The results indicate that both internal and external validity were higher in the models that used the photoperiod as an indicator to start to cumulate temperature. The use of the unified model for modeling the start and peak dates in the different localities provides standardized results for the comparative study. The use of regional models grouping localities by varieties and climate similarities indicate that local adaptation would not be an important factor in predicting olive phenological responses face to the global temperature increase.

NUTRItion and CLIMate (NUTRICLIM): investigating the relationship between climate variables and childhood malnutrition through agriculture, an exploratory study in Burkina Faso.

PubMed

Sorgho, Raissa; Franke, Jonas; Simboro, Seraphin; Phalkey, Revati; Saeurborn, Rainer

Malnutrition remains a leading cause of death in children in low- and middle-income countries; this will be aggravated by climate change. Annually, 6.9 million deaths of children under 5 were attributable directly or indirectly to malnutrition. Although these figures have recently decreased, evidence shows that a world with a medium climate (local warming up to 3-4 °C) will create an additional 25.2 million malnourished children. This proof of concept study explores the relationships between childhood malnutrition (more specifically stunting), regional agricultural yields, and climate variables through the use of remote sensing (RS) satellite imaging along with algorithms to predict the effect of climate variability on agricultural yields and on malnutrition of children under 5. The success of this proof of purpose study, NUTRItion and CLIMate (NUTRICLIM), should encourage researchers to apply both concept and tools to study of the link between weather variability, crop yield, and malnutrition on a larger scale. It would also allow for linking such micro-level data to climate models and address the challenge of projecting the additional impact of childhood malnutrition from climate change to various policy relevant time horizons.

A Method of Relating General Circulation Model Simulated Climate to the Observed Local Climate. Part I: Seasonal Statistics.

NASA Astrophysics Data System (ADS)

Karl, Thomas R.; Wang, Wei-Chyung; Schlesinger, Michael E.; Knight, Richard W.; Portman, David

1990-10-01

Important surface observations such as the daily maximum and minimum temperature, daily precipitation, and cloud ceilings often have localized characteristics that are difficult to reproduce with the current resolution and the physical parameterizations in state-of-the-art General Circulation climate Models (GCMs). Many of the difficulties can be partially attributed to mismatches in scale, local topography. regional geography and boundary conditions between models and surface-based observations. Here, we present a method, called climatological projection by model statistics (CPMS), to relate GCM grid-point flee-atmosphere statistics, the predictors, to these important local surface observations. The method can be viewed as a generalization of the model output statistics (MOS) and perfect prog (PP) procedures used in numerical weather prediction (NWP) models. It consists of the application of three statistical methods: 1) principle component analysis (FICA), 2) canonical correlation, and 3) inflated regression analysis. The PCA reduces the redundancy of the predictors The canonical correlation is used to develop simultaneous relationships between linear combinations of the predictors, the canonical variables, and the surface-based observations. Finally, inflated regression is used to relate the important canonical variables to each of the surface-based observed variables.We demonstrate that even an early version of the Oregon State University two-level atmospheric GCM (with prescribed sea surface temperature) produces free-atmosphere statistics than can, when standardized using the model's internal means and variances (the MOS-like version of CPMS), closely approximate the observed local climate. When the model data are standardized by the observed free-atmosphere means and variances (the PP version of CPMS), however, the model does not reproduce the observed surface climate as well. Our results indicate that in the MOS-like version of CPMS the differences between the output of a ten-year GCM control run and the surface-based observations are often smaller than the differences between the observations of two ten-year periods. Such positive results suggest that GCMs may already contain important climatological information that can be used to infer the local climate.

Local topography increasingly influences the mass balance of a retreating cirque glacier

USGS Publications Warehouse

Florentine, Caitlyn; Harper, Joel T.; Fagre, Daniel B.; Moore, Johnnie; Peitzsch, Erich H.

2018-01-01

Local topographically driven processes – such as wind drifting, avalanching, and shading – are known to alter the relationship between the mass balance of small cirque glaciers and regional climate. Yet partitioning such local effects from regional climate influence has proven difficult, creating uncertainty in the climate representativeness of some glaciers. We address this problem for Sperry Glacier in Glacier National Park, USA, using field-measured surface mass balance, geodetic constraints on mass balance, and regional climate data recorded at a network of meteorological and snow stations. Geodetically derived mass changes during 1950–1960, 1960–2005, and 2005–2014 document average mass change rates during each period at −0.22 ± 0.12, −0.18 ± 0.05, and −0.10 ± 0.03 m w.e. yr−1, respectively. A correlation of field-measured mass balance and regional climate variables closely (i.e., within 0.08 m w.e. yr−1) predicts the geodetically measured mass loss from 2005 to 2014. However, this correlation overestimates glacier mass balance for 1950–1960 by +1.20 ± 0.95 m w.e. yr−1. Our analysis suggests that local effects, not represented in regional climate variables, have become a more dominant driver of the net mass balance as the glacier lost 0.50 km2 and retreated further into its cirque.

Prominent Midlatitude Circulation Signature in High Asia's Surface Climate During Monsoon

NASA Astrophysics Data System (ADS)

Mölg, Thomas; Maussion, Fabien; Collier, Emily; Chiang, John C. H.; Scherer, Dieter

2017-12-01

High Asia has experienced strong environmental changes in recent decades, as evident in records of glaciers, lakes, tree rings, and vegetation. The multiscale understanding of the climatic drivers, however, is still incomplete. In particular, few systematic assessments have evaluated to what degree, if at all, the midlatitude westerly circulation modifies local surface climates in the reach of the Indian Summer Monsoon. This paper shows that a southward shift of the upper-tropospheric westerlies contributes significantly to climate variability in the core monsoon season (July-September) by two prominent dipole patterns at the surface: cooling in the west of High Asia contrasts with warming in the east, while moist anomalies in the east and northwest occur with drying along the southwestern margins. Circulation anomalies help to understand the dipoles and coincide with shifts in both the westerly wave train and the South Asian High, which imprint on air mass advection and local energy budgets. The relation of the variabilities to a well-established index of midlatitude climate dynamics allows future research on climate proxies to include a fresh hypothesis for the interpretation of environmental changes.

Large and local-scale influences on physical and chemical characteristics of coastal waters of Western Europe during winter

NASA Astrophysics Data System (ADS)

Tréguer, Paul; Goberville, Eric; Barrier, Nicolas; L'Helguen, Stéphane; Morin, Pascal; Bozec, Yann; Rimmelin-Maury, Peggy; Czamanski, Marie; Grossteffan, Emilie; Cariou, Thierry; Répécaud, Michel; Quéméner, Loic

2014-11-01

There is now a strong scientific consensus that coastal marine systems of Western Europe are highly sensitive to the combined effects of natural climate variability and anthropogenic climate change. However, it still remains challenging to assess the spatial and temporal scales at which climate influence operates. While large-scale hydro-climatic indices, such as the North Atlantic Oscillation (NAO) or the East Atlantic Pattern (EAP) and the weather regimes such as the Atlantic Ridge (AR), are known to be relevant predictors of physical processes, changes in coastal waters can also be related to local hydro-meteorological and geochemical forcing. Here, we study the temporal variability of physical and chemical characteristics of coastal waters located at about 48°N over the period 1998-2013 using (1) sea surface temperature, (2) sea surface salinity and (3) nutrient concentration observations for two coastal sites located at the outlet of the Bay of Brest and off Roscoff, (4) river discharges of the major tributaries close to these two sites and (5) regional and local precipitation data over the region of interest. Focusing on the winter months, we characterize the physical and chemical variability of these coastal waters and document changes in both precipitation and river runoffs. Our study reveals that variability in coastal waters is connected to the large-scale North Atlantic atmospheric circulation but is also partly explained by local river influences. Indeed, while the NAO is strongly related to changes in sea surface temperature at the Brest and Roscoff sites, the EAP and the AR have a major influence on precipitations, which in turn modulate river discharges that impact sea surface salinity at the scale of the two coastal stations.

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

NASA Astrophysics Data System (ADS)

Holman, I.; Rey Vicario, D.

2016-12-01

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

Cloudy Windows: What GCM Ensembles, Reanalyses and Observations Tell Us About Uncertainty in Greenland's Future Climate and Surface Melting

NASA Astrophysics Data System (ADS)

Reusch, D. B.

2016-12-01

Any analysis that wants to use a GCM-based scenario of future climate benefits from knowing how much uncertainty the GCM's inherent variability adds to the development of climate change predictions. This is extra relevant in the polar regions due to the potential of global impacts (e.g., sea level rise) from local (ice sheet) climate changes such as more frequent/intense surface melting. High-resolution, regional-scale models using GCMs for boundary/initial conditions in future scenarios inherit a measure of GCM-derived externally-driven uncertainty. We investigate these uncertainties for the Greenland ice sheet using the 30-member CESM1.0-CAM5-BGC Large Ensemble (CESMLE) for recent (1981-2000) and future (2081-2100, RCP 8.5) decades. Recent simulations are skill-tested against the ERA-Interim reanalysis and AWS observations with results informing future scenarios. We focus on key variables influencing surface melting through decadal climatologies, nonlinear analysis of variability with self-organizing maps (SOMs), regional-scale modeling (Polar WRF), and simple melt models. Relative to the ensemble average, spatially averaged climatological July temperature anomalies over a Greenland ice-sheet/ocean domain are mostly between +/- 0.2 °C. The spatial average hides larger local anomalies of up to +/- 2 °C. The ensemble average itself is 2 °C cooler than ERA-Interim. SOMs extend our diagnostics by providing a concise, objective summary of model variability as a set of generalized patterns. For CESMLE, the SOM patterns summarize the variability of multiple realizations of climate. Changes in pattern frequency by ensemble member show the influence of initial conditions. For example, basic statistical analysis of pattern frequency yields interquartile ranges of 2-4% for individual patterns across the ensemble. In climate terms, this tells us about climate state variability through the range of the ensemble, a potentially significant source of melt-prediction uncertainty. SOMs can also capture the different trajectories of climate due to intramodel variability over time. Polar WRF provides higher resolution regional modeling with improved, polar-centric model physics. Simple melt models allow us to characterize impacts of the upstream uncertainties on estimates of surface melting.

Downscaling climate information for local disease mapping.

PubMed

Bernardi, M; Gommes, R; Grieser, J

2006-06-01

The study of the impacts of climate on human health requires the interdisciplinary efforts of health professionals, climatologists, biologists, and social scientists to analyze the relationships among physical, biological, ecological, and social systems. As the disease dynamics respond to variations in regional and local climate, climate variability affects every region of the world and the diseases are not necessarily limited to specific regions, so that vectors may become endemic in other regions. Climate data at local level are thus essential to evaluate the dynamics of vector-borne disease through health-climate models and most of the times the climatological databases are not adequate. Climate data at high spatial resolution can be derived by statistical downscaling using historical observations but the method is limited by the availability of historical data at local level. Since the 90s', the statistical interpolation of climate data has been an important priority of the Agrometeorology Group of the Food and Agriculture Organization of the United Nations (FAO), as they are required for agricultural planning and operational activities at the local level. Since 1995, date of the first FAO spatial interpolation software for climate data, more advanced applications have been developed such as SEDI (Satellite Enhanced Data Interpolation) for the downscaling of climate data, LOCCLIM (Local Climate Estimator) and the NEW_LOCCLIM in collaboration with the Deutscher Wetterdienst (German Weather Service) to estimate climatic conditions at locations for which no observations are available. In parallel, an important effort has been made to improve the FAO climate database including at present more than 30,000 stations worldwide and expanding the database from developing countries coverage to global coverage.

Statistical Downscaling in Multi-dimensional Wave Climate Forecast

NASA Astrophysics Data System (ADS)

Camus, P.; Méndez, F. J.; Medina, R.; Losada, I. J.; Cofiño, A. S.; Gutiérrez, J. M.

2009-04-01

Wave climate at a particular site is defined by the statistical distribution of sea state parameters, such as significant wave height, mean wave period, mean wave direction, wind velocity, wind direction and storm surge. Nowadays, long-term time series of these parameters are available from reanalysis databases obtained by numerical models. The Self-Organizing Map (SOM) technique is applied to characterize multi-dimensional wave climate, obtaining the relevant "wave types" spanning the historical variability. This technique summarizes multi-dimension of wave climate in terms of a set of clusters projected in low-dimensional lattice with a spatial organization, providing Probability Density Functions (PDFs) on the lattice. On the other hand, wind and storm surge depend on instantaneous local large-scale sea level pressure (SLP) fields while waves depend on the recent history of these fields (say, 1 to 5 days). Thus, these variables are associated with large-scale atmospheric circulation patterns. In this work, a nearest-neighbors analog method is used to predict monthly multi-dimensional wave climate. This method establishes relationships between the large-scale atmospheric circulation patterns from numerical models (SLP fields as predictors) with local wave databases of observations (monthly wave climate SOM PDFs as predictand) to set up statistical models. A wave reanalysis database, developed by Puertos del Estado (Ministerio de Fomento), is considered as historical time series of local variables. The simultaneous SLP fields calculated by NCEP atmospheric reanalysis are used as predictors. Several applications with different size of sea level pressure grid and with different temporal domain resolution are compared to obtain the optimal statistical model that better represents the monthly wave climate at a particular site. In this work we examine the potential skill of this downscaling approach considering perfect-model conditions, but we will also analyze the suitability of this methodology to be used for seasonal forecast and for long-term climate change scenario projection of wave climate.

Regeneration potential of Taxodium distichum swamps and climate change

USGS Publications Warehouse

Middleton, B.A.

2009-01-01

Seed bank densities respond to factors across local to landscape scales, and therefore, knowledge of these responses may be necessary in forecasting the effects of climate change on the regeneration of species. This study relates the seed bank densities of species of Taxodium distichum swamps to local water regime and regional climate factors at five latitudes across the Mississippi River Alluvial Valley from southern Illinois to Louisiana. In an outdoor nursery setting, the seed banks of twenty-five swamps were exposed to non-flooded (freely drained) or flooded treatments, and the number and species of seeds germinating were recorded from each swamp during one growing season. Based on ANOVA analysis, the majority of dominant species had a higher rate of germination in non-flooded versus flooded treatments. Similarly, an NMS comparison, which considered the local water regime and regional climate of the swamps, found that the species of seeds germinating, almost completely shifted under non-flooded versus flooded treatments. For example, in wetter northern swamps, seeds of Taxodium distichum germinated in non-flooded conditions, but did not germinate from the same seed banks in flooded conditions. In wetter southern swamps, seeds of Eleocharis cellulosa germinated in flooded conditions, but did not germinate in non-flooded conditions. The strong relationship of seed germination and density relationships with local water regime and regional climate variables suggests that the forecasting of climate change effects on swamps and other wetlands needs to consider a variety of interrelated variables to make adequate projections of the regeneration responses of species to climate change. Because regeneration is an important aspect of species maintenance and restoration, climate drying could influence the species distribution of these swamps in the future. ?? 2008 Springer Science+Business Media B.V.

Climate warming alters effects of management on population viability of threatened species: results from a 30-year experimental study on a rare orchid.

PubMed

Sletvold, Nina; Dahlgren, Johan P; Oien, Dag-Inge; Moen, Asbjørn; Ehrlén, Johan

2013-09-01

Climate change is expected to influence the viability of populations both directly and indirectly, via species interactions. The effects of large-scale climate change are also likely to interact with local habitat conditions. Management actions designed to preserve threatened species therefore need to adapt both to the prevailing climate and local conditions. Yet, few studies have separated the direct and indirect effects of climatic variables on the viability of local populations and discussed the implications for optimal management. We used 30 years of demographic data to estimate the simultaneous effects of management practice and among-year variation in four climatic variables on individual survival, growth and fecundity in one coastal and one inland population of the perennial orchid Dactylorhiza lapponica in Norway. Current management, mowing, is expected to reduce competitive interactions. Statistical models of how climate and management practice influenced vital rates were incorporated into matrix population models to quantify effects on population growth rate. Effects of climate differed between mown and control plots in both populations. In particular, population growth rate increased more strongly with summer temperature in mown plots than in control plots. Population growth rate declined with spring temperature in the inland population, and with precipitation in the coastal population, and the decline was stronger in control plots in both populations. These results illustrate that both direct and indirect effects of climate change are important for population viability and that net effects depend both on local abiotic conditions and on biotic conditions in terms of management practice and intensity of competition. The results also show that effects of management practices influencing competitive interactions can strongly depend on climatic factors. We conclude that interactions between climate and management should be considered to reliably predict future population viability and optimize conservation actions. © 2013 John Wiley & Sons Ltd.

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

Perlwitz, J.; Knutson, T.; Kossin, J. P.; LeGrande, A. N.

2017-01-01

The causes of regional climate trends cannot be understood without considering the impact of variations in large-scale atmospheric circulation and an assessment of the role of internally generated climate variability. There are contributions to regional climate trends from changes in large-scale latitudinal circulation, which is generally organized into three cells in each hemisphere-Hadley cell, Ferrell cell and Polar cell-and which determines the location of subtropical dry zones and midlatitude jet streams. These circulation cells are expected to shift poleward during warmer periods, which could result in poleward shifts in precipitation patterns, affecting natural ecosystems, agriculture, and water resources. In addition, regional climate can be strongly affected by non-local responses to recurring patterns (or modes) of variability of the atmospheric circulation or the coupled atmosphere-ocean system. These modes of variability represent preferred spatial patterns and their temporal variation. They account for gross features in variance and for teleconnections which describe climate links between geographically separated regions. Modes of variability are often described as a product of a spatial climate pattern and an associated climate index time series that are identified based on statistical methods like Principal Component Analysis (PC analysis), which is also called Empirical Orthogonal Function Analysis (EOF analysis), and cluster analysis.

A data centred method to estimate and map changes in the full distribution of daily surface temperature

NASA Astrophysics Data System (ADS)

Chapman, Sandra; Stainforth, David; Watkins, Nicholas

2016-04-01

Characterizing how our climate is changing includes local information which can inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles or thresholds in distributions of variables such as daily surface temperature. Here we focus on these local changes and on a model independent method to transform daily observations into patterns of local climate change. Our method [1] is 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 how fast different quantiles of the distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. For temperature, changes in the distribution itself can yield robust results [2]. We demonstrate how the fundamental timescales of anthropogenic climate change limit the identification of societally relevant aspects of changes. We show that it is nevertheless possible to extract, solely from observations, some confident quantified assessments of change at certain thresholds and locations [3]. We demonstrate this approach using E-OBS gridded data [4] timeseries of local daily surface temperature from specific locations across Europe over the last 60 years. [1] Chapman, S. C., D. A. Stainforth, N. W. Watkins, On estimating long term local climate trends, Phil. Trans. Royal Soc., A,371 20120287 (2013) [2] Stainforth, D. A. S. C. Chapman, N. W. Watkins, Mapping climate change in European temperature distributions, ERL 8, 034031 (2013) [3] Chapman, S. C., Stainforth, D. A., Watkins, N. W. Limits to the quantification of local climate change, ERL 10, 094018 (2015) [4] Haylock M. R. et al ., A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119, (2008)

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.

Weak climatic control of stand-scale fire history during the late holocene.

PubMed

Gavin, Daniel G; Hu, Feng Sheng; Lertzman, Kenneth; Corbett, Peter

2006-07-01

Forest fire occurrence is affected by multiple controls that operate at local to regional scales. At the spatial scale of forest stands, regional climatic controls may be obscured by local controls (e.g., stochastic ignitions, topography, and fuel loads), but the long-term role of such local controls is poorly understood. We report here stand-scale (<100 ha) fire histories of the past 5000 years based on the analysis of sediment charcoal at two lakes 11 km apart in southeastern British Columbia. The two lakes are today located in similar subalpine forests, and they likely have experienced the same late-Holocene climatic changes because of their close proximity. We evaluated two independent properties of fire history: (1) fire-interval distribution, a measure of the overall incidence of fire, and (2) fire synchroneity, a measure of the co-occurrence of fire (here, assessed at centennial to millennial time scales due to the resolution of sediment records). Fire-interval distributions differed between the sites prior to, but not after, 2500 yr before present. When the entire 5000-yr period is considered, no statistical synchrony between fire-episode dates existed between the two sites at any temporal scale, but for the last 2500 yr marginal levels of synchrony occurred at centennial scales. Each individual fire record exhibited little coherency with regional climate changes. In contrast, variations in the composite record (average of both sites) matched variations in climate evidenced by late-Holocene glacial advances. This was probably due to the increased sample size and spatial extent represented by the composite record (up to 200 ha) plus increased regional climatic variability over the last several millennia, which may have partially overridden local, non-climatic controls. We conclude that (1) over past millennia, neighboring stands with similar modern conditions may have experienced different fire intervals and asynchronous patterns in fire episodes, likely because local controls outweighed the synchronizing effect of climate; (2) the influence of climate on fire occurrence is more strongly expressed when climatic variability is relatively great; and (3) multiple records from a region are essential if climate-fire relations are to be reliably described.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors

NASA Astrophysics Data System (ADS)

Liu, Meixian; Xu, Xianli; Sun, Alex

2015-07-01

Climate extremes can cause devastating damage to human society and ecosystems. Recent studies have drawn many conclusions about trends in climate extremes, but few have focused on quantitative analysis of their spatial variability and underlying mechanisms. By using the techniques of overlapping moving windows, the Mann-Kendall trend test, correlation, and stepwise regression, this study examined the spatial-temporal variation of precipitation extremes and investigated the potential key factors influencing this variation in southwestern (SW) China, a globally important biodiversity hot spot and climate-sensitive region. Results showed that the changing trends of precipitation extremes were not spatially uniform, but the spatial variability of these precipitation extremes decreased from 1959 to 2012. Further analysis found that atmospheric circulations rather than local factors (land cover, topographic conditions, etc.) were the main cause of such precipitation extremes. This study suggests that droughts or floods may become more homogenously widespread throughout SW China. Hence, region-wide assessments and coordination are needed to help mitigate the economic and ecological impacts.

Preparedness for climate change among local health department officials in New York state: a comparison with national survey results.

PubMed

Carr, Jessie L; Sheffield, Perry E; Kinney, Patrick L

2012-01-01

Climate-change adaptation strategies that address locally specific climate hazards are critical for preventing negative health outcomes, and local public health care officials are key foci for adaptation planning. To assess New York State Local Health Department officials' perceptions and preparedness related to climate-sensitive health areas, and compare these with a national sample. Online survey instrument, originally used in a national survey of local health department (LHD) officials. New York State. Eligible participants included all New York State city and county LHD officials, 1 respondent per LHD. LHD officials' perceptions of (1) local climate-related public health effects, (2) preparation status and programming areas of LHDs, and (3) necessary resources to better address climate-related health risks. : Survey participants, representing a 54% response rate (with 93% of respondents completing more than 90% of the questions), perceived climate change as relevant to public health, and most noted that some of their existing programs already use or are planning to use climate adaptation strategies. Overall, fewer New York State respondents identified concerns or related expertise compared with the previous national survey. Many respondents expressed uncertainty regarding necessary additional resources. This type of assessment makes clear the high variability in perceived impacts and capacity at the level of LHD jurisdictions, and underscores the importance of sustained support for local climate-change preparedness programming. The implications of these findings are germane to other states with similar decentralized jurisdiction of public health. Findings from such surveys can bolster existing LHD programs, as well as inform long-term and emergency planning for climate change.

Minimizing irrigation water demand: An evaluation of shifting planting dates in Sri Lanka.

PubMed

Rivera, Ashley; Gunda, Thushara; Hornberger, George M

2018-05-01

Climate change coupled with increasing demands for water necessitates an improved understanding of the water-food nexus at a scale local enough to inform farmer adaptations. Such assessments are particularly important for nations with significant small-scale farming and high spatial variability in climate, such as Sri Lanka. By comparing historical patterns of irrigation water requirements (IWRs) to rice planting records, we estimate that shifting rice planting dates to earlier in the season could yield water savings of up to 6%. Our findings demonstrate the potential of low-cost adaptation strategies to help meet crop production demands in water-scarce environments. This local-scale assessment of IWRs in Sri Lanka highlights the value of using historical data to inform agricultural management of water resources when high-skilled forecasts are not available. Given national policies prioritizing in-country production and farmers' sensitivities to water stress, decision-makers should consider local degrees of climate variability in institutional design of irrigation management structures.

Humans and seasonal climate variability threaten large-bodied coral reef fish with small ranges

PubMed Central

Mellin, C.; Mouillot, D.; Kulbicki, M.; McClanahan, T. R.; Vigliola, L.; Bradshaw, C. J. A.; Brainard, R. E.; Chabanet, P.; Edgar, G. J.; Fordham, D. A.; Friedlander, A. M.; Parravicini, V.; Sequeira, A. M. M.; Stuart-Smith, R. D.; Wantiez, L.; Caley, M. J.

2016-01-01

Coral reefs are among the most species-rich and threatened ecosystems on Earth, yet the extent to which human stressors determine species occurrences, compared with biogeography or environmental conditions, remains largely unknown. With ever-increasing human-mediated disturbances on these ecosystems, an important question is not only how many species can inhabit local communities, but also which biological traits determine species that can persist (or not) above particular disturbance thresholds. Here we show that human pressure and seasonal climate variability are disproportionately and negatively associated with the occurrence of large-bodied and geographically small-ranging fishes within local coral reef communities. These species are 67% less likely to occur where human impact and temperature seasonality exceed critical thresholds, such as in the marine biodiversity hotspot: the Coral Triangle. Our results identify the most sensitive species and critical thresholds of human and climatic stressors, providing opportunity for targeted conservation intervention to prevent local extinctions. PMID:26839155

Demographic Responses To Climate Manipulations Across a Species Range

NASA Astrophysics Data System (ADS)

Oldfather, M. F.

2016-12-01

Species biogeographic responses to climate change will occur through the local extinction and establishment of populations. The overall performance of populations across a species range is shaped by the idiosyncratic sensitivities of demographic rates to the changing climate conditions. Heterogeneous topography partially decouples temperature and soil moisture presenting an opportunity to disentangle demographic sensitivity to multiple local climate variables and refine range shift predictions in response to complex climate change. Since 2013, I have monitored 16 populations of a long-lived alpine plant, Ivesia lycopodioides var. scandularis (Rosaceae) across the entirety of its altitudinal range in the arid White Mountains, CA (3350 - 4420m). I quantified microclimatic soil moisture and temperature, and the demographic rates of over 4,000 individuals. Demographic rates exhibited sensitivity to accumulated degree-days (ex. reproduction), soil volumetric water content (ex. germination), or the interaction between these climate variables (ex. survival). These observations motivated an experimental test of the relationship between demography and local climate with manipulations of increased summertime temperature and precipitation in nine populations. All demographic rates were sensitive to the climate manipulations and the magnitude of the demographic response depended on the population's location within the range. However, the modeled population growth rate was only minimally affected by the manipulations in most populations. The inverse responses of many of the demographic rates may allow populations to demographically buffer against the climate manipulations. However, in one low elevation edge population the negative effect of heating on survival overwhelmed the positive effect on germination, indicating that the capacity of populations to demographically buffer may have a limit.

Dengue Vector Dynamics (Aedes aegypti) Influenced by Climate and Social Factors in Ecuador: Implications for Targeted Control

PubMed Central

Stewart Ibarra, Anna M.; Ryan, Sadie J.; Beltrán, Efrain; Mejía, Raúl; Silva, Mercy; Muñoz, Ángel

2013-01-01

Background Dengue fever, a mosquito-borne viral disease, is now the fastest spreading tropical disease globally. Previous studies indicate that climate and human behavior interact to influence dengue virus and vector (Aedes aegypti) population dynamics; however, the relative effects of these variables depends on local ecology and social context. We investigated the roles of climate and socio-ecological factors on Ae. aegypti population dynamics in Machala, a city in southern coastal Ecuador where dengue is hyper-endemic. Methods/Principal findings We studied two proximate urban localities where we monitored weekly Ae. aegypti oviposition activity (Nov. 2010-June 2011), conducted seasonal pupal surveys, and surveyed household to identify dengue risk factors. The results of this study provide evidence that Ae. aegypti population dynamics are influenced by social risk factors that vary by season and lagged climate variables that vary by locality. Best-fit models to predict the presence of Ae. aegypti pupae included parameters for household water storage practices, access to piped water, the number of households per property, condition of the house and patio, and knowledge and perceptions of dengue. Rainfall and minimum temperature were significant predictors of oviposition activity, although the effect of rainfall varied by locality due to differences in types of water storage containers. Conclusions These results indicate the potential to reduce the burden of dengue in this region by conducting focused vector control interventions that target high-risk households and containers in each season and by developing predictive models using climate and non-climate information. These findings provide the region's public health sector with key information for conducting time and location-specific vector control campaigns, and highlight the importance of local socio-ecological studies to understand dengue dynamics. See Text S1 for an executive summary in Spanish. PMID:24324542

Growth gains from selective breeding in a spruce hybrid zone do not compromise local adaptation to climate.

PubMed

MacLachlan, Ian R; Yeaman, Sam; Aitken, Sally N

2018-02-01

Hybrid zones contain extensive standing genetic variation that facilitates rapid responses to selection. The Picea glauca  ×  Picea engelmannii hybrid zone in western Canada is the focus of tree breeding programs that annually produce ~90 million reforestation seedlings. Understanding the direct and indirect effects of selective breeding on adaptive variation is necessary to implement assisted gene flow (AGF) polices in Alberta and British Columbia that match these seedlings with future climates. We decomposed relationships among hybrid ancestry, adaptive traits, and climate to understand the implications of selective breeding for climate adaptations and AGF strategies. The effects of selection on associations among hybrid index estimated from ~6,500 SNPs, adaptive traits, and provenance climates were assessed for ~2,400 common garden seedlings. Hybrid index differences between natural and selected seedlings within breeding zones were small in Alberta (average +2%), but larger and more variable in BC (average -7%, range -24% to +1%), slightly favoring P. glauca ancestry. The average height growth gain of selected seedlings over natural seedlings within breeding zones was 36% (range 12%-86%). Clines in growth with temperature-related variables were strong, but differed little between selected and natural populations. Seedling hybrid index and growth trait associations with evapotranspiration-related climate variables were stronger in selected than in natural seedlings, indicating possible preadaptation to drier future climates. Associations among cold hardiness, hybrid ancestry, and cold-related climate variables dominated signals of local adaptation and were preserved in breeding populations. Strong hybrid ancestry-phenotype-climate associations suggest that AGF will be necessary to match interior spruce breeding populations with shifting future climates. The absence of antagonistic selection responses among traits and maintenance of cold adaptation in selected seedlings suggests breeding populations can be safely redeployed using AGF prescriptions similar to those of natural populations.

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.

Vulnerability Assessment of Natural Disasters for Small and Mid-Sized Streams due to Climate Change and Stream Improvement

NASA Astrophysics Data System (ADS)

Choi, D.; Jun, H. D.; Kim, S.

2012-04-01

Vulnerability assessment plays an important role in drawing up climate change adaptation plans. Although there are some studies on broad vulnerability assessment in Korea, there have been very few studies to develop and apply locally focused and specific sector-oriented climate change vulnerability indicators. Especially, there has seldom been any study to investigate the effect of an adaptation project on assessing the vulnerability status to climate change for fundamental local governments. In order to relieve adverse effects of climate change, Korean government has performed the project of the Major Four Rivers (Han, Geum, Nakdong and Yeongsan river) Restoration since 2008. It is expected that water level in main stream of 4 rivers will be dropped through this project, but flood effect will be mainly occurred in small and mid-sized streams which flows in main stream. Hence, we examined how much the project of the major four rivers restoration relieves natural disasters. Conceptual framework of vulnerability-resilience index to climate change for the Korean fundamental local governments is defined as a function of climate exposure, sensitivity, and adaptive capacity. Then, statistical data on scores of proxy variables assumed to comprise climate change vulnerability for local governments are collected. Proxy variables and estimated temporary weights of them are selected by surveying a panel of experts using Delphi method, and final weights are determined by modified Entropy method. Developed vulnerability-resilience index was applied to Korean fundamental local governments and it is calculated under each scenario as follows. (1) Before the major four rivers restoration, (2) 100 years after represented climate change condition without the major four rivers restoration, (3) After the major four rivers restoration without representing climate change (this means present climate condition) and (4) After the major four rivers restoration and 100 years after represented climate change condition. In the results of calculated vulnerability-resilience index of each scenario, it can be noticed that vulnerability of watersheds which are located near main stream of four rivers is alleviated, but because of climate change, vulnerability is getting high in most watersheds. Also, considering future climate change and river restoration, vulnerability of several watersheds is relieved by river restoration. Acknowledges This work was funded by the National Emergency Management Agency (NEMA) in Korea Program under Grant NEMA-10-NH-04.

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.

A 2,000-year reconstruction of the rain-fed maize agricultural niche in the US Southwest.

PubMed

Bocinsky, R Kyle; Kohler, Timothy A

2014-12-04

Humans experience, adapt to and influence climate at local scales. Paleoclimate research, however, tends to focus on continental, hemispheric or global scales, making it difficult for archaeologists and paleoecologists to study local effects. Here we introduce a method for high-frequency, local climate-field reconstruction from tree-rings. We reconstruct the rain-fed maize agricultural niche in two regions of the southwestern United States with dense populations of prehispanic farmers. Niche size and stability are highly variable within and between the regions. Prehispanic rain-fed maize farmers tended to live in agricultural refugia--areas most reliably in the niche. The timing and trajectory of the famous thirteenth century Pueblo migration can be understood in terms of relative niche size and stability. Local reconstructions like these illuminate the spectrum of strategies past humans used to adapt to climate change by recasting climate into the distributions of resources on which they depended.

A downscaling method for the assessment of local climate change

NASA Astrophysics Data System (ADS)

Bruno, E.; Portoghese, I.; Vurro, M.

2009-04-01

The use of complimentary models is necessary to study the impact of climate change scenarios on the hydrological response at different space-time scales. However, the structure of GCMs is such that their space resolution (hundreds of kilometres) is too coarse and not adequate to describe the variability of extreme events at basin scale (Burlando and Rosso, 2002). To bridge the space-time gap between the climate scenarios and the usual scale of the inputs for hydrological prediction models is a fundamental requisite for the evaluation of climate change impacts on water resources. Since models operate a simplification of a complex reality, their results cannot be expected to fit with climate observations. Identifying local climate scenarios for impact analysis implies the definition of more detailed local scenario by downscaling GCMs or RCMs results. Among the output correction methods we consider the statistical approach by Déqué (2007) reported as a ‘Variable correction method' in which the correction of model outputs is obtained by a function build with the observation dataset and operating a quantile-quantile transformation (Q-Q transform). However, in the case of daily precipitation fields the Q-Q transform is not able to correct the temporal property of the model output concerning the dry-wet lacunarity process. An alternative correction method is proposed based on a stochastic description of the arrival-duration-intensity processes in coherence with the Poissonian Rectangular Pulse scheme (PRP) (Eagleson, 1972). In this proposed approach, the Q-Q transform is applied to the PRP variables derived from the daily rainfall datasets. Consequently the corrected PRP parameters are used for the synthetic generation of statistically homogeneous rainfall time series that mimic the persistency of daily observations for the reference period. Then the PRP parameters are forced through the GCM scenarios to generate local scale rainfall records for the 21st century. The statistical parameters characterizing daily storm occurrence, storm intensity and duration needed to apply the PRP scheme are considered among STARDEX collection of extreme indices.

Signatures of large-scale and local climates on the demography of white-tailed ptarmigan in Rocky Mountain National Park, Colorado, USA.

PubMed

Wang, Guiming; Hobbs, N Thompson; Galbraith, Hector; Giesen, Kenneth M

2002-09-01

Global climate change may impact wildlife populations by affecting local weather patterns, which, in turn, can impact a variety of ecological processes. However, it is not clear that local variations in ecological processes can be explained by large-scale patterns of climate. The North Atlantic oscillation (NAO) is a large-scale climate phenomenon that has been shown to influence the population dynamics of some animals. Although effects of the NAO on vertebrate population dynamics have been studied, it remains uncertain whether it broadly predicts the impact of weather on species. We examined the ability of local weather data and the NAO to explain the annual variation in population dynamics of white-tailed ptarmigan ( Lagopus leucurus) in Rocky Mountain National Park, USA. We performed canonical correlation analysis on the demographic subspace of ptarmigan and local-climate subspace defined by the empirical orthogonal function (EOF) using data from 1975 to 1999. We found that two subspaces were significantly correlated on the first canonical variable. The Pearson correlation coefficient of the first EOF values of the demographic and local-climate subspaces was significant. The population density and the first EOF of local-climate subspace influenced the ptarmigan population with 1-year lags in the Gompertz model. However, the NAO index was neither related to the first two EOF of local-climate subspace nor to the first EOF of the demographic subspace of ptarmigan. Moreover, the NAO index was not a significant term in the Gompertz model for the ptarmigan population. Therefore, local climate had stronger signature on the demography of ptarmigan than did a large-scale index, i.e., the NAO index. We conclude that local responses of wildlife populations to changing climate may not be adequately explained by models that project large-scale climatic patterns.

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

NASA Technical Reports Server (NTRS)

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

2015-01-01

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

Reconstructing the 20th century high-resolution climate of the southeastern United States

NASA Astrophysics Data System (ADS)

Dinapoli, Steven M.; Misra, Vasubandhu

2012-10-01

We dynamically downscale the 20th Century Reanalysis (20CR) to a 10-km grid resolution from 1901 to 2008 over the southeastern United States and the Gulf of Mexico using the Regional Spectral Model. The downscaled data set, which we call theFlorida Climate Institute-Florida State University Land-Atmosphere Reanalysis for theSoutheastern United States at 10-km resolution (FLAReS1.0), will facilitate the study of the effects of low-frequency climate variability and major historical climate events on local hydrology and agriculture. To determine the suitability of the FLAReS1.0 downscaled data set for any subsequent applied climate studies, we compare the annual, seasonal, and diurnal variability of temperature and precipitation in the model to various observation data sets. In addition, we examine the model's depiction of several meteorological phenomena that affect the climate of the region, including extreme cold waves, summer sea breezes and associated convective activity, tropical cyclone landfalls, and midlatitude frontal systems. Our results show that temperature and precipitation variability are well-represented by FLAReS1.0 on most time scales, although systematic biases do exist in the data. FLAReS1.0 accurately portrays some of the major weather phenomena in the region, but the severity of extreme weather events is generally underestimated. The high resolution of FLAReS1.0 makes it more suitable for local climate studies than the coarser 20CR.

Guess-Work and Reasonings on Centennial Evolution of Surface Air Temperature in Russia. Part IV: Towards Economic Estimations of Climate-Related Damages from the Bifurcation Analysis Viewpoint

NASA Astrophysics Data System (ADS)

Kolokolov, Yury; Monovskaya, Anna

The paper completes the cycle of the research devoted to the development of the experimental bifurcation analysis (not computer simulations) in order to answer the following questions: whether qualitative changes occur in the dynamics of local climate systems in a centennial timescale?; how to analyze such qualitative changes with daily resolution for local and regional space-scales?; how to establish one-to-one daily correspondence between the dynamics evolution and economic consequences for productions? To answer the questions, the unconventional conceptual model to describe the local climate dynamics was proposed and verified in the previous parts. That model (HDS-model) originates from the hysteresis regulator with double synchronization and has a variable structure due to competition between the amplitude quantization and the time quantization. The main advantage of the HDS-model is connected with the possibility to describe “internally” (on the basis of the self-regulation) the specific causal effects observed in the dynamics of local climate systems instead of “external” description of three states of the hysteresis behavior of climate systems (upper, lower and transient states). As a result, the evolution of the local climate dynamics is based on the bifurcation diagrams built by processing the data of meteorological observations, where the strange effects of the essential interannual daily variability of annual temperature variation are taken into account and explained. It opens the novel possibilities to analyze the local climate dynamics taking into account the observed resultant of all internal and external influences on each local climate system. In particular, the paper presents the viewpoint on how to estimate economic damages caused by climate-related hazards through the bifurcation analysis. That viewpoint includes the following ideas: practically each local climate system is characterized by its own time pattern of the natural qualitative changes in temperature dynamics over a century, so, any unified time window to determine the local climatic norms seems to be questionable; the temperature limits determined for climate-related technological hazards should be reasoned by the conditions of artificial human activity, but not by the climatic norms; the damages caused by such hazards can be approximately estimated in relation to the average annual profit of each production. Now, it becomes possible to estimate the minimal and maximal numbers of the specified hazards per year in order, first of all, to avoid unforeseen latent damages. Also, it becomes possible to make some useful relative estimation concerning damage and profit. We believe that the results presented in the cycle illustrate great practical competence of the current advances in the experimental bifurcation analysis. In particular, the developed QHS-analysis provides the novel prospects towards both how to adapt production to climatic changes and how to compensate negative technological impacts on environment.

Improving the interpretability of climate landscape metrics: An ecological risk analysis of Japan's Marine Protected Areas.

PubMed

García Molinos, Jorge; Takao, Shintaro; Kumagai, Naoki H; Poloczanska, Elvira S; Burrows, Michael T; Fujii, Masahiko; Yamano, Hiroya

2017-10-01

Conservation efforts strive to protect significant swaths of terrestrial, freshwater and marine ecosystems from a range of threats. As climate change becomes an increasing concern, these efforts must take into account how resilient-protected spaces will be in the face of future drivers of change such as warming temperatures. Climate landscape metrics, which signal the spatial magnitude and direction of climate change, support a convenient initial assessment of potential threats to and opportunities within ecosystems to inform conservation and policy efforts where biological data are not available. However, inference of risk from purely physical climatic changes is difficult unless set in a meaningful ecological context. Here, we aim to establish this context using historical climatic variability, as a proxy for local adaptation by resident biota, to identify areas where current local climate conditions will remain extant and future regional climate analogues will emerge. This information is then related to the processes governing species' climate-driven range edge dynamics, differentiating changes in local climate conditions as promoters of species range contractions from those in neighbouring locations facilitating range expansions. We applied this approach to assess the future climatic stability and connectivity of Japanese waters and its network of marine protected areas (MPAs). We find 88% of Japanese waters transitioning to climates outside their historical variability bounds by 2035, resulting in large reductions in the amount of available climatic space potentially promoting widespread range contractions and expansions. Areas of high connectivity, where shifting climates converge, are present along sections of the coast facilitated by the strong latitudinal gradient of the Japanese archipelago and its ocean current system. While these areas overlap significantly with areas currently under significant anthropogenic pressures, they also include much of the MPA network that may provide stepping-stone protection for species that must shift their distribution because of climate change. © 2017 John Wiley & Sons Ltd.

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.

Simulation of an ensemble of future climate time series with an hourly weather generator

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.; Kim, J.

2010-12-01

There is evidence that climate change is occurring in many regions of the world. The necessity of climate change predictions at the local scale and fine temporal resolution is thus warranted for hydrological, ecological, geomorphological, and agricultural applications that can provide thematic insights into the corresponding impacts. Numerous downscaling techniques have been proposed to bridge the gap between the spatial scales adopted in General Circulation Models (GCM) and regional analyses. Nevertheless, the time and spatial resolutions obtained as well as the type of meteorological variables may not be sufficient for detailed studies of climate change effects at the local scales. In this context, this study presents a stochastic downscaling technique that makes use of an hourly weather generator to simulate time series of predicted future climate. Using a Bayesian approach, the downscaling procedure derives distributions of factors of change for several climate statistics from a multi-model ensemble of GCMs. Factors of change are sampled from their distributions using a Monte Carlo technique to entirely account for the probabilistic information obtained with the Bayesian multi-model ensemble. Factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. The weather generator can reproduce a wide set of climate variables and statistics over a range of temporal scales, from extremes, to the low-frequency inter-annual variability. The final result of such a procedure is the generation of an ensemble of hourly time series of meteorological variables that can be considered as representative of future climate, as inferred from GCMs. The generated ensemble of scenarios also accounts for the uncertainty derived from multiple GCMs used in downscaling. Applications of the procedure in reproducing present and future climates are presented for different locations world-wide: Tucson (AZ), Detroit (MI), and Firenze (Italy). The stochastic downscaling is carried out with eight GCMs from the CMIP3 multi-model dataset (IPCC 4AR, A1B scenario).

Detection of the Coupling between Vegetation Leaf Area and Climate in a Multifunctional Watershed, Northwestern China

Treesearch

Lu Hao; Cen Pan; Peilong Liu; Decheng Zhou; Liangxia Zhang; Zhe Xiong; Yongqiang Liu; Ge Sun

2016-01-01

Accurate detection and quantification of vegetation dynamics and drivers of observed climatic and anthropogenic change in space and time is fundamental for our understanding of the atmosphere–biosphere interactions at local and global scales. This case study examined the coupled spatial patterns of vegetation dynamics and climatic variabilities during the past...

'Tales of Symphonia': extinction dynamics in response to past climate change in Madagascan rainforests.

PubMed

Virah-Sawmy, Malika; Bonsall, Michael B; Willis, Katherine J

2009-12-23

Madagascar's rainforests are among the most biodiverse in the world. Understanding the population dynamics of important species within these forests in response to past climatic variability provides valuable insight into current and future species composition. Here, we use a population-level approach to analyse palaeoecological records over the last 5300 years to understand how populations of Symphonia cf. verrucosa became locally extinct in some rainforest fragments along the southeast coast of Madagascar in response to rapid climate change, yet persisted in others. Our results indicate that regional (climate) variability contributed to synchronous decline of S. cf. verrucosa populations in these forests. Superimposed on regional fluctuations were local processes that could have contributed or mitigated extinction. Specifically, in the forest with low soil nutrients, population model predictions indicated that there was coexistence between S. cf. verrucosa and Erica spp., but in the nutrient-rich forest, interspecific effects between Symphonia and Erica spp. may have pushed Symphonia to extinction at the peak of climatic change. We also demonstrate that Symphonia is a good indicator of a threshold event, exhibiting erratic fluctuations prior to and long after the critical climatic point has passed.

Changes in climate variability with reference to land quality and agriculture in Scotland.

PubMed

Brown, Iain; Castellazzi, Marie

2015-06-01

Classification and mapping of land capability represents an established format for summarising spatial information on land quality and land-use potential. By convention, this information incorporates bioclimatic constraints through the use of a long-term average. However, climate change means that land capability classification should also have a dynamic temporal component. Using an analysis based upon Land Capability for Agriculture in Scotland, it is shown that this dynamism not only involves the long-term average but also shorter term spatiotemporal patterns, particularly through changes in interannual variability. Interannual and interdecadal variations occur both in the likelihood of land being in prime condition (top three capability class divisions) and in class volatility from year to year. These changing patterns are most apparent in relation to the west-east climatic gradient which is mainly a function of precipitation regime and soil moisture. Analysis is also extended into the future using climate results for the 2050s from a weather generator which show a complex interaction between climate interannual variability and different soil types for land quality. In some locations, variability of land capability is more likely to decrease because the variable climatic constraints are relaxed and the dominant constraint becomes intrinsic soil properties. Elsewhere, climatic constraints will continue to be influential. Changing climate variability has important implications for land-use planning and agricultural management because it modifies local risk profiles in combination with the current trend towards agricultural intensification and specialisation.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Using global Climate Impact Indicators to assess water resource availability in a Mediterranean mountain catchment: the Sierra Nevada study case (Spain) in the SWICCA platform

NASA Astrophysics Data System (ADS)

José Pérez-Palazón, María; Pimentel, Rafael; Sáenz de Rodrigáñez, Marta; Gulliver, Zacarias; José Polo, María

2017-04-01

Climate services provide water resource managements and users with science-based information on the likely impacts associated to the future climate scenarios. Mountainous areas are especially vulnerable to climate variations due to the expected changes in the snow regime, among others; in Mediterranean regions, this shift involves significant effects on the river flow regime and water resource availability and management. The Guadalfeo River Basin is a 1345 km2 mountainous, coastal catchment in southern Spain, ranging from the Mediterranean Sea coastline to the Sierra Nevada mountains to the north (up to 3450 m a.s.l.) within a 40-km distance. The climate variability adds complexity to this abrupt topography and heterogeneous area. The uncertainty associated to snow occurrence and persistence for the next decades poses a challenge for the current and future water resource uses in the area. The development of easy-to-use local climate indicators and derived decision-making variables is key to assess and face the economic impact of the potential changes. The SWICCA (Service for Water Indicators in Climate Change Adaptation) Platform (http://swicca.climate.copernicus.eu/) has been developed under the Copernicus Climate Change Service (C3S) and provides global climate and hydrology indicators on a Pan-European scale. Different case studies are included to assess the platform development and contents, and analyse the indicators' performance from a proof-of-concept approach that includes end-users feedbacks. The Guadalfeo River Basin is one of these case studies. This work presents the work developed so far to analyse and use the SWICCA Climate Impact Indicators (CIIs) related to river flow in this mountainous area, and the first set of local indicators specifically designed to assess selected end-users on the potential impact associated to different climate scenarios. Different CIIs were extracted from the SWICCA interface and tested against the local information available in the case study. The Essential Climate Variables used were precipitation and flow daily values, obtained at different spatial scales. The analysis led to the use of SWICCA-river flow on a catchment scale as the most suitable global CIIs in this area. Further treatment included local downscaling by means of transfer functions and a final relative anomaly correction. Three final end-users (clients) were identified within the water resource management framework: 1) mini hydropower facilities at the head areas, 2) urban supply at the southern area, and 3) water management decision makers (reservoir operation). From the corrected CIIs, local indicators were defined from the interaction with each client, to tailor water services easily and readily usable. Knowledge brokering from this interaction resulted in a first identification of a set of 4, 3 and 4 indicators for hydropower generation, urban users and water resource decision-makers, respectively, with different time scales. The projections of three future climate scenarios were assessed for each indicator and presented to each client. Local indicators are an efficient tool to assess the potential range of water allocation possibilities in this area on an annual and decadal basis, and get a deeper insight of the seasonal future potential regime of water resource availability. The results are good examples of key information for decision making in the future, and show how to derive local indicators with impact in the short and medium term planning in heterogeneous catchments in this region.

Greenhouse gas scenario sensitivity and uncertainties in precipitation projections for central Belgium

NASA Astrophysics Data System (ADS)

Van Uytven, E.; Willems, P.

2018-03-01

Climate change impact assessment on meteorological variables involves large uncertainties as a result of incomplete knowledge on the future greenhouse gas concentrations and climate model physics, next to the inherent internal variability of the climate system. Given that the alteration in greenhouse gas concentrations is the driver for the change, one expects the impacts to be highly dependent on the considered greenhouse gas scenario (GHS). In this study, we denote this behavior as GHS sensitivity. Due to the climate model related uncertainties, this sensitivity is, at local scale, not always that strong as expected. This paper aims to study the GHS sensitivity and its contributing role to climate scenarios for a case study in Belgium. An ensemble of 160 CMIP5 climate model runs is considered and climate change signals are studied for precipitation accumulation, daily precipitation intensities and wet day frequencies. This was done for the different seasons of the year and the scenario periods 2011-2040, 2031-2060, 2051-2081 and 2071-2100. By means of variance decomposition, the total variance in the climate change signals was separated in the contribution of the differences in GHSs and the other model-related uncertainty sources. These contributions were found dependent on the variable and season. Following the time of emergence concept, the GHS uncertainty contribution is found dependent on the time horizon and increases over time. For the most distinct time horizon (2071-2100), the climate model uncertainty accounts for the largest uncertainty contribution. The GHS differences explain up to 18% of the total variance in the climate change signals. The results point further at the importance of the climate model ensemble design, specifically the ensemble size and the combination of climate models, whereupon climate scenarios are based. The numerical noise, introduced at scales smaller than the skillful scale, e.g. at local scale, was not considered in this study.

Climate of the Kennedy Space Center and vicinity

NASA Technical Reports Server (NTRS)

Mailander, Joseph L.

1990-01-01

Climate plays a large role in determining the biota of a region. Summary data are presented for climate variables of ecological importance including precipitation, temperature, evapotranspiration, wind, isolation, lightning, and humidity. The John F. Kennedy Space Center, Cape Canaveral Air Force Station, and surrounding area are sampled intensively for climatic conditions; data are presented for the barrier island, Merritt Island, and the mainland, which represents the range of conditions in the local area. Climatic figures, database listings, and historic data (pre-1931) are presented in the appendix.

Rainfall pattern variability as climate change impact in The Wallacea Region

NASA Astrophysics Data System (ADS)

Pujiastuti, I.; Nurjani, E.

2018-04-01

The objective of the study is to observe the characteristic variability of rainfall pattern in the city located in every rainfall type, local (Kendari), monsoon (Manado), and equatorial (Palu). The result will be compared to determine which has the most significantly precipitation changing due to climate change impact. Rainfall variability in Indonesia illustrates precipitation variation thus the important variability is the variability of monthly rainfall. Monthly precipitation data for the period of 1961-2010 are collected from Indonesian Agency for Meteorological, Climatological, and Geophysical Agency. This data is calculated with the normal test statistical method to analyze rainfall variability. The result showed the pattern of trend and variability of rainfall in every city with the own characteristic which determines the rainfall type. Moreover, there is comparison of rainfall pattern changing between every rainfall type. This information is useful for climate change mitigation and adaptation strategies especially in water resource management form precipitation as well as the occurrence of meteorological disasters.

Global patterns of declining temperature variability from the Last Glacial Maximum to the Holocene

NASA Astrophysics Data System (ADS)

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

2018-02-01

Changes in climate variability are as important for society to address as are changes in mean climate. Contrasting temperature variability during the Last Glacial Maximum and the Holocene can provide insights into the relationship between the mean state of the climate and its variability. However, although glacial-interglacial changes in variability have been quantified for Greenland, a global view remains elusive. Here we use a network of marine and terrestrial temperature proxies to show that temperature variability decreased globally by a factor of four as the climate warmed by 3-8 degrees Celsius from the Last Glacial Maximum (around 21,000 years ago) to the Holocene epoch (the past 11,500 years). This decrease had a clear zonal pattern, with little change in the tropics (by a factor of only 1.6-2.8) and greater change in the mid-latitudes of both hemispheres (by a factor of 3.3-14). By contrast, Greenland ice-core records show a reduction in temperature variability by a factor of 73, suggesting influences beyond local temperature or a decoupling of atmospheric and global surface temperature variability for Greenland. The overall pattern of reduced variability can be explained by changes in the meridional temperature gradient, a mechanism that points to further decreases in temperature variability in a warmer future.

Global patterns of declining temperature variability from the Last Glacial Maximum to the Holocene.

PubMed

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

2018-02-15

Changes in climate variability are as important for society to address as are changes in mean climate. Contrasting temperature variability during the Last Glacial Maximum and the Holocene can provide insights into the relationship between the mean state of the climate and its variability. However, although glacial-interglacial changes in variability have been quantified for Greenland, a global view remains elusive. Here we use a network of marine and terrestrial temperature proxies to show that temperature variability decreased globally by a factor of four as the climate warmed by 3-8 degrees Celsius from the Last Glacial Maximum (around 21,000 years ago) to the Holocene epoch (the past 11,500 years). This decrease had a clear zonal pattern, with little change in the tropics (by a factor of only 1.6-2.8) and greater change in the mid-latitudes of both hemispheres (by a factor of 3.3-14). By contrast, Greenland ice-core records show a reduction in temperature variability by a factor of 73, suggesting influences beyond local temperature or a decoupling of atmospheric and global surface temperature variability for Greenland. The overall pattern of reduced variability can be explained by changes in the meridional temperature gradient, a mechanism that points to further decreases in temperature variability in a warmer future.

An Observationally-Centred Method to Quantify the Changing Shape of Local Temperature Distributions

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2014-12-01

For climate sensitive decisions and adaptation planning, guidance on how local climate is changing is needed at the specific thresholds relevant to particular impacts or policy endeavours. This requires the quantification of how the distributions of variables, such as daily temperature, are changing at specific quantiles. These temperature distributions are non-normal and vary both geographically and in time. We present a method[1,2] for analysing local climatic time series data to assess which quantiles of the local climatic distribution show the greatest and most robust changes. We have demonstrated this approach using the E-OBS gridded dataset[3] which consists of time series of local daily temperature 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. The change in temperature can be tracked at a temperature threshold, at a likelihood, or at a given return time, independently for each geographical location. Geographical correlations are thus an output of our method and reflect both climatic properties (local and synoptic), and spatial correlations inherent in the observation methodology. We find as an output many regionally consistent patterns of response of potential value in adaptation planning. For instance, in a band from Northern France to Denmark the hottest days in the summer temperature distribution have seen changes of at least 2°C over a 43 year period; over four times the global mean change over the same period. We discuss methods to quantify the robustness of these observed sensitivities and their statistical likelihood. This approach also quantifies the level of detail at which one might wish to see agreement between climate models and observations if such models are to be used directly as tools to assess climate change impacts at local scales. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, Phil. Trans. R. Soc. A, 371 20120287. [2] D A Stainforth, S C Chapman, N W Watkins, 2013, Environ. Res. Lett. 8, 034031 [3] Haylock, M.R. et al., 2008, J. Geophys. Res (Atmospheres), 113, D20119

Hydroclimatic variability in the Lake Mondsee region and its relationships with large-scale climate anomaly patterns

NASA Astrophysics Data System (ADS)

Rimbu, Norel; Ionita, Monica; Swierczynski, Tina; Brauer, Achim; Kämpf, Lucas; Czymzik, Markus

2017-04-01

Flood triggered detrital layers in varved sediments of Lake Mondsee, located at the northern fringe of the European Alps (47°48'N,13°23'E), provide an important archive of regional hydroclimatic variability during the mid- to late Holocene. To improve the interpretation of the flood layer record in terms of large-scale climate variability, we investigate the relationships between observational hydrological records from the region, like the Mondsee lake level, the runoff of the lake's main inflow Griesler Ache, with observed precipitation and global climate patterns. The lake level shows a strong positive linear trend during the observational period in all seasons. Additionally, lake level presents important interannual to multidecadal variations. These variations are associated with distinct seasonal atmospheric circulation patterns. A pronounced anomalous anticyclonic center over the Iberian Peninsula is associated with high lake levels values during winter. This center moves southwestward during spring, summer and autumn. In the same time, a cyclonic anomaly center is recorded over central and western Europe. This anomalous circulation extends southwestward from winter to autumn. Similar atmospheric circulation patterns are associated with river runoff and precipitation variability from the region. High lake levels are associated with positive local precipitation anomalies in all seasons as well as with negative local temperature anomalies during spring, summer and autumn. A correlation analysis reveals that lake level, runoff and precipitation variability is related to large-scale sea surface temperature anomaly patterns in all seasons suggesting a possible impact of large-scale climatic modes, like the North Atlantic Oscillation and Atlantic Multidecadal Oscillation on hydroclimatic variability in the Lake Mondsee region. The results presented in this study can be used for a more robust interpretation of the long flood layer record from Lake Mondsee sediments in terms of regional and large-scale climate variability during the past.

A new method to detect transitory signatures and local time/space variability structures in the climate system: the scale-dependent correlation analysis

NASA Astrophysics Data System (ADS)

Rodó, Xavier; Rodríguez-Arias, Miquel-Àngel

2006-10-01

The study of transitory signals and local variability structures in both/either time and space and their role as sources of climatic memory, is an important but often neglected topic in climate research despite its obvious importance and extensive coverage in the literature. Transitory signals arise either from non-linearities, in the climate system, transitory atmosphere-ocean couplings, and other processes in the climate system evolving after a critical threshold is crossed. These temporary interactions that, though intense, may not last long, can be responsible for a large amount of unexplained variability but are normally considered of limited relevance and often, discarded. With most of the current techniques at hand these typology of signatures are difficult to isolate because the low signal-to-noise ratio in midlatitudes, the limited recurrence of the transitory signals during a customary interval of data considered. Also, there is often a serious problem arising from the smoothing of local or transitory processes if statistical techniques are applied, that consider all the length of data available, rather than taking into account the size of the specific variability structure under investigation. Scale-dependent correlation (SDC) analysis is a new statistical method capable of highlighting the presence of transitory processes, these former being understood as temporary significant lag-dependent autocovariance in a single series, or covariance structures between two series. This approach, therefore, complements other approaches such as those resulting from the families of wavelet analysis, singular-spectrum analysis and recurrence plots. A main feature of SDC is its high-performance for short time series, its ability to characterize phase-relationships and thresholds in the bivariate domain. Ultimately, SDC helps tracking short-lagged relationships among processes that locally or temporarily couple and uncouple. The use of SDC is illustrated in the present paper by means of some synthetic time-series examples of increasing complexity, and it is compared with wavelet analysis in order to provide a well-known reference of its capabilities. A comparison between SDC and companion techniques is also addressed and results are exemplified for the specific case of some relevant El Niño-Southern Oscillation teleconnections.

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

PubMed Central

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

2012-01-01

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

Climate variables explain neutral and adaptive variation within salmonid metapopulations: The importance of replication in landscape genetics

USGS Publications Warehouse

Hand, Brian K.; Muhlfeld, Clint C.; Wade, Alisa A.; Kovach, Ryan; Whited, Diane C.; Narum, Shawn R.; Matala, Andrew P.; Ackerman, Michael W.; Garner, B. A.; Kimball, John S; Stanford, Jack A.; Luikart, Gordon

2016-01-01

Understanding how environmental variation influences population genetic structure is important for conservation management because it can reveal how human stressors influence population connectivity, genetic diversity and persistence. We used riverscape genetics modelling to assess whether climatic and habitat variables were related to neutral and adaptive patterns of genetic differentiation (population-specific and pairwise FST) within five metapopulations (79 populations, 4583 individuals) of steelhead trout (Oncorhynchus mykiss) in the Columbia River Basin, USA. Using 151 putatively neutral and 29 candidate adaptive SNP loci, we found that climate-related variables (winter precipitation, summer maximum temperature, winter highest 5% flow events and summer mean flow) best explained neutral and adaptive patterns of genetic differentiation within metapopulations, suggesting that climatic variation likely influences both demography (neutral variation) and local adaptation (adaptive variation). However, we did not observe consistent relationships between climate variables and FST across all metapopulations, underscoring the need for replication when extrapolating results from one scale to another (e.g. basin-wide to the metapopulation scale). Sensitivity analysis (leave-one-population-out) revealed consistent relationships between climate variables and FST within three metapopulations; however, these patterns were not consistent in two metapopulations likely due to small sample sizes (N = 10). These results provide correlative evidence that climatic variation has shaped the genetic structure of steelhead populations and highlight the need for replication and sensitivity analyses in land and riverscape genetics.

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.

Spatial synchrony of local populations has increased in association with the recent Northern Hemisphere climate trend.

PubMed

Post, Eric; Forchhammer, Mads C

2004-06-22

According to ecological theory, populations whose dynamics are entrained by environmental correlation face increased extinction risk as environmental conditions become more synchronized spatially. This prediction is highly relevant to the study of ecological consequences of climate change. Recent empirical studies have indicated, for example, that large-scale climate synchronizes trophic interactions and population dynamics over broad spatial scales in freshwater and terrestrial systems. Here, we present an analysis of century-scale, spatially replicated data on local weather and the population dynamics of caribou in Greenland. Our results indicate that spatial autocorrelation in local weather has increased with large-scale climatic warming. This increase in spatial synchrony of environmental conditions has been matched, in turn, by an increase in the spatial synchrony of local caribou populations toward the end of the 20th century. Our results indicate that spatial synchrony in environmental conditions and the populations influenced by them are highly variable through time and can increase with climatic warming. We suggest that if future warming can increase population synchrony, it may also increase extinction risk.

Modeling of local sea level rise and its future projection under climate change using regional information through EOF analysis

NASA Astrophysics Data System (ADS)

Naren, A.; Maity, Rajib

2017-12-01

Sea level rise is one of the manifestations of climate change and may cause a threat to the coastal regions. Estimates from global circulation models (GCMs) are either not available on coastal locations due to their coarse spatial resolution or not reliable since the mismatch between (interpolated) GCM estimates at coastal locations and actual observation over historical period is significantly different. We propose a semi-empirical framework to model the local sea level rise (SLR) using the possibly existing relationship between local SLR and regional atmospheric/oceanic variables. Selection of set of input variables mostly based on the literature bears the signature of both atmospheric and oceanic variables that possibly have an effect on SLR. The proposed approach offers a method to extract the combined information hidden in the regional fields of atmospheric/oceanic variables for a specific target coastal location. Generality of the approach ensures the inclusion of more variables in the set of inputs depending on the geographical location of any coastal station. For demonstration, 14 coastal locations along the Indian coast and islands are considered and a set of regional atmospheric and oceanic variables are considered. After development and validation of the model at each coastal location with the historical data, the model is further used for future projection of local SLR up to the year 2100 for three different future emission scenarios represented by representative concentration pathways (RCPs)—RCP2.6, RCP4.5, and RCP8.5. The maximum projected SLR is found to vary from 260.65 to 393.16 mm (RCP8.5) by the end of 2100 among the locations considered. Outcome of the proposed approach is expected to be useful in regional coastal management and in developing mitigation strategies in a changing climate.

Millennial-scale variability in the local radiocarbon reservoir age of the Florida Keys reef tract during the Holocene

NASA Astrophysics Data System (ADS)

Ashe, E.; Toth, L. T.; Cheng, H.; Edwards, R. L.; Richey, J. N.

2016-12-01

The oceanic passage between the Florida Keys and Cuba, known as the Straits of Florida, provides a critical connection between the tropics and northern Atlantic. Changes in the character of water masses transported through this region may ultimately have important impacts on high-latitude climate variability. Although recent studies have documented significant changes in the density of regional surface waters over millennial timescales, little is known about the contribution of local- to regional-scale changes in circulation to surface-water variability. Local variability in the radiocarbon age, ΔR, of surface waters can be used to trace changes in local water-column mixing and/or changes in regional source water over a variety of spatial and temporal scales. We reconstructed "snapshots" of ΔR variability across the Florida Keys reef tract during the last 10,000 years by dating 68 unaltered corals collected from Holocene reef cores with both U-series and radiocarbon techniques. We combined the snapshots of ΔR into a semi-empirical model to develop a robust statistical reconstruction of millennial-scale variability in ΔR on the Florida Keys reef tract. Our model demonstrates that ΔR varied significantly during the Holocene, with relatively high values during the early Holocene and around 3000 years BP and relatively low values around 7000 years BP and at present. We compare the trends in ΔR to existing paleoceanographic reconstructions to evaluate the relative contribution of local upwelling versus changes in source water to the region as a whole in driving local radiocarbon variability, and discuss the importance of these results to our understanding of regional-scale oceanographic and climatic variability during the Holocene. We also discuss the implications of our results for radiocarbon dating of marine samples from south Florida and present a model of ΔR versus 14C age that can be used to improve the accuracy of radiocarbon calibrations from this region.

Blending Pan-European and local hydrological models for water resource assessment in Mediterranean areas: lessons learnt from a mountainous catchment

NASA Astrophysics Data System (ADS)

José Polo, María; José Pérez-Palazón, María; Saénz de Rodrigáñez, Marta; Pimentel, Rafael; Arheimer, Berit

2017-04-01

Global hydrological models provide scientists and technicians with distributed data over medium to large areas from which assessment of water resource planning and use can be easily performed. However, scale conflicts between global models' spatial resolution and the local significant spatial scales in heterogeneous areas usually pose a constraint for the direct use and application of these models' results. The SWICCA (Service for Water Indicators in Climate Change Adaptation) Platform developed under the Copernicus Climate Change Service (C3S) offers a wide range of both climate and hydrological indicators obtained on a global scale with different time and spatial resolutions. Among the different study cases supporting the SWICCA demonstration of local impact assessment, the Sierra Nevada study case (South Spain) is a representative example of mountainous coastal catchments in the Mediterranean region. This work shows the lessons learnt during the study case development to derive local impact indicator tailored to suit the local end-users of water resource in this snow-dominated area. Different approaches were followed to select the most accurate method to downscale the global data and variables to the local level in a highly abrupt topography, in a sequential step approach. 1) SWICCA global climate variable downscaling followed by river flow simulation from a local hydrological model in selected control points in the catchment, together with 2) SWICCA global river flow values downscaling to the control points followed by corrections with local transfer functions were both tested against the available local river flow series of observations during the reference period. This test was performed for the different models and the available spatial resolutions included in the SWICCA platform. From the results, the second option, that is, the use of SWICCA river flow variables, performed the best approximations, once the local transfer functions were applied to the global values and an additional correction was performed based on the relative anomalies obtained instead of the absolute values. This approach was used to derive the future projections of selected local indicators for each end-user in the area under different climate change scenarios. Despite the spatial scale conflicts, the SWICCA river flow indicators (simulated by the E-HYPEv3.1.2 model) succeeded in approximating the observations during the reference period 1970-2000 when provided on a catchment scale, once local transfer functions and further anomaly correction were performed. Satisfactory results were obtained on a monthly scale for river flow in the main stream of the watershed, and on a daily scale for the headwater streams. The accessibility to the hydrological model WiMMed, which includes a snow module, locally validated in the study area has been crucial to downscale the SWICCA results and prove their usefulness.

A regime shift in the Sun-Climate connection with the end of the Medieval Climate Anomaly.

PubMed

Smirnov, D A; Breitenbach, S F M; Feulner, G; Lechleitner, F A; Prufer, K M; Baldini, J U L; Marwan, N; Kurths, J

2017-09-11

Understanding the influence of changes in solar activity on Earth's climate and distinguishing it from other forcings, such as volcanic activity, remains a major challenge for palaeoclimatology. This problem is best approached by investigating how these variables influenced past climate conditions as recorded in high precision paleoclimate archives. In particular, determining if the climate system response to these forcings changes through time is critical. Here we use the Wiener-Granger causality approach along with well-established cross-correlation analysis to investigate the causal relationship between solar activity, volcanic forcing, and climate as reflected in well-established Intertropical Convergence Zone (ITCZ) rainfall proxy records from Yok Balum Cave, southern Belize. Our analysis reveals a consistent influence of volcanic activity on regional Central American climate over the last two millennia. However, the coupling between solar variability and local climate varied with time, with a regime shift around 1000-1300 CE after which the solar-climate coupling weakened considerably.

Regionally synchronous fires in interior British Columbia, Canada, driven by interannual climate variability and weakly associated with large-scale climate patterns between AD 1600-1900

NASA Astrophysics Data System (ADS)

Harvey, J. E.; Smith, D. J.

2016-12-01

We investigated the influence of climate variability on forest fire occurrence in west central British Columbia (BC), Canada, between AD 1600 and 1900. Fire history was reconstructed at 8 sites in the Cariboo-Chilcotin region and we identified 46 local (fires that affected 1 site) and 16 moderate (fires that affected 2 sites) fires. Preexisting fire history data collected from nearby sites was incorporated to identify 17 regionally synchronous fire years (fires that affected ³ 3 sites). Interannual and multidecadal relationships between fire occurrence and the Palmer Drought Severity Index (PDSI), El Nino Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and the Pacific North American (PNA) pattern were examined, in addition to the effects of phase interactions between ENSO and PDO. We examined multiple reconstructions of PDO and ENSO and utilized three methodological approaches to characterize climate-fire relationships. We found that the influence of interannual climate expressed as PDSI, increasingly synchronized the occurrence of of fires from local to regional fires. Regional fires were associated with anomalously dry, warm conditions in the year of the fire and in years preceding the fire. We also identified an association between local fires and antecedent moisture conditions, where wetter and cooler conditions persisted 2-3 years prior to fire. This finding suggests that moisture-driven fine fuel development and proximity to grasslands could function as key determinants of local (small-scale) fire history parameters. The relationships we identified between regional fires and ENSO, PDO and PNA suggest that large-scale patterns of climate variability exert a weak and/or inconsistent influence over fire activity in west central BC between AD 1600-1900. The strongest relationships between regional fires and large-scale climate patterns were identified when ENSO and PDO were both in positive phases. We also documented a relationship between regional fires and positive years of the PNA pattern. Our findings suggest that long-term fire planning using predictions of large scale climate patterns may be limited in west central BC, however, the consideration of additive phases of ENSO and PDO, and the PNA pattern, may be effective and has been suggested by others in the inland Pacific Northwest.

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

PubMed

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

2015-05-01

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

Response of Urban Systems to Climate Change in Europe: Heat Stress Exposure and the Effect on Human Health

NASA Astrophysics Data System (ADS)

Stevens, Catherine; Thomas, Bart; Grommen, Mart

2015-04-01

Climate change is driven by global processes such as the global ocean circulation and its variability over time leading to changing weather patterns on regional scales as well as changes in the severity and occurrence of extreme events such as heavy rain- and windstorms, floods, drought, heat waves, etc. The summer 2003 European heat wave was the hottest summer on record in Europe over the past centuries leading to health crises in several countries like France and caused up to 70.000 excess deaths over four months in Central and Western Europe. The main risks induced by global climate change in urbanised areas are considered to be overheating and resulting health effects, increased exposure to flood events, increased damage losses from extreme weather conditions but also shortages in the provision of life-sustaining services. Moreover, the cities themselves create specific or inherent risks and urban adaptation is often very demanding. As most of Europe's inhabitants live in cities, it is of particular relevance to examine the impact of climate variability on urban areas and their populations. The present study focusses on the identification of heat stress variables related to human health and the extraction of this information by processing daily temperature statistics of local urban climate simulations over multiple timeframes of 20 years and three different European cities based on recent, near future and far future global climate predictions. The analyses have been conducted in the framework of the NACLIM FP7 project funded by the European Commission involving local stakeholders such as the cities of Antwerp (Belgium), Berlin (Germany) and Almada (Portugal) represented by different climate and urban characteristics. Apart from the urban-rural temperature increment (urban heat island effect), additional heat stress parameters such as the average number of heat wave days together with their duration and intensities have been covered during this research. In a subsequent step, the heat stress variables are superposed on relevant socio-economic datasets targeting total population and its distribution per age class as well as vulnerable institutions such as hospitals, schools, rest homes and child/day care facilities in order to generate heat stress exposure maps for each use case city and various climate, urban planning and mitigation scenarios. The specifications and requirements for the various scenarios have been consolidated in close collaboration with the local stakeholders during dedicated end-users workshops. The results of this study will allow urban planners and policy makers facing the challenges of climate change and develop sound strategies for evolving towards sustainable and climate resilient cities.

Impact of transient climate change upon Grouse population dynamics in the Italian Alps

NASA Astrophysics Data System (ADS)

Pirovano, Andrea; Bocchiola, Daniele

2010-05-01

Understanding the effect of short to medium term weather condition, and of transient global warming upon wildlife species life history is essential to predict the demographic consequences therein, and possibly develop adaptation strategies, especially in game species, where hunting mortality may play an important role in population dynamics. We carried out a preliminary investigation of observed impact of weather variables upon population dynamics indexes of three alpine Grouse species (i.e. Rock Ptarmigan, Lagopus Mutus, Black Grouse, Tetrao Tetrix, Rock Partridge, Alectoris Graeca), nested within central Italian Alps, based upon 15 years (1995-2009) of available censuses data, provided by the Sondrio Province authority. We used a set of climate variables already highlighted within recent literature for carrying considerable bearing on Grouse population dynamics, including e.g. temperature at hatching time and during winter, snow cover at nesting, and precipitation during nursing period. We then developed models of Grouses' population dynamics by explicitly driving population change according to their dependence upon the significant weather variables and population density and we evaluated objective indexes to assess the so obtained predictive power. Eventually, we develop projection of future local climate, based upon locally derived trends, and upon projections from GCMs (A2 IPCC storyline) already validated for the area, to project forward in time (until 2100 or so) the significant climatic variables, which we then use to force population dynamics models of the target species. The projected patterns obtained through this exercise are discussed and compared against those expected under stationary climate conditions at present, and preliminary conclusions are drawn.

Adaptation to Climatic Hazards in the Savannah Ecosystem: Improving Adaptation Policy and Action

NASA Astrophysics Data System (ADS)

Yiran, Gerald A. B.; Stringer, Lindsay C.

2017-10-01

People in Ghana's savannah ecosystem have historically experienced a range of climatic hazards that have affected their livelihoods. In view of current climate variability and change, and projected increases in extreme events, adaptation to climate risks is vital. Policies have been put in place to enhance adaptation across sub-Saharan Africa in accordance with international agreements. At the same time, local people, through experience, have learned to adapt. This paper examines current policy actions and their implementation alongside an assessment of barriers to local adaptation. In doing so it links adaptation policy and practice. Policy documents were analysed that covered key livelihood sectors, which were identified as climate sensitive. These included agriculture, water, housing and health policies, as well as the National Climate Change Policy. In-depth interviews and focus group discussions were also held with key stakeholders in the Upper East Region of Ghana. Analyses were carried using thematic content analysis. Although policies and actions complement each other, their integration is weak. Financial, institutional, social, and technological barriers hinder successful local implementation of some policy actions, while lack of local involvement in policy formulation also hinders adaptation practice. Integration of local perspectives into policy needs to be strengthened in order to enhance adaptation. Coupled with this is a need to consider adaptation to climate change in development policies and to pursue efforts to reduce or remove the key barriers to implementation at the local level.

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

El Niño, Climate, and Cholera Associations in Piura, Peru, 1991-2001: A Wavelet Analysis.

PubMed

Ramírez, Iván J; Grady, Sue C

2016-03-01

In Peru, it was hypothesized that epidemic cholera in 1991 was linked to El Niño, the warm phase of El Niño-Southern Oscillation. While previous studies demonstrated an association in 1997-1998, using cross-sectional data, they did not assess the consistency of this relationship across the decade. Thus, how strong or variable an El Niño-cholera relationship was in Peru or whether El Niño triggered epidemic cholera early in the decade remains unknown. In this study, wavelet and mediation analyses were used to characterize temporal patterns among El Niño, local climate variables (rainfall, river discharge, and air temperature), and cholera incidence in Piura, Peru from 1991 to 2001 and to estimate the mediating effects of local climate on El Niño-cholera relationships. The study hypothesis is that El Niño-related connections with cholera in Piura were transient and interconnected via local climate pathways. Overall, our findings provide evidence that a strong El Niño-cholera link, mediated by local hydrology, existed in the latter part of the 1990s but found no evidence of an El Niño association in the earlier part of the decade, suggesting that El Niño may not have precipitated cholera emergence in Piura. Further examinations of cholera epicenters in Peru are recommended to support these results in Piura. For public health planning, the results may improve existing efforts that utilize El Niño monitoring for preparedness during future climate-related extremes in the region.

Generating High Resolution Climate Scenarios Through Regional Climate Modelling Over Southern Africa

NASA Astrophysics Data System (ADS)

Ndhlovu, G. Z.; Woyessa, Y. E.; Vijayaraghavan, S.

2017-12-01

limate change has impacted the global environment and the Continent of Africa, especially Southern Africa, regarded as one of the most vulnerable regions in Africa, has not been spared from these impacts. Global Climate Models (GCMs) with coarse horizontal resolutions of 150-300 km do not provide sufficient details at the local basin scale due to mismatch between the size of river basins and the grid cell of the GCM. This makes it difficult to apply the outputs of GCMs directly to impact studies such as hydrological modelling. This necessitates the use of regional climate modelling at high resolutions that provide detailed information at regional and local scales to study both climate change and its impacts. To this end, an experiment was set up and conducted with PRECIS, a regional climate model, to generate climate scenarios at a high resolution of 25km for the local region in Zambezi River basin of Southern Africa. The major input data used included lateral and surface boundary conditions based on the GCMs. The data is processed, analysed and compared with CORDEX climate change project data generated for Africa. This paper, highlights the major differences of the climate scenarios generated by PRECIS Model and CORDEX Project for Africa and further gives recommendations for further research on generation of climate scenarios. The climatic variables such as precipitation and temperatures have been analysed for flood and droughts in the region. The paper also describes the setting up and running of an experiment using a high-resolution PRECIS model. In addition, a description has been made in running the model and generating the output variables on a sub basin scale. Regional climate modelling which provides information on climate change impact may lead to enhanced understanding of adaptive water resources management. Understanding the regional climate modelling results on sub basin scale is the first step in analysing complex hydrological processes and a basis for designing of adaptation and mitigation strategies in the region. Key words: Climate change, regional climate modelling, hydrological processes, extremes, scenarios [1] Corresponding author: Email:gndhlovu@cut.ac.za Tel:+27 (0) 51 507 3072

The periodicity of Plasmodium vivax and Plasmodium falciparum in Venezuela.

PubMed

Grillet, María-Eugenia; El Souki, Mayida; Laguna, Francisco; León, José Rafael

2014-01-01

We investigated the periodicity of Plasmodium vivax and P. falciparum incidence in time-series of malaria data (1990-2010) from three endemic regions in Venezuela. In particular, we determined whether disease epidemics were related to local climate variability and regional climate anomalies such as the El Niño Southern Oscillation (ENSO). Malaria periodicity was found to exhibit unique features in each studied region. Significant multi-annual cycles of 2- to about 6-year periods were identified. The inter-annual variability of malaria cases was coherent with that of SSTs (ENSO), mainly at temporal scales within the 3-6 year periods. Additionally, malaria cases were intensified approximately 1 year after an El Niño event, a pattern that highlights the role of climate inter-annual variability in the epidemic patterns. Rainfall mediated the effect of ENSO on malaria locally. Particularly, rains from the last phase of the season had a critical role in the temporal dynamics of Plasmodium. The malaria-climate relationship was complex and transient, varying in strength with the region and species. By identifying temporal cycles of malaria we have made a first step in predicting high-risk years in Venezuela. Our findings emphasize the importance of analyzing high-resolution spatial-temporal data to better understand malaria transmission dynamics. Copyright © 2013 Elsevier B.V. All rights reserved.

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

PubMed

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

2017-06-14

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

The local and global climate forcings induced inhomogeneity of Indian rainfall.

PubMed

Nair, P J; Chakraborty, A; Varikoden, H; Francis, P A; Kuttippurath, J

2018-04-16

India is home for more than a billion people and its economy is largely based on agrarian society. Therefore, rainfall received not only decides its livelihood, but also influences its water security and economy. This situation warrants continuous surveillance and analysis of Indian rainfall. These kinds of studies would also help forecasters to better tune their models for accurate weather prediction. Here, we introduce a new method for estimating variability and trends in rainfall over different climate regions of India. The method based on multiple linear regression helps to assess contributions of different remote and local climate forcings to seasonal and regional inhomogeneity in rainfall. We show that the Indian Summer Monsoon Rainfall (ISMR) variability is governed by Eastern and Central Pacific El Niño Southern Oscillation, equatorial zonal winds, Atlantic zonal mode and surface temperatures of the Arabian Sea and Bay of Bengal, and the North East Monsoon Rainfall variability is controlled by the sea surface temperature of the North Atlantic and extratropial oceans. Also, our analyses reveal significant positive trends (0.43 mm/day/dec) in the North West for ISMR in the 1979-2017 period. This study cautions against the significant changes in Indian rainfall in a perspective of global climate change.

Geographic variation in opinions on climate change at state and local scales in the USA

NASA Astrophysics Data System (ADS)

Howe, Peter D.; Mildenberger, Matto; Marlon, Jennifer R.; Leiserowitz, Anthony

2015-06-01

Addressing climate change in the United States requires enactment of national, state and local mitigation and adaptation policies. The success of these initiatives depends on public opinion, policy support and behaviours at appropriate scales. Public opinion, however, is typically measured with national surveys that obscure geographic variability across regions, states and localities. Here we present independently validated high-resolution opinion estimates using a multilevel regression and poststratification model. The model accurately predicts climate change beliefs, risk perceptions and policy preferences at the state, congressional district, metropolitan and county levels, using a concise set of demographic and geographic predictors. The analysis finds substantial variation in public opinion across the nation. Nationally, 63% of Americans believe global warming is happening, but county-level estimates range from 43 to 80%, leading to a diversity of political environments for climate policy. These estimates provide an important new source of information for policymakers, educators and scientists to more effectively address the challenges of climate change.

Land Cover Land Use change and soil organic carbon under climate variability in the semi-arid West African Sahel (1960-2050)

NASA Astrophysics Data System (ADS)

Dieye, Amadou M.

Land Cover Land Use (LCLU) change affects land surface processes recognized to influence climate change at local, national and global levels. Soil organic carbon is a key component for the functioning of agro-ecosystems and has a direct effect on the physical, chemical and biological characteristics of the soil. The capacity to model and project LCLU change is of considerable interest for mitigation and adaptation measures in response to climate change. A combination of remote sensing analyses, qualitative social survey techniques, and biogeochemical modeling was used to study the relationships between climate change, LCLU change and soil organic carbon in the semi-arid rural zone of Senegal between 1960 and 2050. For this purpose, four research hypotheses were addressed. This research aims to contribute to an understanding of future land cover land use change in the semi-arid West African Sahel with respect to climate variability and human activities. Its findings may provide insights to enable policy makers at local to national levels to formulate environmentally and economically adapted policy decisions. This dissertation research has to date resulted in two published and one submitted paper.

Influence of spatial resolution on precipitation simulations for the central Andes Mountains

NASA Astrophysics Data System (ADS)

Trachte, Katja; Bendix, Jörg

2013-04-01

The climate of South America is highly influenced by the north-south oriented Andes Mountains. Their complex structure causes modifications of large-scale atmospheric circulations resulting in various mesoscale phenomena as well as a high variability in the local conditions. Due to their height and length the terrain generates distinctly climate conditions between the western and the eastern slopes. While in the tropical regions along the western flanks the conditions are cold and arid, the eastern slopes are dominated by warm-moist and rainy air coming from the Amazon basin. Below 35° S the situation reverses with rather semiarid conditions in the eastern part and temperate rainy climate along southern Chile. Generally, global circulation models (GCMs) describe the state of the global climate and its changes, but are disabled to capture regional or even local features due to their coarse resolution. This is particularly true in heterogeneous regions such as the Andes Mountains, where local driving features, e. g. local circulation systems, highly varies on small scales and thus, lead to a high variability of rainfall distributions. An appropriate technique to overcome this problem and to gain regional and local scale rainfall information is the dynamical downscaling of the global data using a regional climate model (RCM). The poster presents results of the evaluation of the performance of the Weather Research and Forecasting (WRF) model over South America with special focus on the central Andes Mountains of Ecuador. A sensitivity study regarding the cumulus parametrization, microphysics, boundary layer processes and the radiation budget is conducted. With 17 simulations consisting of 16 parametrization scheme combinations and 1 default run a suitable model set-up for climate research in this region is supposed to be evaluated. The simulations were conducted in a two-way nested mode i) to examine the best physics scheme combination for the target and ii) to analyze the impact of spatial resolution and thus, the representation of the terrain on the result.

ENSO-driven climate variability promotes periodic major outbreaks of dengue in Venezuela.

PubMed

Vincenti-Gonzalez, M F; Tami, A; Lizarazo, E F; Grillet, M E

2018-04-10

Dengue is a mosquito-borne viral disease of global impact. In Venezuela, dengue has emerged as one of the most important public health problems of urban areas with frequent epidemics since 2001. The long-term pattern of this disease has involved not only a general upward trend in cases but also a dramatic increase in the size and frequency of epidemic outbreaks. By assuming that climate variability has a relevant influence on these changes in time, we quantified the periodicity of dengue incidence in time-series of data from two northern regions of Venezuela. Disease cycles of 1 and 3-4 years (p < 0.05) were detected. We determined that dengue cycles corresponded with local climate and the El Niño Southern Oscillation (ENSO) variation at both seasonal and inter-annual scales (every 2-3 years). Dengue incidence peaks were more prevalent during the warmer and dryer years of El Niño confirming that ENSO is a regional climatic driver of such long-term periodicity through local changes in temperature and rainfall. Our findings support the evidence of the effect of climate on dengue dynamics and advocate the incorporation of climate information in the surveillance and prediction of this arboviral disease in Venezuela.

Single-Locus versus Multilocus Patterns of Local Adaptation to Climate in Eastern White Pine (Pinus strobus, Pinaceae)

PubMed Central

Zinck, John W. R.

2016-01-01

Natural plant populations are often adapted to their local climate and environmental conditions, and populations of forest trees offer some of the best examples of this pattern. However, little empirical work has focused on the relative contribution of single-locus versus multilocus effects to the genetic architecture of local adaptation in plants/forest trees. Here, we employ eastern white pine (Pinus strobus) to test the hypothesis that it is the inter-genic effects that primarily drive climate-induced local adaptation. The genetic structure of 29 range-wide natural populations of eastern white pine was determined in relation to local climatic factors using both a reference set of SSR markers, and SNPs located in candidate genes putatively involved in adaptive response to climate. Comparisons were made between marker sets using standard single-locus outlier analysis, single-locus and multilocus environment association analyses and a novel implementation of Population Graphs. Magnitudes of population structure were similar between the two marker sets. Outlier loci consistent with diversifying selection were rare for both SNPs and SSRs. However, genetic distances based on the multilocus among population covariances (cGD) were significantly more correlated to climate, even after correcting for spatial effects, for SNPs as compared to SSRs. Coalescent simulations confirmed that the differences in mutation rates between SSRs and SNPs did not affect the topologies of the Population Graphs, and hence values of cGD and their correlations with associated climate variables. We conclude that the multilocus covariances among populations primarily reflect adaptation to local climate and environment in eastern white pine. This result highlights the complexity of the genetic architecture of adaptive traits, as well as the need to consider multilocus effects in studies of local adaptation. PMID:27387485

Holocene palaeohydrological history of the Tǎul Muced peat bog (Northern Carpathians, Romania) based on testate amoebae (Protozoa) and plant macrofossils

NASA Astrophysics Data System (ADS)

Cosmin Diaconu, Andrei; Feurdean, Angelica; Lamentowicz, Mariusz; Gałka, Mariusz; Tanţǎu, Ioan

2016-04-01

Knowledge of past local vs. regional hydro-climate variability is a priority in climate research. This is because ecosystems and human depend on local climatic conditions and the magnitude of these climate changes is more variable at local and regional rather than at global scales. Ombrotrophic bogs are highly suitable for hydro-climate reconstructions as they are entirely dependent on the water from precipitation. We used stratigraphy, radiocarbon dating, testate amoebae (TA) and plant macrofossils on a peat profile from an ombrotrophic bog (Tǎul Muced) located in the Biosphere Reserve of the Rodna National Park Romania. We performed quantitative reconstruction of the depth to water table (DWT) and pH over the last 8000 years in a continental area of CE Europe. We identified six main stages in the development of the bog based on changes in TA assemblages in time. Wet conditions and pH between 2 and 4.5 were recorded between 4600-2750 and 1300-400 cal. yr BP, by the occurrence of Archerella flavum, Amphitrema wrightianum and Hyalosphenia papilio. This was associated to a local vegetation primarily composed of Sphagnum magellanicum and S. angustifolium. Dry stages and pH of 2.5 to 5 were inferred between 7550-4600, 2750-1300 and -50 cal. yr BP, by the dominance of Nebela militaris, Difflugia pulex and Phryganella acropodia. These overall dry conditions were also connected with increased abundance of Eriophorum vaginatum. The period between 400 and -50 cal. yr BP was characterized by a rapid shift from dry to wet conditions on the surface of the bog. Vegetation shifted from Sphagnum magellanicum to Sphagnum russowii dominated community. Our reconstruction remains in relatively good agreement with other palaeohydrological records from Central Eastern Europe. However, it shows contrasting conditions to others particularly with records from NW Europe. The valuable information regarding bog hydrology offered by our record puts an accent on the need of more regional TA based reconstruction studies, to get a compressive picture of larger spatial scales of hydro-climate variability in Europe.

Choosing and using climate change scenarios for ecological-impact assessments and conservation decisions

USGS Publications Warehouse

Amy K. Snover,; Nathan J. Mantua,; Littell, Jeremy; Michael A. Alexander,; Michelle M. McClure,; Janet Nye,

2013-01-01

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment.

Climate variability and human impact in South America during the last 2000 years: synthesis and perspectives from pollen records

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2016-02-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation-climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America - 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

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.

Climate Trends and Farmers' Perceptions of Climate Change in Zambia.

PubMed

Mulenga, Brian P; Wineman, Ayala; Sitko, Nicholas J

2017-02-01

A number of studies use meteorological records to analyze climate trends and assess the impact of climate change on agricultural yields. While these provide quantitative evidence on climate trends and the likely effects thereof, they incorporate limited qualitative analysis of farmers' perceptions of climate change and/or variability. The present study builds on the quantitative methods used elsewhere to analyze climate trends, and in addition compares local narratives of climate change with evidence found in meteorological records in Zambia. Farmers offer remarkably consistent reports of a rainy season that is growing shorter and less predictable. For some climate parameters-notably, rising average temperature-there is a clear overlap between farmers' observations and patterns found in the meteorological records. However, the data do not support the perception that the rainy season used to begin earlier, and we generally do not detect a reported increase in the frequency of dry spells. Several explanations for these discrepancies are offered. Further, we provide policy recommendations to help farmers adapt to climate change/variability, as well as suggestions to shape future climate change policies, programs, and research in developing countries.

The CSAICLAWPS project: a multi-scalar, multi-data source approach to providing climate services for both modelling of climate change impacts on crop yields and development of community-level adaptive capacity for sustainable food security

NASA Astrophysics Data System (ADS)

Forsythe, N. D.; Fowler, H. J.

2017-12-01

The "Climate-smart agriculture implementation through community-focused pursuit of land and water productivity in South Asia" (CSAICLAWPS) project is a research initiative funded by the (UK) Royal Society through its Challenge Grants programme which is part of the broader UK Global Challenges Research Fund (GCRF). CSAICLAWPS has three objectives: a) development of "added-value" - bias assessed, statistically down-scaled - climate projections for selected case study sites across South Asia; b) investigation of crop failure modes under both present (observed) and future (projected) conditions; and c) facilitation of developing local adaptive capacity and resilience through stakeholder engagement. At AGU we will be presenting both next steps and progress to date toward these three objectives: [A] We have carried out bias assessments of a substantial multi-model RCM ensemble (MME) from the CORDEX South Asia (CORDEXdomain for case studies in three countries - Pakistan, India and Sri Lanka - and (stochastically) produced synthetic time-series for these sites from local observations using a Python-based implementation of the principles underlying the Climate Research Unit Weather Generator (CRU-WG) in order to enable probabilistic simulation of current crop yields. [B] We have characterised present response of local crop yields to climate variability in key case study sites using AquaCrop simulations parameterised based on input (agronomic practices, soil conditions, etc) from smallholder farmers. [C] We have implemented community-based hydro-climatological monitoring in several case study "revenue villages" (panchayats) in the Nainital District of Uttarakhand. The purpose of this is not only to increase availability of meteorological data, but also has the aspiration of, over time, leading to enhanced quantitative awareness of present climate variability and potential future conditions (as projected by RCMs). Next steps in our work will include: 1) future crop yield simulations driven by "perturbation" of synthetic time-series using "change factors from the CORDEX-SA MME; 2) stakeholder dialogues critically evaluating potential strategies at the grassroots (implementation) level to mitigate impacts of climate variability and change on crop yields.

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

PubMed

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

2017-01-01

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

The influence of local spring temperature variance on temperature sensitivity of spring phenology.

PubMed

Wang, Tao; Ottlé, Catherine; Peng, Shushi; Janssens, Ivan A; Lin, Xin; Poulter, Benjamin; Yue, Chao; Ciais, Philippe

2014-05-01

The impact of climate warming on the advancement of plant spring phenology has been heavily investigated over the last decade and there exists great variability among plants in their phenological sensitivity to temperature. However, few studies have explicitly linked phenological sensitivity to local climate variance. Here, we set out to test the hypothesis that the strength of phenological sensitivity declines with increased local spring temperature variance, by synthesizing results across ground observations. We assemble ground-based long-term (20-50 years) spring phenology database (PEP725 database) and the corresponding climate dataset. We find a prevalent decline in the strength of phenological sensitivity with increasing local spring temperature variance at the species level from ground observations. It suggests that plants might be less likely to track climatic warming at locations with larger local spring temperature variance. This might be related to the possibility that the frost risk could be higher in a larger local spring temperature variance and plants adapt to avoid this risk by relying more on other cues (e.g., high chill requirements, photoperiod) for spring phenology, thus suppressing phenological responses to spring warming. This study illuminates that local spring temperature variance is an understudied source in the study of phenological sensitivity and highlight the necessity of incorporating this factor to improve the predictability of plant responses to anthropogenic climate change in future studies. © 2013 John Wiley & Sons Ltd.

Urban Impact Assessment and Adaptation Strategies to Climate Change in Europe: A Case Study for Antwerp, Berlin and Almada

NASA Astrophysics Data System (ADS)

Stevens, Catherine; Thomas, Bart

2014-05-01

Climate change is driven by global processes such as the global ocean circulation and its variability over time leading to changing weather patterns on regional scales as well as changes in the severity and occurrence of extreme events such as heat waves. For example, the summer 2003 European heat wave caused up to 70.000 excess deaths over four months in Central and Western Europe. As around 75% of Europe's population resides in urban areas, it is of particular relevance to examine the impact of seasonal to decadal-scale climate variability on urban areas and their populations. This study aims at downscaling the spatially coarse resolution CMIP5 climate predictions to the local urban scale and investigating the relation between heat waves and the urban-rural temperature increment (urban heat island effect). The resulting heat stress effect is not only driven by climatic variables but also impacted by urban morphology. Moreover, the exposure varies significantly with the geographical location. All this information is coupled with relevant socio-economic datasets such as population density, age structure, etc. focussing on human health. The analyses are conducted in the framework of the NACLIM FP7 project funded by the European Commission involving local stakeholders such as the cities of Antwerp (BE), Berlin (DE) and Almada (PT) represented by different climate and urban characteristics. The end-user needs have been consolidated in a climate services plan including the production of heat risk exposure maps and the analysis of various scenarios considering e.g. the uncertainty of the global climate predictions, urban expansion over time and the impact of mitigation measures such as green roofs. The results of this study will allow urban planners and policy makers facing the challenges of climate change and develop sound strategies for the design and management of climate resilient cities.

Household perceptions of coastal hazards and climate change in the Central Philippines.

PubMed

Combest-Friedman, Chelsea; Christie, Patrick; Miles, Edward

2012-12-15

As a tropical archipelagic nation, the Philippines is particularly susceptible to coastal hazards, which are likely to be exacerbated by climate change. To improve coastal hazard management and adaptation planning, it is imperative that climate information be provided at relevant scales and that decision-makers understand the causes and nature of risk in their constituencies. Focusing on a municipality in the Central Philippines, this study examines local meteorological information and explores household perceptions of climate change and coastal hazard risk. First, meteorological data and local perceptions of changing climate conditions are assessed. Perceived changes in climate include an increase in rainfall and rainfall variability, an increase in intensity and frequency of storm events and sea level rise. Second, factors affecting climate change perceptions and perceived risk from coastal hazards are determined through statistical analysis. Factors tested include social status, economic standing, resource dependency and spatial location. Results indicate that perceived risk to coastal hazards is most affected by households' spatial location and resource dependency, rather than socio-economic conditions. However, important differences exist based on the type of hazard and nature of risk being measured. Resource dependency variables are more significant in determining perceived risk from coastal erosion and sea level rise than flood events. Spatial location is most significant in determining households' perceived risk to their household assets, but not perceived risk to their livelihood. Copyright © 2012 Elsevier Ltd. All rights reserved.

Analyzing changes in the beef cattle ranching communities of acatic and tepatitlan de morelos, jalisco, Mexico related to land cover and climate variability

NASA Astrophysics Data System (ADS)

Trevino-Pena, Melva B.

The impacts of climate change on the environment at the global scale can be determined through the use of large-scale circulation models; however, the results from these models are difficult to interpret at the regional or local levels. Regional vulnerability analyses consider the knowledge of locals, which may provide insight into the effects of climate variability on the environment at smaller scales, and most importantly, the effects that these developments are having on society. The objective of this research was to analyze the vulnerability to climate variability of the beef cattle ranching communities of the municipalities of Acatic and of Tepatitlan de Morelos, Jalisco, Mexico. These municipalities are found in a region of the state referred to as "Los Altos". The economy of Los Altos largely relies on agricultural and farming practices; these sectors provide the largest source of employment in the area. In the two municipalities that comprise the study area, the beef cattle industry is one of the strongest economic activities. Climate variability poses great threat on these communities because the main economic activities of the region are highly dependent on natural resources. To have a better understanding of the human-environment interactions in this region, remote sensing methods were applied. Three Landsat Thematic Mapper (TM) images (years: 1985, 1993 and 2000) were employed to generate land use and land cover classification maps of the study area; these maps were then subjected to a change detections analysis. Some of the land use and land cover categories experienced more change than others; among those was the category of water, shrub land and crop land. The area covered by water nearly doubled from 1985 to 1993 and then nearly decreased by half by the year 2000. From 1985 to 1993, here was a decrease in the shrub land of about 1200 ha and concurrently an increase in the crop land of about 1400 ha. From 1993 to 2000 there was an increase in the shrub land category of about 430 ha and a decrease in the crop land category of about 690 ha. To gain insight into the effects of climate variability on the livelihoods of these communities, nine local beef cattle ranchers were interviewed on a one-on-one basis. All participants believe that the local beef cattle industry is highly valuable to the economy and culture of the region. All participants also mentioned that notable variations in to the climate have been occurring in recent decades; mainly precipitation scarcity and higher temperatures. The locals believe that these changes are the result of extensive deforestation. In past decades, deforestation of native vegetation has been intensely performed in order to make land available for agricultural purposes. Therefore, among the various adaptation measures to the changes presented in the climate, the cattle ranchers talked about planting trees. People believe that the "vision" of the region is changing and that reforestation has become a priority in this land. To determine the exact causes of the climate changes experienced in this region, further investigations have to be done. However, it is certain that these changes are having implications on the economic activities of the region; the people of these communities will continue facing difficulties if the present changes in the regional climate continue to develop. The employment of proper adaptation measures has the potential to reduce climate-related losses within the livestock and agricultural sectors. Therefore, it is crucial that preventive measures are taken by the members of these communities before the effects of climate change worsen in the region.

Relating large-scale climate variability to local species abundance: ENSO forcing and shrimp in Breton Sound, Louisiana, USA

USGS Publications Warehouse

Piazza, Bryan P.; LaPeyre, Megan K.; Keim, B.D.

2010-01-01

Climate creates environmental constraints (filters) that affect the abundance and distribution of species. In estuaries, these constraints often result from variability in water flow properties and environmental conditions (i.e. water flow, salinity, water temperature) and can have significant effects on the abundance and distribution of commercially important nekton species. We investigated links between large-scale climate variability and juvenile brown shrimp Farfantepenaeus aztecus abundance in Breton Sound estuary, Louisiana (USA). Our goals were to (1) determine if a teleconnection exists between local juvenile brown shrimp abundance and the El Niño Southern Oscillation (ENSO) and (2) relate that linkage to environmental constraints that may affect juvenile brown shrimp recruitment to, and survival in, the estuary. Our results identified a teleconnection between winter ENSO conditions and juvenile brown shrimp abundance in Breton Sound estuary the following spring. The physical connection results from the impact of ENSO on winter weather conditions in Breton Sound (air pressure, temperature, and precipitation). Juvenile brown shrimp abundance effects lagged ENSO by 3 mo: lower than average abundances of juvenile brown shrimp were caught in springs following winter El Niño events, and higher than average abundances of brown shrimp were caught in springs following La Niña winters. Salinity was the dominant ENSO-forced environmental filter for juvenile brown shrimp. Spring salinity was cumulatively forced by winter river discharge, winter wind forcing, and spring precipitation. Thus, predicting brown shrimp abundance requires incorporating climate variability into models.

Ageing, exposure to pollution, and interactions between climate change and local seasons as oxidant conditions predicting incident hematologic malignancy at KINSHASA University clinics, Democratic Republic of CONGO (DRC).

PubMed

Nkanga, Mireille Solange Nganga; Longo-Mbenza, Benjamin; Adeniyi, Oladele Vincent; Ngwidiwo, Jacques Bikaula; Katawandja, Antoine Lufimbo; Kazadi, Paul Roger Beia; Nzonzila, Alain Nganga

2017-08-23

The global burden of hematologic malignancy (HM) is rapidly rising with aging, exposure to polluted environments, and global and local climate variability all being well-established conditions of oxidative stress. However, there is currently no information on the extent and predictors of HM at Kinshasa University Clinics (KUC), DR Congo (DRC). This study evaluated the impact of bio-clinical factors, exposure to polluted environments, and interactions between global climate changes (EL Nino and La Nina) and local climate (dry and rainy seasons) on the incidence of HM. This hospital-based prospective cohort study was conducted at Kinshasa University Clinics in DR Congo. A total of 105 black African adult patients with anaemia between 2009 and 2016 were included. HM was confirmed by morphological typing according to the French-American-British (FAB) Classification System. Gender, age, exposure to traffic pollution and garages/stations, global climate variability (El Nino and La Nina), and local climate (dry and rainy seasons) were potential independent variables to predict incident HM using Cox regression analysis and Kaplan Meier curves. Out of the total 105 patients, 63 experienced incident HM, with an incidence rate of 60%. After adjusting for gender, HIV/AIDS, and other bio-clinical factors, the most significant independent predictors of HM were age ≥ 55 years (HR = 2.4; 95% CI 1.4-4.3; P = 0.003), exposure to pollution and garages or stations (HR = 4.9; 95% CI 2-12.1; P < 0.001), combined local dry season + La Nina (HR = 4.6; 95%CI 1.8-11.8; P < 0.001), and combined local dry season + El Nino (HR = 4; 95% CI 1.6-9.7; P = 0.004). HM types included acute myeloid leukaemia (28.6% n = 18), multiple myeloma (22.2% n = 14), myelodysplastic syndromes (15.9% n = 10), chronic myeloid leukaemia (15.9% n = 10), chronic lymphoid leukaemia (9.5% n = 6), and acute lymphoid leukaemia (7.9% n = 5). After adjusting for confounders using Cox regression analysis, age ≥ 55 years, exposure to pollution, combined local dry season + La Nina and combined local dry season + El Nino were the most significant predictors of incident hematologic malignancy. These findings highlight the importance of aging, pollution, the dry season, El Nino and La Nina as related to global warming as determinants of hematologic malignancies among African patients from Kinshasa, DR Congo. Cancer registries in DRC and other African countries will provide more robust database for future researches on haematological malignancies in the region.

Disentangling the relative role of climate change on tree growth in an extreme Mediterranean environment.

PubMed

Madrigal-González, Jaime; Andivia, Enrique; Zavala, Miguel A; Stoffel, Markus; Calatayud, Joaquín; Sánchez-Salguero, Raúl; Ballesteros-Cánovas, Juan

2018-06-14

Climate change can impair ecosystem functions and services in extensive dry forests worldwide. However, attribution of climate change impacts on tree growth and forest productivity is challenging due to multiple inter-annual patterns of climatic variability associated with atmospheric and oceanic circulations. Moreover, growth responses to rising atmospheric CO 2 , namely carbon fertilization, as well as size ontogenetic changes can obscure the climate change signature as well. Here we apply Structural Equation Models (SEM) to investigate the relative role of climate change on tree growth in an extreme Mediterranean environment (i.e., extreme in terms of the combination of sandy-unconsolidated soils and climatic aridity). Specifically, we analyzed potential direct and indirect pathways by which different sources of climatic variability (i.e. warming and precipitation trends, the North Atlantic Oscillation, [NAO]; the Mediterranean Oscillation, [MOI]; the Atlantic Mediterranean Oscillation, [AMO]) affect aridity through their control on local climate (in terms of mean annual temperature and total annual precipitation), and subsequently tree productivity, in terms of basal area increments (BAI). Our results support the predominant role of Diameter at Breast Height (DHB) as the main growth driver. In terms of climate, NAO and AMO are the most important drivers of tree growth through their control of aridity (via effects of precipitation and temperature, respectively). Furthermore and contrary to current expectations, our findings also support a net positive role of climate warming on growth over the last 50 years and suggest that impacts of climate warming should be evaluated considering multi-annual and multi-decadal periods of local climate defined by atmospheric and oceanic circulation in the North Atlantic. Copyright © 2018 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.

Climate variability and human impact on the environment in South America during the last 2000 years: synthesis and perspectives

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2015-07-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past two millennia. Global efforts to reconstruct regional climate modes are in the process of validating and integrating paleo-proxies. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to its unknown spatial and temporal coverage. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last two millennia. We identify the pollen records with the required temporal characteristics for PAGES-2 ka climate modelling and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local scale responses to climate modes, thus it is necessary to understand how vegetation-climate interactions might diverge under variable settings. Additionally, pollen is an excellent indicator of human impact through time. Evidence for human land use in pollen records is useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. The LOTRED-SA-2 k initiative provides the ideal framework for the integration of the various paleoclimatic sub-disciplines and paleo-science, thereby jumpstarting and fostering multi-disciplinary research into environmental change on centennial and millennial time scales.

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.

Integrating Climate Information and Decision Processes for Regional Climate Resilience

NASA Astrophysics Data System (ADS)

Buizer, James; Goddard, Lisa; Guido, Zackry

2015-04-01

An integrated multi-disciplinary team of researchers from the University of Arizona and the International Research Institute for Climate and Society at Columbia University have joined forces with communities and institutions in the Caribbean, South Asia and West Africa to develop relevant, usable climate information and connect it to real decisions and development challenges. The overall objective of the "Integrating Climate Information and Decision Processes for Regional Climate Resilience" program is to build community resilience to negative impacts of climate variability and change. We produce and provide science-based climate tools and information to vulnerable peoples and the public, private, and civil society organizations that serve them. We face significant institutional challenges because of the geographical and cultural distance between the locale of climate tool-makers and the locale of climate tool-users and because of the complicated, often-inefficient networks that link them. To use an accepted metaphor, there is great institutional difficulty in coordinating the supply of and the demand for useful climate products that can be put to the task of building local resilience and reducing climate vulnerability. Our program is designed to reduce the information constraint and to initiate a linkage that is more demand driven, and which provides a set of priorities for further climate tool generation. A demand-driven approach to the co-production of appropriate and relevant climate tools seeks to meet the direct needs of vulnerable peoples as these needs have been canvassed empirically and as the benefits of application have been adequately evaluated. We first investigate how climate variability and climate change affect the livelihoods of vulnerable peoples. In so doing we assess the complex institutional web within which these peoples live -- the public agencies that serve them, their forms of access to necessary information, the structural constraints under which they make their decisions, and the non-public institutions of support that are available to them. We then interpret this complex reality in terms of the demand for science-based climate products and analyze the channels through which such climate support must pass, thus linking demand assessment with the scientific capacity to create appropriate decision support tools. In summary, the approach we employ is: 1) Demand-driven, beginning with a knowledge of the impacts of climate variability and change upon targeted populations, 2) Focused on vulnerability and resilience, which requires an understanding of broader networks of institutional actors who contribute to the adaptive capacity of vulnerable peoples, 3) Needs-based in that the climate needs matrix set priorities for the assessment of relevant climate products, 4) Dynamic in that the producers of climate products are involved at the point of demand assessment and can respond directly to stated needs, 5) Reflective in that the impacts of climate product interventions are subject to monitoring and evaluation throughout the process. Methods, approaches and preliminary results of our work in the Caribbean will be presented.

Planning for Production of Freshwater Fish Fry in a Variable Climate in Northern Thailand.

PubMed

Uppanunchai, Anuwat; Apirumanekul, Chusit; Lebel, Louis

2015-10-01

Provision of adequate numbers of quality fish fry is often a key constraint on aquaculture development. The management of climate-related risks in hatchery and nursery management operations has not received much attention, but is likely to be a key element of successful adaptation to climate change in the aquaculture sector. This study explored the sensitivities and vulnerability of freshwater fish fry production in 15 government hatcheries across Northern Thailand to climate variability and evaluated the robustness of the proposed adaptation measures. This study found that hatcheries have to consider several factors when planning production, including: taking into account farmer demand; production capacity of the hatchery; availability of water resources; local climate and other area factors; and, individual species requirements. Nile tilapia is the most commonly cultured species of freshwater fish. Most fry production is done in the wet season, as cold spells and drought conditions disrupt hatchery production and reduce fish farm demand in the dry season. In the wet season, some hatcheries are impacted by floods. Using a set of scenarios to capture major uncertainties and variability in climate, this study suggests a couple of strategies that should help make hatchery operations more climate change resilient, in particular: improving hatchery operations and management to deal better with risks under current climate variability; improving monitoring and information systems so that emerging climate-related risks are known sooner and understood better; and, research and development on alternative species, breeding programs, improving water management and other features of hatchery operations.

Land - Ocean Climate Linkages and the Human Evolution - New ICDP and IODP Drilling Initiatives in the East African Rift Valley and SW Indian Ocean

NASA Astrophysics Data System (ADS)

Zahn, R.; Feibel, C.; Co-Pis, Icdp/Iodp

2009-04-01

The past 5 Ma were marked by systematic shifts towards colder climates and concomitant reorganizations in ocean circulation and marine heat transports. Some of the changes involved plate-tectonic shifts such as the closure of the Panamanian Isthmus and restructuring of the Indonesian archipelago that affected inter-ocean communications and altered the world ocean circulation. These changes induced ocean-atmosphere feedbacks with consequences for climates globally and locally. Two new ICDP and IODP drilling initiatives target these developments from the perspectives of marine and terrestrial palaeoclimatology and the human evolution. The ICDP drilling initiative HSPDP ("Hominid Sites and Paleolakes Drilling Project"; ICDP ref. no. 10/07) targets lacustrine depocentres in Ethiopia (Hadar) and Kenya (West Turkana, Olorgesailie, Magadi) to retrieve sedimentary sequences close to the places and times where various species of hominins lived over currently available outcrop records. The records will provide a spatially resolved record of the East African environmental history in conjunction with climate variability at orbital (Milankovitch) and sub-orbital (ENSO decadal) time scales. HSPDP specifically aims at (1) compiling master chronologies for outcrops around each of the depocentres; (2) assessing which aspects of the paleoenvironmental records are a function of local origin (hydrology, hydrogeology) and which are linked with regional or larger-scale signals; (3) correlating broad-scale patterns of hominin phylogeny with the global beat of climate variability and (4) correlating regional shifts in the hominin fossil and archaeological record with more local patterns of paleoenvironmental change. Ultimately the aim is to test hypotheses that link physical and cultural adaptations in the course of the hominin evolution to local environmental change and variability. The IODP initiative SAFARI ("Southern African Climates, Agulhas Warm Water Transports and Retroflection, and Interocean Exchanges"; IODP ref. no. 702-full) aims at deciphering the late Neogene ocean history of the SW Indian Ocean. SAFARI specifically targets the Agulhas Current in the SW Indian Ocean that constitutes the strongest western boundary current in the southern hemisphere oceans. The Current transports warm and saline surface waters from the tropical Indian Ocean to the southern tip of Africa. Exchanges with the atmosphere influence eastern and southern African climates including individual weather systems such as extra-tropical cyclone formation in the region and rainfall patterns. Ocean models further suggest the "leakage" of Agulhas water around South Africa into the Atlantic potentially modulates the Atlantic meridional overturning circulation (MOC) with consequences for climate globally. The SAFARI drilling initiative aims to retrieve a suite of long drill cores along the southeast African margin and in the Indian-Atlantic ocean gateway. SAFARI will shed light on the history of Agulhas Current warm water transports along the southeast African margin during the late Neogene and its linking with ocean-climate developments. Specific objectives of SAFARI are to test (1) the sensitivity of the Agulhas Current to changing climates of the Plio/Pleistocene, including upstream forcing linked with equatorial Indian Ocean changes and Indonesian Throughflow; (2) the Current's influence on eastern and southern Africa climates, including rain fall patterns and vegetation changes; (3) buoyancy transfer to the Atlantic by Agulhas leakage around southern Africa, and (4) the contribution of variable Agulhas Leakage to shifts of the Atlantic MOC during episodes of major ocean and climate reorganizations of the past 5 Ma. These studies will provide insight into the Current's influence on eastern and southern African terrestrial climates, including its possible impact on the late Neogene evolution of large mammals including hominids. The ICDP and IODP drilling campaigns will enable us to establish the linkages between the ocean climatology of the SW Indian and terrestrial climates of Eastern Africa during key periods of global climate change. Combining the ICDP records of East African terrestrial climate at key hominin sites with IODP records of marine climate variability at the SE African continental margin will help to test if pulses of hominin evolutionary innovation were linked with periods of enhanced variability of local terrestrial environments and marine climatology of the Indian Ocean. * co-PIs of the ICDP initiative HSPDP are A.S. Cohen, R. Arrowsmith, A.K. Behrensmeyer, C. Feibel, R. Johnson, Z. Kubsa, D. Olago, R. Potts, R. Renaut * co-PIs of the IODP initiative SAFARI are R. Zahn, I. Hall, R. Schneider, M. Á. Bárcena, S. Barker, A. Biastoch, Chr. Charles, J. Compton, R. Cowling, P. Diz, L. Dupont, J.-A. Flores, S. Goldstein, S. Hemming, K. Holmgren, J. Lee-Thorp, G. Knorr, C. Lear, A. Mazaud, G. Mortyn, F. Peeters, B. Preu, R. Rickaby, J. Rogers, A. Rosell-Mele, Chr. Reason, V. Spiess, M. Trauth, G. Uenzelmann-Neben, S. Weldeab, P. Ziveri

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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.

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

NASA Astrophysics Data System (ADS)

Parsons, Luke Alexander

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

Climate Drivers of Spatiotemporal Variability of Precipitation in the Source Region of Yangtze River

NASA Astrophysics Data System (ADS)

Du, Y.; Berndtsson, R.; An, D.; Yuan, F.

2017-12-01

Variability of precipitation regime has significant influence on the environment sustainability in the source region of Yangtze River, especially when the vegetation degradation and biodiversity reduction have already occurred. Understanding the linkage between variability of local precipitation and global teleconnection patterns is essential for water resources management. Based on physical reasoning, indices of the climate drivers can provide a practical way of predicting precipitation. Due to high seasonal variability of precipitation, climate drivers of the seasonal precipitation also varies. However, few reports have gone through the teleconnections between large scale patterns with seasonal precipitation in the source region of Yangtze River. The objectives of this study are therefore (1) assessment of temporal trend and spatial variability of precipitation in the source region of Yangtze River; (2) identification of climate indices with strong influence on seasonal precipitation anomalies; (3) prediction of seasonal precipitation based on revealed climate indices. Principal component analysis and Spearman rank correlation were used to detect significant relationships. A feed-forward artificial neural network(ANN) was developed to predict seasonal precipitation using significant correlated climate indices. Different influencing climate indices were revealed for precipitation in each season, with significant level and lag times. Significant influencing factors were selected to be the predictors for ANN model. With correlation coefficients between observed and simulated precipitation over 0.5, the results were eligible to predict the precipitation of spring, summer and winter using teleconnections, which can improve integrated water resources management in the source region of Yangtze River.

Guess-Work and Reasonings on Centennial Evolution of Surface Air Temperature in Russia. Part III: Where is the Joint Between Norms and Hazards from a Bifurcation Analysis Viewpoint?

NASA Astrophysics Data System (ADS)

Kolokolov, Yury; Monovskaya, Anna

2016-06-01

The paper continues the application of the bifurcation analysis in the research on local climate dynamics based on processing the historically observed data on the daily average land surface air temperature. Since the analyzed data are from instrumental measurements, we are doing the experimental bifurcation analysis. In particular, we focus on the discussion where is the joint between the normal dynamics of local climate systems (norms) and situations with the potential to create damages (hazards)? We illustrate that, perhaps, the criteria for hazards (or violent and unfavorable weather factors) relate mainly to empirical considerations from human opinion, but not to the natural qualitative changes of climate dynamics. To build the bifurcation diagrams, we base on the unconventional conceptual model (HDS-model) which originates from the hysteresis regulator with double synchronization. The HDS-model is characterized by a variable structure with the competition between the amplitude quantization and the time quantization. Then the intermittency between three periodical processes is considered as the typical behavior of local climate systems instead of both chaos and quasi-periodicity in order to excuse the variety of local climate dynamics. From the known specific regularities of the HDS-model dynamics, we try to find a way to decompose the local behaviors into homogeneous units within the time sections with homogeneous dynamics. Here, we present the first results of such decomposition, where the quasi-homogeneous sections (QHS) are determined on the basis of the modified bifurcation diagrams, and the units are reconstructed within the limits connected with the problem of shape defects. Nevertheless, the proposed analysis of the local climate dynamics (QHS-analysis) allows to exhibit how the comparatively modest temperature differences between the mentioned units in an annual scale can step-by-step expand into the great temperature differences of the daily variability at a centennial scale. Then the norms and the hazards relate to the fundamentally different viewpoints, where the time sections of months and, especially, seasons distort the causal effects of natural dynamical processes. The specific circumstances to realize the qualitative changes of the local climate dynamics are summarized by the notion of a likely periodicity. That, in particular, allows to explain why 30-year averaging remains the most common rule so far, but the decadal averaging begins to substitute that rule. We believe that the QHS-analysis can be considered as the joint between the norms and the hazards from a bifurcation analysis viewpoint, where the causal effects of the local climate dynamics are projected into the customary timescale only at the last step. We believe that the results could be interesting to develop the fields connected with climatic change and risk assessment.

Remote-sensing based approach to forecast habitat quality under climate change scenarios.

PubMed

Requena-Mullor, Juan M; López, Enrique; Castro, Antonio J; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071-2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios.

Remote-sensing based approach to forecast habitat quality under climate change scenarios

PubMed Central

Requena-Mullor, Juan M.; López, Enrique; Castro, Antonio J.; Alcaraz-Segura, Domingo; Castro, Hermelindo; Reyes, Andrés; Cabello, Javier

2017-01-01

As climate change is expected to have a significant impact on species distributions, there is an urgent challenge to provide reliable information to guide conservation biodiversity policies. In addressing this challenge, we propose a remote sensing-based approach to forecast the future habitat quality for European badger, a species not abundant and at risk of local extinction in the arid environments of southeastern Spain, by incorporating environmental variables related with the ecosystem functioning and correlated with climate and land use. Using ensemble prediction methods, we designed global spatial distribution models for the distribution range of badger using presence-only data and climate variables. Then, we constructed regional models for an arid region in the southeast Spain using EVI (Enhanced Vegetation Index) derived variables and weighting the pseudo-absences with the global model projections applied to this region. Finally, we forecast the badger potential spatial distribution in the time period 2071–2099 based on IPCC scenarios incorporating the uncertainty derived from the predicted values of EVI-derived variables. By including remotely sensed descriptors of the temporal dynamics and spatial patterns of ecosystem functioning into spatial distribution models, results suggest that future forecast is less favorable for European badgers than not including them. In addition, change in spatial pattern of habitat suitability may become higher than when forecasts are based just on climate variables. Since the validity of future forecast only based on climate variables is currently questioned, conservation policies supported by such information could have a biased vision and overestimate or underestimate the potential changes in species distribution derived from climate change. The incorporation of ecosystem functional attributes derived from remote sensing in the modeling of future forecast may contribute to the improvement of the detection of ecological responses under climate change scenarios. PMID:28257501

An ecological genetic delineation of local seed-source provenance for ecological restoration

PubMed Central

Krauss, Siegfried L; Sinclair, Elizabeth A; Bussell, John D; Hobbs, Richard J

2013-01-01

An increasingly important practical application of the analysis of spatial genetic structure within plant species is to help define the extent of local provenance seed collection zones that minimize negative impacts in ecological restoration programs. Here, we derive seed sourcing guidelines from a novel range-wide assessment of spatial genetic structure of 24 populations of Banksia menziesii (Proteaceae), a widely distributed Western Australian tree of significance in local ecological restoration programs. An analysis of molecular variance (AMOVA) of 100 amplified fragment length polymorphism (AFLP) markers revealed significant genetic differentiation among populations (ΦPT = 0.18). Pairwise population genetic dissimilarity was correlated with geographic distance, but not environmental distance derived from 15 climate variables, suggesting overall neutrality of these markers with regard to these climate variables. Nevertheless, Bayesian outlier analysis identified four markers potentially under selection, although these were not correlated with the climate variables. We calculated a global R-statistic using analysis of similarities (ANOSIM) to test the statistical significance of population differentiation and to infer a threshold seed collection zone distance of ∼60 km (all markers) and 100 km (outlier markers) when genetic distance was regressed against geographic distance. Population pairs separated by >60 km were, on average, twice as likely to be significantly genetically differentiated than population pairs separated by <60 km, suggesting that habitat-matched sites within a 30-km radius around a restoration site genetically defines a local provenance seed collection zone for B. menziesii. Our approach is a novel probability-based practical solution for the delineation of a local seed collection zone to minimize negative genetic impacts in ecological restoration. PMID:23919158

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.

Linear and non-linear responses of vegetation and soils to glacial-interglacial climate change in a Mediterranean refuge.

PubMed

Holtvoeth, Jens; Vogel, Hendrik; Valsecchi, Verushka; Lindhorst, Katja; Schouten, Stefan; Wagner, Bernd; Wolff, George A

2017-08-14

The impact of past global climate change on local terrestrial ecosystems and their vegetation and soil organic matter (OM) pools is often non-linear and poorly constrained. To address this, we investigated the response of a temperate habitat influenced by global climate change in a key glacial refuge, Lake Ohrid (Albania, Macedonia). We applied independent geochemical and palynological proxies to a sedimentary archive from the lake over the penultimate glacial-interglacial transition (MIS 6-5) and the following interglacial (MIS 5e-c), targeting lake surface temperature as an indicator of regional climatic development and the supply of pollen and biomarkers from the vegetation and soil OM pools to determine local habitat response. Climate fluctuations strongly influenced the ecosystem, however, lake level controls the extent of terrace surfaces between the shoreline and mountain slopes and hence local vegetation, soil development and OM export to the lake sediments. There were two phases of transgressional soil erosion from terrace surfaces during lake-level rise in the MIS 6-5 transition that led to habitat loss for the locally dominant pine vegetation as the terraces drowned. Our observations confirm that catchment morphology plays a key role in providing refuges with low groundwater depth and stable soils during variable climate.

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

Adaptation to climate through flowering phenology: a case study in Medicago truncatula.

PubMed

Burgarella, Concetta; Chantret, Nathalie; Gay, Laurène; Prosperi, Jean-Marie; Bonhomme, Maxime; Tiffin, Peter; Young, Nevin D; Ronfort, Joelle

2016-07-01

Local climatic conditions likely constitute an important selective pressure on genes underlying important fitness-related traits such as flowering time, and in many species, flowering phenology and climatic gradients strongly covary. To test whether climate shapes the genetic variation on flowering time genes and to identify candidate flowering genes involved in the adaptation to environmental heterogeneity, we used a large Medicago truncatula core collection to examine the association between nucleotide polymorphisms at 224 candidate genes and both climate variables and flowering phenotypes. Unlike genome-wide studies, candidate gene approaches are expected to enrich for the number of meaningful trait associations because they specifically target genes that are known to affect the trait of interest. We found that flowering time mediates adaptation to climatic conditions mainly by variation at genes located upstream in the flowering pathways, close to the environmental stimuli. Variables related to the annual precipitation regime reflected selective constraints on flowering time genes better than the other variables tested (temperature, altitude, latitude or longitude). By comparing phenotype and climate associations, we identified 12 flowering genes as the most promising candidates responsible for phenological adaptation to climate. Four of these genes were located in the known flowering time QTL region on chromosome 7. However, climate and flowering associations also highlighted largely distinct gene sets, suggesting different genetic architectures for adaptation to climate and flowering onset. © 2016 John Wiley & Sons Ltd.

Climate Justice in Rural Southeastern United States: A Review of Climate Change Impacts and Effects on Human Health.

PubMed

Gutierrez, Kristie S; LePrevost, Catherine E

2016-02-03

Climate justice is a local, national, and global movement to protect at-risk populations who are disproportionately affected by climate change. The social context for this review is the Southeastern region of the United States, which is particularly susceptible to climate change because of the geography of the area and the vulnerabilities of the inhabiting populations. Negative human health effects on variable and vulnerable populations within the Southeast region due to changing climate are concerning, as health threats are not expected to produce parallel effects among all individuals. Vulnerable communities, such as communities of color, indigenous people, the geographically isolated, and those who are socioeconomically disadvantaged and already experiencing poor environmental quality, are least able to respond and adapt to climate change. Focusing on vulnerable populations in the Southeastern United States, this review is a synthesis of the recent (2010 to 2015) literature-base on the health effects connected to climate change. This review also addresses local and regional mitigation and adaptation strategies for citizens and leaders to combat direct and indirect human health effects related to a changing climate.

Landscape genomics reveal signatures of local adaptation in barley (Hordeum vulgare L.)

PubMed Central

Abebe, Tiegist D.; Naz, Ali A.; Léon, Jens

2015-01-01

Land plants are sessile organisms that cannot escape the adverse climatic conditions of a given environment. Hence, adaptation is one of the solutions to surviving in a challenging environment. This study was aimed at detecting adaptive loci in barley landraces that are affected by selection. To that end, a diverse population of barley landraces was analyzed using the genotyping by sequencing approach. Climatic data for altitude, rainfall and temperature were collected from 61 weather sites near the origin of selected landraces across Ethiopia. Population structure analysis revealed three groups whereas spatial analysis accounted significant similarities at shorter geographic distances (< 40 Km) among barley landraces. Partitioning the variance between climate variables and geographic distances indicated that climate variables accounted for most of the explainable genetic variation. Markers by climatic variables association analysis resulted in altogether 18 and 62 putative adaptive loci using Bayenv and latent factor mixed model (LFMM), respectively. Subsequent analysis of the associated SNPs revealed putative candidate genes for plant adaptation. This study highlights the presence of putative adaptive loci among barley landraces representing original gene pool of the farming communities. PMID:26483825

Development of a drought forecasting model for the Asia-Pacific region using remote sensing and climate data: Focusing on Indonesia

NASA Astrophysics Data System (ADS)

Rhee, Jinyoung; Kim, Gayoung; Im, Jungho

2017-04-01

Three regions of Indonesia with different rainfall characteristics were chosen to develop drought forecast models based on machine learning. The 6-month Standardized Precipitation Index (SPI6) was selected as the target variable. The models' forecast skill was compared to the skill of long-range climate forecast models in terms of drought accuracy and regression mean absolute error (MAE). Indonesian droughts are known to be related to El Nino Southern Oscillation (ENSO) variability despite of regional differences as well as monsoon, local sea surface temperature (SST), other large-scale atmosphere-ocean interactions such as Indian Ocean Dipole (IOD) and Southern Pacific Convergence Zone (SPCZ), and local factors including topography and elevation. Machine learning models are thus to enhance drought forecast skill by combining local and remote SST and remote sensing information reflecting initial drought conditions to the long-range climate forecast model results. A total of 126 machine learning models were developed for the three regions of West Java (JB), West Sumatra (SB), and Gorontalo (GO) and six long-range climate forecast models of MSC_CanCM3, MSC_CanCM4, NCEP, NASA, PNU, POAMA as well as one climatology model based on remote sensing precipitation data, and 1 to 6-month lead times. When compared the results between the machine learning models and the long-range climate forecast models, West Java and Gorontalo regions showed similar characteristics in terms of drought accuracy. Drought accuracy of the long-range climate forecast models were generally higher than the machine learning models with short lead times but the opposite appeared for longer lead times. For West Sumatra, however, the machine learning models and the long-range climate forecast models showed similar drought accuracy. The machine learning models showed smaller regression errors for all three regions especially with longer lead times. Among the three regions, the machine learning models developed for Gorontalo showed the highest drought accuracy and the lowest regression error. West Java showed higher drought accuracy compared to West Sumatra, while West Sumatra showed lower regression error compared to West Java. The lower error in West Sumatra may be because of the smaller sample size used for training and evaluation for the region. Regional differences of forecast skill are determined by the effect of ENSO and the following forecast skill of the long-range climate forecast models. While shown somewhat high in West Sumatra, relative importance of remote sensing variables was mostly low in most cases. High importance of the variables based on long-range climate forecast models indicates that the forecast skill of the machine learning models are mostly determined by the forecast skill of the climate models.

Impacts of Irrigation on Daily Extremes in the Coupled Climate System

NASA Technical Reports Server (NTRS)

Puma, Michael J.; Cook, Benjamin I.; Krakauer, Nir; Gentine, Pierre; Nazarenka, Larissa; Kelly, Maxwell; Wada, Yoshihide

2014-01-01

Widespread irrigation alters regional climate through changes to the energy and water budgets of the land surface. Within general circulation models, simulation studies have revealed significant changes in temperature, precipitation, and other climate variables. Here we investigate the feedbacks of irrigation with a focus on daily extremes at the global scale. We simulate global climate for the year 2000 with and without irrigation to understand irrigation-induced changes. Our simulations reveal shifts in key climate-extreme metrics. These findings indicate that land cover and land use change may be an important contributor to climate extremes both locally and in remote regions including the low-latitudes.

The Practitioner's Dilemma: How to Assess the Credibility of Downscaled Climate Projections

NASA Technical Reports Server (NTRS)

Barsugli, Joseph J.; Guentchev, Galina; Horton, Radley M.; Wood, Andrew; Mearns, Lindo O.; Liang, Xin-Zhong; Winkler, Julia A.; Dixon, Keith; Hayhoe, Katharine; Rood, Richard B.;

Assessing the potential impact and uncertainty of climate, land use change and demographic trends on malaria transmission in Africa by 2050.

NASA Astrophysics Data System (ADS)

Tompkins, Adrian; Caporaso, Luca; Colon-Gonzalez, Felipe

2014-05-01

Previous analyses of data has shown that in addition to variability and longer term trends in climate variables, both land use change (LUC) and population mobility and urbanisation trends can impact malaria transmission intensities and socio-economic burden. With the new regional VECTRI dynamical malaria model it is now possible to examine these in an integrated modelling framework. Using 5 global climate models which were bias corrected using the WATCH data for the recent ISIMIP project, the four Representative Concentration Pathways (RCP), population projections disaggregated from the Shared Socioeconomic Pathways (SSP) and Land use change from the HYDE model output used in the CMIP5 process, we construct a multi-member ensemble of malaria transmission intensity projections for 2050. The ensemble integrations indicate that climate has the leading impact on malaria changes, but that population growth and urbanisation can offset the effect of climate locally. LUC impacts can also be significant on the local scale but their assessment is highly uncertain and only indicative in this study. It is argued that the study should be repeated with a range of malaria models or VECTRI configurations in order to assess the additional uncertainty due to the malaria model assumptions.

A Synoptic Weather Typing Approach to Assess Climate Change Impacts on Meteorological and Hydrological Risks at Local Scale in South-Central Canada

NASA Astrophysics Data System (ADS)

Cheng, Chad Shouquan; Li, Qian; Li, Guilong

2010-05-01

The synoptic weather typing approach has become popular in evaluating the impacts of climate change on a variety of environmental problems. One of the reasons is its ability to categorize a complex set of meteorological variables as a coherent index, which can facilitate analyses of local climate change impacts. The weather typing method has been applied in Environment Canada to analyze climatic change impacts on various meteorological/hydrological risks, such as freezing rain, heavy rainfall, high-/low-flow events, air pollution, and human health. These studies comprise of three major parts: (1) historical simulation modeling to verify the hazardous events, (2) statistical downscaling to provide station-scale future climate information, and (3) estimates of changes in frequency and magnitude of future hazardous meteorological/hydrological events in this century. To achieve these goals, in addition to synoptic weather typing, the modeling conceptualizations in meteorology and hydrology and various linear/nonlinear regression techniques were applied. Furthermore, a formal model result verification process has been built into the entire modeling exercise. The results of the verification, based on historical observations of the outcome variables predicted by the models, showed very good agreement. This paper will briefly summarize these research projects, focusing on the modeling exercise and results.

Extratropical Respones to Amazon Deforestation

NASA Astrophysics Data System (ADS)

Badger, A.; Dirmeyer, P.

2014-12-01

Land-use change (LUC) is known to impact local climate conditions through modifications of land-atmosphere interactions. Large-scale LUC, such as Amazon deforestation, could have a significant effect on the local and regional climates. The question remains as to what the global impact of large-scale LUC could be, as previous modeling studies have shown non-local responses due to Amazon deforestation. A common shortcoming in many previous modeling studies is the use of prescribed ocean conditions, which can act as a boundary condition to dampen the global response with respect to changes in the mean and variability. Using fully coupled modeling simulations with the Community Earth System Model version 1.2.0, the Amazon rainforest has been replaced with a distribution of representative tropical crops. Through the modifications of local land-atmosphere interactions, a significant change in the region, both at the surface and throughout the atmosphere, can be quantified. Accompanying these local changes are significant changes to the atmospheric circulation across all scales, thus modifying regional climates in other locales. Notable impacts include significant changes in precipitation, surface fluxes, basin-wide sea surface temperatures and ENSO behavior.

Estimation of climate change impact on dead fuel moisture at local scale by using weather generators

NASA Astrophysics Data System (ADS)

Pellizzaro, Grazia; Bortolu, Sara; Dubrovsky, Martin; Arca, Bachisio; Ventura, Andrea; Duce, Pierpaolo

2015-04-01

The moisture content of dead fuel is an important variable in fire ignition and fire propagation. Moisture exchange in dead materials is controlled by physical processes, and is clearly dependent on atmospheric changes. According to projections of future climate in Southern Europe, changes in temperature, precipitation and extreme events are expected. More prolonged drought seasons could influence fuel moisture content and, consequently, the number of days characterized by high ignition danger in Mediterranean ecosystems. The low resolution of the climate data provided by the general circulation models (GCMs) represents a limitation for evaluating climate change impacts at local scale. For this reason, the climate research community has called to develop appropriate downscaling techniques. One of the downscaling approaches, which transform the raw outputs from the climate models (GCMs or RCMs) into data with more realistic structure, is based on linking a stochastic weather generator with the climate model outputs. Weather generators linked to climate change scenarios can therefore be used to create synthetic weather series (air temperature and relative humidity, wind speed and precipitation) representing present and future climates at local scale. The main aims of this work are to identify useful tools to determine potential impacts of expected climate change on dead fuel status in Mediterranean shrubland and, in particular, to estimate the effect of climate changes on the number of days characterized by critical values of dead fuel moisture. Measurements of dead fuel moisture content (FMC) in Mediterranean shrubland were performed by using humidity sensors in North Western Sardinia (Italy) for six years. Meteorological variables were also recorded. Data were used to determine the accuracy of the Canadian Fine Fuels Moisture Code (FFM code) in modelling moisture dynamics of dead fuel in Mediterranean vegetation. Critical threshold values of FFM code for Mediterranean climate were identified by percentile analysis, and new fuel moisture code classes were also defined. A stochastic weather generator (M&Rfi), linked to climate change scenarios derived from 17 available General Circulation Models (GCMs), was used to produce synthetic weather series, representing present and future climates, for four selected sites located in North Western Sardinia, Italy. The number of days with critical FFM code values for present and future climate were calculated and the potential impact of future climate change was analysed.

A Data Centred Method to Estimate and Map Changes in the Full Distribution of Daily Precipitation and Its Exceedances

NASA Astrophysics Data System (ADS)

Chapman, S. C.; Stainforth, D. A.; Watkins, N. W.

2014-12-01

Estimates of how our climate is changing are needed locally in order to inform adaptation planning decisions. This requires quantifying the geographical patterns in changes at specific quantiles or thresholds in distributions of variables such as daily temperature or precipitation. We develop a method[1] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes, to specifically address the challenges presented by 'heavy tailed' distributed variables such as daily precipitation. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the relative amount of precipitation in those extreme precipitation days. Our method is 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 how fast different quantiles of precipitation distributions are changing. This involves both determining which quantiles and geographical locations show the greatest change but also, those at which any change is highly uncertain. We demonstrate this approach using E-OBS gridded data[2] timeseries of local daily precipitation from specific locations across Europe over the last 60 years. We treat geographical location and precipitation as independent variables and thus obtain as outputs the pattern of change at a given threshold of precipitation and with geographical location. This is model- independent, thus providing data of direct value in model calibration and assessment. Our results identify regionally consistent patterns which, dependent on location, show systematic increase in precipitation on the wettest days, shifts in precipitation patterns to less moderate days and more heavy days, and drying across all days which is of potential value in adaptation planning. [1] S C Chapman, D A Stainforth, N W Watkins, 2013 Phil. Trans. R. Soc. A, 371 20120287; D. A. Stainforth, S. C. Chapman, N. W. Watkins, 2013 Environ. Res. Lett. 8, 034031 [2] Haylock et al. 2008 J. Geophys. Res (Atmospheres), 113, D20119

Fluvial processes in Puget Sound rivers and the Pacific Northwest [Chapter 3

Treesearch

John M. Buffington; Richard D. Woodsmith; Derek B. Booth; David R. Montgomery

2003-01-01

The variability of topography, geology, climate; vegetation, and land use in the Pacific Northwest creates considerable spatial and temporal variability of fluvial processes and reach-scale channel type. Here we identify process domains of typical Pacific Northwest watersheds and examine local physiographic and geologic controls on channel processes and response...

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

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.

Noise-induced transitions and shifts in a climate-vegetation feedback model.

PubMed

Alexandrov, Dmitri V; Bashkirtseva, Irina A; Ryashko, Lev B

2018-04-01

Motivated by the extremely important role of the Earth's vegetation dynamics in climate changes, we study the stochastic variability of a simple climate-vegetation system. In the case of deterministic dynamics, the system has one stable equilibrium and limit cycle or two stable equilibria corresponding to two opposite (cold and warm) climate-vegetation states. These states are divided by a separatrix going across a point of unstable equilibrium. Some possible stochastic scenarios caused by different externally induced natural and anthropogenic processes inherit properties of deterministic behaviour and drastically change the system dynamics. We demonstrate that the system transitions across its separatrix occur with increasing noise intensity. The climate-vegetation system therewith fluctuates, transits and localizes in the vicinity of its attractor. We show that this phenomenon occurs within some critical range of noise intensities. A noise-induced shift into the range of smaller global average temperatures corresponding to substantial oscillations of the Earth's vegetation cover is revealed. Our analysis demonstrates that the climate-vegetation interactions essentially contribute to climate dynamics and should be taken into account in more precise and complex models of climate variability.

A synthesis of Plio-Pleistocene leaf wax biomarker records of hydrological variation in East Africa and their relationship with hominin evolution

NASA Astrophysics Data System (ADS)

Lupien, R.; Russell, J. M.; Campisano, C. J.; Feibel, C. S.; Deino, A. L.; Kingston, J.; Potts, R.; Cohen, A. S.

2017-12-01

Climate change is thought to play a critical role in human evolution. However, the mechanisms behind this relationship are difficult to test due to a lack of long, high-quality paleoclimate records from hominin fossil locales. We improve the understanding of this relationship by examining Plio-Pleistocene lake sediment cores from East Africa that were drilled by the Hominin Sites and Paleolakes Drilling Project, an international effort to study the environment in which our hominin ancestors evolved and dispersed. We have analyzed organic geochemical signals of climate from drill cores from Ethiopia and Kenya spanning the Pliocene to recent time (from north to south: paleolake Hadar, Lake Turkana, Lake Baringo, and paleolake Koora). Specifically, we analyzed the hydrogen isotopic composition of terrestrial leaf waxes, which records changes in regional atmospheric circulation and hydrology. We reconstructed quantitative records of rainfall amount at each of the study sites, which host sediment spanning different geologic times and regions. By compiling these records, we test hominin evolutionary hypotheses as well as crucial questions about climate trend and variability. We find that there is a gradual or step-wise enrichment in δDwax, signifying a trend from a wet to dry climate, from the Pliocene to the Pleistocene, perhaps implying an influence of global temperature, ice sheet extent, and/or atmospheric greenhouse gas concentrations on East African climate. However, the shift is small relative to the amplitude of orbital-scale isotopic variations. The records indicate a strong influence of eccentricity-modulated orbital precession, and imply that local insolation effects are the likely cause of East African precipitation. Several of the intervals of high isotopic variability coincide with key hominin fossil or technological transitions, suggesting that climate variability plays a key role in hominin evolution.

CIRUN: Climate Information Responding to User Needs

NASA Astrophysics Data System (ADS)

Busalacchi, A. J.

2009-12-01

The Earth System will experience real climate change over the next 50 years, exceeding the scope of natural climate variability. A paramount question facing society is how to adapt to this certainty of climate variability and change. In response, OSTP and NOAA are considering how comprehensive climate services would best inform decisions about adaptation. Similarly, NASA is considering the optimal configuration of the next generation of Earth, environmental, and climate observations to be deployed over the coming 10-20 years. Moreover, much of the added-value information for specific climate-related decisions will be provided by private, academic and non-governmental organizations. In this context, over the past several years the University of Maryland has established the CIRUN (Climate Information: Responding to User Needs) initiative to identify the nature of national needs for climate information and services from a decision support perspective. To date, CIRUN has brought together decisionmakers in a number of sectors to help understand their perspectives on climate with the goal of improving the usefulness of climate information, observations and prediction products to specific user communities. CIRUN began with a major workshop in October 2007 that convened 430 participants in agriculture, parks and recreation, terrestrial ecosystems, insurance/investment, energy, national security, state/local/municipal, water, human health, commerce and manufacturing, transportation, and coastal/marine sectors. Plenary speakers such as Norman Augustine, R. James Woolsey, James Mahoney, and former Senator Joseph Tydings, breakout panel sessions, and participants provided input based on the following: - How would you characterize the exposure or vulnerability to climate variability or change impacting your organization? - Does climate variability and/or change currently factor into your organization's objectives or operations? - Are any of your existing plans being affected by climate or projections of climate change? - Is your organization developing a plan for adapting to climate change? - What are your needs for climate observations, predictions, and services? Please cite one or more specific examples when possible. - Do you currently have access to the climate information your organization needs? - What next steps are needed to assure effective use of climate services in your decision making? As a result, a dialogue with various user communities and a subsequent series of more sector specific workshops has been established regarding how significantly enhanced climate observations, data management, modeling, and predictions can provide valuable decision support for business and policy decisions. In particular, CIRUN has helped - To identify how users, stakeholders, and decision makers are influenced by climate on time scales from seasons to decades - To identify the needs and requirements of users, stakeholders, and decision makers for climate information, observations, predictions, and services from global to local scales - To identify what adaptation measures are being considered in the private and public sectors, and how this might result in new classes of information for decision support - To recommend principal elements of the path forward toward more effective use of climate services in decision making.

Who, What, Where, When, and Why: Demographic and Ecological Factors Contributing to Hostile School Climate for Lesbian, Gay, Bisexual, and Transgender Youth

ERIC Educational Resources Information Center

Kosciw, Joseph G.; Greytak, Emily A.; Diaz, Elizabeth M.

2009-01-01

This study examines how locational (region and locale), community-level (school district poverty and adult educational attainment), and school district-level (district size and ratios of students to key school personnel) variables are related to indicators of hostile school climate for lesbian, gay, bisexual, and transgender (LGBT) youth.…

Internal Physical Features of a Land Surface Model Employing a Tangent Linear Model

NASA Technical Reports Server (NTRS)

Yang, Runhua; Cohn, Stephen E.; daSilva, Arlindo; Joiner, Joanna; Houser, Paul R.

1997-01-01

The Earth's land surface, including its biomass, is an integral part of the Earth's weather and climate system. Land surface heterogeneity, such as the type and amount of vegetative covering., has a profound effect on local weather variability and therefore on regional variations of the global climate. Surface conditions affect local weather and climate through a number of mechanisms. First, they determine the re-distribution of the net radiative energy received at the surface, through the atmosphere, from the sun. A certain fraction of this energy increases the surface ground temperature, another warms the near-surface atmosphere, and the rest evaporates surface water, which in turn creates clouds and causes precipitation. Second, they determine how much rainfall and snowmelt can be stored in the soil and how much instead runs off into waterways. Finally, surface conditions influence the near-surface concentration and distribution of greenhouse gases such as carbon dioxide. The processes through which these mechanisms interact with the atmosphere can be modeled mathematically, to within some degree of uncertainty, on the basis of underlying physical principles. Such a land surface model provides predictive capability for surface variables including ground temperature, surface humidity, and soil moisture and temperature. This information is important for agriculture and industry, as well as for addressing fundamental scientific questions concerning global and local climate change. In this study we apply a methodology known as tangent linear modeling to help us understand more deeply, the behavior of the Mosaic land surface model, a model that has been developed over the past several years at NASA/GSFC. This methodology allows us to examine, directly and quantitatively, the dependence of prediction errors in land surface variables upon different vegetation conditions. The work also highlights the importance of accurate soil moisture information. Although surface variables are predicted imperfectly due to inherent uncertainties in the modeling process, our study suggests how satellite observations can be combined with the model, through land surface data assimilation, to improve their prediction.

The potential impacts of climate variability and change on air pollution-related health effects in the United States.

PubMed Central

Bernard, S M; Samet, J M; Grambsch, A; Ebi, K L; Romieu, I

2001-01-01

Climate change may affect exposures to air pollutants by affecting weather, anthropogenic emissions, and biogenic emissions and by changing the distribution and types of airborne allergens. Local temperature, precipitation, clouds, atmospheric water vapor, wind speed, and wind direction influence atmospheric chemical processes, and interactions occur between local and global-scale environments. If the climate becomes warmer and more variable, air quality is likely to be affected. However, the specific types of change (i.e., local, regional, or global), the direction of change in a particular location (i.e., positive or negative), and the magnitude of change in air quality that may be attributable to climate change are a matter of speculation, based on extrapolating present understanding to future scenarios. There is already extensive evidence on the health effects of air pollution. Ground-level ozone can exacerbate chronic respiratory diseases and cause short-term reductions in lung function. Exposure to particulate matter can aggravate chronic respiratory and cardiovascular diseases, alter host defenses, damage lung tissue, lead to premature death, and possibly contribute to cancer. Health effects of exposures to carbon monoxide, sulfur dioxide, and nitrogen dioxide can include reduced work capacity, aggravation of existing cardiovascular diseases, effects on pulmonary function, respiratory illnesses, lung irritation, and alterations in the lung's defense systems. Adaptations to climate change should include ensuring responsiveness of air quality protection programs to changing pollution levels. Research needs include basic atmospheric science work on the association between weather and air pollutants; improving air pollution models and their linkage with climate change scenarios; and closing gaps in the understanding of exposure patterns and health effects. PMID:11359687

The potential impacts of climate variability and change on air pollution-related health effects in the United States.

PubMed

Bernard, S M; Samet, J M; Grambsch, A; Ebi, K L; Romieu, I

2001-05-01

Climate change may affect exposures to air pollutants by affecting weather, anthropogenic emissions, and biogenic emissions and by changing the distribution and types of airborne allergens. Local temperature, precipitation, clouds, atmospheric water vapor, wind speed, and wind direction influence atmospheric chemical processes, and interactions occur between local and global-scale environments. If the climate becomes warmer and more variable, air quality is likely to be affected. However, the specific types of change (i.e., local, regional, or global), the direction of change in a particular location (i.e., positive or negative), and the magnitude of change in air quality that may be attributable to climate change are a matter of speculation, based on extrapolating present understanding to future scenarios. There is already extensive evidence on the health effects of air pollution. Ground-level ozone can exacerbate chronic respiratory diseases and cause short-term reductions in lung function. Exposure to particulate matter can aggravate chronic respiratory and cardiovascular diseases, alter host defenses, damage lung tissue, lead to premature death, and possibly contribute to cancer. Health effects of exposures to carbon monoxide, sulfur dioxide, and nitrogen dioxide can include reduced work capacity, aggravation of existing cardiovascular diseases, effects on pulmonary function, respiratory illnesses, lung irritation, and alterations in the lung's defense systems. Adaptations to climate change should include ensuring responsiveness of air quality protection programs to changing pollution levels. Research needs include basic atmospheric science work on the association between weather and air pollutants; improving air pollution models and their linkage with climate change scenarios; and closing gaps in the understanding of exposure patterns and health effects.

Habitat availability and gene flow influence diverging local population trajectories under scenarios of climate change: a place-based approach.

PubMed

Schwalm, Donelle; Epps, Clinton W; Rodhouse, Thomas J; Monahan, William B; Castillo, Jessica A; Ray, Chris; Jeffress, Mackenzie R

2016-04-01

Ecological niche theory holds that species distributions are shaped by a large and complex suite of interacting factors. Species distribution models (SDMs) are increasingly used to describe species' niches and predict the effects of future environmental change, including climate change. Currently, SDMs often fail to capture the complexity of species' niches, resulting in predictions that are generally limited to climate-occupancy interactions. Here, we explore the potential impact of climate change on the American pika using a replicated place-based approach that incorporates climate, gene flow, habitat configuration, and microhabitat complexity into SDMs. Using contemporary presence-absence data from occupancy surveys, genetic data to infer connectivity between habitat patches, and 21 environmental niche variables, we built separate SDMs for pika populations inhabiting eight US National Park Service units representing the habitat and climatic breadth of the species across the western United States. We then predicted occurrence probability under current (1981-2010) and three future time periods (out to 2100). Occurrence probabilities and the relative importance of predictor variables varied widely among study areas, revealing important local-scale differences in the realized niche of the American pika. This variation resulted in diverse and - in some cases - highly divergent future potential occupancy patterns for pikas, ranging from complete extirpation in some study areas to stable occupancy patterns in others. Habitat composition and connectivity, which are rarely incorporated in SDM projections, were influential in predicting pika occupancy in all study areas and frequently outranked climate variables. Our findings illustrate the importance of a place-based approach to species distribution modeling that includes fine-scale factors when assessing current and future climate impacts on species' distributions, especially when predictions are intended to manage and conserve species of concern within individual protected areas. © 2015 John Wiley & Sons Ltd.

Maritime climate influence on chaparral composition and diversity in the coast range of central California.

PubMed

Vasey, Michael C; Parker, V Thomas; Holl, Karen D; Loik, Michael E; Hiatt, Seth

2014-09-01

We investigated the hypothesis that maritime climatic factors associated with summer fog and low cloud stratus (summer marine layer) help explain the compositional diversity of chaparral in the coast range of central California. We randomly sampled chaparral species composition in 0.1-hectare plots along a coast-to-interior gradient. For each plot, climatic variables were estimated and soil samples were analyzed. We used Cluster Analysis and Principle Components Analysis to objectively categorize plots into climate zone groups. Climate variables, vegetation composition and various diversity measures were compared across climate zone groups using ANOVA and nonmetric multidimensional scaling. Differences in climatic variables that relate to summer moisture availability and winter freeze events explained the majority of variance in measured conditions and coincided with three chaparral assemblages: maritime (lowland coast where the summer marine layer was strongest), transition (upland coast with mild summer marine layer influence and greater winter precipitation), and interior sites that generally lacked late summer water availability from either source. Species turnover (β-diversity) was higher among maritime and transition sites than interior sites. Coastal chaparral differs from interior chaparral in having a higher obligate seeder to facultative seeder (resprouter) ratio and by being dominated by various Arctostaphylos species as opposed to the interior dominant, Adenostoma fasciculatum. The maritime climate influence along the California central coast is associated with patterns of woody plant composition and β-diversity among sites. Summer fog in coastal lowlands and higher winter precipitation in coastal uplands combine to lower late dry season water deficit in coastal chaparral and contribute to longer fire return intervals that are associated with obligate seeders and more local endemism. Soil nutrients are comparatively less important in explaining plant community composition, but heterogeneous azonal soils contribute to local endemism and promote isolated chaparral patches within the dominant forest vegetation along the coast.

Global map of solar power production efficiency, considering micro climate factors

NASA Astrophysics Data System (ADS)

Hassanpour Adeh, E.; Higgins, C. W.

2017-12-01

Natural resources degradation and greenhouse gas emissions are creating a global crisis. Renewable energy is the most reliable option to mitigate this environmental dilemma. Abundancy of solar energy makes it highly attractive source of electricity. The existing global spatial maps of available solar energy are created with various models which consider the irradiation, latitude, cloud cover, elevation, shading and aerosols, and neglect the influence of local meteorological conditions. In this research, the influences of microclimatological variables on solar energy productivity were investigated with an in-field study at the Rabbit Hills solar arrays near Oregon State University. The local studies were extended to a global level, where global maps of solar power were produced, taking the micro climate variables into account. These variables included: temperature, relative humidity, wind speed, wind direction, solar radiation. The energy balance approach was used to synthesize the data and compute the efficiencies. The results confirmed that the solar power efficiency can be directly affected by the air temperature and wind speed.

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

NASA Astrophysics Data System (ADS)

Fisher, Jeremy Isaac

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

Climate-Smart Seedlot Selection Tool: Reforestation and Restoration for the 21st Century

NASA Astrophysics Data System (ADS)

Stevenson-Molnar, N.; Howe, G.; St Clair, B.; Bachelet, D. M.; Ward, B. C.

2017-12-01

Local populations of trees are generally adapted to their local climates. Historically, this has meant that local seed zones based on geography and elevation have been used to guide restoration and reforestation. In the face of climate change, seeds from local sources will likely be subjected to climates significantly different from those to which they are currently adapted. The Seedlot Selection Tool (SST) offers a new approach for matching seed sources with planting sites based on future climate scenarios. The SST is a mapping program designed for forest managers and researchers. Users can use the tool to to find seedlots for a given planting site, or to find potential planting sites for a given seedlot. Users select a location (seedlot or planting site), climate scenarios (a climate to which seeds are adapted, and a current or future climate scenario), climate variables, and transfer limits (the maximum climatic distance that is considered a suitable match). Transfer limits are provided by the user, or derived from the range of values within a geographically defined seed zone. The tool calculates scores across the landscape based on an area's similarity, in a multivariate climate space, to the input. Users can explore results on an interactive map, and export PDF and PowerPoint reports, including a map of the results along with the inputs used. Planned future improvements include support for non-forest use cases and ability to download results as GeoTIFF data. The Seedlot Selection Tool and its source code are available online at https://seedlotselectiontool.org. It is co-developed by the United States Forest Service, Oregon State University, and the Conservation Biology Institute.

Modelling climate change and malaria transmission.

PubMed

Parham, Paul E; Michael, Edwin

2010-01-01

The impact of climate change on human health has received increasing attention in recent years, with potential impacts due to vector-borne diseases only now beginning to be understood. As the most severe vector-borne disease, with one million deaths globally in 2006, malaria is thought most likely to be affected by changes in climate variables due to the sensitivity of its transmission dynamics to environmental conditions. While considerable research has been carried out using statistical models to better assess the relationship between changes in environmental variables and malaria incidence, less progress has been made on developing process-based climate-driven mathematical models with greater explanatory power. Here, we develop a simple model of malaria transmission linked to climate which permits useful insights into the sensitivity of disease transmission to changes in rainfall and temperature variables. Both the impact of changes in the mean values of these key external variables and importantly temporal variation in these values are explored. We show that the development and analysis of such dynamic climate-driven transmission models will be crucial to understanding the rate at which P. falciparum and P. vivax may either infect, expand into or go extinct in populations as local environmental conditions change. Malaria becomes endemic in a population when the basic reproduction number R0 is greater than unity and we identify an optimum climate-driven transmission window for the disease, thus providing a useful indicator for determing how transmission risk may change as climate changes. Overall, our results indicate that considerable work is required to better understand ways in which global malaria incidence and distribution may alter with climate change. In particular, we show that the roles of seasonality, stochasticity and variability in environmental variables, as well as ultimately anthropogenic effects, require further study. The work presented here offers a theoretical framework upon which this future research may be developed.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Understanding multidecadal variability in ENSO amplitude

NASA Astrophysics Data System (ADS)

Russell, A.; Gnanadesikan, A.

2013-12-01

Sea surface temperatures (SSTs) in the tropical Pacific vary as a result of the coupling between the ocean and atmosphere driven largely by the El Niño - Southern Oscillation (ENSO). ENSO has a large impact on the local climate and hydrology of the tropical Pacific, as well as broad-reaching effects on global climate. ENSO amplitude is known to vary on long timescales, which makes it very difficult to quantify its response to climate change and constrain the physical processes that drive it. In order to assess the extent of unforced multidecadal changes in ENSO variability, a linear regression of local SST changes is applied to the GFDL CM2.1 model 4000-yr pre-industrial control run. The resulting regression coefficient strengths, which represent the sensitivity of SST changes to thermocline depth and zonal wind stress, vary by up to a factor of 2 on multi-decadal time scales. This long-term modulation in ocean-atmosphere coupling is highly correlated with ENSO variability, but do not explain the reasons for such variability. Variation in the relationship between SST changes and wind stress points to a role for changing stratification in the central equatorial Pacific in modulating ENSO amplitudes with stronger stratification reducing the response to winds. The main driving mechanism we have identified for higher ENSO variance are changes in the response of zonal winds to SST anomalies. The shifting convection and precipitation patterns associated with the changing state of the atmosphere also contribute to the variability of the regression coefficients. These mechanisms drive much of the variability in ENSO amplitude and hence ocean-atmosphere coupling in the tropical Pacific.

The role of internal climate variability for interpreting climate change scenarios

NASA Astrophysics Data System (ADS)

Maraun, Douglas

2013-04-01

When communicating information on climate change, the use of multi-model ensembles has been advocated to sample uncertainties over a range as wide as possible. To meet the demand for easily accessible results, the ensemble is often summarised by its multi-model mean signal. In rare cases, additional uncertainty measures are given to avoid loosing all information on the ensemble spread, e.g., the highest and lowest projected values. Such approaches, however, disregard the fundamentally different nature of the different types of uncertainties and might cause wrong interpretations and subsequently wrong decisions for adaptation. Whereas scenario and climate model uncertainties are of epistemic nature, i.e., caused by an in principle reducible lack of knowledge, uncertainties due to internal climate variability are aleatory, i.e., inherently stochastic and irreducible. As wisely stated in the proverb "climate is what you expect, weather is what you get", a specific region will experience one stochastic realisation of the climate system, but never exactly the expected climate change signal as given by a multi model mean. Depending on the meteorological variable, region and lead time, the signal might be strong or weak compared to the stochastic component. In cases of a low signal-to-noise ratio, even if the climate change signal is a well defined trend, no trends or even opposite trends might be experienced. Here I propose to use the time of emergence (TOE) to quantify and communicate when climate change trends will exceed the internal variability. The TOE provides a useful measure for end users to assess the time horizon for implementing adaptation measures. Furthermore, internal variability is scale dependent - the more local the scale, the stronger the influence of internal climate variability. Thus investigating the TOE as a function of spatial scale could help to assess the required spatial scale for implementing adaptation measures. I exemplify this proposal with a recently published study on the TOE for mean and heavy precipitation trends in Europe. In some regions trends emerge only late in the 21st century or even later, suggesting that in these regions adaptation to internal variability rather than to climate change is required. Yet in other regions the climate change signal is strong, urging for timely adaptation. Douglas Maraun, When at what scale will trends in European mean and heavy precipitation emerge? Env. Res. Lett., in press, 2013.

Why and How the Dairy Farmers of India are Vulnerable to the Impacts of Climate Variability and Change?

NASA Astrophysics Data System (ADS)

Radhakrishnan, A.; Gupta, J.

2017-12-01

Climate change and variability has added many atrociousness to India's food security challenges and the relationship between the asset components of farmers and climate change is always complex. In India, dairy farming substantially contributes towards the food security and always plays a supportive role to agriculture from the adversities. This study provides an overview of the socio economic and livelihood vulnerability of small holder dairy farmers of India to climate change and variability in three dimensions — sensitivity, exposure and adaptive capacity by combining 70 indicators and 12 major components. The livelihood and socio economic vulnerability of dairy farmers to climate change and variability is assessed at taluka level in India through detailed house hold level data of livelihoods of Western Ghats region of India collected by several levels of survey and through Participatory Rural Appraisal (PRA) techniques from selected farmers complemented by thirty years of gridded weather data and other secondary data sources. The index score of dairy based livelihoods of Maharashtra was highly negative compared to other states with about 50 percent of farmers having high level of vulnerability with significant tradeoff between milk productivity and health, food, natural disasters-climate variability components. It finds that ensuring food security in the scenario of climate change will be a dreadful challenge and recommends identification of different potential options depending on local contexts at grass root level, the adoption of sustainable agricultural practices, focusing on improving the adaptive capacity component, provision of livelihood security, preparing the extensionists of Krishi Vigyan Kendras (KVKs)- universities to deal with the risks through extensive training programmes, long-term relief measures in the event of natural disasters, workshops on climate science and communication and promoting farmer centric extension system.

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.

High-Resolution Climate Data Visualization through GIS- and Web-based Data Portals

NASA Astrophysics Data System (ADS)

WANG, X.; Huang, G.

2017-12-01

Sound decisions on climate change adaptation rely on an in-depth assessment of potential climate change impacts at regional and local scales, which usually requires finer resolution climate projections at both spatial and temporal scales. However, effective downscaling of global climate projections is practically difficult due to the lack of computational resources and/or long-term reference data. Although a large volume of downscaled climate data has been make available to the public, how to understand and interpret the large-volume climate data and how to make use of the data to drive impact assessment and adaptation studies are still challenging for both impact researchers and decision makers. Such difficulties have become major barriers preventing informed climate change adaptation planning at regional scales. Therefore, this research will explore new GIS- and web-based technologies to help visualize the large-volume regional climate data with high spatiotemporal resolutions. A user-friendly public data portal, named Climate Change Data Portal (CCDP, http://ccdp.network), will be established to allow intuitive and open access to high-resolution regional climate projections at local scales. The CCDP offers functions of visual representation through geospatial maps and data downloading for a variety of climate variables (e.g., temperature, precipitation, relative humidity, solar radiation, and wind) at multiple spatial resolutions (i.e., 25 - 50 km) and temporal resolutions (i.e., annual, seasonal, monthly, daily, and hourly). The vast amount of information the CCDP encompasses can provide a crucial basis for assessing impacts of climate change on local communities and ecosystems and for supporting better decision making under a changing climate.

Climate change impacts on human exposures to air pollution ...

EPA Pesticide Factsheets

This is an abstract for a presentations at the Annual Conference of the International Society on Exposure Science and Environmental Epidemiology. This presentation will serve as an introduction to the symposium. As we consider the potential health impacts of a warming planet, the relationships between climate change and air pollutants become increasingly important to understand. These relationships are complex and highly variable, causing a variety of environmental impacts at local, regional and global scales. Human exposures and health impacts for air pollutants have the potential to be altered by changes in climate through multiple factors that drive population exposures to these pollutants. Research on this topic will provide both state and local governments with the tools and scientific knowledge base to undertake any necessary adaptation of the air pollution regulations and/or public health management systems in the face of climate change.

Local weather, regional climate, and annual survival of the northern spotted owl

USGS Publications Warehouse

Glenn, E.M.; Anthony, R.G.; Forsman, E.D.; Olson, G.S.

2011-01-01

We used an information-theoretical approach and Cormack-Jolly-Seber models for open populations in program MARK to examine relationships between survival rates of Northern Spotted Owls and a variety of local weather variables and long-term climate variables. In four of the six populations examined, survival was positively associated with wetter than normal conditions during the growing season or high summer temperatures. At the three study areas located at the highest elevations, survival was positively associated with winter temperature but also had a negative or quadratic relation with the number of storms and winter precipitation. A metaanalysis of all six areas combined indicated that annual survival was most strongly associated with phase shifts in the Southern Oscillation and Pacific Decadal Oscillation, which reflect large-scale temperature and precipitation patterns in this region. Climate accounted for a variable amount (1-41%) of the total process variation in annual survival but for more year-to-year variation (3-66%) than did spatial variation among owl territories (0-7%). Negative associations between survival and cold, wet winters and nesting seasons were similar to those found in other studies of the Spotted Owl. The relationships between survival and growing-season precipitation and regional climate patterns, however, had not been reported for this species previously. Climate-change models for the first half of the 21st century predict warmer, wetter winters and hotter, drier summers for the Pacific Northwest. Our results indicate that these conditions could decrease Spotted Owl survival in some areas. Copyright ?? The Cooper Ornithological Society 2011.

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.

Identifying bird and reptile vulnerabilities to climate change in the southwestern United States

USGS Publications Warehouse

Hatten, James R.; Giermakowski, J. Tomasz; Holmes, Jennifer A.; Nowak, Erika M.; Johnson, Matthew J.; Ironside, Kirsten E.; van Riper, Charles; Peters, Michael; Truettner, Charles; Cole, Kenneth L.

2016-07-06

Current and future breeding ranges of 15 bird and 16 reptile species were modeled in the Southwestern United States. Rather than taking a broad-scale, vulnerability-assessment approach, we created a species distribution model (SDM) for each focal species incorporating climatic, landscape, and plant variables. Baseline climate (1940–2009) was characterized with Parameter-elevation Regressions on Independent Slopes Model (PRISM) data and future climate with global-circulation-model data under an A1B emission scenario. Climatic variables included monthly and seasonal temperature and precipitation; landscape variables included terrain ruggedness, soil type, and insolation; and plant variables included trees and shrubs commonly associated with a focal species. Not all species-distribution models contained a plant, but if they did, we included a built-in annual migration rate for more accurate plant-range projections in 2039 or 2099. We conducted a group meta-analysis to (1) determine how influential each variable class was when averaged across all species distribution models (birds or reptiles), and (2) identify the correlation among contemporary (2009) habitat fragmentation and biological attributes and future range projections (2039 or 2099). Projected changes in bird and reptile ranges varied widely among species, with one-third of the ranges predicted to expand and two-thirds predicted to contract. A group meta-analysis indicated that climatic variables were the most influential variable class when averaged across all models for both groups, followed by landscape and plant variables (birds), or plant and landscape variables (reptiles), respectively. The second part of the meta-analysis indicated that numerous contemporary habitat-fragmentation (for example, patch isolation) and biological-attribute (for example, clutch size, longevity) variables were significantly correlated with the magnitude of projected range changes for birds and reptiles. Patch isolation was a significant trans-specific driver of projected bird and reptile ranges, suggesting that strategic actions should focus on restoration and enhancement of habitat at local and regional scales to promote landscape connectivity and conservation of core areas.

Factors regulating year‐class strength of Silver Carp throughout the Mississippi River basin

USGS Publications Warehouse

Sullivan, Christopher J.; Weber, Michael J.; Pierce, Clay; Wahl, David H.; Phelps, Quinton E.; Camacho, Carlos A.; Colombo, Robert E.

2018-01-01

Recruitment of many fish populations is inherently highly variable inter‐annually. However, this variability can be synchronous at broad geographic scales due to fish dispersal and climatic conditions. Herein, we investigated recruitment synchrony of Silver Carp Hypophthalmichthys molitrix across the Mississippi River basin. Year‐class strength (YCS) and synchrony of nine populations (max linear distance = 806.4 km) was indexed using catch‐curve residuals correlated between sites and related to local and regional climatic conditions. Overall, Silver Carp YCS was not synchronous among populations, suggesting local environmental factors are more important determinants of YCS than large‐scale environmental factors. Variation in Silver Carp YCS was influenced by river base flow and discharge variability at each site, indicating that extended periods of static local discharge benefit YCS. Further, river discharge and air temperature were correlated and synchronized among sites, but only similarities in river discharge was correlated with Silver Carp population synchrony, indicating that similarities in discharge (i.e., major flood) among sites can positively synchronize Silver Carp YCS. The positive correlation between Silver Carp YCS and river discharge synchrony suggests that regional flood regimes are an important force determining the degree of population synchrony among Mississippi River Silver Carp populations.

Watershed Adaptation Measures to Climate Change Impacts: A case of Kiha Watershed in Albertine Graben

NASA Astrophysics Data System (ADS)

Zizinga, A.

2017-12-01

Watershed Adaptation Measures to Climate Change Impacts: A case of Kiha Watershed in Albertine GrabenAlex Zizinga1, Moses Tenywa2, Majaliwa Jackson Gilbert1, 1Makerere University, Department of Environmental Sciences, O Box 7062, Kampala, Uganda 1Makerere University, Department of Agricultural Production, P.O Box 7062, Kampala, Uganda Corresponding author: azizinga@caes.mak.ac.ug AbstractThe most pressing issues local communities in Uganda are facing result from land-use and land cover changes exacerbated by climate change impacts. A key issue is the documentation of land-cover changes visible with the ongoing clearance of remaining forests, bush-lands and wetlands for expanding farmland for sugarcane production, producing charcoal and collecting firewood for local distilleries using imported molasses. Decision-makers, resource managers, farmers and practitioners must build their capacity for adaptive measures. Here we present the potential impacts of climate change on watershed hydrological processes in the River Kiha Watershed, located in Western Uganda, Lake Albert Water Management Zone, by using social learning techniques incorporating water users, local stakeholders and researchers. The research team examined different farming and economic activities within the watershed to assess their impacts on catchment water resources, namely on water quality and discharge of river Kiha. We present the impacts of locally induced climate change, which are already manifested in increasing seasonal variability of rainfall. The study aims at answering questions posed by local communities and stakeholders about climate change and its effects on livelihood and key resources, specifically water and soils within the Kiha watershed. Key words: Climate change impacts, Social Learning and Watershed Management

Incremental dynamical downscaling for probabilistic analysis based on multiple GCM projections

NASA Astrophysics Data System (ADS)

Wakazuki, Y.

2015-12-01

A dynamical downscaling method for probabilistic regional scale climate change projections was developed to cover an uncertainty of multiple general circulation model (GCM) climate simulations. The climatological increments (future minus present climate states) estimated by GCM simulation results were statistically analyzed using the singular vector decomposition. Both positive and negative perturbations from the ensemble mean with the magnitudes of their standard deviations were extracted and were added to the ensemble mean of the climatological increments. The analyzed multiple modal increments were utilized to create multiple modal lateral boundary conditions for the future climate regional climate model (RCM) simulations by adding to an objective analysis data. This data handling is regarded to be an advanced method of the pseudo-global-warming (PGW) method previously developed by Kimura and Kitoh (2007). The incremental handling for GCM simulations realized approximated probabilistic climate change projections with the smaller number of RCM simulations. Three values of a climatological variable simulated by RCMs for a mode were used to estimate the response to the perturbation of the mode. For the probabilistic analysis, climatological variables of RCMs were assumed to show linear response to the multiple modal perturbations, although the non-linearity was seen for local scale rainfall. Probability of temperature was able to be estimated within two modes perturbation simulations, where the number of RCM simulations for the future climate is five. On the other hand, local scale rainfalls needed four modes simulations, where the number of the RCM simulations is nine. The probabilistic method is expected to be used for regional scale climate change impact assessment in the future.

Stability of ENSO and Its Tropical Pacific Teleconnections over the Last Millennium

NASA Technical Reports Server (NTRS)

Lewis, Sophie; Legrande, A. N.

2015-01-01

Determining past changes in the amplitude, frequency and teleconnections of the El Nio Southern Oscillation (ENSO) is important for understanding its potential sensitivity to future anthropogenic climate change. Palaeo-reconstructions from proxy records provide long-term information of ENSO interactions with the background climatic state through time. However, it remains unclear how ENSO characteristics have changed through time, and precisely which signals proxies record. Proxy interpretations are underpinned by the assumption of stationarity in relationships between local and remote climates, and often utilise archives from single locations located in the Pacific Ocean to reconstruct ENSO histories. Here, we investigate the stationarity of ENSO teleconnections using the Last Millennium experiment of CMIP5 (Coupled Model Intercomparison Project phase 5) (Taylor et al., 2012). We show that modelled ENSO characteristics vary on decadal- to centennial-scales, resulting from internal variability and external forcings, such as tropical volcanic eruptions. Furthermore, the relationship between ENSO conditions and local climates across the Pacific basin varies throughout the Last Millennium. Results show the stability of teleconnections is regionally dependent and proxies may reveal complex changes in teleconnected patterns, rather than large-scale changes in base ENSO characteristics. As such, proxy insights into ENSO likely require evidence to be synthesised over large spatial areas in order to deconvolve changes occurring in the NINO3.4 region from those pertaining to proxy-relevant local climatic variables. To obtain robust histories of the ENSO and its remote impacts, we recommend interpretations of proxy records should be considered in conjunction with palaeo-reconstructions from within the Central Pacific

Paleoeskimo Demographic History in the Canadian Arctic (ca. 4800-800 B.P.) and its Relationship to Mid-Late Holocene Climate Variability.

NASA Astrophysics Data System (ADS)

Savelle, J. M.

2014-12-01

Paleoeskimos were the first occupants of the central and eastern Canadian Arctic, spreading east from the Bering Strait region beginning approximately 4800 B.P., and occupied much of the Canadian Arctic through to their eventual disappearance ca. 800 B.P. Extensive regional archaeological site surveys throughout this area by the author and Arthur S. Dyke indicate that Paleoskimo populations underwent a series of population 'boom' (rapid expansion) and 'bust' (population declines and local extinctions) over the 4,000 year occupation history, including in the purported stable 'core area' of Foxe Basin. In this paper, we examine the contemporaneity of the local boom and bust cycles in a pan-Canadian Arctic context, and in turn examine the relationship of these cycles to mid-late Holocene climate variability.

The Importance of Biotic vs. Abiotic Drivers of Local Plant Community Composition Along Regional Bioclimatic Gradients

PubMed Central

Klanderud, Kari; Vandvik, Vigdis; Goldberg, Deborah

2015-01-01

We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages. PMID:26091266

The Importance of Biotic vs. Abiotic Drivers of Local Plant Community Composition Along Regional Bioclimatic Gradients.

PubMed

Klanderud, Kari; Vandvik, Vigdis; Goldberg, Deborah

2015-01-01

We assessed if the relative importance of biotic and abiotic factors for plant community composition differs along environmental gradients and between functional groups, and asked which implications this may have in a warmer and wetter future. The study location is a unique grid of sites spanning regional-scale temperature and precipitation gradients in boreal and alpine grasslands in southern Norway. Within each site we sampled vegetation and associated biotic and abiotic factors, and combined broad- and fine-scale ordination analyses to assess the relative explanatory power of these factors for species composition. Although the community responses to biotic and abiotic factors did not consistently change as predicted along the bioclimatic gradients, abiotic variables tended to explain a larger proportion of the variation in species composition towards colder sites, whereas biotic variables explained more towards warmer sites, supporting the stress gradient hypothesis. Significant interactions with precipitation suggest that biotic variables explained more towards wetter climates in the sub alpine and boreal sites, but more towards drier climates in the colder alpine. Thus, we predict that biotic interactions may become more important in alpine and boreal grasslands in a warmer future, although more winter precipitation may counteract this trend in oceanic alpine climates. Our results show that both local and regional scales analyses are needed to disentangle the local vegetation-environment relationships and their regional-scale drivers, and biotic interactions and precipitation must be included when predicting future species assemblages.

Making the best of climatic variability: options for upgrading rainfed farming in water scarce regions.

PubMed

Rockström, J

2004-01-01

Coping with climatic variability for livelihood security is part of everyday life for rural communities in semi-arid and dry sub-humid savannas. Water scarcity caused by rainfall fluctuations is common, causing meteorological droughts and dry spells. However, this paper indicates, based on experiences in sub-Saharan Africa and India, that the social impact on rural societies of climatically induced droughts is exaggerated. Instead, water scarcity causing food deficits is more often caused by management induced droughts and dry spells. A conceptual framework to distinguish between manageable and unmanageable droughts is presented. It is suggested that climatic droughts require focus on social resilience building instead of land and water resource management. Focus is then set on the manageable part of climatic variability, namely the almost annual occurrence of dry spells, short 2-4 week periods of no rainfall, affecting farmer yields. On-farm experiences in savannas of sub-Saharan Africa of water harvesting systems for dry spell mitigation are presented. It is shown that bridging dry spells combined with soil fertility management can double and even triple on-farm yield levels. Combined with innovative systems to ensure maximum plant water availability and water uptake capacity, through adoption of soil fertility improvement and conservation tillage systems, there is a clear opportunity to upgrade rainfed farming systems in vulnerable savanna environments, through appropriate local management of climatic variability.

Local farmers' perceptions of climate change and local adaptive strategies: a case study from the Middle Yarlung Zangbo River Valley, Tibet, China.

PubMed

Li, Chunyan; Tang, Ya; Luo, Han; Di, Baofeng; Zhang, Liyun

2013-10-01

Climate change affects the productivity of agricultural ecosystems. Farmers cope with climate change based on their perceptions of changing climate patterns. Using a case study from the Middle Yarlung Zangbo River Valley, we present a new research framework that uses questionnaire and interview methods to compare local farmers' perceptions of climate change with the adaptive farming strategies they adopt. Most farmers in the valley believed that temperatures had increased in the last 30 years but did not note any changes in precipitation. Most farmers also reported sowing and harvesting hulless barley 10-15 days earlier than they were 20 years ago. In addition, farmers observed that plants were flowering and river ice was melting earlier in the season, but they did not perceive changes in plant germination, herbaceous vegetation growth, or other spring seasonal events. Most farmers noticed an extended fall season signified by delays in the freezing of rivers and an extended growing season for grassland vegetation. The study results showed that agricultural practices in the study area are still traditional; that is, local farmers' perceptions of climate change and their strategies to mitigate its impacts were based on indigenous knowledge and their own experiences. Adaptive strategies included adjusting planting and harvesting dates, changing crop species, and improving irrigation infrastructure. However, the farmers' decisions could not be fully attributed to their concerns about climate change. Local farming systems exhibit high adaptability to climate variability. Additionally, off-farm income has reduced the dependence of the farmers on agriculture, and an agricultural subsidy from the Chinese Central Government has mitigated the farmers' vulnerability. Nevertheless, it remains necessary for local farmers to build a system of adaptive climate change strategies that combines traditional experience and indigenous knowledge with scientific research and government polices as key factors.

Local Farmers' Perceptions of Climate Change and Local Adaptive Strategies: A Case Study from the Middle Yarlung Zangbo River Valley, Tibet, China

NASA Astrophysics Data System (ADS)

Li, Chunyan; Tang, Ya; Luo, Han; Di, Baofeng; Zhang, Liyun

2013-10-01

Climate change affects the productivity of agricultural ecosystems. Farmers cope with climate change based on their perceptions of changing climate patterns. Using a case study from the Middle Yarlung Zangbo River Valley, we present a new research framework that uses questionnaire and interview methods to compare local farmers' perceptions of climate change with the adaptive farming strategies they adopt. Most farmers in the valley believed that temperatures had increased in the last 30 years but did not note any changes in precipitation. Most farmers also reported sowing and harvesting hulless barley 10-15 days earlier than they were 20 years ago. In addition, farmers observed that plants were flowering and river ice was melting earlier in the season, but they did not perceive changes in plant germination, herbaceous vegetation growth, or other spring seasonal events. Most farmers noticed an extended fall season signified by delays in the freezing of rivers and an extended growing season for grassland vegetation. The study results showed that agricultural practices in the study area are still traditional; that is, local farmers' perceptions of climate change and their strategies to mitigate its impacts were based on indigenous knowledge and their own experiences. Adaptive strategies included adjusting planting and harvesting dates, changing crop species, and improving irrigation infrastructure. However, the farmers' decisions could not be fully attributed to their concerns about climate change. Local farming systems exhibit high adaptability to climate variability. Additionally, off-farm income has reduced the dependence of the farmers on agriculture, and an agricultural subsidy from the Chinese Central Government has mitigated the farmers' vulnerability. Nevertheless, it remains necessary for local farmers to build a system of adaptive climate change strategies that combines traditional experience and indigenous knowledge with scientific research and government polices as key factors.

Local Populations of Arabidopsis thaliana Show Clear Relationship between Photoperiodic Sensitivity of Flowering Time and Altitude

PubMed Central

Lewandowska-Sabat, Anna M.; Fjellheim, Siri; Olsen, Jorunn E.; Rognli, Odd A.

2017-01-01

Adaptation of plants to local conditions that vary substantially within their geographic range is essential for seasonal timing of flowering, a major determinant of plant reproductive success. This study investigates photoperiodic responses in natural populations of Arabidopsis thaliana from high northern latitudes and their significance for local adaptation. Thirty lineages from ten local A. thaliana populations, representing different locations across an altitudinal gradient (2–850 m a.s.l.) in Norway, were grown under uniform controlled conditions, and used to screen for responses to five different photoperiods. We studied relationships between variation in photoperiodic sensitivity of flowering time, altitude, and climatic factors associated with the sites of origin. We found that variation in response to photoperiod is significantly correlated with altitude and climatic variables associated with the sites of origin of the populations. Populations originating from lower altitudes showed stronger photoperiodic sensitivity than populations from higher altitudes. Our results indicate that the altitudinal climatic gradient generates clinal variation in adaptive traits in A. thaliana. PMID:28659966

Choosing and using climate-change scenarios for ecological-impact assessments and conservation decisions.

PubMed

Snover, Amy K; Mantua, Nathan J; Littell, Jeremy S; Alexander, Michael A; McClure, Michelle M; Nye, Janet

2013-12-01

Increased concern over climate change is demonstrated by the many efforts to assess climate effects and develop adaptation strategies. Scientists, resource managers, and decision makers are increasingly expected to use climate information, but they struggle with its uncertainty. With the current proliferation of climate simulations and downscaling methods, scientifically credible strategies for selecting a subset for analysis and decision making are needed. Drawing on a rich literature in climate science and impact assessment and on experience working with natural resource scientists and decision makers, we devised guidelines for choosing climate-change scenarios for ecological impact assessment that recognize irreducible uncertainty in climate projections and address common misconceptions about this uncertainty. This approach involves identifying primary local climate drivers by climate sensitivity of the biological system of interest; determining appropriate sources of information for future changes in those drivers; considering how well processes controlling local climate are spatially resolved; and selecting scenarios based on considering observed emission trends, relative importance of natural climate variability, and risk tolerance and time horizon of the associated decision. The most appropriate scenarios for a particular analysis will not necessarily be the most appropriate for another due to differences in local climate drivers, biophysical linkages to climate, decision characteristics, and how well a model simulates the climate parameters and processes of interest. Given these complexities, we recommend interaction among climate scientists, natural and physical scientists, and decision makers throughout the process of choosing and using climate-change scenarios for ecological impact assessment. Selección y Uso de Escenarios de Cambio Climático para Estudios de Impacto Ecológico y Decisiones de Conservación. © 2013 Society for Conservation Biology.

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

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

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

DOE PAGES

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; ...

2016-10-04

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth’s climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modesmore » and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this article, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.« less

Spatial Patterns of Sea Level Variability Associated with Natural Internal Climate Modes

NASA Astrophysics Data System (ADS)

Han, Weiqing; Meehl, Gerald A.; Stammer, Detlef; Hu, Aixue; Hamlington, Benjamin; Kenigson, Jessica; Palanisamy, Hindumathi; Thompson, Philip

2017-01-01

Sea level rise (SLR) can exert significant stress on highly populated coastal societies and low-lying island countries around the world. Because of this, there is huge societal demand for improved decadal predictions and future projections of SLR, particularly on a local scale along coastlines. Regionally, sea level variations can deviate considerably from the global mean due to various geophysical processes. These include changes of ocean circulations, which partially can be attributed to natural, internal modes of variability in the complex Earth's climate system. Anthropogenic influence may also contribute to regional sea level variations. Separating the effects of natural climate modes and anthropogenic forcing, however, remains a challenge and requires identification of the imprint of specific climate modes in observed sea level change patterns. In this paper, we review our current state of knowledge about spatial patterns of sea level variability associated with natural climate modes on interannual-to-multidecadal timescales, with particular focus on decadal-to-multidecadal variability. Relevant climate modes and our current state of understanding their associated sea level patterns and driving mechanisms are elaborated separately for the Pacific, the Indian, the Atlantic, and the Arctic and Southern Oceans. We also discuss the issues, challenges and future outlooks for understanding the regional sea level patterns associated with climate modes. Effects of these internal modes have to be taken into account in order to achieve more reliable near-term predictions and future projections of regional SLR.

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.

Holocene environmental changes inferred from biological and sedimentological proxies in a high elevation Great Basin lake in the northern Ruby Mountains, Nevada, USA

USGS Publications Warehouse

Wahl, David B.; Starratt, Scott W.; Anderson, Lysanna; Kusler, Jennifer E.; Fuller, Christopher C.; Addison, Jason A.; Wan, Elmira

2015-01-01

Multi-proxy analyses were conducted on a sediment core from Favre Lake, a high elevation cirque lake in the northern Ruby Mountains, Nevada, and provide a ca. 7600 year record of local and regional environmental change. Data indicate that lake levels were lower from 7600-5750 cal yr BP, when local climate was warmer and/or drier than today. Effective moisture increased after 5750 cal yr BP and remained relatively wet, and possibly cooler, until ca. 3750 cal yr BP. Results indicate generally dry conditions but also enhanced climatic variability from 3750-1750 cal yr BP, after which effective moisture increased. The timing of major changes in the Favre Lake proxy data are roughly coeval and in phase with those recorded in several paleoclimate studies across the Great Basin, suggesting regional climatic controls on local conditions and similar responses at high and low altitudes.

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.

Improved methods for estimating local terrestrial water dynamics from GRACE in the Northern High Plains

NASA Astrophysics Data System (ADS)

Seyoum, Wondwosen M.; Milewski, Adam M.

2017-12-01

Investigating terrestrial water cycle dynamics is vital for understanding the recent climatic variability and human impacts in the hydrologic cycle. In this study, a downscaling approach was developed and tested, to improve the applicability of terrestrial water storage (TWS) anomaly data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission for understanding local terrestrial water cycle dynamics in the Northern High Plains region. A non-parametric, artificial neural network (ANN)-based model, was utilized to downscale GRACE data by integrating it with hydrological variables (e.g. soil moisture) derived from satellite and land surface model data. The downscaling model, constructed through calibration and sensitivity analysis, was used to estimate TWS anomaly for watersheds ranging from 5000 to 20,000 km2 in the study area. The downscaled water storage anomaly data were evaluated using water storage data derived from an (1) integrated hydrologic model, (2) land surface model (e.g. Noah), and (3) storage anomalies calculated from in-situ groundwater level measurements. Results demonstrate the ANN predicts monthly TWS anomaly within the uncertainty (conservative error estimate = 34 mm) for most of the watersheds. Seasonal derived groundwater storage anomaly (GWSA) from the ANN correlated well (r = ∼0.85) with GWSAs calculated from in-situ groundwater level measurements for a watershed size as small as 6000 km2. ANN downscaled TWSA matches closely with Noah-based TWSA compared to standard GRACE extracted TWSA at a local scale. Moreover, the ANN-downscaled change in TWS replicated the water storage variability resulting from the combined effect of climatic and human impacts (e.g. abstraction). The implications of utilizing finer resolution GRACE data for improving local and regional water resources management decisions and applications are clear, particularly in areas lacking in-situ hydrologic monitoring networks.

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.

Results from the VALUE perfect predictor experiment: process-based evaluation

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Soares, Pedro; Hertig, Elke; Brands, Swen; Huth, Radan; Cardoso, Rita; Kotlarski, Sven; Casado, Maria; Pongracz, Rita; Bartholy, Judit

2016-04-01

Until recently, the evaluation of downscaled climate model simulations has typically been limited to surface climatologies, including long term means, spatial variability and extremes. But these aspects are often, at least partly, tuned in regional climate models to match observed climate. The tuning issue is of course particularly relevant for bias corrected regional climate models. In general, a good performance of a model for these aspects in present climate does therefore not imply a good performance in simulating climate change. It is now widely accepted that, to increase our condidence in climate change simulations, it is necessary to evaluate how climate models simulate relevant underlying processes. In other words, it is important to assess whether downscaling does the right for the right reason. Therefore, VALUE has carried out a broad process-based evaluation study based on its perfect predictor experiment simulations: the downscaling methods are driven by ERA-Interim data over the period 1979-2008, reference observations are given by a network of 85 meteorological stations covering all European climates. More than 30 methods participated in the evaluation. In order to compare statistical and dynamical methods, only variables provided by both types of approaches could be considered. This limited the analysis to conditioning local surface variables on variables from driving processes that are simulated by ERA-Interim. We considered the following types of processes: at the continental scale, we evaluated the performance of downscaling methods for positive and negative North Atlantic Oscillation, Atlantic ridge and blocking situations. At synoptic scales, we considered Lamb weather types for selected European regions such as Scandinavia, the United Kingdom, the Iberian Pensinsula or the Alps. At regional scales we considered phenomena such as the Mistral, the Bora or the Iberian coastal jet. Such process-based evaluation helps to attribute biases in surface variables to underlying processes and ultimately to improve climate models.

Scrub typhus islands in the Taiwan area and the association between scrub typhus disease and forest land use and farmer population density: geographically weighted regression.

PubMed

Tsai, Pui-Jen; Yeh, Hsi-Chyi

2013-04-29

The Taiwan area comprises the main island of Taiwan and several small islands located off the coast of the Southern China. The eastern two-thirds of Taiwan are characterized by rugged mountains covered with tropical and subtropical vegetation. The western region of Taiwan is characterized by flat or gently rolling plains. Geographically, the Taiwan area is diverse in ecology and environment, although scrub typhus threatens local human populations. In this study, we investigate the effects of seasonal and meteorological factors on the incidence of scrub typhus infection among 10 local climate regions. The correlation between the spatial distribution of scrub typhus and cultivated forests in Taiwan, as well as the relationship between scrub typhus incidence and the population density of farm workers is examined. We applied Pearson's product moment correlation to calculate the correlation between the incidence of scrub typhus and meteorological factors among 10 local climate regions. We used the geographically weighted regression (GWR) method, a type of spatial regression that generates parameters disaggregated by the spatial units of analysis, to detail and map each regression point for the response variables of the standardized incidence ratio (SIR)-district scrub typhus. We also applied the GWR to examine the explanatory variables of types of forest-land use and farm worker density in Taiwan in 2005. In the Taiwan Area, scrub typhus endemic areas are located in the southeastern regions and mountainous townships of Taiwan, as well as the Pescadore, Kinmen, and Matou Islands. Among these islands and low-incidence areas in the central western and southwestern regions of Taiwan, we observed a significant correlation between scrub typhus incidence and surface temperature. No similar significant correlation was found in the endemic areas (e.g., the southeastern region and the mountainous area of Taiwan). Precipitation correlates positively with scrub typhus incidence in 3 local climate regions (i.e., Taiwan's central western and southwestern regions, and the Kinmen Islands). Relative humidity correlates positively with incidence in Southwestern Taiwan and the Kinmen Islands. The number of wet days correlates positively with incidence in Southwestern Taiwan. The duration of sunshine correlates positively with incidence in Central Western Taiwan, as well as the Kinmen and Matou Islands. In addition, the 10 local climatic regions can be classified into the following 3 groups, based on the warm-cold seasonal fluctuations in scrub typhus incidence: (a) Type 1, evident in 5 local climate regions (Taiwan's northern, northwestern, northeastern, and southeastern regions, as well as the mountainous area); (b) Type 2 (Taiwan's central western and southwestern regions, and the Pescadore Islands); and (c) Type 3 (the Kinmen and Matou Islands). In the GWR models, the response variable of the SIR-district scrub typhus has a statistically significantly positive association with 2 explanatory variables (farm worker population density and timber management). In addition, other explanatory variables (recreational forests, natural reserves, and "other purpose" areas) show positive or negative signs for parameter estimates in various locations in Taiwan. Negative signs of parameter estimates occurred only for the explanatory variables of national protectorates, plantations, and clear-cut areas. The results of this study show that scrub typhus in Taiwan can be classified into 3 types. Type 1 exhibits no climatic effect, whereas the incidence of Type 2 correlates positively with higher temperatures during the warm season, and the incidence of Type 3 correlates positively with higher surface temperatures and longer hours of sunshine. The results also show that in the mountainous township areas of Taiwan's central and southern regions, as well as in Southeastern Taiwan, higher SIR values for scrub typhus are associated with the following variables: farm worker population density, timber management, and area type (i.e., recreational forest, natural reserve, or other purpose).

Scrub typhus islands in the Taiwan area and the association between scrub typhus disease and forest land use and farmer population density: geographically weighted regression

PubMed Central

2013-01-01

Background The Taiwan area comprises the main island of Taiwan and several small islands located off the coast of the Southern China. The eastern two-thirds of Taiwan are characterized by rugged mountains covered with tropical and subtropical vegetation. The western region of Taiwan is characterized by flat or gently rolling plains. Geographically, the Taiwan area is diverse in ecology and environment, although scrub typhus threatens local human populations. In this study, we investigate the effects of seasonal and meteorological factors on the incidence of scrub typhus infection among 10 local climate regions. The correlation between the spatial distribution of scrub typhus and cultivated forests in Taiwan, as well as the relationship between scrub typhus incidence and the population density of farm workers is examined. Methods We applied Pearson’s product moment correlation to calculate the correlation between the incidence of scrub typhus and meteorological factors among 10 local climate regions. We used the geographically weighted regression (GWR) method, a type of spatial regression that generates parameters disaggregated by the spatial units of analysis, to detail and map each regression point for the response variables of the standardized incidence ratio (SIR)-district scrub typhus. We also applied the GWR to examine the explanatory variables of types of forest-land use and farm worker density in Taiwan in 2005. Results In the Taiwan Area, scrub typhus endemic areas are located in the southeastern regions and mountainous townships of Taiwan, as well as the Pescadore, Kinmen, and Matou Islands. Among these islands and low-incidence areas in the central western and southwestern regions of Taiwan, we observed a significant correlation between scrub typhus incidence and surface temperature. No similar significant correlation was found in the endemic areas (e.g., the southeastern region and the mountainous area of Taiwan). Precipitation correlates positively with scrub typhus incidence in 3 local climate regions (i.e., Taiwan’s central western and southwestern regions, and the Kinmen Islands). Relative humidity correlates positively with incidence in Southwestern Taiwan and the Kinmen Islands. The number of wet days correlates positively with incidence in Southwestern Taiwan. The duration of sunshine correlates positively with incidence in Central Western Taiwan, as well as the Kinmen and Matou Islands. In addition, the 10 local climatic regions can be classified into the following 3 groups, based on the warm-cold seasonal fluctuations in scrub typhus incidence: (a) Type 1, evident in 5 local climate regions (Taiwan’s northern, northwestern, northeastern, and southeastern regions, as well as the mountainous area); (b) Type 2 (Taiwan’s central western and southwestern regions, and the Pescadore Islands); and (c) Type 3 (the Kinmen and Matou Islands). In the GWR models, the response variable of the SIR-district scrub typhus has a statistically significantly positive association with 2 explanatory variables (farm worker population density and timber management). In addition, other explanatory variables (recreational forests, natural reserves, and “other purpose” areas) show positive or negative signs for parameter estimates in various locations in Taiwan. Negative signs of parameter estimates occurred only for the explanatory variables of national protectorates, plantations, and clear-cut areas. Conclusion The results of this study show that scrub typhus in Taiwan can be classified into 3 types. Type 1 exhibits no climatic effect, whereas the incidence of Type 2 correlates positively with higher temperatures during the warm season, and the incidence of Type 3 correlates positively with higher surface temperatures and longer hours of sunshine. The results also show that in the mountainous township areas of Taiwan’s central and southern regions, as well as in Southeastern Taiwan, higher SIR values for scrub typhus are associated with the following variables: farm worker population density, timber management, and area type (i.e., recreational forest, natural reserve, or other purpose). PMID:23627966

Hydrological Responses of Andean Lakes and Tropical Floodplains to Climate Variability and Human Intervention: an Integrative Modelling Framework

NASA Astrophysics Data System (ADS)

Hoyos, I. C.; González Morales, C.; Serna López, J. P.; Duque, C. L.; Canon Barriga, J. E.; Dominguez, F.

2013-12-01

Andean water bodies in tropical regions are significantly influenced by fluctuations associated with climatic and anthropogenic drivers, which implies long term changes in mountain snow peaks, land covers and ecosystems, among others. Our work aims at providing an integrative framework to realistically assess the possible future of natural water bodies with different degrees of human intervention. We are studying in particular the evolution of three water bodies in Colombia: two Andean lakes and a floodplain wetland. These natural reservoirs represent the accumulated effect of hydrological processes in their respective basins, which exhibit different patterns of climate variability and distinct human intervention and environmental histories. Modelling the hydrological responses of these local water bodies to climate variability and human intervention require an understanding of the strong linkage between geophysical and social factors. From the geophysical perspective, the challenge is how to downscale global climate projections in the local context: complex orography and relative lack of data. To overcome this challenge we combine the correlational and physically based analysis of several sources of spatially distributed biophysical and meteorological information to accurately determine aspects such as moisture sources and sinks and past, present and future local precipitation and temperature regimes. From the social perspective, the challenge is how to adequately represent and incorporate into the models the likely response of social agents whose water-related interests are diverse and usually conflictive. To deal with the complexity of these systems we develop interaction matrices, which are useful tools to holistically discuss and represent each environment as a complex system. Our goal is to assess partially the uncertainties of the hydrological balances in these intervened water bodies we establish climate/social scenarios, using hybrid models that combine the computational power of numerical simulations (of both physical and social components) with interactive responses given by users who define strategies and make decisions in real time, providing valuable information about people's attitudes and choices regarding future climate perspectives. Part of our interest with this project is to effectively transfer the knowledge and scientific information gathered to the communities in a way that is useful and propositive. To this end we developed a website (http://peerlagoscolombia.udea.edu.co) that includes relevant information about the project outcomes. We also developed and installed telemetric hydrologic stations in each site, whose data on water storage levels and basic meteorological variables can be accessed online. Acknowledgement: this project is funded by the USAID-NSF PEER program (First cycle, project 31).

Translating climate data for business decisions

NASA Astrophysics Data System (ADS)

Steinberg, N.

2015-12-01

Businesses are bound to play an integral role in global and local climate change adaptation efforts, and integrating climate science into business decision-making can help protect companies' bottom-line and the communities which they depend upon. Yet many companies do not have good means to measure and manage climate risks. There are inherent limiting factors to incorporating climate data into existing operations and sourcing strategies. Spatial and temporal incongruities between climate and business models can make integration cumbersome. Even when such incongruities are resolved, raw climate data must undergo multiple transformations until the data is deemed actionable or otherwise translatable in dollar terms. However, the predictability of future impacts is advancing along with the use of second-order variables such as Cooling Degree Days and Water-Limited Crop productivity, helping business managers make better decisions about future energy and water demand requirements under the prospect of rising temperatures and more variable rainfall. This presentation will discuss the methods and opportunities for transforming raw climate data into business metrics. Results for the 2015 Corporate Adaptation Survey, led by Four Twenty Seven and in partnership with Notre Dame Global Adaptation Index, will also be presented to illustrate existing gaps between climate science and its application in the business context.

Ocean currents modify the coupling between climate change and biogeographical shifts.

PubMed

García Molinos, J; Burrows, M T; Poloczanska, E S

2017-05-02

Biogeographical shifts are a ubiquitous global response to climate change. However, observed shifts across taxa and geographical locations are highly variable and only partially attributable to climatic conditions. Such variable outcomes result from the interaction between local climatic changes and other abiotic and biotic factors operating across species ranges. Among them, external directional forces such as ocean and air currents influence the dispersal of nearly all marine and many terrestrial organisms. Here, using a global meta-dataset of observed range shifts of marine species, we show that incorporating directional agreement between flow and climate significantly increases the proportion of explained variance. We propose a simple metric that measures the degrees of directional agreement of ocean (or air) currents with thermal gradients and considers the effects of directional forces in predictions of climate-driven range shifts. Ocean flows are found to both facilitate and hinder shifts depending on their directional agreement with spatial gradients of temperature. Further, effects are shaped by the locations of shifts in the range (trailing, leading or centroid) and taxonomic identity of species. These results support the global effects of climatic changes on distribution shifts and stress the importance of framing climate expectations in reference to other non-climatic interacting factors.

The NOAA Local Climate Analysis Tool - An Application in Support of a Weather Ready Nation

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Horsfall, F. M.

2012-12-01

Citizens across the U.S., including decision makers from the local to the national level, have a multitude of questions about climate, such as the current state and how that state fits into the historical context, and more importantly, how climate will impact them, especially with regard to linkages to extreme weather events. Developing answers to these types of questions for locations has typically required extensive work to gather data, conduct analyses, and generate relevant explanations and graphics. Too frequently providers don't have ready access to or knowledge of reliable, trusted data sets, nor sound, scientifically accepted analysis techniques such that they can provide a rapid response to queries they receive. In order to support National Weather Service (NWS) local office forecasters with information they need to deliver timely responses to climate-related questions from their customers, we have developed the Local Climate Analysis Tool (LCAT). LCAT uses the principles of artificial intelligence to respond to queries, in particular, through use of machine technology that responds intelligently to input from users. A user translates customer questions into primary variables and issues and LCAT pulls the most relevant data and analysis techniques to provide information back to the user, who in turn responds to their customer. Most responses take on the order of 10 seconds, which includes providing statistics, graphical displays of information, translations for users, metadata, and a summary of the user request to LCAT. Applications in Phase I of LCAT, which is targeted for the NWS field offices, include Climate Change Impacts, Climate Variability Impacts, Drought Analysis and Impacts, Water Resources Applications, Attribution of Extreme Events, and analysis techniques such as time series analysis, trend analysis, compositing, and correlation and regression techniques. Data accessed by LCAT are homogenized historical COOP and Climate Prediction Center climate division data available at NCDC. Applications for other NOAA offices and Federal agencies are currently being investigated, such as incorporation of tidal data, fish stocks, sea surface temperature, health-related data, and analyses relevant to those datasets. We will describe LCAT, its basic functionality, examples of analyses, and progress being made to provide the tool to a broader audience in support of ocean, fisheries, and health applications.

Climate Justice in Rural Southeastern United States: A Review of Climate Change Impacts and Effects on Human Health

PubMed Central

Gutierrez, Kristie S.; LePrevost, Catherine E.

2016-01-01

Climate justice is a local, national, and global movement to protect at-risk populations who are disproportionately affected by climate change. The social context for this review is the Southeastern region of the United States, which is particularly susceptible to climate change because of the geography of the area and the vulnerabilities of the inhabiting populations. Negative human health effects on variable and vulnerable populations within the Southeast region due to changing climate are concerning, as health threats are not expected to produce parallel effects among all individuals. Vulnerable communities, such as communities of color, indigenous people, the geographically isolated, and those who are socioeconomically disadvantaged and already experiencing poor environmental quality, are least able to respond and adapt to climate change. Focusing on vulnerable populations in the Southeastern United States, this review is a synthesis of the recent (2010 to 2015) literature-base on the health effects connected to climate change. This review also addresses local and regional mitigation and adaptation strategies for citizens and leaders to combat direct and indirect human health effects related to a changing climate. PMID:26848673

Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?

NASA Astrophysics Data System (ADS)

Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven

2017-04-01

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to constrain model uncertainty for an - assumed to be - ungauged basin. This shows that our method is promising for reconstructing long-term flow data for ungauged catchments on the Pacific side of Central America, and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.

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.

Santa Ana Winds of Southern California: Their Climatology and Variability Spanning 6.5 Decades from Regional Dynamical Modelling

NASA Astrophysics Data System (ADS)

Guzman-Morales, J.; Gershunov, A.

2015-12-01

Santa Ana Winds (SAWs) are an integral feature of the regional climate of Southern California/Northern Baja California region. In spite of their tremendous episodic impacts on the health, economy and mood of the region, climate-scale behavior of SAW is poorly understood. In the present work, we identify SAWs in mesoscale dynamical downscaling of a global reanalysis product and construct an hourly SAW catalogue spanning 65 years. We describe the long-term SAW climatology at relevant time-space resolutions, i.e, we developed local and regional SAW indices and analyse their variability on hourly, daily, annual, and multi-decadal timescales. Local and regional SAW indices are validated with available anemometer observations. Characteristic behaviors are revealed, e.g. the SAW intensity-duration relationship. At interdecadal time scales, we find that seasonal SAW activity is sensitive to prominent large-scale low-frequency modes of climate variability rooted in the tropical and north Pacific ocean-atmosphere system that are also known to affect the hydroclimate of this region. Lastly, we do not find any long-term trend in SAW frequency and intensity as previously reported. Instead, we identify a significant long-term trend in SAW behavior whereby contribution of extreme SAW events to total seasonal SAW activity has been increasing at the expense of moderate events. These findings motivate further investigation on SAW evolution in future climate and its impact on wildfires.

Impact of Variable-Resolution Meshes on Regional Climate Simulations

NASA Astrophysics Data System (ADS)

Fowler, L. D.; Skamarock, W. C.; Bruyere, C. L.

2014-12-01

The Model for Prediction Across Scales (MPAS) is currently being used for seasonal-scale simulations on globally-uniform and regionally-refined meshes. Our ongoing research aims at analyzing simulations of tropical convective activity and tropical cyclone development during one hurricane season over the North Atlantic Ocean, contrasting statistics obtained with a variable-resolution mesh against those obtained with a quasi-uniform mesh. Analyses focus on the spatial distribution, frequency, and intensity of convective and grid-scale precipitations, and their relative contributions to the total precipitation as a function of the horizontal scale. Multi-month simulations initialized on May 1st 2005 using ERA-Interim re-analyses indicate that MPAS performs satisfactorily as a regional climate model for different combinations of horizontal resolutions and transitions between the coarse and refined meshes. Results highlight seamless transitions for convection, cloud microphysics, radiation, and land-surface processes between the quasi-uniform and locally- refined meshes, despite the fact that the physics parameterizations were not developed for variable resolution meshes. Our goal of analyzing the performance of MPAS is twofold. First, we want to establish that MPAS can be successfully used as a regional climate model, bypassing the need for nesting and nudging techniques at the edges of the computational domain as done in traditional regional climate modeling. Second, we want to assess the performance of our convective and cloud microphysics parameterizations as the horizontal resolution varies between the lower-resolution quasi-uniform and higher-resolution locally-refined areas of the global domain.

Impact of Variable-Resolution Meshes on Regional Climate Simulations

NASA Astrophysics Data System (ADS)

Fowler, L. D.; Skamarock, W. C.; Bruyere, C. L.

2013-12-01

The Model for Prediction Across Scales (MPAS) is currently being used for seasonal-scale simulations on globally-uniform and regionally-refined meshes. Our ongoing research aims at analyzing simulations of tropical convective activity and tropical cyclone development during one hurricane season over the North Atlantic Ocean, contrasting statistics obtained with a variable-resolution mesh against those obtained with a quasi-uniform mesh. Analyses focus on the spatial distribution, frequency, and intensity of convective and grid-scale precipitations, and their relative contributions to the total precipitation as a function of the horizontal scale. Multi-month simulations initialized on May 1st 2005 using NCEP/NCAR re-analyses indicate that MPAS performs satisfactorily as a regional climate model for different combinations of horizontal resolutions and transitions between the coarse and refined meshes. Results highlight seamless transitions for convection, cloud microphysics, radiation, and land-surface processes between the quasi-uniform and locally-refined meshes, despite the fact that the physics parameterizations were not developed for variable resolution meshes. Our goal of analyzing the performance of MPAS is twofold. First, we want to establish that MPAS can be successfully used as a regional climate model, bypassing the need for nesting and nudging techniques at the edges of the computational domain as done in traditional regional climate modeling. Second, we want to assess the performance of our convective and cloud microphysics parameterizations as the horizontal resolution varies between the lower-resolution quasi-uniform and higher-resolution locally-refined areas of the global domain.

Analysis of Vegetation Index Variations and the Asian Monsoon Climate

NASA Technical Reports Server (NTRS)

Shen, Sunhung; Leptoukh, Gregory G.; Gerasimov, Irina

2012-01-01

Vegetation growth depends on local climate. Significant anthropogenic land cover and land use change activities over Asia have changed vegetation distribution as well. On the other hand, vegetation is one of the important land surface variables that influence the Asian Monsoon variability through controlling atmospheric energy and water vapor conditions. In this presentation, the mean and variations of vegetation index of last decade at regional scale resolution (5km and higher) from MODIS have been analyzed. Results indicate that the vegetation index has been reduced significantly during last decade over fast urbanization areas in east China, such as Yangtze River Delta, where local surface temperatures were increased significantly in term of urban heat Island. The relationship between vegetation Index and climate (surface temperature, precipitation) over a grassland in northern Asia and over a woody savannas in southeast Asia are studied. In supporting Monsoon Asian Integrated Regional Study (MAIRS) program, the data in this study have been integrated into Giovanni, the online visualization and analysis system at NASA GES DISC. Most images in this presentation are generated from Giovanni system.

Spatial and Temporal Means and Variability of Arctic Sea Ice Climate Indicators from Satellite Data

NASA Astrophysics Data System (ADS)

Peng, G.; Meier, W.; Bliss, A. C.; Steele, M.; Dickinson, S.

2017-12-01

Arctic sea ice has been undergoing rapid and accelerated loss since satellite-based measurements became available in late 1970s, especially the summer ice coverage. For the Arctic as a whole, the long-term trend for the annual sea ice extent (SIE) minimum is about -13.5±2.93 % per decade change relative to the 1979-2015 climate average, while the trends of the annual SIE minimum for the local regions can range from 0 to up to -42 % per decade. This presentation aims to examine and baseline spatial and temporal means and variability of Arctic sea ice climate indicators, such as the annual SIE minimum and maximum, snow/ice melt onset, etc., from a consistent, inter-calibrated, long-term time series of remote sensing sea ice data for understanding regional vulnerability and monitoring ice state for climate adaptation and risk mitigation.

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

PubMed

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

2015-09-01

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

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.

Adaptation of water resource systems to an uncertain future

NASA Astrophysics Data System (ADS)

Walsh, C. L.; Blenkinsop, S.; Fowler, H. J.; Burton, A.; Dawson, R. J.; Glenis, V.; Manning, L. J.; Kilsby, C. G.

2015-09-01

Globally, water resources management faces significant challenges from changing climate and growing populations. At local scales, the information provided by climate models is insufficient to support the water sector in making future adaptation decisions. Furthermore, projections of change in local water resources are wrought with uncertainties surrounding natural variability, future greenhouse gas emissions, model structure, population growth and water consumption habits. To analyse the magnitude of these uncertainties, and their implications for local scale water resource planning, we present a top-down approach for testing climate change adaptation options using probabilistic climate scenarios and demand projections. An integrated modelling framework is developed which implements a new, gridded spatial weather generator, coupled with a rainfall-runoff model and water resource management simulation model. We use this to provide projections of the number of days, and associated uncertainty that will require implementation of demand saving measures such as hose pipe bans and drought orders. Results, which are demonstrated for the Thames basin, UK, indicate existing water supplies are sensitive to a changing climate and an increasing population, and that the frequency of severe demand saving measures are projected to increase. Considering both climate projections and population growth the median number of drought order occurrences may increase five-fold. The effectiveness of a range of demand management and supply options have been tested and shown to provide significant benefits in terms of reducing the number of demand saving days. We found that increased supply arising from various adaptation options may compensate for increasingly variable flows; however, without reductions in overall demand for water resources such options will be insufficient on their own to adapt to uncertainties in the projected changes in climate and population. For example, a 30 % reduction in overall demand by 2050 has a greater impact on reducing the frequency of drought orders than any of the individual or combinations of supply options; hence a portfolio of measures are required.

The Mediterranean Sea regime shift at the end of the 1980s, and intriguing parallelisms with other European basins.

PubMed

Conversi, Alessandra; Fonda Umani, Serena; Peluso, Tiziana; Molinero, Juan Carlos; Santojanni, Alberto; Edwards, Martin

2010-05-19

Regime shifts are abrupt changes encompassing a multitude of physical properties and ecosystem variables, which lead to new regime conditions. Recent investigations focus on the changes in ecosystem diversity and functioning associated to such shifts. Of particular interest, because of the implication on climate drivers, are shifts that occur synchronously in separated basins. In this work we analyze and review long-term records of Mediterranean ecological and hydro-climate variables and find that all point to a synchronous change in the late 1980s. A quantitative synthesis of the literature (including observed oceanic data, models and satellite analyses) shows that these years mark a major change in Mediterranean hydrographic properties, surface circulation, and deep water convection (the Eastern Mediterranean Transient). We provide novel analyses that link local, regional and basin scale hydrological properties with two major indicators of large scale climate, the North Atlantic Oscillation index and the Northern Hemisphere Temperature index, suggesting that the Mediterranean shift is part of a large scale change in the Northern Hemisphere. We provide a simplified scheme of the different effects of climate vs. temperature on pelagic ecosystems. Our results show that the Mediterranean Sea underwent a major change at the end of the 1980s that encompassed atmospheric, hydrological, and ecological systems, for which it can be considered a regime shift. We further provide evidence that the local hydrography is linked to the larger scale, northern hemisphere climate. These results suggest that the shifts that affected the North, Baltic, Black and Mediterranean (this work) Seas at the end of the 1980s, that have been so far only partly associated, are likely linked as part a northern hemisphere change. These findings bear wide implications for the development of climate change scenarios, as synchronous shifts may provide the key for distinguishing local (i.e., basin) anthropogenic drivers, such as eutrophication or fishing, from larger scale (hemispheric) climate drivers.

Science and Strategic - Climate Implications

NASA Astrophysics Data System (ADS)

Tindall, J. A.; Moran, E. H.

2008-12-01

Energy of weather systems greatly exceeds energy produced and used by humans. Variation in this energy causes climate variability potentially resulting in local, national, and/or global catastrophes beyond our ability to deter the loss of life and economic destabilization. Large scale natural disasters routinely result in shortages of water, disruption of energy supplies, and destruction of infrastructure. The resulting unforeseen and disastrous events occurring beyond national emergency preparation, as related to climate variability, could insight civil unrest due to dwindling and/or inaccessible resources necessary for survival. Lack of these necessary resources in impacted countries often leads to wars. Climate change coupled with population growth, which exposes more of the population to potential risks associated with climate and environmental change, demands faster technological response. Understanding climate/associated environmental changes, the relation to human activity and behavior, and including this in national and international emergency/security management plans would alleviate shortcomings in our present and future technological status. The scale of environmental change will determine the potential magnitude of civil unrest at the local, national, and/or global level along with security issues at each level. Commonly, security issues related to possible civil unrest owing to temporal environmental change is not part of a short and/or long-term strategy, yet recent large-scale disasters are reminders that system failures (as in hurricane Katrina) include acknowledged breaches to individual, community, and infrastructure security. Without advance planning and management concerning environmental change, oncoming and climate related events will intensify the level of devastation and human catastrophe. Depending upon the magnitude and period of catastrophic events and/or environmental changes, destabilization of agricultural systems, energy supplies, and other lines of commodities often results in severely unbalanced supply and demand ratios, which eventually affect the entire global community. National economies potentially risk destabilization, which is especially important since economics plays a major role in strategic planning. This presentation will address these issues and the role that science can play in human sustainability and local, national, and international security.

Interannual rainfall variability and SOM-based circulation classification

NASA Astrophysics Data System (ADS)

Wolski, Piotr; Jack, Christopher; Tadross, Mark; van Aardenne, Lisa; Lennard, Christopher

2018-01-01

Self-Organizing Maps (SOM) based classifications of synoptic circulation patterns are increasingly being used to interpret large-scale drivers of local climate variability, and as part of statistical downscaling methodologies. These applications rely on a basic premise of synoptic climatology, i.e. that local weather is conditioned by the large-scale circulation. While it is clear that this relationship holds in principle, the implications of its implementation through SOM-based classification, particularly at interannual and longer time scales, are not well recognized. Here we use a SOM to understand the interannual synoptic drivers of climate variability at two locations in the winter and summer rainfall regimes of South Africa. We quantify the portion of variance in seasonal rainfall totals that is explained by year to year differences in the synoptic circulation, as schematized by a SOM. We furthermore test how different spatial domain sizes and synoptic variables affect the ability of the SOM to capture the dominant synoptic drivers of interannual rainfall variability. Additionally, we identify systematic synoptic forcing that is not captured by the SOM classification. The results indicate that the frequency of synoptic states, as schematized by a relatively disaggregated SOM (7 × 9) of prognostic atmospheric variables, including specific humidity, air temperature and geostrophic winds, captures only 20-45% of interannual local rainfall variability, and that the residual variance contains a strong systematic component. Utilising a multivariate linear regression framework demonstrates that this residual variance can largely be explained using synoptic variables over a particular location; even though they are used in the development of the SOM their influence, however, diminishes with the size of the SOM spatial domain. The influence of the SOM domain size, the choice of SOM atmospheric variables and grid-point explanatory variables on the levels of explained variance, is consistent with the general understanding of the dominant processes and atmospheric variables that affect rainfall variability at a particular location.

Araucaria growth response to solar and climate variability in South Brazil

NASA Astrophysics Data System (ADS)

Prestes, Alan; Klausner, Virginia; Rojahn da Silva, Iuri; Ojeda-González, Arian; Lorensi, Caren

2018-05-01

In this work, the Sun-Earth-climate relationship is studied using tree growth rings of Araucaria angustifolia (Bertol.) O. Kuntze collected in the city of Passo Fundo, located in the state of Rio Grande do Sul (RS), Brazil. These samples were previously studied by Rigozo et al. (2008); however, their main interest was to search for the solar periodicities in the tree-ring width mean time series without interpreting the rest of the periodicities found. The question arises as to what are the drivers related to those periodicities. For this reason, the classical method of spectral analysis by iterative regression and wavelet methods are applied to find periodicities and trends present in each tree-ring growth, in Southern Oscillation Index (SOI), and in annual mean temperature anomaly between the 24 and 44° S. In order to address the aforementioned question, this paper discusses the correlation between the growth rate of the tree rings with temperature and SOI. In each tree-ring growth series, periods between 2 and 7 years were found, possibly related to the El Niño/La Niña phenomena, and a ˜ 23-year period was found, which may be related to temperature variation. These novel results might represent the tree-ring growth response to local climate conditions during its lifetime, and to nonlinear coupling between the Sun and the local climate variability responsible to the regional climate variations.

Statistical downscaling of daily precipitation over Llobregat river basin in Catalonia (Spain) using three downscaling methods.

NASA Astrophysics Data System (ADS)

Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.

2009-09-01

Any long-term change in the patterns of average weather in a global or regional scale is called climate change. It may cause a progressive increase of atmospheric temperature and consequently may change the amount, frequency and intensity of precipitation. All these changes of meteorological parameters may modify the water cycle: run-off, infiltration, aquifer recharge, etc. Recent studies in Catalonia foresee changes in hydrological systems caused by climate change. This will lead to alterations in the hydrological cycle that could impact in land use, in the regimen of water extractions, in the hydrological characteristics of the territory and reduced groundwater recharge. Besides, can expect a loss of flow in rivers. In addition to possible increases in the frequency of extreme rainfall, being necessary to modify the design of infrastructure. Because this, it work focuses on studying the impacts of climate change in one of the most important basins in Catalonia, the Llobregat River Basin. The basin is the hub of the province of Barcelona. It is a highly populated and urbanized catchment, where water resources are used for different purposes, as drinking water production, agricultural irrigation, industry and hydro-electrical energy production. In consequence, many companies and communities depend on these resources. To study the impact of climate change in the Llobregat basin, storms (frequency, intensity) mainly, we will need regional climate change information. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and environmental impact studies. Downscaling methods to assess the effect of large-scale circulations on local parameters have. Statistical downscaling methods are based on the view that regional climate can be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or "predictors" for which GCMs are trustable to regional or local surface "predictands" for which models are less skilful. The main advantage of these methods is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. Three statistical downscaling methods are applied: Analogue method, Delta Change and Direct Forcing. These methods have been used to determine daily precipitation projections at rain gauge location to study the intensity, frequency and variability of storms in a context of climate change in the Llobregat River Basin in Catalonia, Spain. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. Two stakeholders involved in the project provided the historical time series: Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET).

Effects of Global Change on U.S. Urban Areas: Vulnerabilities, Impacts, and Adaptation

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Wilbanks, Thomas J.; Kirshen, Paul; Romero-Lankao, Patricia; Rosenzweig, Cynthia; Ruth, Mattias; Solecki, William; Tarr, Joel

2008-01-01

This slide presentation reviews some of the effects that global change has on urban areas in the United States and how the growth of urban areas will affect the environment. It presents the elements of our Synthesis and Assessment Report (SAP) report that relate to what vulnerabilities and impacts will occur, what adaptation responses may take place, and what possible effects on settlement patterns and characteristics will potentially arise, on human settlements in the U.S. as a result of climate change and climate variability. We will also present some recommendations about what should be done to further research on how climate change and variability will impact human settlements in the U.S., as well as how to engage government officials, policy and decision makers, and the general public in understanding the implications of climate change and variability on the local and regional levels. Additionally, we wish to explore how technology such as remote sensing data coupled with modeling, can be employed as synthesis tools for deriving insight across a spectrum of impacts (e.g. public health, urban planning for mitigation strategies) on how cities can cope and adapt to climate change and variability. This latter point parallels the concepts and ideas presented in the U.S. National Academy of Sciences, Decadal Survey report on "Earth Science Applications from Space: National Imperatives for the Next Decade and Beyond" wherein the analysis of the impacts of climate change and variability, human health, and land use change are listed as key areas for development of future Earth observing remote sensing systems.

The continuum of hydroclimate variability in western North America during the last millennium

USGS Publications Warehouse

Ault, Toby R.; Cole, Julia E.; Overpeck, Jonathan T.; Pederson, Gregory T.; St. George, Scott; Otto-Bliesner, Bette; Woodhouse, Connie A.; Deser, Clara

2013-01-01

The distribution of climatic variance across the frequency spectrum has substantial importance for anticipating how climate will evolve in the future. Here we estimate power spectra and power laws (ß) from instrumental, proxy, and climate model data to characterize the hydroclimate continuum in western North America (WNA). We test the significance of our estimates of spectral densities and ß against the null hypothesis that they reflect solely the effects of local (non-climate) sources of autocorrelation at the monthly timescale. Although tree-ring based hydroclimate reconstructions are generally consistent with this null hypothesis, values of ß calculated from long-moisture sensitive chronologies (as opposed to reconstructions), and other types of hydroclimate proxies, exceed null expectations. We therefore argue that there is more low-frequency variability in hydroclimate than monthly autocorrelation alone can generate. Coupled model results archived as part of the Climate Model Intercomparison Project 5 (CMIP5) are consistent with the null hypothesis and appear unable to generate variance in hydroclimate commensurate with paleoclimate records. Consequently, at decadal to multidecadal timescales there is more variability in instrumental and proxy data than in the models, suggesting that the risk of prolonged droughts under climate change may be underestimated by CMIP5 simulations of the future.

An empirical test of the relative and combined effects of land-cover and climate change on local colonization and extinction.

PubMed

Yalcin, Semra; Leroux, Shawn James

2018-04-14

Land-cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land-cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981-1985 and 2001-2005 are correlated with land-cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land-cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land-cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land-cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land-cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land-cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction. © 2018 John Wiley & Sons Ltd.

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

DOE PAGES

Dong, Xiaoli; Cohen, Matthew J.; Martin, Jonathan B.; ...

2018-05-18

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study.more » Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.« less

Ecohydrologic processes and soil thickness feedbacks control limestone-weathering rates in a karst landscape

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

Dong, Xiaoli; Cohen, Matthew J.; Martin, Jonathan B.

Here, chemical weathering of bedrock plays an essential role in the formation and evolution of Earth's critical zone. Over geologic time, the negative feedback between temperature and chemical weathering rates contributes to the regulation of Earth climate. The challenge of understanding weathering rates and the resulting evolution of critical zone structures lies in complicated interactions and feedbacks among environmental variables, local ecohydrologic processes, and soil thickness, the relative importance of which remains unresolved. We investigate these interactions using a reactive-transport kinetics model, focusing on a low-relief, wetland-dominated karst landscape (Big Cypress National Preserve, South Florida, USA) as a case study.more » Across a broad range of environmental variables, model simulations highlight primary controls of climate and soil biological respiration, where soil thickness both supplies and limits transport of biologically derived acidity. Consequently, the weathering rate maximum occurs at intermediate soil thickness. The value of the maximum weathering rate and the precise soil thickness at which it occurs depend on several environmental variables, including precipitation regime, soil inundation, vegetation characteristics, and rate of groundwater drainage. Simulations for environmental conditions specific to Big Cypress suggest that wetland depressions in this landscape began to form around beginning of the Holocene with gradual dissolution of limestone bedrock and attendant soil development, highlighting large influence of age-varying soil thickness on weathering rates and consequent landscape development. While climatic variables are often considered most important for chemical weathering, our results indicate that soil thickness and biotic activity are equally important. Weathering rates reflect complex interactions among soil thickness, climate, and local hydrologic and biotic processes, which jointly shape the supply and delivery of chemical reactants, and the resulting trajectories of critical zone and karst landscape development.« less

Spatial match-mismatch between juvenile fish and prey provides a mechanism for recruitment variability across contrasting climate conditions in the eastern Bering Sea.

PubMed

Siddon, Elizabeth Calvert; Kristiansen, Trond; Mueter, Franz J; Holsman, Kirstin K; Heintz, Ron A; Farley, Edward V

2013-01-01

Understanding mechanisms behind variability in early life survival of marine fishes through modeling efforts can improve predictive capabilities for recruitment success under changing climate conditions. Walleye pollock (Theragra chalcogramma) support the largest single-species commercial fishery in the United States and represent an ecologically important component of the Bering Sea ecosystem. Variability in walleye pollock growth and survival is structured in part by climate-driven bottom-up control of zooplankton composition. We used two modeling approaches, informed by observations, to understand the roles of prey quality, prey composition, and water temperature on juvenile walleye pollock growth: (1) a bioenergetics model that included local predator and prey energy densities, and (2) an individual-based model that included a mechanistic feeding component dependent on larval development and behavior, local prey densities and size, and physical oceanographic conditions. Prey composition in late-summer shifted from predominantly smaller copepod species in the warmer 2005 season to larger species in the cooler 2010 season, reflecting differences in zooplankton composition between years. In 2010, the main prey of juvenile walleye pollock were more abundant, had greater biomass, and higher mean energy density, resulting in better growth conditions. Moreover, spatial patterns in prey composition and water temperature lead to areas of enhanced growth, or growth 'hot spots', for juvenile walleye pollock and survival may be enhanced when fish overlap with these areas. This study provides evidence that a spatial mismatch between juvenile walleye pollock and growth 'hot spots' in 2005 contributed to poor recruitment while a higher degree of overlap in 2010 resulted in improved recruitment. Our results indicate that climate-driven changes in prey quality and composition can impact growth of juvenile walleye pollock, potentially severely affecting recruitment variability.

Disentangling synergistic climate drivers on the evolution of two species of planktonic foraminifera on regional and global scales

NASA Astrophysics Data System (ADS)

Brombacher, A.; Wilson, P. A.; Bailey, I.; Ezard, T. H. G.

2016-02-01

Evolution is driven by a combination of biotic and abiotic factors. When quantifying the effects of abiotic drivers, evolutionary change is generally described as a response to a single environmental parameter assumed to represent global climate. However, climate is a complex system of many interacting factors and characterized by high regional variability. Therefore, to understand the role of climate in evolutionary change, we need to consider multiple environmental parameters, across local, regional and global scales, as well as their interactions. The deep-sea microfossil record is sufficiently complete that sufficiently continuous multivariate climatic and multivariate trait data can be obtained from the same samples. Here we present morphological records of the planktonic foraminifera species Globoconella puncticulata and Truncorotalia crassaformis over a 500,000-year interval directly preceding the extinction of G. puncticulata (2.41 Ma). Material was collected from five North Atlantic sites (ODP Sites 659 [18° N], 925 [3° N] and 981 [55° N], IODP Site U1313 [41° N] and DSDP Site 606 [37° N]). Test size and shape of over 35,000 individuals were measured and compared to site-specific records of sea surface temperature, primary productivity and marine aeolian dust deposition, as well as to global records of ice volume, ocean circulation and atmospheric CO2, and all two-way interactions. Morphological parameters respond weakly to individual climate parameters. Once interactions among all studied climate parameters were incorporated, abiotic change explained around 35% of the evolutionary variance. Observed covariances between environmental parameters vary strongly with glacial-interglacial cyclicity, implying that the relationships among climate variables and their relative influences on evolutionary change varied through time. This time dependence cautions against unfettered use of dimension reduction techniques, such as principal components analysis, to extract a single, supposedly dominant, proxy. Furthermore species' responses differed between geographic locations, impressing the need to test how interactions among multiple climate variables at different regional settings shape the biotic microevolutionary response to local and global abiotic change.

Uncertainty in Twenty-First-Century CMIP5 Sea Level Projections

NASA Technical Reports Server (NTRS)

Little, Christopher M.; Horton, Radley M.; Kopp, Robert E.; Oppenheimer, Michael; Yip, Stan

2015-01-01

The representative concentration pathway (RCP) simulations included in phase 5 of the Coupled Model Intercomparison Project (CMIP5) quantify the response of the climate system to different natural and anthropogenic forcing scenarios. These simulations differ because of 1) forcing, 2) the representation of the climate system in atmosphere-ocean general circulation models (AOGCMs), and 3) the presence of unforced (internal) variability. Global and local sea level rise projections derived from these simulations, and the emergence of distinct responses to the four RCPs depend on the relative magnitude of these sources of uncertainty at different lead times. Here, the uncertainty in CMIP5 projections of sea level is partitioned at global and local scales, using a 164-member ensemble of twenty-first-century simulations. Local projections at New York City (NYSL) are highlighted. The partition between model uncertainty, scenario uncertainty, and internal variability in global mean sea level (GMSL) is qualitatively consistent with that of surface air temperature, with model uncertainty dominant for most of the twenty-first century. Locally, model uncertainty is dominant through 2100, with maxima in the North Atlantic and the Arctic Ocean. The model spread is driven largely by 4 of the 16 AOGCMs in the ensemble; these models exhibit outlying behavior in all RCPs and in both GMSL and NYSL. The magnitude of internal variability varies widely by location and across models, leading to differences of several decades in the local emergence of RCPs. The AOGCM spread, and its sensitivity to model exclusion and/or weighting, has important implications for sea level assessments, especially if a local risk management approach is utilized.

Direct observations of ice seasonality reveal changes in climate over the past 320–570 years

USGS Publications Warehouse

Sharma, Sapna; Magnuson, John J.; Batt, Ryan D.; Winslow, Luke; Korhonen, Johanna; Yasuyuki Aono,

2016-01-01

Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality.

Direct observations of ice seasonality reveal changes in climate over the past 320–570 years

PubMed Central

Sharma, Sapna; Magnuson, John J.; Batt, Ryan D.; Winslow, Luke A.; Korhonen, Johanna; Aono, Yasuyuki

2016-01-01

Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality. PMID:27113125

Water quality in the Schuylkill River, Pennsylvania: the potential for long-lead forecasts

NASA Astrophysics Data System (ADS)

Block, P. J.; Peralez, J.

2012-12-01

Prior analysis of pathogen levels in the Schuylkill River has led to a categorical daily forecast of water quality (denoted as red, yellow, or green flag days.) The forecast, available to the public online through the Philadelphia Water Department, is predominantly based on the local precipitation forecast. In this study, we explore the feasibility of extending the forecast to the seasonal scale by associating large-scale climate drivers with local precipitation and water quality parameter levels. This advance information is relevant for recreational activities, ecosystem health, and water treatment (energy, chemicals), as the Schuylkill provides 40% of Philadelphia's water supply. Preliminary results indicate skillful prediction of average summertime water quality parameters and characteristics, including chloride, coliform, turbidity, alkalinity, and others, using season-ahead oceanic and atmospheric variables, predominantly from the North Atlantic. Water quality parameter trends, including historic land use changes along the river, association with climatic variables, and prediction models will be presented.

Stalagmite high resolution local paleoclimatic proxies for Late Holocene in Mesoamerica: Exploring role of moisture upon the development of Mesoamerican cultures.

NASA Astrophysics Data System (ADS)

Martínez Izquierdo, H. B.; Bernal, J. P.; Pérez Enriquez, R.; Böhnel, H.; Morales-Malacara, J. B.; Solari, L.; Gómez-Tuena, A.

2010-03-01

The relationship between climate change and culture development in Mesoamerica is complex to unravel since many written archives were destroyed during natural disasters and cultural conflicts such as Spanish conquest. Local paleoclimate records offer a way to reconstruct this relationship. Stalagmites are amongst the most reliable records of past climate variability, due to their evolution in closed-system conditions, ease of dating, and inclusion of several geochemical proxies (such as calcite oxygen and carbon isotopic composition, trace element concentration and/or elemental ratios, color and grey-tone scale). Recently, stalagmites have been used as records to explore the climatic change during Holocene and its cultural relation in Mediterranean, Asian, North American and east African cultures. Only few works were made, however, for Mesoamerican cultures. We study here a banded stalagmite belonging to Jalpan, Queretaro, central Mexico. This stalagmite was found actively growing, with its base dated at 6.85 +/- 0.3 Ka B.P. A high resolution LA-ICP-MS Mg/Ca analysis as well as grey tone analysis were obtained in order to create annual resolution time series. The proxies were correlated with local and north Atlantic paleoclimate records. Such proxies also show signals associated with volcanic eruptions (Tacana, el Chichon, Popocatepetl and Ceboruco) during the Classic period. Other signals are associated with Maya civilization collapse. These results portray the relationship between the agricultural and population patterns with moisture variability for the center of Mexico (Teotihuacan influence zone) during late Formative and Classic period. Finally, we observe patterns such as the corresponding to the little ice age and the anthropogenic climate warming, the latter correlated with local precipitation data.

Errors and uncertainties in regional climate simulations of rainfall variability over Tunisia: a multi-model and multi-member approach

NASA Astrophysics Data System (ADS)

Fathalli, Bilel; Pohl, Benjamin; Castel, Thierry; Safi, Mohamed Jomâa

2018-02-01

Temporal and spatial variability of rainfall over Tunisia (at 12 km spatial resolution) is analyzed in a multi-year (1992-2011) ten-member ensemble simulation performed using the WRF model, and a sample of regional climate hindcast simulations from Euro-CORDEX. RCM errors and skills are evaluated against a dense network of local rain gauges. Uncertainties arising, on the one hand, from the different model configurations and, on the other hand, from internal variability are furthermore quantified and ranked at different timescales using simple spread metrics. Overall, the WRF simulation shows good skill for simulating spatial patterns of rainfall amounts over Tunisia, marked by strong altitudinal and latitudinal gradients, as well as the rainfall interannual variability, in spite of systematic errors. Mean rainfall biases are wet in both DJF and JJA seasons for the WRF ensemble, while they are dry in winter and wet in summer for most of the used Euro-CORDEX models. The sign of mean annual rainfall biases over Tunisia can also change from one member of the WRF ensemble to another. Skills in regionalizing precipitation over Tunisia are season dependent, with better correlations and weaker biases in winter. Larger inter-member spreads are observed in summer, likely because of (1) an attenuated large-scale control on Mediterranean and Tunisian climate, and (2) a larger contribution of local convective rainfall to the seasonal amounts. Inter-model uncertainties are globally stronger than those attributed to model's internal variability. However, inter-member spreads can be of the same magnitude in summer, emphasizing the important stochastic nature of the summertime rainfall variability over Tunisia.

Quantifying how the full local distribution of daily precipitation is changing and its uncertainties

NASA Astrophysics Data System (ADS)

Stainforth, David; Chapman, Sandra; Watkins, Nicholas

2016-04-01

The study of the consequences of global warming would benefit from quantification of geographical patterns of change at specific thresholds or quantiles, and better understandings of the intrinsic uncertainties in such quantities. For precipitation a range of indices have been developed which focus on high percentiles (e.g. rainfall falling on days above the 99th percentile) and on absolute extremes (e.g. maximum annual one day precipitation) but scientific assessments are best undertaken in the context of changes in the whole climatic distribution. Furthermore, the relevant thresholds for climate-vulnerable policy decisions, adaptation planning and impact assessments, vary according to the specific sector and location of interest. We present a methodology which maintains the flexibility to provide information at different thresholds for different downstream users, both scientists and decision makers. We develop a method[1,2] for analysing local climatic timeseries to assess which quantiles of the local climatic distribution show the greatest and most robust changes in daily precipitation data. We extract from the data quantities that characterize the changes in time of the likelihood of daily precipitation above a threshold and of the amount of precipitation on those days. Our method is 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 how fast different quantiles of precipitation distributions are changing. This involves not only determining which quantiles and geographical locations show the greatest and smallest changes, but also those at which uncertainty undermines the ability to make confident statements about any change there may be. We demonstrate this approach using E-OBS gridded data[3] which are timeseries of local daily precipitation across Europe over the last 60+ years. We treat geographical location and precipitation as independent variables and thus obtain as outputs the geographical pattern of change at given thresholds of precipitation. This information is model- independent, thus providing data of direct value in model calibration and assessment. [1] S C Chapman, D A Stainforth, N W Watkins, 2013, On Estimating Local Long Term Climate Trends, Phil. Trans. R. Soc. A, 371 20120287; D. A. Stainforth, 2013 [2] S C Chapman, D A Stainforth, N W Watkins, 2015 Limits to the quantification of local climate change, ERL,10, 094018 (2015), ERL,10, 094018 [3] M R Haylock et al . 2008: A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres), 113, D20119

Effects of local and large-scale climate patterns on estuarine resident fishes: The example of Pomatoschistus microps and Pomatoschistus minutus

NASA Astrophysics Data System (ADS)

Nyitrai, Daniel; Martinho, Filipe; Dolbeth, Marina; Rito, João; Pardal, Miguel A.

2013-12-01

Large-scale and local climate patterns are known to influence several aspects of the life cycle of marine fish. In this paper, we used a 9-year database (2003-2011) to analyse the populations of two estuarine resident fishes, Pomatoschistus microps and Pomatoschistus minutus, in order to determine their relationships with varying environmental stressors operating over local and large scales. This study was performed in the Mondego estuary, Portugal. Firstly, the variations in abundance, growth, population structure and secondary production were evaluated. These species appeared in high densities in the beginning of the study period, with subsequent occasional high annual density peaks, while their secondary production was lower in dry years. The relationships between yearly fish abundance and the environmental variables were evaluated separately for both species using Spearman correlation analysis, considering the yearly abundance peaks for the whole population, juveniles and adults. Among the local climate patterns, precipitation, river runoff, salinity and temperature were used in the analyses, and North Atlantic Oscillation (NAO) index and sea surface temperature (SST) were tested as large-scale factors. For P. microps, precipitation and NAO were the significant factors explaining abundance of the whole population, the adults and the juveniles as well. Regarding P. minutus, for the whole population, juveniles and adults river runoff was the significant predictor. The results for both species suggest a differential influence of climate patterns on the various life cycle stages, confirming also the importance of estuarine resident fishes as indicators of changes in local and large-scale climate patterns, related to global climate change.

Determinants of extinction-colonization dynamics in Mediterranean butterflies: the role of landscape, climate and local habitat features.

PubMed

Fernández-Chacón, Albert; Stefanescu, Constantí; Genovart, Meritxell; Nichols, James D; Hines, James E; Páramo, Ferran; Turco, Marco; Oro, Daniel

2014-01-01

Many species are found today in the form of fragmented populations occupying patches of remnant habitat in human-altered landscapes. The persistence of these population networks requires a balance between extinction and colonization events assumed to be primarily related to patch area and isolation, but the contribution of factors such as the characteristics of patch and matrix habitats, the species' traits (habitat specialization and dispersal capabilities) and variation in climatic conditions have seldom been evaluated simultaneously. The identification of environmental variables associated with patch occupancy and turnover may be especially useful to enhance the persistence of multiple species under current global change. However, for robust inference on occupancy and related parameters, we must account for detection errors, a commonly overlooked problem that leads to biased estimates and misleading conclusions about population dynamics. Here, we provide direct empirical evidence of the effects of different environmental variables on the extinction and colonization rates of a rich butterfly community in the western Mediterranean. The analysis was based on a 17-year data set containing detection/nondetection data on 73 butterfly species for 26 sites in north-eastern Spain. Using multiseason occupancy models, which take into account species' detectability, we were able to obtain robust estimates of local extinction and colonization probabilities for each species and test the potential effects of site covariates such as the area of suitable habitat, topographic variability, landscape permeability around the site and climatic variability in aridity conditions. Results revealed a general pattern across species with local habitat composition and landscape features as stronger predictors of occupancy dynamics compared with topography and local aridity. Increasing area of suitable habitat in a site strongly decreased local extinction risks and, for a number of species, both higher amounts of suitable habitat and more permeable landscapes increased colonization rates. Nevertheless, increased topographic variability decreased the extinction risk of bad dispersers, a group of species with significantly lower colonization rates. Our models predicted higher sensitivity of the butterfly assemblages to deterministic changes in habitat features rather than to stochastic weather patterns, with some relationships being clearly dependent on the species' traits. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

Spatial and temporal variability in forest growth in the Olympic Mountains, Washington: sensitivity to climatic variability.

Treesearch

Melisa L. Holman; David L. Peterson

2006-01-01

We compared annual basal area increment (BAI) at different spatial scales among all size classes and species at diverse locations in the wet western and dry northeastern Olympic Mountains. Weak growth correlations at small spatial scales (average R = 0.084-0.406) suggest that trees are responding to local growth conditions. However, significant...

Vegetation change, malnutrition and violence in the Horn of Africa

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

Precipitation variability within the West Pacific Warm Pool over the past 120 ka: Evidence from the Davao Gulf, southern Philippines

NASA Astrophysics Data System (ADS)

Fraser, Nicholas; Kuhnt, Wolfgang; Holbourn, Ann; Bolliet, Timothé; Andersen, Nils; Blanz, Thomas; Beaufort, Luc

2014-11-01

Proxy records of hydrologic variability in the West Pacific Warm Pool (WPWP) have revealed wide-scale changes in past convective activity in response to orbital and suborbital climate forcings. However, attributing proxy responses to regional changes in WPWP hydrology versus local variations in precipitation requires independent records linking the terrestrial and marine realms. We present high-resolution stable isotope, UK'37 sea surface temperature, X-ray fluorescence (XRF) core scanning, and coccolithophore-derived paleoproductivity records covering the past 120 ka from International Marine Global Change (IMAGES) Program Core MD06-3075 (6°29'N, 125°50'E, water depth 1878 m), situated in the Davao Gulf on the southern side of Mindanao. XRF-derived log(Fe/Ca) records provide a robust proxy for runoff-driven sedimentary discharge from Mindanao, while past changes in local productivity are associated with variable freshwater runoff and stratification of the surface layer. Significant precessional-scale variability in sedimentary discharge occurred during marine isotope stage (MIS) 5, with peaks in discharge contemporaneous with Northern Hemisphere summer insolation minima. We attribute these changes to the latitudinal migration of the Intertropical Convergence Zone (ITCZ) over the WPWP together with variability in the strength of the Walker circulation acting on precessional timescales. Between 60 and 15 ka sedimentary discharge at Mindanao was muted, displaying little orbital- or millennial-scale variability, likely in response to weakened precessional insolation forcing and lower sea level driving increased subsidence of air masses over the exposed Sunda Shelf. These results highlight the high degree of local variability in the precipitation response to past climate changes in the WPWP.

The idiosyncrasies of streams: local variability mitigates vulnerability of trout to changing conditions

Treesearch

Andrea Watts; Brooke Penaluna; Jason Dunham

2016-01-01

Land use and climate change are two key factors with the potential to affect stream conditions and fish habitat. Since the 1950s, Washington and Oregon have required forest practices designed to mitigate the effects of timber harvest on streams and fish. Yet questions remain about the extent to which these practices are effective. Add in the effects of climate change—...

Land Cover Land Use Change and Soil Organic Carbon under Climate Variability in the Semi-Arid West African Sahel (1960-2050)

ERIC Educational Resources Information Center

Dieye, Amadou M.

2016-01-01

Land Cover Land Use (LCLU) change affects land surface processes recognized to influence climate change at local, national and global levels. Soil organic carbon is a key component for the functioning of agro-ecosystems and has a direct effect on the physical, chemical and biological characteristics of the soil. The capacity to model and project…

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...

Global Climatic Indices Influence on Rainfall Spatiotemporal Distribution : A Case Study from Morocco

NASA Astrophysics Data System (ADS)

Elkadiri, R.; Zemzami, M.; Phillips, J.

2017-12-01

The climate of Morocco is affected by the Mediterranean Sea, the Atlantic Ocean the Sahara and the Atlas mountains, creating a highly variable spatial and temporal distribution. In this study, we aim to decompose the rainfall in Morocco into global and local signals and understand the contribution of the climatic indices (CIs) on rainfall. These analyses will contribute in understanding the Moroccan climate that is typical of other Mediterranean and North African climatic zones. In addition, it will contribute in a long-term prediction of climate. The constructed database ranges from 1950 to 2013 and consists of monthly data from 147 rainfall stations and 37 CIs data provided mostly by the NOAA Climate Prediction Center. The next general steps were followed: (1) the study area was divided into 9 homogenous climatic regions and weighted precipitation was calculated for each region to reduce the local effects. (2) Each CI was decomposed into nine components of different frequencies (D1 to D9) using wavelet multiresolution analysis. The four lowest frequencies of each CI were selected. (3) Each of the original and resulting signals were shifted from one to six months to account for the effect of the global patterns. The application of steps two and three resulted in the creation of 1225 variables from the original 37 CIs. (4) The final 1225 variables were used to identify links between the global and regional CIs and precipitation in each of the nine homogenous regions using stepwise regression and decision tree. The preliminary analyses and results were focused on the north Atlantic zone and have shown that the North Atlantic Oscillation (PC-based) from NCAR (NAOPC), the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), the Western Mediterranean Oscillation (WMO) and the Extreme Eastern Tropical Pacific Sea Surface Temperature (NINO12) have the highest correlation with rainfall (33%, 30%, 27%, 21% and -20%, respectively). In addition the 4-months lagged NINO12 and the 6-months lagged NAOPC and WMO have a collective contribution of more than 45% of the rainfall signal. Low frequencies are also represented in the rainfall; especially the 5th and 4th components of the decomposed CIs (48% and 42% of the frequencies, respectively) suggesting their potential contribution in the interannual rainfall variability.

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.

Value of the GENS Forecast Ensemble as a Tool for Adaptation of Economic Activity to Climate Change

NASA Astrophysics Data System (ADS)

Hancock, L. O.; Alpert, J. C.; Kordzakhia, M.

2009-12-01

In an atmosphere of uncertainty as to the magnitude and direction of climate change in upcoming decades, one adaptation mechanism has emerged with consensus support: the upgrade and dissemination of spatially-resolved, accurate forecasts tailored to the needs of users. Forecasting can facilitate the changeover from dependence on climatology that is increasingly out of date. The best forecasters are local, but local forecasters face great constraints in some countries. Indeed, it is no coincidence that some areas subject to great weather variability and strong processes of climate change are economically vulnerable: mountainous regions, for example, where heavy and erratic flooding can destroy the value built up by households over years. It follows that those best placed to benefit from forecasting upgrades may not be those who have invested in the greatest capacity to date. More-flexible use of the global forecasts may contribute to adaptation. NOAA anticipated several years ago that their forecasts could be used in new ways in the future, and accordingly prepared sockets for easy access to their archives. These could be used to empower various national and regional capacities. Verification to identify practical lead times for the economically important variables is a needed first step. This presentation presents the verification that our team has undertaken, a pilot effort in which we considered variables of interest to economic actors in several lower income countries, cf. shepherds in a remote area of Central Asia, and verified the ensemble forecasts of those variables.

Predicting Local Dengue Transmission in Guangzhou, China, through the Influence of Imported Cases, Mosquito Density and Climate Variability

PubMed Central

Sang, Shaowei; Yin, Wenwu; Bi, Peng; Zhang, Honglong; Wang, Chenggang; Liu, Xiaobo; Chen, Bin; Yang, Weizhong; Liu, Qiyong

2014-01-01

Introduction Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF), a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue’s control and prevention purpose. Methodology and Principal Findings Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA) was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC) and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8%) imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags. Conclusions Imported DF cases and mosquito density play a critical role in local DF transmission, together with weather variables. The establishment of an early warning system, using existing surveillance datasets will help to control and prevent dengue in Guangzhou, China. PMID:25019967

Predicting local dengue transmission in Guangzhou, China, through the influence of imported cases, mosquito density and climate variability.

PubMed

Sang, Shaowei; Yin, Wenwu; Bi, Peng; Zhang, Honglong; Wang, Chenggang; Liu, Xiaobo; Chen, Bin; Yang, Weizhong; Liu, Qiyong

2014-01-01

Each year there are approximately 390 million dengue infections worldwide. Weather variables have a significant impact on the transmission of Dengue Fever (DF), a mosquito borne viral disease. DF in mainland China is characterized as an imported disease. Hence it is necessary to explore the roles of imported cases, mosquito density and climate variability in dengue transmission in China. The study was to identify the relationship between dengue occurrence and possible risk factors and to develop a predicting model for dengue's control and prevention purpose. Three traditional suburbs and one district with an international airport in Guangzhou city were selected as the study areas. Autocorrelation and cross-correlation analysis were used to perform univariate analysis to identify possible risk factors, with relevant lagged effects, associated with local dengue cases. Principal component analysis (PCA) was applied to extract principal components and PCA score was used to represent the original variables to reduce multi-collinearity. Combining the univariate analysis and prior knowledge, time-series Poisson regression analysis was conducted to quantify the relationship between weather variables, Breteau Index, imported DF cases and the local dengue transmission in Guangzhou, China. The goodness-of-fit of the constructed model was determined by pseudo-R2, Akaike information criterion (AIC) and residual test. There were a total of 707 notified local DF cases from March 2006 to December 2012, with a seasonal distribution from August to November. There were a total of 65 notified imported DF cases from 20 countries, with forty-six cases (70.8%) imported from Southeast Asia. The model showed that local DF cases were positively associated with mosquito density, imported cases, temperature, precipitation, vapour pressure and minimum relative humidity, whilst being negatively associated with air pressure, with different time lags. Imported DF cases and mosquito density play a critical role in local DF transmission, together with weather variables. The establishment of an early warning system, using existing surveillance datasets will help to control and prevent dengue in Guangzhou, China.

Impact of climate variability on various Rabi crops over Northwest India

NASA Astrophysics Data System (ADS)

Nageswararao, M. M.; Dhekale, B. S.; Mohanty, U. C.

2018-01-01

The Indian agriculture with its two prominent cropping seasons [summer ( Kharif) and winter ( Rabi)] is the mainstay of the rural economy. Northwest India (NWI) is an important region for the cultivation of Rabi crops grown during the period from October to April. In the present study, state wise impact analysis is carried out to ascertain the influence of climate indices Nino3.4 region Sea Surface Temperature (SST), Southern Oscillation Index (SOI), Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and local precipitation, soil moisture, minimum ( T min), maximum ( T max) and mean ( T mean) temperatures on different Rabi crops (wheat, gram, rapeseed-mustard, oilseeds, and total Rabi food grains) over NWI during the years 1966-2011. To study the impact of climate variability on different Rabi crops, firstly, the influence of technology on the productivity of these crops has been removed by using linear function, as linear trend has noticed in all the time series. Correlation analysis provides an indication of the influence of local precipitation, soil moisture, T min, T max and T mean and some of its potential predictors (Nino3.4 region SST, SOI, AO, and NAO) on the productivity of different Rabi crops. Overall impact analysis indicates that the productivity of different Rabi crops in most of the places of NWI is most likely influenced by variability in local temperatures. Moreover, Nino3.4 region SST (SOI) positively (negatively) affects the productivity of gram, rapeseed-mustard, and total Rabi oilseeds in most of the states. The results of this study are useful in determining the strategies for increasing sustainable production through better agronomic practices.

Scaling and contextualizing climate-conflict nexus in historical agrarian China

NASA Astrophysics Data System (ADS)

Lee, Harry F.

2017-04-01

This study examines climate-conflict nexus in historical agrarian China in multi-scalar and contextualized approach, illustrating what and how socio-political factors could significantly mediate the climate-violent link in pre-industrial society. Previous empirical large-N studies show that violent conflict in historical agrarian society was triggered by climate-induced food scarcity. The relationship was valid in China, Europe, and various geographic regions in the Northern Hemisphere in pre-industrial era. Nevertheless, the observed relationship has only been verified at a macro level (long-term variability of the nexus is emphasized and data over large area are aggregated), and somewhat generalized in nature (only physical environmental factors are controlled). Three inter-related issues remain unresolved: First, the key explanatory variable of violent conflicts may change substantially at different spatio-temporal scales. It is necessary to check whether the climate-conflict nexus is valid at a micro level (about short-term variability of the nexus and data in finer spatial resolution), and explore how the nexus changes along various spatio-temporal dimensions. Second, as the climate-conflict nexus has only been demonstrated in a broad sense, it is necessary to check whether and how the nexus is mediated by local socio-political context. More non-climatic factors pertinent to the cause and distribution of conflicts (e.g., governance, adaptive mechanisms, etc.) should be considered. Third, the methodology applied in the previous studies assumes spatially-independent observations and linear relationship, which may simplify the climate-conflict link. Moreover, the solitary reliance on quantitative methods may neglect those non-quantifiable socio-political dynamics which mediates the climate-conflict nexus. I plan to address the above issues by using disaggregated spatial analysis and in-depth case studies, with close attention to local and temporal differences and non-linear nature of the climate-conflict link. China will be chosen as study area. Study period will be delimited to AD1-1911. This study represents pioneering research which systematically examines the climate-conflict nexus in pre-industrial society over extended period in multi-scalar and contextualized perspective. By comparing and evaluating the climate-conflict link along various spatio-temporal dimensions and in different socio-political context, it may help to deepen the theoretical understanding of, and also resolve the current debate over, the climate-conflict relationship. Given the large potential changes in climatic regimes projected in coming decades, the findings in this study may have important implications for the social impact of climate change in tropical countries that are in some ways similar to pre-industrial society.

A modern plant-climate research dataset for modelling eastern North American plant taxa.

NASA Astrophysics Data System (ADS)

Gonzales, L. M.; Grimm, E. C.; Williams, J. W.; Nordheim, E. V.

2008-12-01

Continental-scale modern pollen-climate data repositories are a primary data source for paleoclimate reconstructions. However, these repositories can contain artifacts, such as records from different depositional environment and replicate records, that can influence the observed pollen-climate relationships as well as the paleoclimate reconstructions derived from these relationships. In this paper, we address the issues related to these artifacts as we define the methods used to create a research dataset from the North American Modern Pollen Database (Whitmore et al., 2005). Additionally, we define the methods used to select the environmental variables that are best for modeling regional pollen-climate relationships from the research dataset. Because the depositional environment determines the relative strengths of the local and regional pollen signals, combining data from different depositional environments results in pollen abundances that can be influenced by the local pollen signal. Replicate records in pollen-climate datasets can skew pollen-climate relationships by causing an over- or under- representation of pollen abundances in climate space. When these two artifacts are combined, the errors introduced into pollen-climate relationship modeling are compounded. The research dataset we present consists of 2,613 records in eastern North America, of which 70.9% are lacustrine sites. We demonstrate that this new research database improves upon the modeling of regional pollen-climate relationships for eastern North American taxa. The research dataset encompasses the majority of the temperature and mean summer precipitation ranges of the NAMPD's climatic range and 40% of its mean winter precipitation range. NAMPD sites with higher winter precipitation are located along the northwestern coast of North America where a rainshadow effect produces abundant winter precipitation. We present our analysis of the research dataset for use in paleoclimate reconstructions, and recommend that mean winter and summer temperature and precipitation variables be used for pollen-climate relationship modeling.

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.

The Use of Climate Projections in the Modelling of Bud Burst

NASA Astrophysics Data System (ADS)

O'Neill, Bridget F.; Caffara, Amelia; Gleeson, Emily; Semmler, Tido; McGrath, Ray; Donnelly, Alison

2010-05-01

Recent changes in global climate, such as increasing temperature, have had notable effects on the phenology (timing of biological events) of plants. The effects are variable across habitats and between species, but increasing temperatures have been shown to advance certain key phenophases of trees, such as bud burst (beginning of leaf unfolding). This project considered climate change impacts on phenology of plants at a local scale in Ireland. The output from the ENSEMBLES climate simulations were down-scaled to Ireland and utilised by a phenological model to project changes over the next 50-100 years. This project helps to showcase the potential use of climate simulations in phenological research.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

Interannual Variability in the Position and Strength of the East Asian Jet Stream and Its Relation to Large - scale Circulation

NASA Astrophysics Data System (ADS)

Chan, Duo; Zhang, Yang; Wu, Qigang

2013-04-01

East Asian Jet Stream (EASJ) is charactered by obvious interannual variability in strength and position (latitude), with wide impacts on East Asian climate in all seasons. In this study, two indices are established to measure the interannual variability in intensity and position of EAJS. Possible causing factors, including both local signals and non-local large-scale circulation, are examined using NCAP-NCAR reanalysis data to investigate their relations with jet variation. Our analysis shows that the relationship between the interannual variations of EASJ and these factors depends on seasons. In the summer, both the intensity and position of EASJ are closely related to the meridional gradient of local surface temperature, but display no apparent relationship with the larg-scale circulation. In cold seasons (autumn, winter and spring), both the local factor and the large-scale circulation, i.e. the Pacific/North American teleconnection pattern (PNA), play important roles in the interannual variability of the jet intensity. The variability in the jet position, however, is more correlated to the Arctic Oscillation (AO), especially in winter. Diagnostic analysis indicates that transient eddy activity plays an important role in connecting the interannual variability of EASJ position with AO.

Genetically informed ecological niche models improve climate change predictions.

PubMed

Ikeda, Dana H; Max, Tamara L; Allan, Gerard J; Lau, Matthew K; Shuster, Stephen M; Whitham, Thomas G

2017-01-01

We examined the hypothesis that ecological niche models (ENMs) more accurately predict species distributions when they incorporate information on population genetic structure, and concomitantly, local adaptation. Local adaptation is common in species that span a range of environmental gradients (e.g., soils and climate). Moreover, common garden studies have demonstrated a covariance between neutral markers and functional traits associated with a species' ability to adapt to environmental change. We therefore predicted that genetically distinct populations would respond differently to climate change, resulting in predicted distributions with little overlap. To test whether genetic information improves our ability to predict a species' niche space, we created genetically informed ecological niche models (gENMs) using Populus fremontii (Salicaceae), a widespread tree species in which prior common garden experiments demonstrate strong evidence for local adaptation. Four major findings emerged: (i) gENMs predicted population occurrences with up to 12-fold greater accuracy than models without genetic information; (ii) tests of niche similarity revealed that three ecotypes, identified on the basis of neutral genetic markers and locally adapted populations, are associated with differences in climate; (iii) our forecasts indicate that ongoing climate change will likely shift these ecotypes further apart in geographic space, resulting in greater niche divergence; (iv) ecotypes that currently exhibit the largest geographic distribution and niche breadth appear to be buffered the most from climate change. As diverse agents of selection shape genetic variability and structure within species, we argue that gENMs will lead to more accurate predictions of species distributions under climate change. © 2016 John Wiley & Sons Ltd.

Regional and local species richness in an insular environment: Serpentine plants in California

USGS Publications Warehouse

Harrison, S.; Safford, H.D.; Grace, J.B.; Viers, J.H.; Davies, K.F.

2006-01-01

We asked how the richness of the specialized (endemic) flora of serpentine rock outcrops in California varies at both the regional and local scales. Our study had two goals: first, to test whether endemic richness is affected by spatial habitat structure (e.g., regional serpentine area, local serpentine outcrop area, regional and local measures of outcrop isolation), and second, to conduct this test in the context of a broader assessment of environmental influences (e.g., climate, soils, vegetation, disturbance) and historical influences (e.g., geologic age, geographic province) on local and regional species richness. We measured endemic and total richness and environmental variables in 109 serpentine sites (1000-m2 paired plots) in 78 serpentine-containing regions of the state. We used structural equation modeling (SEM) to simultaneously relate regional richness to regionalscale predictors, and local richness to both local-scale and regional-scale predictors. Our model for serpentine endemics explained 66% of the variation in local endemic richness based on local environment (vegetation, soils, rock cover) and on regional endemic richness. It explained 73% of the variation in regional endemic richness based on regional environment (climate and productivity), historical factors (geologic age and geographic province), and spatial structure (regional total area of serpentine, the only significant spatial variable in our analysis). We did not find a strong influence of spatial structure on species richness. However, we were able to distinguish local vs. regional influences on species richness to a novel extent, despite the existence of correlations between local and regional conditions. ?? 2006 by the Ecological Society of America.

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).

Impacts of 2000-2050 Climate Change on Fine Particulate Matter (PM2.5) Air Quality in China Based on Statistical Projections Using an Ensemble of Global Climate Models

NASA Astrophysics Data System (ADS)

Leung, D. M.; Tai, A. P. K.; Shen, L.; Moch, J. M.; van Donkelaar, A.; Mickley, L. J.

2017-12-01

Fine particulate matter (PM2.5) air quality is strongly dependent on not only on emissions but also meteorological conditions. Here we examine the dominant synoptic circulation patterns that control day-to-day PM2.5 variability over China. We perform principal component (PC) analysis on 1998-2016 NCEP/NCAR Reanalysis I daily meteorological fields to diagnose distinct synoptic meteorological modes, and perform PC regression on spatially interpolated 2014-2016 daily mean PM2.5 concentrations in China to identify modes dominantly explaining PM2.5 variability. We find that synoptic systems, e.g., cold-frontal passages, maritime inflow and frontal precipitation, can explain up to 40% of the day-to-day PM2.5 variability in major metropolitan regions in China. We further investigate how annually changing frequencies of synoptic systems, as well as changing local meteorology, drive interannual PM2.5 variability. We apply a spectral analysis on the PC time series to obtain the 1998-2016 annual median synoptic frequency, and use a forward-selection multiple linear regression (MLR) model of satellite-derived 1998-2015 annual mean PM2.5 concentrations on local meteorology and synoptic frequency, selecting predictors that explain the highest fraction of interannual PM2.5 variability while guarding against multicollinearity. To estimate the effect of climate change on future PM2.5 air quality, we project a multimodel ensemble of 15 CMIP5 models under the RCP8.5 scenario on the PM2.5-to-meteorology sensitivities derived for the present-day from the MLR model. Our results show that climate change could be responsible for increases in PM2.5 of more than 25 μg m-3 in northwestern China and 10 mg m-3 in northeastern China by the 2050s. Increases in synoptic frequency of cold-frontal passages cause only a modest 1 μg m-3 decrease in PM2.5 in North China Plain. Our analyses show that climate change imposes a significant penalty on air quality over China and poses serious threat on human health under the RCP8.5 future.

Assessing the biophysical and socio-economic potential of Sustainable Land Management and Water Harvesting Technologies for rainfed agriculture across semi-arid Africa.

NASA Astrophysics Data System (ADS)

Irvine, Brian; Fleskens, Luuk; Kirkby, Mike

2016-04-01

Stakeholders in recent EU projects identified soil erosion as the most frequent driver of land degradation in semi-arid environments. In a number of sites, historic land management and rainfall variability are recognised as contributing to the serious environmental impact. In order to consider the potential of sustainable land management and water harvesting techniques stakeholders and study sites from the projects selected and trialled both local technologies and promising technologies reported from other sites . The combined PESERA and DESMICE modelling approach considered the regional effects of the technologies in combating desertification both in environmental and socio-economical terms. Initial analysis was based on long term average climate data with the model run to equilibrium. Current analysis, primarily based on the WAHARA study sites considers rainfall variability more explicitly in time series mode. The PESERA-DESMICE approach considers the difference between a baseline scenario and a (water harvesting) technology scenario, typically, in terms of productivity, financial viability and scope for reducing erosion risk. A series of 50 year rainfall realisations are generated from observed data to capture a full range of the climatic variability. Each realisation provides a unique time-series of rainfall and through modelling can provide a simulated time-series of crop yield and erosion risk for both baseline conditions and technology scenarios. Subsequent realisations and model simulations add to an envelope of the potential crop yield and cost-benefit relations. The development of such envelopes helps express the agricultural and erosional risk associated with climate variability and the potential for conservation measures to absorb the risk, highlighting the probability of achieving a given crop yield or erosion limit. Information that can directly inform or influence the local adoption of conservation measures under the climatic variability in semi-arid areas

Community phylogenetics at the biogeographical scale: cold tolerance, niche conservatism and the structure of North American forests.

PubMed

Hawkins, Bradford A; Rueda, Marta; Rangel, Thiago F; Field, Richard; Diniz-Filho, José Alexandre F; Linder, Peter

2014-01-01

Aim The fossil record has led to a historical explanation for forest diversity gradients within the cool parts of the Northern Hemisphere, founded on a limited ability of woody angiosperm clades to adapt to mid-Tertiary cooling. We tested four predictions of how this should be manifested in the phylogenetic structure of 91,340 communities: (1) forests to the north should comprise species from younger clades (families) than forests to the south; (2) average cold tolerance at a local site should be associated with the mean family age (MFA) of species; (3) minimum temperature should account for MFA better than alternative environmental variables; and (4) traits associated with survival in cold climates should evolve under a niche conservatism constraint. Location The contiguous United States. Methods We extracted angiosperms from the US Forest Service's Forest Inventory and Analysis database. MFA was calculated by assigning age of the family to which each species belongs and averaging across the species in each community. We developed a phylogeny to identify phylogenetic signal in five traits: realized cold tolerance, seed size, seed dispersal mode, leaf phenology and height. Phylogenetic signal representation curves and phylogenetic generalized least squares were used to compare patterns of trait evolution against Brownian motion. Eleven predictors structured at broad or local scales were generated to explore relationships between environment and MFA using random forest and general linear models. Results Consistent with predictions, (1) southern communities comprise angiosperm species from older families than northern communities, (2) cold tolerance is the trait most strongly associated with local MFA, (3) minimum temperature in the coldest month is the environmental variable that best describes MFA, broad-scale variables being much stronger correlates than local-scale variables, and (4) the phylogenetic structures of cold tolerance and at least one other trait associated with survivorship in cold climates indicate niche conservatism. Main conclusions Tropical niche conservatism in the face of long-term climate change, probably initiated in the Late Cretaceous associated with the rise of the Rocky Mountains, is a strong driver of the phylogenetic structure of the angiosperm component of forest communities across the USA. However, local deterministic and/or stochastic processes account for perhaps a quarter of the variation in the MFA of local communities.

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

Improved National Response to Climate Change: Aligning USGCRP reports and the U.S. Climate Resilience Toolkit

NASA Astrophysics Data System (ADS)

Lipschultz, F.; Dahlman, L. E.; Herring, D.; Fox, J. F.

2017-12-01

As part of an effort to coordinate production and distribution of scientific climate information across the U.S. Government, and to spur adaptation actions across the nation, the U.S. Global Change Research Program (USGCRP) has worked to better integrate the U.S. Climate Resilience Toolkit (CRT) and its Climate Explorer (CE) tool into USGCRP activities and products. Much of the initial CRT content was based on the Third National Climate Assessment (NCA3). The opportunity to integrate current development of NCA4—scheduled for release in late 2018—with CRT and CE can enhance all three projects and result in a useable and "living" NCA that is part of USGCRP's approach to sustained climate assessment. To coordinate this work, a USGCRP-led science team worked with CRT staff and CE developers to update the set of climate projections displayed in the CE tool. In concert with the USGCRP scenarios effort, the combined team selected the Localized Constructed Analogs (LOCA) dataset for the updated version of CE, based on its capabilities for capturing climate extremes and local climate variations. The team identified 28 variables from the LOCA dataset for display in the CE; many of these variables will also be used in USGCRP reports. In CRT engagements, communities with vulnerable assets have expressed a high value for the ability to integrate climate data available through the CE with data related to non-climate stressors in their locations. Moving forward, the teams intend to serve climate information needs at additional spatial scales by making NCA4 content available via CE's capability for dynamic interaction with climate-relevant datasets. This will permit users to customize the extent of data they access for decision-making, starting with the static NCA4 report. Additionally, NCA4 case studies and other content can be linked to more in-depth content within the CRT site. This capability will enable more frequent content updates than can be managed with quadrennial NCA reports. Overall, enhanced integration between USGCRP and CRT will provide consistent information for communities that are assessing their climate vulnerabilities or considering adaptation options.

A strong control of the South American SeeSaw on the intra-seasonal variability of the isotopic composition of precipitation in the Bolivian Andes

NASA Astrophysics Data System (ADS)

Vimeux, Françoise; Tremoy, Guillaume; Risi, Camille; Gallaire, Robert

2011-07-01

Water stable isotopes (δ) in tropical regions are a valuable tool to study both convective processes and climate variability provided that local and remote controls on δ are well known. Here, we examine the intra-seasonal variability of the event-based isotopic composition of precipitation (δD Zongo) in the Bolivian Andes (Zongo valley, 16°20'S-67°47'W) from September 1st, 1999 to August 31st, 2000. We show that the local amount effect is a very poor parameter to explain δD Zongo. We thus explore the property of water isotopes to integrate both temporal and spatial convective activities. We first show that the local convective activity averaged over the 7-8 days preceding the rainy event is an important control on δD Zongo during the rainy season (~ 40% of the δD Zongo variability is captured). This could be explained by the progressive depletion of local water vapor by unsaturated downdrafts of convective systems. The exploration of remote convective controls on δD Zongo shows a strong influence of the South American SeeSaw (SASS) which is the first climate mode controlling the precipitation variability in tropical South America during austral summer. Our study clearly evidences that temporal and spatial controls are not fully independent as the 7-day averaged convection in the Zongo valley responds to the SASS. Our results are finally used to evaluate a water isotope enabled atmospheric general circulation model (LMDZ-iso), using the stretched grid functionality to run zoomed simulations over the entire South American continent (15°N-55°S; 30°-85°W). We find that zoomed simulations capture the intra-seasonal isotopic variation and its controls, though with an overestimated local sensitivity, and confirm the role of a remote control on δ according to a SASS-like dipolar structure.

Climate Resiliency Planning: Making Extreme Event Science Useful for Managers and Planners in Northern Nevada

NASA Astrophysics Data System (ADS)

McCarthy, M.; Kenneston, A.; Wall, T. U.; Brown, T. J.; Redmond, K. T.

2014-12-01

Effective climate resiliency planning at the regional level requires extensive interactive dialogue among climate scientists, emergency managers, public health officials, urban planners, social scientists, and policy makers. Engaging federal, tribal, state, local governments and private sector business and infrastructure owners/operators in defining, assessing and characterizing the impacts of extreme events allows communities to understand how different events "break the system" forcing local communities to seek support and resources from state/federal governments and/or the private sector and what actions can be taken proactively to mitigate consequences and accelerate recovery. The Washoe County Regional Resiliency Study was prepared in response to potential climate variability related impacts specific to the Northern Nevada Region. The last several decades have seen dramatic growth in the region, coupled with increased resource demands that have forced local governments to consider how those impacts will affect the region and may, in turn, impact the region's ability to provide essential services. The Western Regional Climate Center of the Desert Research Institute provided a synthesis of climate studies with predictions regarding plausible changes in the local climate of Northern California and Nevada for the next 50 years. In general, these predictions indicate that the region's climate is undergoing a gradual shift, which will primarily affect the frequency, amount, and form of precipitation in the Sierra Nevada and Great Basin. Changes in water availability and other extreme events may have serious and long lasting effects in the Northern Nevada Region, and create a variety of social, environmental and economic concerns. A range of extreme events were considered including Adverse Air Quality, Droughts, Floods, Heat Waves, High Wind, Structure Fires, Wildland Fires, and Major Winter Storms. Due to the complexity of our climate systems, and the difficulty in specifying how severe the climate effects may be or how those impacts compound existing hazards in the system, the Resiliency Study focused on identifying a variety of 'no regrets' policy options that can help the local communities anticipate, respond and recover faster and more efficiently to climate extremes.

Assessment of regional climate change and development of climate adaptation decision aids in the Southwestern US

NASA Astrophysics Data System (ADS)

Darmenova, K.; Higgins, G.; Kiley, H.; Apling, D.

2010-12-01

Current General Circulation Models (GCMs) provide a valuable estimate of both natural and anthropogenic climate changes and variability on global scales. At the same time, future climate projections calculated with GCMs are not of sufficient spatial resolution to address regional needs. Many climate impact models require information at scales of 50 km or less, so dynamical downscaling is often used to estimate the smaller-scale information based on larger scale GCM output. To address current deficiencies in local planning and decision making with respect to regional climate change, our research is focused on performing a dynamical downscaling with the Weather Research and Forecasting (WRF) model and developing decision aids that translate the regional climate data into actionable information for users. Our methodology involves development of climatological indices of extreme weather and heating/cooling degree days based on WRF ensemble runs initialized with the NCEP-NCAR reanalysis and the European Center/Hamburg Model (ECHAM5). Results indicate that the downscale simulations provide the necessary detailed output required by state and local governments and the private sector to develop climate adaptation plans. In addition we evaluated the WRF performance in long-term climate simulations over the Southwestern US and validated against observational datasets.

Investigating the Control of Ocean-Atmospheric Oscillations on Global Terrestrial Evaporation

NASA Astrophysics Data System (ADS)

Martens, B.; Waegeman, W.; Dorigo, W.; Verhoest, N.; Miralles, D. G.

2017-12-01

Intra-annual and multi-decadal variability in Earth's climate is strongly driven by periodic oscillations in the coupled state of our atmosphere and ocean. These oscillations do not only impact climate in nearby regions, but can also have an effect on the climate in remote areas, a phenomenon that is often referred to as teleconnection. Because changes in local climate immediately affect terrestrial ecosystems through a series of complex processes, ocean-atmospheric oscillations are expected to influence land evaporation; i.e. the return flux of water from land into the atmosphere. In this presentation, the effects of ocean-atmospheric oscillations on global terrestrial evaporation are analysed. We use multi-decadal, satellite-based observations of different climate variables (air temperature, radiation, precipitation) in combination with a simple supervised learning method - the Least Absolute Shrinkage and Selection Operator - to detect the impact of sixteen leading ocean-atmospheric oscillations on terrestrial evaporation. The latter is retrieved using the Global Land Evaporation Amsterdam Model (GLEAM). The analysis reveals hotspot regions in which more than 30% of the inter-annual variability in terrestrial evaporation can be explained by ocean-atmospheric oscillations. The impact is different per region and season, and can typically be attributed to a small subset of oscillations. For instance, the dynamics in terrestrial evaporation over eastern Australia are substantially impacted by both the El Niño Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) during Austral spring. Using the same learning method, but targeting terrestrial evaporation based on its local climatic drivers (air temperature, precipitation, and radiation), shows the dominant control of precipitation on terrestrial evaporation in Australia, suggesting that both ENSO and IOD affect the precipitation, in his turn influencing evaporation. The latter is confirmed by regressing precipitation to the ocean-atmospheric oscillations. The results of our study allow for a better understanding of the link between ocean-atmosphere dynamics and terrestrial bio-geochemical cycles, and may help improve the prediction of future changes in the water cycle over the continents.

Relation between climatic factors, diet and reproductive parameters of Little Terns over a decade

NASA Astrophysics Data System (ADS)

Ramos, Jaime A.; Pedro, Patrícia; Matos, Antonio; Paiva, Vitor H.

2013-11-01

We used 10 years of data on clutch size, egg size and diet, and 8 years of data on timing of laying on Little Terns (Sternula albifrons) breeding in Ria Formosa lagoon system, Algarve, Portugal to assess whether diet acts as an important intermediary between climatic conditions and breeding parameters. We used Generalized Linear Models to relate (1) the relative occurrence and size of the main prey species, sand smelts (Atherina spp.), with environmental variables, a large-scale climate variable, the North Atlantic Oscillation (NAO) index, and a local scale variable, the sea-surface temperature (SST), and (2) the respective effects of sand smelts relative occurrence, NAO index and SST on Little Tern breeding parameters. The diet of Little Terns was dominated by sand smelts, with a frequency occurrence of over 60% in all years. The winter SST (February) was negatively associated with the relative occurrence of sand smelts in the diet of Little Terns during the breeding season which, in turn, was positively associated with Little Tern clutch size. Our results suggest that negative NAO conditions in the Atlantic Ocean, often associated with rougher sea conditions (greater vertical mixing, stronger winds and lower SST) were related with earlier breeding, and lower SST in the surroundings of the colony during winter-spring favour the abundance of prey fish for Little Terns as well as their reproductive parameters. Climate patterns at both large and local scales are likely to change in the future, which may have important implications for estuarine seabirds in Southern Europe.

Spatio-temporal variability of urban heat islands in local climate zones of Delhi-NCR

NASA Astrophysics Data System (ADS)

Budhiraja, Bakul; Pathak, Prasad; Agrawal, Girish

2017-10-01

Land use change is at the nexus of human territory expansion and urbanization. Human intrusion disturbs the natural heat energy balance of the area, although a new equilibrium of energy flux is attained but with greater diurnal range and adversely affecting the geo/physical variables. Modification in the trend of these variables causes a phenomenon known as Urban Heat Island (UHI) i.e. a dome of heat is formed around the city which has 7-10 °C high temperature than the nearby rural area at night. The study focuses on Surface UHI conventionally studied using thermal band of the remotely sensed satellite images. Land Surface Temperature (LST) is determined for the year 2015 using Landsat 8 for Delhi National Capital Region (NCR). This region was chosen because it is the biggest urban agglomeration in India, many satellite cities are coming in periphery and it has temperate climate. Quantification of UHI is predictably done using UHI intensity that is the difference between representative Urban and rural temperature. Recently the definition of urban and rural has been questioned because of various kinds of configurations of urban spaces across the globe. Delhi NCR urban configurations vary spatially- thus one UHI intensity does not give a deep understanding of the micro-climate. Advancement was made recently to standardize UHI intensity by dividing city into Local Climate Zones (LCZ), comes with 17 broad categories. LCZ map of Delhi NCR has been acquired from World Urban Database. The seasonality in LST across LCZ has been determined along with identifying warmest and coolest LCZ.

Risk Communication: The Role of the South Carolina State Climatology Office.

NASA Astrophysics Data System (ADS)

Smith, David J.; Purvis, John C.; Felts, Arthur

1995-12-01

The federally supported state climatologist program ended in 1972. Thereafter, most states supported these endeavors in coordination with the National Climatic Data Center, but the current state programs vary widely. One of the functions of state climate programs that evolved since 1972 is acting as a liaison between the National Weather Service and various state agencies. This role is most apparent and controversial in coordinating state and local government response to severe weather and extreme climate anomalies such as drought, flood, winter storms, and tropical cyclones. The activities of the climate office in South Carolina during Hurricane Hugo in September 1989 and the October 1990 floods reveal how these interactions occur in one state that mandated these activities. The state climate office had to react to shifting weather conditions and to variable political conditions that affect public organizations. The climate office in South Carolina acts to interpret weather information, develop scenarios and predictions, and to assist in postevent damage surveys. This review is presented to acknowledge and document the expanding role of the state climate office in South Carolina in response to state and local government needs for weather forecast interpretation and expert guidance in the event of severe weather.

Carboniferous climate teleconnections archived in coupled bioapatite δ18OPO4 and 87Sr/86Sr records from the epicontinental Donets Basin, Ukraine

NASA Astrophysics Data System (ADS)

Montañez, Isabel P.; Osleger, Dillon J.; Chen, Jitao; Wortham, Barbara E.; Stamm, Robert G.; Nemyrovska, Tamara I.; Griffin, Julie M.; Poletaev, Vladislav I.; Wardlaw, Bruce R.

2018-06-01

Reconstructions of paleo-seawater chemistry are largely inferred from biogenic records of epicontinental seas. Recent studies provide considerable evidence for large-scale spatial and temporal variability in the environmental dynamics of these semi-restricted seas that leads to the decoupling of epicontinental isotopic records from those of the open ocean. We present conodont apatite δ18OPO4 and 87Sr/86Sr records spanning 24 Myr of the late Mississippian through Pennsylvanian derived from the U-Pb calibrated cyclothemic succession of the Donets Basin, eastern Ukraine. On a 2 to 6 Myr-scale, systematic fluctuations in bioapatite δ18OPO4 and 87Sr/86Sr broadly follow major shifts in the Donets onlap-offlap history and inferred regional climate, but are distinct from contemporaneous more open-water δ18OPO4 and global seawater Sr isotope trends. A -1 to -6‰ offset in Donets δ18OPO4 values from those of more open-water conodonts and greater temporal variability in δ18OPO4 and 87Sr/86Sr records are interpreted to primarily record climatically driven changes in local environmental processes in the Donets sea. Systematic isotopic shifts associated with Myr-scale sea-level fluctuations, however, indicate an extrabasinal driver. We propose a mechanistic link to glacioeustasy through a teleconnection between high-latitude ice changes and atmospheric pCO2 and regional monsoonal circulation in the Donets region. Inferred large-magnitude changes in Donets seawater salinity and temperature, not archived in the more open-water or global contemporaneous records, indicate a modification of the global climate signal in the epicontinental sea through amplification or dampening of the climate signal by local and regional environmental processes. This finding of global climate change filtered through local processes has implications for the use of conodont δ18OPO4 and 87Sr/86Sr values as proxies of paleo-seawater composition, mean temperature, and glacioeustasy.

Carboniferous climate teleconnections archived in coupled bioapatite δ18OPO4 and 87Sr/86Sr records from the epicontinental Donets Basin, Ukraine

USGS Publications Warehouse

Montanez, Isabel P.; Osleger, Dillon J.; Chen, J.-H.; Wortham, Barbara E.; Stamm, Robert G.; Nemyrovska, Tamara I.; Griffin, Julie M.; Poletaev, Vladislav I.; Wardlaw, Bruce R.

2018-01-01

Reconstructions of paleo-seawater chemistry are largely inferred from biogenic records of epicontinental seas. Recent studies provide considerable evidence for large-scale spatial and temporal variability in the environmental dynamics of these semi-restricted seas that leads to the decoupling of epicontinental isotopic records from those of the open ocean. We present conodont apatite δ18OPO4 and 87Sr/86Sr records spanning 24 Myr of the late Mississippian through Pennsylvanian derived from the U–Pb calibrated cyclothemic succession of the Donets Basin, eastern Ukraine. On a 2 to 6 Myr-scale, systematic fluctuations in bioapatite δ18OPO4 and 87Sr/86Sr broadly follow major shifts in the Donets onlap–offlap history and inferred regional climate, but are distinct from contemporaneous more open-water δ18OPO4 and global seawater Sr isotope trends. A −1 to −6‰ offset in Donets δ18OPO4 values from those of more open-water conodonts and greater temporal variability in δ18OPO4 and 87Sr/86Sr records are interpreted to primarily record climatically driven changes in local environmental processes in the Donets sea. Systematic isotopic shifts associated with Myr-scale sea-level fluctuations, however, indicate an extrabasinal driver. We propose a mechanistic link to glacioeustasy through a teleconnection between high-latitude ice changes and atmospheric pCO2 and regional monsoonal circulation in the Donets region. Inferred large-magnitude changes in Donets seawater salinity and temperature, not archived in the more open-water or global contemporaneous records, indicate a modification of the global climate signal in the epicontinental sea through amplification or dampening of the climate signal by local and regional environmental processes. This finding of global climate change filtered through local processes has implications for the use of conodont δ18OPO4 and 87Sr/86Sr values as proxies of paleo-seawater composition, mean temperature, and glacioeustasy.

Climate of a high altitude lake basin and lake-atmosphere interactions - observations and atmospheric modelling

NASA Astrophysics Data System (ADS)

Maussion, F.; Kropacek, J.; Finkelnburg, R.; Scherer, D.

2012-04-01

Large lakes and inland water bodies have a significant influence on their local climate. The hydrometeorological effect of inland water bodies is varying greatly between seasons, years and contrasting climatic conditions. It is generally hypothesised that the cool air above the lake will inhibit convection in summer; conversely, the relatively warm lake in late-autumn will initiate convective instability that may generate strong snowfalls. In this study we focus on the lake Nam Co (2'000 sq.km, 4700 m a.s.l). Located in a transition zone between the continental climate of Central Asia and the Indian Monsoon system, the Nam Co lake is covered by ice from mid-January to end of April and reaches surface temperatures of 13 °C in summer. We address three main research questions: (i) what is the influence of the Nam Co lake on local meteorological variables over the course of the year, (ii) what is the impact of the timing of the lake freezing on late-autumn and winter precipitation fields and (iii) how will the influence of the lake evolve in the context of a changing climate? In order to answer these questions, we combine satellite observations of lake surface temperatures from the ARC-Lake product and atmospheric modelling using the WRF model. The spatio-temporal variability of temperature, wind and precipitation fields during the last decade are analyzed using high-resolution (up to 2 km) simulations. The positive impact of the assimilation of the lake surface temperatures for the initialization of the model is analysed and discussed, as well as the combined influences of the large scale (westerlies, monsoon) and local (orographic) forcings. Our results are of relevance for any regional climate or hydrological modelling study and bring new insights in our understanding of the complex hydrometeorological processes taking place on the Tibetan Plateau.

Ecological role and services of tropical mangrove ecosystems: a reassessment

USGS Publications Warehouse

Lee, Shing Yip; Primavera, Jurgene H.; Dahdouh-Guebas, Farid; McKee, Karen; Bosire, Jared O.; Cannicci, Stefano; Diele, Karen; Fromard, Francois; Koedam, Nico; Marchand, Cyril; Mendelssohn, Irving; Mukherjee, Nibedita; Record, Sydne

2014-01-01

Knowledge of thresholds, spatio-temporal scaling and variability due to geographic, biogeographic and socio-economic settings will improve the management of mangrove ecosystem services. Many drivers respond to global trends in climate change and local changes such as urbanization. While mangroves have traditionally been managed for subsistence, future governance models must involve partnerships between local custodians of mangroves and offsite beneficiaries of the services.

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

PubMed Central

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

2014-01-01

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

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

PubMed

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

2014-01-01

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

Recent changes in aquatic biota in subarctic Fennoscandia - the role of global and local environmental variables

NASA Astrophysics Data System (ADS)

Weckström, Jan; Leppänen, Jaakko; Sorvari, Sanna; Kaukolehto, Marjut; Weckström, Kaarina; Korhola, Atte

2013-04-01

The Arctic, representing a fifth of the earth's surface, is highly sensitive to the predicted future warming and it has indeed been warming up faster than most other regions. This makes the region critically important and highlights the need to investigate the earliest signals of global warming and its impacts on the arctic and subarctic aquatic ecosystems and their biota. It has been demonstrated that many Arctic freshwater ecosystems have already experienced dramatic and unpreceded regime shifts during the last ca. 150 years, primarily driven by climate warming. However, despite the indisputable impact of climate-related variables on freshwater ecosystems other, especially local-scale catchment related variables (e.g. geology, vegetation, human activities) may override the climate signal and become the primary factor in shaping the structure of aquatic ecosystems. Although many studies have contributed to an improved understanding of limnological and hydrobiological features of Artic and subarctic lakes, much information is still needed especially on the interaction between the biotic and abiotic components, i.e. on factors controlling the food web dynamics in these sensitive aquatic ecosystems. This is of special importance as these lakes are of great value in water storage, flood prevention, and maintenance of biodiversity, in addition to which they are vital resources for settlement patterns, food production, recreation, and tourism. In this study we compare the pre-industrial sediment assemblages of primary producers (diatoms and Pediastrum) and primary consumers (cladoceran and chironomids) with their modern assemblages (a top-bottom approach) from 50 subarctic Fennoscandian lakes. We will evaluate the recent regional pattern of changes in aquatic assemblages, and assess how coherent the lakes' responses are across the subarctic area. Moreover, the impact of global (e.g. climate, precipitation) and local (e.g. lake and its catchment characteristics) scale environmental changes on the aquatic biota will be compared and discussed.

Projected climate and agronomic implications for corn production in the Northeastern United States.

PubMed

Prasad, Rishi; Gunn, Stephan Kpoti; Rotz, Clarence Alan; Karsten, Heather; Roth, Greg; Buda, Anthony; Stoner, Anne M K

2018-01-01

Corn has been a pillar of American agriculture for decades and continues to receive much attention from the scientific community for its potential to meet the food, feed and fuel needs of a growing human population in a changing climate. By midcentury, global temperature increase is expected to exceed 2°C where local effects on heat, cold and precipitation extremes will vary. The Northeast United States is a major dairy producer, corn consumer, and is cited as the fastest warming region in the contiguous U.S. It is important to understand how key agronomic climate variables affect corn growth and development so that adaptation strategies can be tailored to local climate changes. We analyzed potential local effects of climate change on corn growth and development at three major dairy locations in the Northeast (Syracuse, New York; State College, Pennsylvania and Landisville, Pennsylvania) using downscaled projected climate data (2000-2100) from nine Global Climate Models under two emission pathways (Representative Concentration Pathways (RCP) 4.5 and 8.5). Our analysis indicates that corn near the end of the 21st century will experience fewer spring and fall freezes, faster rate of growing degree day accumulation with a reduction in time required to reach maturity, greater frequencies of daily high temperature ≥35°C during key growth stages such as silking-anthesis and greater water deficit during reproductive (R1-R6) stages. These agronomic anomalies differ between the three locations, illustrating varying impacts of climate change in the more northern regions vs. the southern regions of the Northeast. Management strategies such as shifting the planting dates based on last spring freeze and irrigation during the greatest water deficit stages (R1-R6) will partially offset the projected increase in heat and drought stress. Future research should focus on understanding the effects of global warming at local levels and determining adaptation strategies that meet local needs.

Range expansion through fragmented landscapes under a variable climate

PubMed Central

Bennie, Jonathan; Hodgson, Jenny A; Lawson, Callum R; Holloway, Crispin TR; Roy, David B; Brereton, Tom; Thomas, Chris D; Wilson, Robert J

2013-01-01

Ecological responses to climate change may depend on complex patterns of variability in weather and local microclimate that overlay global increases in mean temperature. Here, we show that high-resolution temporal and spatial variability in temperature drives the dynamics of range expansion for an exemplar species, the butterfly Hesperia comma. Using fine-resolution (5 m) models of vegetation surface microclimate, we estimate the thermal suitability of 906 habitat patches at the species' range margin for 27 years. Population and metapopulation models that incorporate this dynamic microclimate surface improve predictions of observed annual changes to population density and patch occupancy dynamics during the species' range expansion from 1982 to 2009. Our findings reveal how fine-scale, short-term environmental variability drives rates and patterns of range expansion through spatially localised, intermittent episodes of expansion and contraction. Incorporating dynamic microclimates can thus improve models of species range shifts at spatial and temporal scales relevant to conservation interventions. PMID:23701124

Cholera and shigellosis in Bangladesh: similarities and differences in population dynamics under climate forcing

NASA Astrophysics Data System (ADS)

Pascual, M.; Cash, B.; Reiner, R.; King, A.; Emch, M.; Yunus, M.; Faruque, A. S.

2012-12-01

The influence of climate variability on the population dynamics of infectious diseases is considered a large scale, regional, phenomenon, and as such, has been previously addressed for cholera with temporal models that do not incorporate fine-scale spatial structure. In our previous work, evidence for a role of ENSO (El Niño Southern Oscillation) on cholera in Bangladesh was elucidated, and shown to influence the regional climate through precipitation. With a probabilistic spatial model for cholera dynamics in the megacity of Dhaka, we found that the action of climate variability (ENSO and flooding) is localized: there is a climate-sensitive urban core that acts to propagate risk to the rest of the city. Here, we consider long-term surveillance data for shigellosis, another diarrheal disease that coexists with cholera in Bangladesh. We compare the patterns of association with climate variables for these two diseases in a rural setting, as well as the spatial structure in their spatio-temporal dynamics in an urban one. Evidence for similar patterns is presented, and discussed in the context of the differences in the routes of transmission of the two diseases and the proposed role of an environmental reservoir in cholera. The similarities provide evidence for a more general influence of hydrology and of socio-economic factors underlying human susceptibility and sanitary conditions.

Life history trade-offs, the intensity of competition, and coexistence in novel and evolving communities under climate change.

PubMed

Lancaster, Lesley T; Morrison, Gavin; Fitt, Robert N

2017-01-19

The consequences of climate change for local biodiversity are little understood in process or mechanism, but these changes are likely to reflect both changing regional species pools and changing competitive interactions. Previous empirical work largely supports the idea that competition will intensify under climate change, promoting competitive exclusions and local extinctions, while theory and conceptual work indicate that relaxed competition may in fact buffer communities from biodiversity losses that are typically witnessed at broader spatial scales. In this review, we apply life history theory to understand the conditions under which these alternative scenarios may play out in the context of a range-shifting biota undergoing rapid evolutionary and environmental change, and at both leading-edge and trailing-edge communities. We conclude that, in general, warming temperatures are likely to reduce life history variation among competitors, intensifying competition in both established and novel communities. However, longer growing seasons, severe environmental stress and increased climatic variability associated with climate change may buffer these communities against intensified competition. The role of life history plasticity and evolution has been previously underappreciated in community ecology, but may hold the key to understanding changing species interactions and local biodiversity under changing climates.This article is part of the themed issue 'Human influences on evolution, and the ecological and societal consequences'. © 2016 The Author(s).

Life history trade-offs, the intensity of competition, and coexistence in novel and evolving communities under climate change

PubMed Central

Morrison, Gavin; Fitt, Robert N.

2017-01-01

The consequences of climate change for local biodiversity are little understood in process or mechanism, but these changes are likely to reflect both changing regional species pools and changing competitive interactions. Previous empirical work largely supports the idea that competition will intensify under climate change, promoting competitive exclusions and local extinctions, while theory and conceptual work indicate that relaxed competition may in fact buffer communities from biodiversity losses that are typically witnessed at broader spatial scales. In this review, we apply life history theory to understand the conditions under which these alternative scenarios may play out in the context of a range-shifting biota undergoing rapid evolutionary and environmental change, and at both leading-edge and trailing-edge communities. We conclude that, in general, warming temperatures are likely to reduce life history variation among competitors, intensifying competition in both established and novel communities. However, longer growing seasons, severe environmental stress and increased climatic variability associated with climate change may buffer these communities against intensified competition. The role of life history plasticity and evolution has been previously underappreciated in community ecology, but may hold the key to understanding changing species interactions and local biodiversity under changing climates. This article is part of the themed issue ‘Human influences on evolution, and the ecological and societal consequences’. PMID:27920390

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.

Interpretation of Recent Temperature Trends in California

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

Duffy, P B; Bonfils, C; Lobell, D

2007-09-21

Regional-scale climate change and associated societal impacts result from large-scale (e.g. well-mixed greenhouse gases) and more local (e.g. land-use change) 'forcing' (perturbing) agents. It is essential to understand these forcings and climate responses to them, in order to predict future climate and societal impacts. California is a fine example of the complex effects of multiple climate forcings. The State's natural climate is diverse, highly variable, and strongly influenced by ENSO. Humans are perturbing this complex system through urbanization, irrigation, and emission of multiple types of aerosols and greenhouse gases. Despite better-than-average observational coverage, we are only beginning to understand themore » manifestations of these forcings in California's temperature record.« less

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Decadal-scale climate drivers for glacial dynamics in Glacier National Park, Montana, USA

USGS Publications Warehouse

Pederson, G.T.; Fagre, D.B.; Gray, S.T.; Graumlich, L.J.

2004-01-01

Little Ice Age (14th-19th centuries A.D.) glacial maxima and 20th century retreat have been well documented in Glacier National Park, Montana, USA. However, the influence of regional and Pacific Basin driven climate variability on these events is poorly understood. We use tree-ring reconstructions of North Pacific surface temperature anomalies and summer drought as proxies for winter glacial accumulation and summer ablation, respectively, over the past three centuries. These records show that the 1850's glacial maximum was likely produced by ???70 yrs of cool/wet summers coupled with high snowpack. Post 1850, glacial retreat coincides with an extended period (>50 yr) of summer drought and low snowpack culminating in the exceptional events of 1917 to 1941 when retreat rates for some glaciers exceeded 100 m/yr. This research highlights potential local and ocean-based drivers of glacial dynamics, and difficulties in separating the effects of global climate change from regional expressions of decadal-scale climate variability. Copyright 2004 by the American Geophysical Union.

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.

A global database with parallel measurements to study non-climatic changes

NASA Astrophysics Data System (ADS)

Venema, Victor; Auchman, Renate; Aguilar, Enric

2017-04-01

In this work we introduce the rationale behind the ongoing compilation of a parallel measurements database, in the framework of the International Surface Temperatures Initiative (ISTI) and with the support of the World Meteorological Organization. We intend this database to become instrumental for a better understanding of inhomogeneities affecting the evaluation of long-term changes in daily climate data. Long instrumental climate records are usually affected by non-climatic changes, due to, e.g., (i) station re- locations, (ii) instrument height changes, (iii) instrumentation changes, (iv) observing environment changes, (v) different sampling intervals or data collection procedures, among others. These so-called inhomogeneities distort the climate signal and can hamper the assessment of long-term trends and variability of climate. Thus to study climatic changes we need to accurately distinguish non-climatic and climatic signals. The most direct way to study the influence of non-climatic changes on the distribution and to understand the reasons for these biases is the analysis of parallel measurements representing the old and new situation (in terms of e.g. instruments, location, different radiation shields, etc.). According to the limited number of available studies and our understanding of the causes of inhomogeneity, we expect that they will have a strong impact on the tails of the distribution of air temperatures and most likely of other climate elements. Our abilities to statistically homogenize daily data will be increased by systematically studying different causes of inhomogeneity replicated through parallel measurements. Current studies of non-climatic changes using parallel data are limited to local and regional case studies. However, the effect of specific transitions depends on the local climate and the most interesting climatic questions are about the systematic large-scale biases produced by transitions that occurred in many regions. Important potentially biasing transitions are the adoption of Stevenson screens, relocations (to airports) efforts to reduce undercatchment of precipitation or the move to automatic weather stations. Thus a large global parallel dataset is highly desirable as it allows for the study of systematic biases in the global record. We are interested in data from all climate variables at all time scales; from annual to sub-daily. High-resolution data is important for understanding the physical causes for the differences between the parallel measurements. For the same reason, we are also interested in other climate variables measured at the same station. For example, in case of parallel air temperature measurements, the influencing factors are expected to be global radiation, wind, humidity and cloud cover; in case of parallel precipitation measurements, wind and wet-bulb temperature are potentially important.

Emergence of the significant local warming of Korea in CMIP5 projections

NASA Astrophysics Data System (ADS)

Boo, Kyung-On; Shim, Sungbo; Kim, Jee-Eun

2016-04-01

According to IPCC AR5, anthropogenic influence on warming is obvious in local scales, especially in some tropical regions. Detection of significant local warming is important for adaptation to climate change of society and ecosystem. Recently much attention has focused on the time of emergence (ToE) for the signal of anthropogenic climate change against the natural climate variability. Motivated from the previous studies, this study analyzes ToE of regional surface air temperature over Korea. Simulations of CMIP5 15 models are used for RCP 2.6, 4.5 and 8.5. For each year, JJA and DJF temperature anomalies are calculated for the time period 1900-1929. For noise of interannual variability, natural-only historical simulations of CMIP5 12 models are used and the standard deviation of the time series is obtained. For signal of warming, we examine the year when the signal above 2 standard deviations is detected in 80% of the models using 30-year smoothed time series. According to our results, interannual variability is larger in land than ocean. Seasonally, it is larger in winter than in summer. Accordingly, ToE of summertime temperature is earlier than that in winter and is expected to appear in 2030s from three RCPs. The seasonal difference is consistent with previous studies. Wintertime ToE appears in 2040s for RCP85 and 2060s for RCP4.5. The different emergence time between RCP8.5 and RCP4.5 reflects the influence of mitigation. In a similar way, daily maximum and minimum temperatures are analyzed. ToE of Tmin appears earlier than that of Tmax and difference is small. Acknowledgements. This study is supported by the National Institute of Meteorological Sciences, Korea Meteorological Administration (NIMR-2012-B-2).

Assessment of Variable Planting Date as an Agricultural Adaptation to Climate Variability in Sri Lanka

NASA Astrophysics Data System (ADS)

Rivera, A.; Gunda, T.; Hornberger, G. M.

2016-12-01

Agriculture accounts for approximately 70% of global freshwater withdrawals. Changes in precipitation patterns due to climate change as well as increasing demands for water necessitate an increased understanding of the water-­food intersection, notably at a local scale to inform farmer adaptations to improve water productivity, i.e., to get more food with less water. Local assessments of water-food security are particularly important for nations with self-sufficiency policies, which prioritize in-country production of certain resources. An ideal case study is the small island nation of Sri Lanka, which has a self-sufficiency policy for its staple food of rice. Because rice is a water-intensive crop, assessment of irrigation water requirements (IWRs) and the associated changes over time is especially important. Previous studies on IWRs of rice in Sri Lanka have failed to consider the Yala (dry) season, when water is scarcest.The goal of this study is to characterize the role that a human decision, setting the planting date, can play in buffering declines in rice yield against changes in precipitation patterns. Using four meteorological stations in the main rice-growing zones in Sri Lanka, we explore (1) general changes in IWRs over time during the Yala season and (2) the impact of the rice planting date. We use both historical data from meteorological stations as well as future projections from regional climate models. Our results indicate that gains can be achieved using a variable planting date relative to a fixed date, in accordance with a similar conclusion for the Maha (wet) season. This local scale assessment of Sri Lanka IWRs will contribute to the growing global literature on the impacts of water scarcity on agriculture and the role that one adaptation measure can play in mitigating deleterious impacts.

Using Impact-Relevant Sensitivities to Efficiently Evaluate and Select Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Vano, J. A.; Kim, J. B.; Rupp, D. E.; Mote, P.

2014-12-01

We outline an efficient approach to help researchers and natural resource managers more effectively use global climate model information in their long-term planning. The approach provides an estimate of the magnitude of change of a particular impact (e.g., summertime streamflow) from a large ensemble of climate change projections prior to detailed analysis. These estimates provide both qualitative information as an end unto itself (e.g., the distribution of future changes between emissions scenarios for the specific impact) and a judicious, defensible evaluation structure that can be used to qualitatively select a sub-set of climate models for further analysis. More specifically, the evaluation identifies global climate model scenarios that both (1) span the range of possible futures for the variable/s most important to the impact under investigation, and (2) come from global climate models that adequately simulate historical climate, providing plausible results for the future climate in the region of interest. To identify how an ecosystem process responds to projected future changes, we methodically sample, using a simple sensitivity analysis, how an impact variable (e.g., streamflow magnitude, vegetation carbon) responds locally to projected regional temperature and precipitation changes. We demonstrate our technique over the Pacific Northwest, focusing on two types of impacts each in three distinct geographic settings: (a) changes in streamflow magnitudes in critical seasons for water management in the Willamette, Yakima, and Upper Columbia River basins; and (b) changes in annual vegetation carbon in the Oregon and Washington Coast Ranges, Western Cascades, and Columbia Basin ecoregions.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

The potential impacts of climate variability and change on health impacts of extreme weather events in the United States.

PubMed

Greenough, G; McGeehin, M; Bernard, S M; Trtanj, J; Riad, J; Engelberg, D

2001-05-01

Extreme weather events such as precipitation extremes and severe storms cause hundreds of deaths and injuries annually in the United States. Climate change may alter the frequency, timing, intensity, and duration of these events. Increases in heavy precipitation have occurred over the past century. Future climate scenarios show likely increases in the frequency of extreme precipitation events, including precipitation during hurricanes, raising the risk of floods. Frequencies of tornadoes and hurricanes cannot reliably be projected. Injury and death are the direct health impacts most often associated with natural disasters. Secondary effects, mediated by changes in ecologic systems and public health infrastructure, also occur. The health impacts of extreme weather events hinge on the vulnerabilities and recovery capacities of the natural environment and the local population. Relevant variables include building codes, warning systems, disaster policies, evacuation plans, and relief efforts. There are many federal, state, and local government agencies and nongovernmental organizations involved in planning for and responding to natural disasters in the United States. Future research on health impacts of extreme weather events should focus on improving climate models to project any trends in regional extreme events and as a result improve public health preparedness and mitigation. Epidemiologic studies of health effects beyond the direct impacts of disaster will provide a more accurate measure of the full health impacts and will assist in planning and resource allocation.

Patterns and perceptions of climate change in a biodiversity conservation hotspot.

PubMed

Hartter, Joel; Stampone, Mary D; Ryan, Sadie J; Kirner, Karen; Chapman, Colin A; Goldman, Abraham

2012-01-01

Quantifying local people's perceptions to climate change, and their assessments of which changes matter, is fundamental to addressing the dual challenge of land conservation and poverty alleviation in densely populated tropical regions To develop appropriate policies and responses, it will be important not only to anticipate the nature of expected changes, but also how they are perceived, interpreted and adapted to by local residents. The Albertine Rift region in East Africa is one of the world's most threatened biodiversity hotspots due to dense smallholder agriculture, high levels of land and resource pressures, and habitat loss and conversion. Results of three separate household surveys conducted in the vicinity of Kibale National Park during the late 2000s indicate that farmers are concerned with variable precipitation. Many survey respondents reported that conditions are drier and rainfall timing is becoming less predictable. Analysis of daily rainfall data for the climate normal period 1981 to 2010 indicates that total rainfall both within and across seasons has not changed significantly, although the timing and transitions of seasons has been highly variable. Results of rainfall data analysis also indicate significant changes in the intra-seasonal rainfall distribution, including longer dry periods within rainy seasons, which may contribute to the perceived decrease in rainfall and can compromise food security. Our results highlight the need for fine-scale climate information to assist agro-ecological communities in developing effective adaptive management.

Patterns and Perceptions of Climate Change in a Biodiversity Conservation Hotspot

PubMed Central

Hartter, Joel; Stampone, Mary D.; Ryan, Sadie J.; Kirner, Karen; Chapman, Colin A.; Goldman, Abraham

2012-01-01

Quantifying local people's perceptions to climate change, and their assessments of which changes matter, is fundamental to addressing the dual challenge of land conservation and poverty alleviation in densely populated tropical regions To develop appropriate policies and responses, it will be important not only to anticipate the nature of expected changes, but also how they are perceived, interpreted and adapted to by local residents. The Albertine Rift region in East Africa is one of the world's most threatened biodiversity hotspots due to dense smallholder agriculture, high levels of land and resource pressures, and habitat loss and conversion. Results of three separate household surveys conducted in the vicinity of Kibale National Park during the late 2000s indicate that farmers are concerned with variable precipitation. Many survey respondents reported that conditions are drier and rainfall timing is becoming less predictable. Analysis of daily rainfall data for the climate normal period 1981 to 2010 indicates that total rainfall both within and across seasons has not changed significantly, although the timing and transitions of seasons has been highly variable. Results of rainfall data analysis also indicate significant changes in the intra-seasonal rainfall distribution, including longer dry periods within rainy seasons, which may contribute to the perceived decrease in rainfall and can compromise food security. Our results highlight the need for fine-scale climate information to assist agro-ecological communities in developing effective adaptive management. PMID:22384244

A blueprint for using climate change predictions in an eco-hydrological study

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.

2009-12-01

There is a growing interest to extend climate change predictions to smaller, catchment-size scales and identify their implications on hydrological and ecological processes. Small scale processes are, in fact, expected to mediate climate changes, producing local effects and feedbacks that can interact with the principal consequences of the change. This is particularly applicable, when a complex interaction, such as the inter-relationship between the hydrological cycle and vegetation dynamics, is considered. This study presents a blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the catchment scale. Climate conditions, present or future, are imposed through input hydrometeorological variables for hydrological and eco-hydrological models. These variables are simulated with an hourly weather generator as an outcome of a stochastic downscaling technique. The generator is parameterized to reproduce the climate of southwestern Arizona for present (1961-2000) and future (2081-2100) conditions. The methodology provides the capability to generate ensemble realizations for the future that take into account the heterogeneous nature of climate predictions from different models. The generated time series of meteorological variables for the two scenarios corresponding to the current and mean expected future serve as input to a coupled hydrological and vegetation dynamics model, “Tethys-Chloris”. The hydrological model reproduces essential components of the land-surface hydrological cycle, solving the mass and energy budget equations. The vegetation model parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, and tissue turnover. The results for the two mean scenarios are compared and discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity The need to account for uncertainties in projections of future climate is discussed and a methodology for propagating these uncertainties into the probability density functions of changes in eco-hydrological variables is presented.

Landscape genomics of Sphaeralcea ambigua in the Mojave Desert: a multivariate, spatially-explicit approach to guide ecological restoration

USGS Publications Warehouse

Shryock, Daniel F.; Havrilla, Caroline A.; DeFalco, Lesley; Esque, Todd C.; Custer, Nathan; Wood, Troy E.

2015-01-01

Local adaptation influences plant species’ responses to climate change and their performance in ecological restoration. Fine-scale physiological or phenological adaptations that direct demographic processes may drive intraspecific variability when baseline environmental conditions change. Landscape genomics characterize adaptive differentiation by identifying environmental drivers of adaptive genetic variability and mapping the associated landscape patterns. We applied such an approach to Sphaeralcea ambigua, an important restoration plant in the arid southwestern United States, by analyzing variation at 153 amplified fragment length polymorphism loci in the context of environmental gradients separating 47 Mojave Desert populations. We identified 37 potentially adaptive loci through a combination of genome scan approaches. We then used a generalized dissimilarity model (GDM) to relate variability in potentially adaptive loci with spatial gradients in temperature, precipitation, and topography. We identified non-linear thresholds in loci frequencies driven by summer maximum temperature and water stress, along with continuous variation corresponding to temperature seasonality. Two GDM-based approaches for mapping predicted patterns of local adaptation are compared. Additionally, we assess uncertainty in spatial interpolations through a novel spatial bootstrapping approach. Our study presents robust, accessible methods for deriving spatially-explicit models of adaptive genetic variability in non-model species that will inform climate change modelling and ecological restoration.

A Framework for Using Rural Markets to Analyze Local Food Shortage Resilience and Mitigation Potential in sub-Saharan Africa based on Evidence from Zambia

NASA Astrophysics Data System (ADS)

Montgomery, M. J.; Baylis, K.; Evans, T. P.

2016-12-01

Climate change is predicted to have negative impacts on agriculture and food security in many parts of sub-Saharan Africa. Regional and temporal climate variability will disburse these effects, creating opportunities to mitigate food shortages through well-studied international, regional, and national food flows and associated food prices. However, most food products consumed and traded by rural smallhold farmers rely on local market exchanges that take place outside the scope of prevalent regional and national market analysis. There is little empirical evidence on these rural markets outside of their potential for smallholder agribusiness. However, they offer an unopened window into local food supply and the nuances of food movements in rural areas. Our research explores how to analyze the cost and availability of food products in rural markets and their connection with each other, as well as with nearby households' food security. This new approach of using food markets as a unit of analysis necessitates a new framework that groups markets based on a hierarchy of variables relevant to their role as food movers and suppliers. In our research, we collected price and source data for 22 commodities bought and sold within 52 rural markets in 12 districts spatially distributed throughout Zambia. We continue to collect data via phone interviews with 206 traders and market managers within these markets each month. We used this data to develop a typology of stationary rural food markets based on their size in terms of traders and buyers, the diversity of commodities available year-round and seasonally, their price transmission with other markets, and their trading scheme and governance. The result is a dynamic framework with varying weights on each variable that classifies which characteristic of markets under which conditions increase their potential for local food shortage resilience and mitigation. We also allocate for commodity-specific scenarios to allow for modeling under climate conditions conducive to different crops.

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

Forecasting European Wildfires Today and in the Future

NASA Astrophysics Data System (ADS)

Navarro Abellan, Maria; Porras Alegre, Ignasi; María Sole, Josep; Gálvez, Pedro; Bielski, Conrad; Nurmi, Pertti

2017-04-01

Society as a whole is increasingly exposed and vulnerable to natural disasters due to extreme weather events exacerbated by climate change. The increased frequency of wildfires is not only a result of a changing climate, but wildfires themselves also produce a significant amount of greenhouse gases that, in-turn, further contribute to global warming. I-REACT (Improving Resilience to Emergencies through Advanced Cyber Technologies) is an innovation project funded by the European Commission , which aims to use social media, smartphones and wearables to improve natural disaster management by integrating existing services, both local and European, into a platform that supports the entire emergency management cycle. In order to assess the impact of climate change on wildfire hazards, METEOSIM designed two different System Processes (SP) that will be integrated into the I-REACT service that can provide information on a variety of time scales. SP1 - Climate Change Impact The climate change impact on climate variables related to fires is calculated by building an ensemble based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) and CORDEX data. A validation and an Empirical-Statistical Downscaling (ESD) calibration are done to assess the changes in the past of the climatic variables related to wildfires (temperature, precipitation, wind, relative humidity and Fire Weather Index). Calculations in the trend and the frequency of extreme events of those variables are done for three time scales: near-term (2011-2040), mid-term (2041-2070) and long term (2071-2100). SP2 - Operational daily forecast of the Canadian Forest Fire Weather Index (FWI) Using ensemble data from the ECMWF and from the GLAMEPS (multi-model ensemble) models, both supplied by the Finnish Meteorological Institute (FMI), the Fire Weather Index (FWI) and its index components are produced for each ensemble member within a wide forecast time range, from a few hours up to 10 days resulting in a probabilistic output of the FWI for different regions in Europe. This work will improve the currently available information to various wildfire information users such as fire departments, the civil protection, local authorities, etc., where accurate and reliable information in extreme weather situations are vital for improving planning and risk management.

Long-Term Climate Forcing in Loggerhead Sea Turtle Nesting

PubMed Central

Van Houtan, Kyle S.; Halley, John M.

2011-01-01

The long-term variability of marine turtle populations remains poorly understood, limiting science and management. Here we use basin-scale climate indices and regional surface temperatures to estimate loggerhead sea turtle (Caretta caretta) nesting at a variety of spatial and temporal scales. Borrowing from fisheries research, our models investigate how oceanographic processes influence juvenile recruitment and regulate population dynamics. This novel approach finds local populations in the North Pacific and Northwest Atlantic are regionally synchronized and strongly correlated to ocean conditions—such that climate models alone explain up to 88% of the observed changes over the past several decades. In addition to its performance, climate-based modeling also provides mechanistic forecasts of historical and future population changes. Hindcasts in both regions indicate climatic conditions may have been a factor in recent declines, but future forecasts are mixed. Available climatic data suggests the Pacific population will be significantly reduced by 2040, but indicates the Atlantic population may increase substantially. These results do not exonerate anthropogenic impacts, but highlight the significance of bottom-up oceanographic processes to marine organisms. Future studies should consider environmental baselines in assessments of marine turtle population variability and persistence. PMID:21589639

Long-term climate forcing in loggerhead sea turtle nesting.

PubMed

Van Houtan, Kyle S; Halley, John M

2011-04-27

The long-term variability of marine turtle populations remains poorly understood, limiting science and management. Here we use basin-scale climate indices and regional surface temperatures to estimate loggerhead sea turtle (Caretta caretta) nesting at a variety of spatial and temporal scales. Borrowing from fisheries research, our models investigate how oceanographic processes influence juvenile recruitment and regulate population dynamics. This novel approach finds local populations in the North Pacific and Northwest Atlantic are regionally synchronized and strongly correlated to ocean conditions--such that climate models alone explain up to 88% of the observed changes over the past several decades. In addition to its performance, climate-based modeling also provides mechanistic forecasts of historical and future population changes. Hindcasts in both regions indicate climatic conditions may have been a factor in recent declines, but future forecasts are mixed. Available climatic data suggests the Pacific population will be significantly reduced by 2040, but indicates the Atlantic population may increase substantially. These results do not exonerate anthropogenic impacts, but highlight the significance of bottom-up oceanographic processes to marine organisms. Future studies should consider environmental baselines in assessments of marine turtle population variability and persistence.

Impact of Climate Variability on Maize Production in Pakistan using Remote Sensing and Machine Learning

NASA Astrophysics Data System (ADS)

Richetti, J.; Ahmad, I.; Aristizabal, F.; Judge, J.

2017-12-01

Determining maize agricultural production under climate variability is valuable to policy makers in Pakistan since maize is the third most produced crop by area after wheat and rice. This study aims to predict the maize production under climate variability. Two-hundred ground truth points of both maize and non-maize land covers were collected from the Faisalabad district during the growing seasons of 2015 and 2016. Landsat-8 images taken in second week of May which correspond spatially and temporally to the local, peak growing season for maize were gathered. For classifying the region training data was constructed for a variety of machine learning algorithms by sampling the second, third, and fourth bands of the Landsat-8 imagery at these reference locations. Cross validation was used for parameter tuning as well as estimating the generalized performances. All the classifiers resulted in overall accuracies of greater than 90% for both years and a support vector machine with a radial basis kernel recorded the maximum accuracy of 97%. The tuned models were used to determine the spatial distribution of maize fields for both growing seasons in the Faisalabad district using parallel processing to improve computation time. The overall classified maize growing area represented 12% difference than that reported by the Crop Reporting Service (CRS) of Punjab Pakistan for both 2015 and 2016. For the agricultural production normalized difference vegetation index from Landsat-8 and climate indicators from ground stations will be used as inputs in a variety of machine learning regression algorithms. The expected results will be compared to actual yield from 64 commercial farms. To verify the impact of climate variability in the maize agricultural production historical climate data from previous 30 years will be used in the developed model to asses the impact of climate variability on the maize production.

Large-scale Meteorological Patterns Associated with Extreme Precipitation Events over Portland, OR

NASA Astrophysics Data System (ADS)

Aragon, C.; Loikith, P. C.; Lintner, B. R.; Pike, M.

2017-12-01

Extreme precipitation events can have profound impacts on human life and infrastructure, with broad implications across a range of stakeholders. Changes to extreme precipitation events are a projected outcome of climate change that warrants further study, especially at regional- to local-scales. While global climate models are generally capable of simulating mean climate at global-to-regional scales with reasonable skill, resiliency and adaptation decisions are made at local-scales where most state-of-the-art climate models are limited by coarse resolution. Characterization of large-scale meteorological patterns associated with extreme precipitation events at local-scales can provide climatic information without this scale limitation, thus facilitating stakeholder decision-making. This research will use synoptic climatology as a tool by which to characterize the key large-scale meteorological patterns associated with extreme precipitation events in the Portland, Oregon metro region. Composite analysis of meteorological patterns associated with extreme precipitation days, and associated watershed-specific flooding, is employed to enhance understanding of the climatic drivers behind such events. The self-organizing maps approach is then used to characterize the within-composite variability of the large-scale meteorological patterns associated with extreme precipitation events, allowing us to better understand the different types of meteorological conditions that lead to high-impact precipitation events and associated hydrologic impacts. A more comprehensive understanding of the meteorological drivers of extremes will aid in evaluation of the ability of climate models to capture key patterns associated with extreme precipitation over Portland and to better interpret projections of future climate at impact-relevant scales.

The Impact of Changing Snowmelt Timing on Non-Irrigated Crop Yield in Idaho

NASA Astrophysics Data System (ADS)

Murray, E. M.; Cobourn, K.; Flores, A. N.; Pierce, J. L.; Kunkel, M. L.

2013-12-01

The impacts of climate change on water resources have implications for both agricultural production and grower welfare. Many mountainous regions in the western U.S. rely on snowmelt as the dominant surface water source, and in Idaho, reconstructions of spring snowmelt timing have demonstrated a trend toward earlier, more variable snowmelt dates within the past 20 years. This earlier date and increased variability in snowmelt timing have serious implications for agriculture, but there is considerable uncertainty about how agricultural impacts vary by region, crop-type, and practices like irrigation vs. dryland farming. Establishing the relationship between snowmelt timing and agricultural yield is important for understanding how changes in large-scale climatic indices (like snowmelt date) may be associated with changes in agricultural yield. This is particularly important where local practitioner behavior is influenced by historically observed relationships between these climate indices and yield. In addition, a better understanding of the influence of changes in snowmelt on non-irrigated crop yield may be extrapolated to better understand how climate change may alter biomass production in non-managed ecosystems. To investigate the impact of snowmelt date on non-irrigated crop yield, we developed a multiple linear regression model to predict historical wheat and barley yield in several Idaho counties as a function of snowmelt date, climate variables (precipitation and growing degree-days), and spatial differences between counties. The relationship between snowmelt timing and non-irrigated crop yield at the county level is strong in many of the models, but differs in magnitude and direction for the two different crops. Results show interesting spatial patterns of variability in the correlation between snowmelt timing and crop yield. In four southern counties that border the Snake River Plain and one county bordering Oregon, non-irrigated wheat and/or barley yield are significantly lower in years with early snowmelt timing, on average (P < 0.10). In contrast, in northern Idaho, barley yield is significantly higher in years with early snowmelt timing. Overall, this statistical modeling exercise indicates that the trend toward earlier snowmelt date may positively impact non-irrigated crop yield in some regions of Idaho, while negatively impacting yield in other areas. Additional research is necessary to identify spatial controls on the variable relationship between snowmelt timing and yield. Regional variability in the response of crops to changes in snowmelt timing may indicate that external factors (e.g. higher amounts of summer rain in northern vs. southern Idaho) may play an important role in crop yield. This study indicates that targeted regional analysis is necessary to determine the influence of climate change on agriculture, as local variability can cause the same forcing to produce opposite results.

Adaptation of water resource systems to an uncertain future

NASA Astrophysics Data System (ADS)

Walsh, Claire L.; Blenkinsop, Stephen; Fowler, Hayley J.; Burton, Aidan; Dawson, Richard J.; Glenis, Vassilis; Manning, Lucy J.; Jahanshahi, Golnaz; Kilsby, Chris G.

2016-05-01

Globally, water resources management faces significant challenges from changing climate and growing populations. At local scales, the information provided by climate models is insufficient to support the water sector in making future adaptation decisions. Furthermore, projections of change in local water resources are wrought with uncertainties surrounding natural variability, future greenhouse gas emissions, model structure, population growth, and water consumption habits. To analyse the magnitude of these uncertainties, and their implications for local-scale water resource planning, we present a top-down approach for testing climate change adaptation options using probabilistic climate scenarios and demand projections. An integrated modelling framework is developed which implements a new, gridded spatial weather generator, coupled with a rainfall-runoff model and water resource management simulation model. We use this to provide projections of the number of days and associated uncertainty that will require implementation of demand saving measures such as hose pipe bans and drought orders. Results, which are demonstrated for the Thames Basin, UK, indicate existing water supplies are sensitive to a changing climate and an increasing population, and that the frequency of severe demand saving measures are projected to increase. Considering both climate projections and population growth, the median number of drought order occurrences may increase 5-fold by the 2050s. The effectiveness of a range of demand management and supply options have been tested and shown to provide significant benefits in terms of reducing the number of demand saving days. A decrease in per capita demand of 3.75 % reduces the median frequency of drought order measures by 50 % by the 2020s. We found that increased supply arising from various adaptation options may compensate for increasingly variable flows; however, without reductions in overall demand for water resources such options will be insufficient on their own to adapt to uncertainties in the projected changes in climate and population. For example, a 30 % reduction in overall demand by 2050 has a greater impact on reducing the frequency of drought orders than any of the individual or combinations of supply options; hence, a portfolio of measures is required.

An engineering economic assessment of whole-house residential wood heating in New York

EPA Science Inventory

Wood devices are being selected increasingly for residential space heating by households in New York State. Motivations for their use include energy independence, mitigating climate change, stimulating local economic development, and reducing exposure to high and variable fuel c...

The Impact of Low-Level Cloud Feedback on Persistent Changes in Atmospheric Circulation in the Pacific

NASA Astrophysics Data System (ADS)

Burgman, R.; Kirtman, B. P.; Clement, A. C.; Vazquez, H.

2017-12-01

Recent studies suggest that low clouds in the Pacific play an important role in the observed decadal climate variability and future climate change. In this study, we implement a novel modeling experiment designed to isolate how interactions between local and remote feedbacks associated with low cloud, SSTs, and the largescale circulation play a significant role in the observed persistence of tropical Pacific SST and associated North American drought. The modeling approach involves the incorporation of observed patterns of satellite-derived shortwave cloud radiative effect (SWCRE) into the coupled model framework and is ideally suited for examining the role of local and large-scale coupled feedbacks and ocean heat transport in Pacific decadal variability. We show that changes in SWCRE forcing in eastern subtropical Pacific alone reproduces much of the observed changes in SST and atmospheric circulation over the past 16 years, including the observed changes in precipitation over much of the Western Hemisphere.

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

Precipitation Indices as a Tool for Climate-Resilient Development in the Peruvian Andes

NASA Astrophysics Data System (ADS)

Chisolm, R. E.; McKinney, D. C.

2016-12-01

The local people living in the mountains of the Ancash Department in Peru have noticed changes in their water supply as climate change has altered precipitation patterns. They are seeking adaptation solutions to help guarantee the reliability of their water supply, but there has been very little analysis of historical data to evaluate and justify these adaptation solutions. In addition, Peru's Ministry of Economy and Finance now requires that climate change be part of the vulnerability assessment for all public investment project proposals, but there are currently no tools or methods of data analysis for including climate change in vulnerability assessments. Compounding the difficulties of considering climate change in the sustainability of development projects is the scarcity of climate data in the region and the difficulty of accessing existing data. To counteract this problem, the Peruvian government recommends using local people's perceptions of change as a proxy for gauged climate data. This work focuses on precipitation data analysis in the mountains of Ancash, Peru. The objectives of this analysis were to determine the accuracy of the local population's perceptions of climate change and to investigate how changes in precipitation patterns might impact public investment projects. The precipitation data analysis was compared to a local study of perceptions of change to determine whether or not these perceptions might be used in lieu of gauged climate data. It appears that people's perceptions of precipitation trends do not accurately reflect the trends observed in the gauged data. The methods of analysis were designed so that the results may be useful for public investment projects with a particular emphasis on agricultural projects. The data were analyzed for trends, seasonal patterns and variability. Dry spells were examined, and the results indicate that droughts during the rainy season have become more frequent and of longer duration. This could have significant impact on agricultural projects. It is likely that the current practice of relying exclusively on wet season rainfall to meet crop water requirements may not be sustainable in the future. Further analysis of climate data is needed to generate a regional climatic characterization that can be used for climate-resilient development projects.

ClimateWizard: A Framework and Easy-to-Use Web-Mapping Tool for Global, Regional, and Local Climate-Change Analysis

NASA Astrophysics Data System (ADS)

Girvetz, E. H.; Zganjar, C.; Raber, G. T.; Hoekstra, J.; Lawler, J. J.; Kareiva, P.

2008-12-01

Now that there is overwhelming evidence of global climate change, scientists, managers and planners (i.e. practitioners) need to assess the potential impacts of climate change on particular ecological systems, within specific geographic areas, and at spatial scales they care about, in order to make better land management, planning, and policy decisions. Unfortunately, this application of climate science to real world decisions and planning has proceeded too slowly because we lack tools for translating cutting-edge climate science and climate-model outputs into something managers and planners can work with at local or regional scales (CCSP 2008). To help increase the accessibility of climate information, we have developed a freely-available, easy-to-use, web-based climate-change analysis toolbox, called ClimateWizard, for assessing how climate has and is projected to change at specific geographic locations throughout the world. The ClimateWizard uses geographic information systems (GIS), web-services (SOAP/XML), statistical analysis platforms (e.g. R- project), and web-based mapping services (e.g. Google Earth/Maps, KML/GML) to provide a variety of different analyses (e.g. trends and departures) and outputs (e.g. maps, graphs, tables, GIS layers). Because ClimateWizard analyzes large climate datasets stored remotely on powerful computers, users of the tool do not need to have fast computers or expensive software, but simply need access to the internet. The analysis results are then provided to users in a Google Maps webpage tailored to the specific climate-change question being asked. The ClimateWizard is not a static product, but rather a framework to be built upon and modified to suit the purposes of specific scientific, management, and policy questions. For example, it can be expanded to include bioclimatic variables (e.g. evapotranspiration) and marine data (e.g. sea surface temperature), as well as improved future climate projections, and climate-change impact analyses involving hydrology, vegetation, wildfire, disease, and food security. By harnessing the power of computer and web- based technologies, the ClimateWizard puts local, regional, and global climate-change analyses in the hands of a wider array of managers, planners, and scientists.

Local and cross-seasonal associations of climate and land use with abundance of monarch butterflies Danaus plexippus

USGS Publications Warehouse

Saunders, Sarah P.; Ries, Leslie; Oberhasuer, Karen S.; Thogmartin, Wayne E.; Zipkin, Elise F.

2017-01-01

Quantifying how climate and land use factors drive population dynamics at regional scales is complex because it depends on the extent of spatial and temporal synchrony among local populations, and the integration of population processes throughout a species’ annual cycle. We modeled weekly, site-specific summer abundance (1994–2013) of monarch butterflies Danaus plexippus at sites across Illinois, USA to assess relative associations of monarch abundance with climate and land use variables during the winter, spring, and summer stages of their annual cycle. We developed negative binomial regression models to estimate monarch abundance during recruitment in Illinois as a function of local climate, site-specific crop cover, and county-level herbicide (glyphosate) application. We also incorporated cross-seasonal covariates, including annual abundance of wintering monarchs in Mexico and climate conditions during spring migration and breeding in Texas, USA. We provide the first empirical evidence of a negative association between county-level glyphosate application and local abundance of adult monarchs, particularly in areas of concentrated agriculture. However, this association was only evident during the initial years of the adoption of herbicide-resistant crops (1994–2003). We also found that wetter and, to a lesser degree, cooler springs in Texas were associated with higher summer abundances in Illinois, as were relatively cool local summer temperatures in Illinois. Site-specific abundance of monarchs averaged approximately one fewer per site from 2004–2013 than during the previous decade, suggesting a recent decline in local abundance of monarch butterflies on their summer breeding grounds in Illinois. Our results demonstrate that seasonal climate and land use are associated with trends in adult monarch abundance, and our approach highlights the value of considering fine-resolution temporal fluctuations in population-level responses to environmental conditions when inferring the dynamics of migratory species.

Millennia-long tree-ring records from Tasmania and New Zealand: a basis for modelling climate variability and forcing, past, present and future

NASA Astrophysics Data System (ADS)

Cook, Edward R.; Buckley, Brendan M.; Palmer, Jonathan G.; Fenwick, Pavla; Peterson, Michael J.; Boswijk, Gretel; Fowler, Anthony

2006-10-01

Progress in the development of millennia-long tree-ring chronologies from Australia and New Zealand is reviewed from the perspective of modelling long-term climate variability there. Three tree species have proved successful in this regard: Huon pine (Lagarostrobos franklinii) from Tasmania, silver pine (L. colensoi) from the South Island of New Zealand, and kauri (Agathis australis) from the North Island of New Zealand. Each of these species is very long-lived and produces abundant quantities of well-preserved wood for extending their tree-ring chronologies back several millennia into the past. The growth patterns on these chronologies strongly correlate with both local and regional warm-season temperature changes over significant areas of the Southern Hemisphere (especially Huon and silver pine) and to ENSO variability emanating from the equatorial Pacific region (especially kauri). In addition, there is evidence for significant, band-limited, multi-decadal and centennial timescale variability in the warm-season temperature reconstruction based on Huon pine tree rings that may be related to slowly varying changes in ocean circulation dynamics in the southern Indian Ocean. This suggests the possibility of long-term climate predictability there. Copyright

A hierarchical perspective on the diversity of butterfly species' responses to weather in the Sierra Nevada Mountains.

PubMed

Nice, Chris C; Forister, Matthew L; Gompert, Zachariah; Fordyce, James A; Shapiro, Arthur M

2014-08-01

An important and largely unaddressed issue in studies of biotic-abiotic relationships is the extent to which closely related species, or species living in similar habitats, have similar responses to weather. We addressed this by applying a hierarchical, Bayesian analytical framework to a long-term data set for butterflies which allowed us to simultaneously investigate responses of the entire fauna and individual species. A small number of variables had community-level effects. In particular, higher total annual snow depth had a positive effect on butterfly occurrences, while spring minimum temperature and El Niño-Southern Oscillation (ENSO) sea-surface variables for April-May had negative standardized coefficients. Our most important finding was that variables with large impacts at the community-level did not necessarily have a consistent response across all species. Species-level responses were much more similar to each other for snow depth compared to the other variables with strong community effects. This variation in species-level responses to weather variables raises important complications for the prediction of biotic responses to shifting climatic conditions. In addition, we found that clear associations with weather can be detected when considering ecologically delimited subsets of the community. For example, resident species and non-ruderal species had a much more unified response to weather variables compared to non-resident species and ruderal species, which suggests local adaptation to climate. These results highlight the complexity of biotic-abiotic interactions and confront that complexity with methodological advances that allow ecologists to understand communities and shifting climates while simultaneously revealing species-specific variation in response to climate.

Alaska Center for Climate Assessment and Policy: Partnering with Decision-Makers in Climate Change Adaptation

NASA Astrophysics Data System (ADS)

White, D.; Trainor, S.; Walsh, J.; Gerlach, C.

2008-12-01

The Alaska Center for Climate Assessment and Policy (ACCAP; www.uaf.edu/accap) is one of several, NOAA funded, Regional Integrated Science and Policy (RISA) programs nation-wide (http://www.climate.noaa.gov/cpo_pa/risa/). Our mission is to assess the socio-economic and biophysical impacts of climate variability in Alaska, make this information available to local and regional decision-makers, and improve the ability of Alaskans to adapt to a changing climate. We partner with the University of Alaska?s Scenario Network for Alaska Planning (SNAP; http://www.snap.uaf.edu/), state and local government, state and federal agencies, industry, and non-profit organizations to communicate accurate and up-to-date climate science and assist in formulating adaptation and mitigation plans. ACCAP and SNAP scientists are members of the Governor?s Climate Change Sub-Cabinet Adaptation and Mitigation Advisory and Technical Working Groups (http://www.climatechange.alaska.gov/), and apply their scientific expertise to provide down-scaled, state-wide maps of temperature and precipitation projections for these groups. An ACCAP scientist also serves as co-chair for the Fairbanks North Star Borough Climate Change Task Force, assisting this group as they work through the five-step model for climate change planning put forward by the International Council for Local Environmental Initiatives (http://www.investfairbanks.com/Taskforces/climate.php). ACCAP scientists work closely with federal resource managers in on a range of projects including: partnering with the U.S. Fish and Wildlife Service to analyze hydrologic changes associated with climate change and related ecological impacts and wildlife management and development issues on Alaska?s North Slope; partnering with members of the Alaska Interagency Wildland Fire Coordinating Group in statistical modeling to predict seasonal wildfire activity and coordinate fire suppression resources state-wide; and working with Alaska Native Elders and resource managers to document traditional ecological knowledge (TEK) and integrate this knowledge with Western science for crafting adaptation response to climate impacts in rural Native Alaska.

Patterns of interannual climate variability in large marine ecosystems

NASA Astrophysics Data System (ADS)

Soares, Helena Cachanhuk; Gherardi, Douglas Francisco Marcolino; Pezzi, Luciano Ponzi; Kayano, Mary Toshie; Paes, Eduardo Tavares

2014-06-01

The purpose of this study is to investigate the vulnerability of the Brazilian and western African Large Marine Ecosystems (LMEs) to local and remote forcing, including the Pacific Decadal Oscillation (PDO) regime shift. The analyses are based on the total and partial correlation between climate indices (Niño3, tropical South Atlantic (TSA), tropical North Atlantic (TNA) and Antarctic oscillation (AAO) and oceanic and atmospheric variables (sea surface temperature (SST), wind stress, Ekman transport, sea level pressure and outgoing longwave radiation). Differences in the correlation fields between the cold and warm PDO indicate that this mode exerts a significant impact on the thermodynamic balance of the ocean-atmosphere system on the South Atlantic ocean, mainly in the South Brazil and Benguela LMEs. The PDO regime shift also resulted in an increase in the spatial variability of SST and wind stress anomalies, mainly along the western African LMEs. Another important finding is the strong AAO influence on the SST anomalies (SSTA) in the South Brazil LME. It is also striking that TSA modulates the relation between El Niño-Southern Oscillation (ENSO) and SSTA, by reducing the influence of ENSO on SSTA during the warm PDO period in the North and East Brazil LMEs and in the Guinea Current LME. The relation between AAO and SSTA on the tropical area is also influenced by the TSA. The results shown here give a clear indication that future ecosystem-based management actions aimed at the conservation of marine resources under climate change need to consider the high complexity of basin-scale interactions between local and remote climate forcings, including their effects on the ocean-atmosphere system of the South Atlantic ocean.

Leaf wax biomarker reconstruction of Early Pleistocene hydrological variation during hominin evolution in West Turkana, Kenya

NASA Astrophysics Data System (ADS)

Lupien, R.; Russell, J. M.; Cohen, A. S.; Feibel, C. S.; Beck, C.; Castañeda, I. S.

2016-12-01

Climate change is thought to play a critical role in human evolution; however, this hypothesis is difficult to test due to a lack of long, high-quality paleoclimate records from key hominin fossil locales. To address this issue, we examine Plio-Pleistocene lake sediment drill cores from East Africa that were recovered by the Hominin Sites and Paleolakes Drilling Project, an international effort to study the environment in which our hominin ancestors evolved and dispersed. With new data we test various evolutionary hypotheses, such as the "variability selection" hypothesis, which posits that high-frequency environmental variations selected for generalist traits that allowed hominins to expand into variable environments. We analyzed organic geochemical signals of climate in lake cores from West Turkana, Kenya, which span 1.87-1.38 Ma and contain the first fossils from Homo erectus. In particular, we present a compound-specific hydrogen isotopic analysis of terrestrial plant waxes (δDwax) that records regional hydrology. The amount effect dominates water isotope fractionation in the tropics; therefore, these data are interpreted to reflect mean annual rainfall, which affects vegetation structure and thus, hominin habitats. The canonical view of East Africa is that climate became drier and increasingly felt high-latitude glacial-interglacial cycles during the Plio-Pleistocene. However, the drying trend seen in some records is not evident in Turkana δDwax, signifying instead a climate with a steady mean state. Spectral and moving variance analyses indicate paleohydrological variations related to both high-latitude glaciation (41 ky cycle) and local insolation-forced monsoons (21 ky cycle). An interval of particularly high-amplitude rainfall variation occurs at 1.7 Ma, which coincides with the intensification of the Walker Circulation. These results identify high- and low-latitude controls on East African paleohydrology during Homo erectus evolution. In particular, the interval of high-amplitude variability coincides with hominin evolution changes and lends support for the "variability selection" hypothesis. Similar analyses of a drill core from Northern Awash, Ethiopia ( 3.3-2.9 Ma) will be presented to compare Pliocene and Pleistocene climate variations.

The predicted CLARREO sampling error of the inter-annual SW variability

NASA Astrophysics Data System (ADS)

Doelling, D. R.; Keyes, D. F.; Nguyen, C.; Macdonnell, D.; Young, D. F.

2009-12-01

The NRC Decadal Survey has called for SI traceability of long-term hyper-spectral flux measurements in order to monitor climate variability. This mission is called the Climate Absolute Radiance and Refractivity Observatory (CLARREO) and is currently defining its mission requirements. The requirements are focused on the ability to measure decadal change of key climate variables at very high accuracy. The accuracy goals are set using anticipated climate change magnitudes, but the accuracy achieved for any given climate variable must take into account the temporal and spatial sampling errors based on satellite orbits and calibration accuracy. The time period to detect a significant trend in the CLARREO record depends on the magnitude of the sampling calibration errors relative to the current inter-annual variability. The largest uncertainty in climate feedbacks remains the effect of changing clouds on planetary energy balance. Some regions on earth have strong diurnal cycles, such as maritime stratus and afternoon land convection; other regions have strong seasonal cycles, such as the monsoon. However, when monitoring inter-annual variability these cycles are only important if the strength of these cycles vary on decadal time scales. This study will attempt to determine the best satellite constellations to reduce sampling error and to compare the error with the current inter-annual variability signal to ensure the viability of the mission. The study will incorporate Clouds and the Earth's Radiant Energy System (CERES) (Monthly TOA/Surface Averages) SRBAVG product TOA LW and SW climate quality fluxes. The fluxes are derived by combining Terra (10:30 local equator crossing time) CERES fluxes with 3-hourly 5-geostationary satellite estimated broadband fluxes, which are normalized using the CERES fluxes, to complete the diurnal cycle. These fluxes were saved hourly during processing and considered the truth dataset. 90°, 83° and 74° inclination precessionary orbits as well as sun-synchronous orbits will be evaluated. This study will focus on the SW radiance, since these low earth orbits are only in daylight for half the orbit. The precessionary orbits were designed to cycle through all solar zenith angles over the course of a year. The inter-annual variability sampling error will be stratified globally/zonally and annually/seasonally and compared with the corresponding truth anomalies.

Increasing importance of precipitation variability on global livestock grazing lands

NASA Astrophysics Data System (ADS)

Sloat, Lindsey L.; Gerber, James S.; Samberg, Leah H.; Smith, William K.; Herrero, Mario; Ferreira, Laerte G.; Godde, Cécile M.; West, Paul C.

2018-03-01

Pastures and rangelands underpin global meat and milk production and are a critical resource for millions of people dependent on livestock for food security1,2. Forage growth, which is highly climate dependent3,4, is potentially vulnerable to climate change, although precisely where and to what extent remains relatively unexplored. In this study, we assess climate-based threats to global pastures, with a specific focus on changes in within- and between-year precipitation variability (precipitation concentration index (PCI) and coefficient of variation of precipitation (CVP), respectively). Relating global satellite measures of vegetation greenness (such as the Normalized Difference Vegetation Index; NDVI) to key climatic factors reveals that CVP is a significant, yet often overlooked, constraint on vegetation productivity across global pastures. Using independent stocking data, we found that areas with high CVP support lower livestock densities than less-variable regions. Globally, pastures experience about a 25% greater year-to-year precipitation variation (CVP = 0.27) than the average global land surface area (0.21). Over the past century, CVP has generally increased across pasture areas, although both positive (49% of pasture area) and negative (31% of pasture area) trends exist. We identify regions in which livestock grazing is important for local food access and economies, and discuss the potential for pasture intensification in the context of long-term regional trends in precipitation variability.

Climate change and human infectious diseases: A synthesis of research findings from global and spatio-temporal perspectives.

PubMed

Liang, Lu; Gong, Peng

2017-06-01

The life cycles and transmission of most infectious agents are inextricably linked with climate. In spite of a growing level of interest and progress in determining climate change effects on infectious disease, the debate on the potential health outcomes remains polarizing, which is partly attributable to the varying effects of climate change, different types of pathogen-host systems, and spatio-temporal scales. We summarize the published evidence and show that over the past few decades, the reported negative or uncertain responses of infectious diseases to climate change has been growing. A feature of the research tendency is the focus on temperature and insect-borne diseases at the local and decadal scale. Geographically, regions experiencing higher temperature anomalies have been given more research attention; unfortunately, the Earth's most vulnerable regions to climate variability and extreme events have been less studied. From local to global scales, agreements on the response of infectious diseases to climate change tend to converge. So far, an abundance of findings have been based on statistical methods, with the number of mechanistic studies slowly growing. Research gaps and trends identified in this study should be addressed in the future. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Links between the built environment, climate and population health: interdisciplinary environmental change research in New York City.

PubMed

Rosenthal, Joyce Klein; Sclar, Elliott D; Kinney, Patrick L; Knowlton, Kim; Crauderueff, Robert; Brandt-Rauf, Paul W

2007-10-01

Global climate change is expected to pose increasing challenges for cities in the following decades, placing greater stress and impacts on multiple social and biophysical systems, including population health, coastal development, urban infrastructure, energy demand, and water supplies. Simultaneously, a strong global trend towards urbanisation of poverty exists, with increased challenges for urban populations and local governance to protect and sustain the wellbeing of growing cities. In the context of these 2 overarching trends, interdisciplinary research at the city scale is prioritised for understanding the social impacts of climate change and variability and for the evaluation of strategies in the built environment that might serve as adaptive responses to climate change. This article discusses 2 recent initiatives of The Earth Institute at Columbia University (EI) as examples of research that integrates the methods and objectives of several disciplines, including environmental health science and urban planning, to understand the potential public health impacts of global climate change and mitigative measures for the more localised effects of the urban heat island in the New York City metropolitan region. These efforts embody 2 distinct research approaches. The New York Climate & Health Project created a new integrated modeling system to assess the public health impacts of climate and land use change in the metropolitan region. The Cool City Project aims for more applied policy-oriented research that incorporates the local knowledge of community residents to understand the costs and benefits of interventions in the built environment that might serve to mitigate the harmful impacts of climate change and variability, and protect urban populations from health stressors associated with summertime heat. Both types of research are potentially useful for understanding the impacts of environmental change at the urban scale, the policies needed to address these challenges, and to train scholars capable of collaborative approaches across the social and biophysical sciences.

Adaptive genetic potential of coniferous forest tree species under climate change: implications for sustainable forest management

NASA Astrophysics Data System (ADS)

Mihai, Georgeta; Birsan, Marius-Victor; Teodosiu, Maria; Dumitrescu, Alexandru; Daia, Mihai; Mirancea, Ionel; Ivanov, Paula; Alin, Alexandru

2017-04-01

Mountain ecosystems are extremely vulnerable to climate change. The real potential for adaptation depends upon the existence of a wide genetic diversity in trees populations, upon the adaptive genetic variation, respectively. Genetic diversity offers the guarantee that forest species can survive, adapt and evolve under the influence of changing environmental conditions. The aim of this study is to evaluate the genetic diversity and adaptive genetic potential of two local species - Norway spruce and European silver fir - in the context of regional climate change. Based on data from a long-term provenance experiments network and climate variables spanning over more than 50 years, we have investigated the impact of climatic factors on growth performance and adaptation of tree species. Our results indicate that climatic and geographic factors significantly affect forest site productivity. Mean annual temperature and annual precipitation amount were found to be statistically significant explanatory variables. Combining the additive genetic model with the analysis of nuclear markers we obtained different images of the genetic structure of tree populations. As genetic indicators we used: gene frequencies, genetic diversity, genetic differentiation, genetic variance, plasticity. Spatial genetic analyses have allowed identifying the genetic centers holding high genetic diversity which will be valuable sources of gene able to buffer the negative effects of future climate change. Correlations between the marginal populations and in the optimal vegetation, between the level of genetic diversity and ecosystem stability, will allow the assessment of future risks arising from current genetic structure. Therefore, the strategies for sustainable forest management have to rely on the adaptive genetic variation and local adaptation of the valuable genetic resources. This work was realized within the framework of the project GENCLIM (Evaluating the adaptive potential of the main coniferous species for a sustainable forest management in the context of climate change), financed by the Executive Agency for Higher Education, Research, Development and Innovation Funding, grant number PN-II-PC-PCCA-2013-4-0695.

Effects of Global Change on U.S. Urban Areas: Vulnerabilities, Impacts, and Adaptation

NASA Astrophysics Data System (ADS)

Quattrochi, D. A.; Wilbanks, T. J.; Kirshen, P. H.; Romero-Lankao, P.; Rosenzweig, C. E.; Ruth, M.; Solecki, W.; Tarr, J. A.

2007-05-01

Human settlements, both large and small, are where the vast majority of people on the Earth live. Expansion of cities both in population and areal extent, is a relentless process that will accelerate in the 21st century. As a consequence of urban growth both in the United States and around the globe, it is important to develop an understanding of how urbanization will affect the local and regional environment. Of equal importance, however, is the assessment of how cities will be impacted by the looming prospects of global climate change and climate variability. The potential impacts of climate change and variability has recently been enunciated by the IPCC's "Climate Change 2007" report. Moreover, the U.S. Climate Change Science Program (CCSP) is preparing a series of "Synthesis and Assessment Products" (SAP) reports to support informed discussion and decision making regarding climate change and variability by policy makers, resource managers, stakeholders, the media, and the general public. We are working on a chapter of SAP 4.6 ("Analysis of the Effects of Global Chance on Human Health and Welfare and Human Systems") wherein we wish to describe the effects of global climate change on human settlements. This paper will present the thoughts and ideas that are being formulated for our SAP report that relate to what vulnerabilities and impacts will occur, what adaptation responses may take place, and what possible effects on settlement patterns and characteristics will potentially arise, on human settlements in the U.S. as a result of climate change and climate variability. We wish to present these ideas and concepts as a "work in progress" that are subject to several rounds of review, and we invite comments from listeners at this session on the rationale and veracity of our thoughts. Additionally, we wish to explore how technology such as remote sensing data coupled with modeling, can be employed as synthesis tools for deriving insight across a spectrum of impacts (e.g. public health, urban planning for mitigation strategies) on how cities can cope and adapt to climate change and variability. This latter point parallels the concepts and ideas presented in the U.S. National Academy of Sciences, Decadal Survey report on "Earth Science Applications from Space: National Imperatives for the Next Decade and Beyond" wherein the analysis of the impacts of climate change and variability, human health, and land use change are listed as key areas for development of future Earth observing remote sensing systems.

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

PubMed

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

2013-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

26 CFR 1.42-10 - Utility allowances.

Code of Federal Regulations, 2012 CFR

2012-04-01

... into account, among other things, local utility rates, property type, climate and degree-day variables... which the building containing the units is located. (c) Changes in applicable utility allowance—(1) In...)), the applicable utility allowance for units changes, the new utility allowance must be used to compute...

26 CFR 1.42-10 - Utility allowances.

Code of Federal Regulations, 2014 CFR

2014-04-01

... into account, among other things, local utility rates, property type, climate and degree-day variables... which the building containing the units is located. (c) Changes in applicable utility allowance—(1) In...)), the applicable utility allowance for units changes, the new utility allowance must be used to compute...

26 CFR 1.42-10 - Utility allowances.

Code of Federal Regulations, 2013 CFR

2013-04-01

... into account, among other things, local utility rates, property type, climate and degree-day variables... which the building containing the units is located. (c) Changes in applicable utility allowance—(1) In...)), the applicable utility allowance for units changes, the new utility allowance must be used to compute...

26 CFR 1.42-10 - Utility allowances.

Code of Federal Regulations, 2011 CFR

2011-04-01

... into account, among other things, local utility rates, property type, climate and degree-day variables... which the building containing the units is located. (c) Changes in applicable utility allowance—(1) In...)), the applicable utility allowance for units changes, the new utility allowance must be used to compute...

26 CFR 1.42-10 - Utility allowances.

Code of Federal Regulations, 2010 CFR

2010-04-01

... into account, among other things, local utility rates, property type, climate and degree-day variables... which the building containing the units is located. (c) Changes in applicable utility allowance—(1) In...)), the applicable utility allowance for units changes, the new utility allowance must be used to compute...

Microclimate in Forest Ecosystem and Landscape Ecology

Treesearch

Jiquan Chen; Sari C. Saunders; Thomas R. Crow; Robert J. Naiman; Kimberley D. Brosofske; Glenn D. Mroz; Brain L. Brookshire; Jerry F. Franklin

1999-01-01

Microclimate is the suite of climatic conditions measured in localized areas near the earth's surface (Geiger 1965). These environmental variables, which include temperature, light, windspeed, and moisture, have been critical throughout human history, providing meaningful indicators for habitat selection and other activities. For example, for 2600 years the...

Influence of climate on the presence of colour polymorphism in two montane reptile species

PubMed Central

Broennimann, Olivier; Ursenbacher, Sylvain; Meyer, Andreas; Golay, Philippe; Monney, Jean-Claude; Schmocker, Hans; Guisan, Antoine; Dubey, Sylvain

2014-01-01

The coloration of ectotherms plays an important role in thermoregulation processes. Dark individuals should heat up faster and be able to reach a higher body temperature than light individuals and should therefore have benefits in cool areas. In central Europe, montane local populations of adder (Vipera berus) and asp viper (Vipera aspis) exhibit a varying proportion of melanistic individuals. We tested whether the presence of melanistic V. aspis and V. berus could be explained by climatic conditions. We measured the climatic niche position and breadth of monomorphic (including strictly patterned individuals) and polymorphic local populations, calculated their niche overlap and tested for niche equivalency and similarity. In accordance with expectations, niche overlap between polymorphic local populations of both species is high, and even higher than that of polymorphic versus monomorphic montane local populations of V. aspis, suggesting a predominant role of melanism in determining the niche of ectothermic vertebrates. However, unexpectedly, the niche of polymorphic local populations of both species is narrower than that of monomorphic ones, indicating that colour polymorphism does not always enable the exploitation of a greater variability of resources, at least at the intraspecific level. Overall, our results suggest that melanism might be present only when the thermoregulatory benefit is higher than the cost of predation. PMID:25392313

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

A vertical hydroclimatology of the Upper Indus Basin and initial insights to potential hydrological change in the region

NASA Astrophysics Data System (ADS)

Forsythe, Nathan; Kilsby, Chris G.; Fowler, Hayley J.; Archer, David R.

2010-05-01

The water resources of the Upper Indus Basin (UIB) are of the utmost importance to the economic wellbeing of Pakistan. The irrigated agriculture made possible by Indus river runoff underpins the food security for Pakistan's nearly 200 million people. Contributions from hydropower account for more than one fifth of peak installed electrical generating capacity in a country where widespread, prolonged load-shedding handicaps business activity and industrial development. Pakistan's further socio-economic development thus depends largely on optimisation of its precious water resources. Confident, accurate projections of future water resource availability and variability are urgent insights needed by development planners and infrastructure managers at all levels. Correctly projecting future hydrological conditions depends first and foremost on a thorough understanding of the underlying mechanisms and processes of present hydroclimatology. The vertical and horizontal spatial variations in key climate parameters (temperature, precipitation) govern the contributions of the various elevation zones and subcatchments comprising the UIB. Trends in this complex mountainous region are highly varied by season and parameter. Observed changes here often do not match general global trends or even necessarily those found in neighbouring regions. This study considers data from a variety sources in order to compose the most complete picture possible of the vertical hydroclimatology of the UIB. The study presents the observed climatology and trends for precipitation and temperature from local observations at long-record meteorological stations (Pakistan Meteorological Department). These data are compared to characterisations of additional water cycle parameters (humidity, cloud, snow cover and snow-water-equivalent) derived from local short-record automatic weather stations, the ECMWF ‘ERA' reanalysis projects and satellite based observations (AVHRR, MODIS, etc). The potential implications of the vertical (hypsometric) distribution of these parameters are considered. Interlinkages between observed changes in these parameters and the evolution of large-scale circulation indices (ENSO, NAO, local vorticity) are also investigated. In parallel to these climatological considerations, the study presents the typology of the observed UIB hydrological regimes -- glacial, nival and pluvial -- including interannual variability as quantified from the available river gauging record. In order to begin to assess potential implications of future climate change on UIB hydrology, key modes of variability in the climate parameters are identified. The study then analyses in detail the corresponding observed anomalies in UIB discharge for years exemplifying these modes. In conclusion, this work postulates potential impacts of changes in the hydrological variability stemming from continuation of estimated present local climatic trends.

Influence of weather on the synchrony of gypsy moth (Lepidoptera: Lymantriidae) outbreaks in New England

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

Williams, D.W.; Liebhold, A.M.

1995-10-01

Outbreaks of the gypsy moth, Lymantria dispar (L.), were partially synchronous across New England states (Massachusetts, Maine, New Hampshire, and Vermont) from 1938 to 1992. To explain this synchrony, we investigated the Moran effect, a hypothesis that local population oscillations, which result form similar density-dependent mechanisms operating at time lags, may be synchronized over wide areas by exposure to common weather patterns. We also investigated the theory of climatic release, which ostulates that outbreaks are triggered by climatic factors favorable for population growth. Time series analysis revealed defoliation series in 2 states as 1st-order autoregressive processes and the other 2more » as periodic 2nd-order autoregressive processes. Defoliation residuals series computed using the autoregressive models for each state were cross correlated with series of weather variables recorded in the respective states. The weather variables significantly correlated with defoliation residuals in all 4 states were minimum temperature and precipitation in mid-December in the same gypsy moth generation and minimum temperature in mid- to late July of the previous generation. These weather variables also were correlated strongly among the 4 states. The analyses supported the predictions of the Moran effect and suggest the common weather may synchronize local populations so as to produce pest outbreaks over wide areas. We did not find convincing evidence to support the theory of climatic release. 41 refs., 7 figs., 4 tabs.« less

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.

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

NASA Astrophysics Data System (ADS)

Zeng, R.; Cai, X.

2016-12-01

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

Assessing Extratropical Influence on Tropical Climatology and Variability with Regional Coupled Data Assimilation

NASA Astrophysics Data System (ADS)

Lu, F.; Liu, Z.; Liu, Y.; Zhang, S.; Jacob, R. L.

2017-12-01

The Regional Coupled Data Assimilation (RCDA) method is introduced as a tool to study coupled climate dynamics and teleconnections. The RCDA method is built on an ensemble-based coupled data assimilation (CDA) system in a coupled general circulation model (CGCM). The RCDA method limits the data assimilation to the desired model components (e.g. atmosphere) and regions (e.g. the extratropics), and studies the ensemble-mean model response (e.g. tropical response to "observed" extratropical atmospheric variability). When applied to the extratropical influence on tropical climate, the RCDA method has shown some unique advantages, namely the combination of a fully coupled model, real-world observations and an ensemble approach. Tropical variability (e.g. El Niño-Southern Oscillation or ENSO) and climatology (e.g. asymmetric Inter-Tropical Convergence Zone or ITCZ) were initially thought to be determined mostly by local forcing and ocean-atmosphere interaction in the tropics. Since late 20th century, numerous studies have showed that extratropical forcing could affect, or even largely determine some aspects of the tropical climate. Due to the coupled nature of the climate system, however, the challenge of determining and further quantifying the causality of extratropical forcing on the tropical climate remains. Using the RCDA method, we have demonstrated significant control of extratropical atmospheric forcing on ENSO variability in a CGCM, both with model-generated and real-world observation datasets. The RCDA method has also shown robust extratropical impact on the tropical double-ITCZ bias in a CGCM. The RCDA method has provided the first systematic and quantitative assessment of extratropical influence on tropical climatology and variability by incorporating real world observations in a CGCM.

TV Weathercasters as Climate Educators: Rationale, Evidence for Effectiveness, and Potential for Nationwide Scale-Up. (Invited)

NASA Astrophysics Data System (ADS)

Maibach, E.; Cullen, H. M.; Witte, J.

2013-12-01

Climate change is influencing every region of the nation through weather and climatic events including heat waves, droughts, extreme precipitation and floods, more intense hurricanes, and forest fires, yet most Americans continue to perceive climate change as a problem distant in time (with impacts a generation or more away), and in space (that will primarily affect other countries, not the United States). This may be caused, in part, due to the fact that climate change is often described in global, abstract, and analytical terms that are hard for people to connect to their own lives. The impacts of climate change, however, can be personally experienced at the local level, including through unusual weather events; cognitive science has shown that the human brain is more adept at learning through personal experience than through analytical reasoning. In this paper we will describe our efforts to enable America's TV weathercasters to embrace the role of climate educator. Weathercasters are a relatively small cohort of highly skilled communication professionals who are optimally positioned to reach a large majority of the American public, and help move their viewers beyond an abstract (distant) notion of global climate change and toward an understanding of climate change that is both local and concrete. Approximately 70% of American adults watch local TV news, and their primary reason for doing so is to learn about the weather. Our research has shown that TV weathercasters are second only to scientists and government science agencies as trusted sources of information about climate change. Our surveys have also shown that - in every region of the country - many TV weathercasters are willing to embrace the role of climate educator, if certain barriers can be overcome. Our experimental pilot-test - in Columbia, South Carolina - of a model developed to help overcome those barriers demonstrated that: when TV weathercasters make an effort to educate their viewers about the local ramifications of climate change, their viewers learn. Our current attempts to scale-up the model on a limited basis - in one state as a field experiment, and elsewhere around the nation on an uncontrolled basis - are showing promise in terms of attracting an increasing numbers of participating weathercasters. Lastly, professional associations that represent TV weathercasters (AMS and NWA), and government agencies that produce climate and weather data for meteorologists (NOAA and NASA), are committed to help scale up this model so that all interested TV weathercasters have easy access to localized information through which to educate their viewers about local weather and related implications of climate change. In sum, by engaging and empowering TV weathercasters as climate educators, we seek to increase public understanding of the relationships among climate, climate variability, climate change, weather extremes and community vulnerability, and we believe this model has considerable potential.

Impact of surface water withdrawals on water storage variations under a changing climate

NASA Astrophysics Data System (ADS)

Ashraf, B.; AghaKouchak, A.; Mousavi Baygi, M.; Alizadeh, A.; Moftakhari, H.; Miao, C.; Arab, D. R.; Anjileli, H.

2016-12-01

Quantitative evaluation of water storage variations in large river basins is an important element of water management, especially in a climate change. In addition, human water use has developed into another strong driver of water storage changes especially in densely populated semiarid and arid areas. In this study, we estimate the normalized human outflow of the thirty main basins in Iran during the past three decades. Then, we investigate the individual and combined effects of climate variability and human water withdrawals on surface water storage in the 21st century in four major basins (Urmia, Karkheh, Karun and Jarrahi) located in semi-arid areas of Iran. These basins are selected because they experienced medium to high human-induced water demand in last decades. We use bias-corrected historical simulations and future projections from 26 General Circulation Models (GCMs) and three climate change scenarios RCP2.6, RCP4.5, RCP8.5). The results show that humans have strongly impacted the water balances of most basins in Iran, dominating potential climate change impacts in the historical period. In fact, the main reason for water scarcity in these regions appears to be due to the increased anthropogenic water demand resulting from substantial socio-economic growth in the past three decades. Furthermore, by the end of the 21st century, the compounding effects of increased irrigation water demand and precipitation variability may lead to severe local water scarcity in these basins. Our study highlights the need to improve our understanding of the hydrologic responses to anthropogenic perturbations, and local water resource management decisions.

Regional patterns of interannual variability of catchment water balances across the continental U.S.: A Budyko framework

NASA Astrophysics Data System (ADS)

Carmona, Alejandra M.; Sivapalan, Murugesu; Yaeger, Mary A.; Poveda, Germán.

2014-12-01

Patterns of interannual variability of the annual water balance are explored using data from 190 MOPEX catchments across the continental U.S. This analysis has led to the derivation of a quantitative, dimensionless, Budyko-type framework to characterize the observed interannual variability of annual water balances. The resulting model is expressed in terms of a humidity index that measures the competition between water and energy availability at the annual time scale, and a similarity parameter (α) that captures the net effects of other short-term climate features and local landscape characteristics. This application of the model to the 190 study catchments revealed the existence of space-time symmetry between spatial (between-catchment) variability and general trends in the temporal (between-year) variability of the annual water balances. The MOPEX study catchments were classified into eight similar catchment groups on the basis of magnitudes of the similarity parameter α. Interesting regional trends of α across the continental U.S. were brought out through identification of similarities between the spatial positions of the catchment groups with the mapping of distinctive ecoregions that implicitly take into account common climatic and vegetation characteristics. In this context, this study has introduced a deep sense of similarity that is evident in observed space-time variability of water balances that also reflect the codependence and coevolution of climate and landscape properties.

Phenology of Honey Bee Swarm Departure in New Jersey, United States.

PubMed

Gilley, D C; Courtright, T J; Thom, C

2018-03-31

Departure of swarms from honey bee (Apis mellifera Linnaeus (Hymenoptera: Apidae)) nests is an important reproductive event for wild honey bee colonies and economically costly in managed bee colonies. The seasonal timing of swarm departure varies regionally and annually, creating challenges for honey bee management and emphasizing the potential for swarming behavior to be affected by plant-pollinator phenological mismatch. In this study, we first document variability in the timing of swarm departure across the large and heterogeneous geographical area of New Jersey over 4 years using 689 swarm-cluster observations. Second, hypothesizing that honey bee colonies adaptively tune the timing of swarm departure to match floral food-resource availability, we predicted that growing degree-days could be used to account for regional and annual variability. To test this idea, we used local weather records to determine the growing degree-day on which each swarm cluster was observed and tested for differences among climate regions and years. The state-wide mean swarm cluster date was May 15 (± 0.6 d), with moderate but significant differences among the state's five climate regions and between years. Use of degree-day information suggests that local heat accumulation can account for some climate-region differences in swarm-departure timing. Annual variation existed on a scale of only several days and was not accounted for by growing degree-days, suggesting little adaptive tuning of swarm-departure timing with respect to local heat accumulation.

Spatiotemporal correlation structure of the Earth's surface temperature

NASA Astrophysics Data System (ADS)

Fredriksen, Hege-Beate; Rypdal, Kristoffer; Rypdal, Martin

2015-04-01

We investigate the spatiotemporal temperature variability for several gridded instrumental and climate model data sets. The temporal variability is analysed by estimating the power spectral density and studying the differences between local and global temperatures, land and sea, and among local temperature records at different locations. The spatiotemporal correlation structure is analysed through cross-spectra that allow us to compute frequency-dependent spatial autocorrelation functions (ACFs). Our results are then compared to theoretical spectra and frequency-dependent spatial ACFs derived from a fractional stochastic-diffusive energy balance model (FEBM). From the FEBM we expect both local and global temperatures to have a long-range persistent temporal behaviour, and the spectral exponent (β) is expected to increase by a factor of two when going from local to global scales. Our comparison of the average local spectrum and the global spectrum shows good agreement with this model, although the FEBM has so far only been studied for a pure land planet and a pure ocean planet, respectively, with no seasonal forcing. Hence it cannot capture the substantial variability among the local spectra, in particular between the spectra for land and sea, and for equatorial and non-equatorial temperatures. Both models and observation data show that land temperatures in general have a low persistence, while sea surface temperatures show a higher, and also more variable degree of persistence. Near the equator the spectra deviate from the power-law shape expected from the FEBM. Instead we observe large variability at time scales of a few years due to ENSO, and a flat spectrum at longer time scales, making the spectrum more reminiscent of that of a red noise process. From the frequency-dependent spatial ACFs we observe that the spatial correlation length increases with increasing time scale, which is also consistent with the FEBM. One consequence of this is that longer-lasting structures must also be wider in space. The spatial correlation length is also observed to be longer for land than for sea. The climate model simulations studied are mainly CMIP5 control runs of length 500-1000 yr. On time scales up to several centuries we do not observe that the difference between the local and global spectral exponents vanish. This also follows from the FEBM and shows that the dynamics is spatiotemporal (not just temporal) even on these time scales.

Life cycles of transient planetary waves

NASA Technical Reports Server (NTRS)

Nathan, Terrence

1993-01-01

In recent years there has been an increasing effort devoted to understanding the physical and dynamical processes that govern the global-scale circulation of the atmosphere. This effort has been motivated, in part, from: (1) a wealth of new satellite data; (2) an urgent need to assess the potential impact of chlorofluorocarbons on our climate; (3) an inadequate understanding of the interactions between the troposphere and stratosphere and the role that such interactions play in short and long-term climate variability; and (4) the realization that addressing changes in our global climate requires understanding the interactions among various components of the earth system. The research currently being carried out represents an effort to address some of these issues by carrying out studies that combine radiation, ozone, seasonal thermal forcing and dynamics. Satellite and ground-based data that is already available is being used to construct basic states for our analytical and numerical models. Significant accomplishments from 1991-1992 are presented and include the following: ozone-dynamics interaction; (2) periodic local forcing and low frequency variability; and (3) steady forcing and low frequency variability.

Real-time monitoring of smallholder farmer responses to intra-seasonal climate variability in central Kenya

NASA Astrophysics Data System (ADS)

Krell, N.; Evans, T. P.; Estes, L. D.; Caylor, K. K.

2017-12-01

While international metrics of food security and water availability are generated as spatial averages at the regional to national levels, climate variability impacts are differentially felt at the household level. This project investigated scales of variability of climate impacts on smallholder farmers using social and environmental data in central Kenya. Using sub-daily real-time environmental measurements to monitor smallholder agriculture, we investigated how changes in seasonal precipitation affected food security around Laikipia county from September 2015 to present. We also conducted SMS-based surveys of over 700 farmers to understand farmers' decision-making within the growing season. Our results highlight field-scale heterogeneity in biophysical and social factors governing crop yields using locally sensed real-time environmental data and weekly farmer-reported information about planting, harvesting, irrigation, and crop yields. Our preliminary results show relationships between changes in seasonal precipitation, NDVI, and soil moisture related to crop yields and decision-making at several scales. These datasets present a unique opportunity to collect highly spatially and temporally resolved information from data-poor regions at the household level.

Impacts of climate change and variability on European agriculture: results of inventory analysis in COST 734 countries.

PubMed

Orlandini, Simone; Nejedlik, Pavol; Eitzinger, Josef; Alexandrov, Vesselin; Toulios, Leonidas; Calanca, Pierluigi; Trnka, Miroslav; Olesen, Jørgen E

2008-12-01

Climate plays a fundamental role in agriculture because of to its influence on production. All processes are regulated by specific climatic requirements. Furthermore, European agriculture, based on highly developed farming techniques, is mainly oriented to high quality food production that is more susceptible to meteorological hazards. These hazards can modify environment-genotype interactions, which can affect the quality of production. The COST 734 Action (Impacts of Climate Change and Variability on European Agriculture), launched in 2006, is composed of 28 signature countries and is funded by the European Commission. The main objective of the Action is the evaluation of possible impacts arising from climate change and variability on agriculture and the assessment of critical thresholds for various European areas. The Action will concentrate on four different tasks: agroclimatic indices and simulation models, including review and assessment of tools used to relate climate and agricultural processes; evaluation of the current trends of agroclimatic indices and model outputs, including remote sensing; developing and assessing future regional and local scenarios of agroclimatic conditions; and risk assessment and foreseen impacts on agriculture. The work will be carried out by respective Working Groups. This paper presents the results of the analysis of the first phase of inventory activity. Specific questionnaires were disseminated among COST 734 countries to collect information on climate change analysis, studies, and impact at the European level. The results were discussed with respect to their spatial distribution in Europe and to identify possible common long- and short-term strategies for adaptation.

Climate Change and Civil Violence

NASA Astrophysics Data System (ADS)

van der Vink, G.; Plancherel, Y.; Hennet, C.; Jones, K. D.; Abdullah, A.; Bradshaw, J.; Dee, S.; Deprez, A.; Pasenello, M.; Plaza-Jennings, E.; Roseman, D.; Sopher, P.; Sung, E.

2009-05-01

The manifestations of climate change can result in humanitarian impacts that reverse progress in poverty- reduction, create shortages of food and resources, lead to migration, and ultimately result in civil violence and conflict. Within the continent of Africa, we have found that environmentally-related variables are either the cause or the confounding factor for over 80% of the civil violence events during the last 10 years. Using predictive climate models and land-use data, we are able to identify populations in Africa that are likely to experience the most severe climate-related shocks. Through geospatial analysis, we are able to overlay these areas of high risk with assessments of both the local population's resiliency and the region's capacity to respond to climate shocks should they occur. The net result of the analysis is the identification of locations that are becoming particularly vulnerable to future civil violence events (vulnerability hotspots) as a result of the manifestations of climate change. For each population group, over 600 social, economic, political, and environmental indicators are integrated statistically to measures the vulnerability of African populations to environmental change. The indicator time-series are filtered for data availability and redundancy, broadly ordered into four categories (social, political, economic and environmental), standardized and normalized. Within each category, the dominant modes of variability are isolated by principal component analysis and the loadings of each component for each variable are used to devise composite index scores. Comparisons of past vulnerability with known environmentally-related conflicts demonstrates the role that such vulnerability hotspot maps can play in evaluating both the potential for, and the significance of, environmentally-related civil violence events. Furthermore, the analysis reveals the major variables that are responsible for the population's vulnerability and therefore provides an opportunity for targeted proactive measures to mitigate certain classes of future civil violence events.

Spatial variability in growth-increment chronologies of long-lived freshwater mussels: Implications for climate impacts and reconstructions

USGS Publications Warehouse

Black, Bryan A.; Dunham, Jason B.; Blundon, Brett W.; Raggon, Mark F.; Zima, Daniela

2010-01-01

Estimates of historical variability in river ecosystems are often lacking, but long-lived freshwater mussels could provide unique opportunities to understand past conditions in these environments. We applied dendrochronology techniques to quantify historical variability in growth-increment widths in valves (shells) of western pearlshell freshwater mussels (Margaritifera falcata). A total of 3 growth-increment chronologies, spanning 19 to 26 y in length, were developed. Growth was highly synchronous among individuals within each site, and to a lesser extent, chronologies were synchronous among sites. All 3 chronologies negatively related to instrumental records of stream discharge, while correlations with measures of water temperature were consistently positive but weaker. A reconstruction of stream discharge was performed using linear regressions based on a mussel growth chronology and the regional Palmer Drought Severity Index (PDSI). Models based on mussel growth and PDSI yielded similar coefficients of prediction (R2Pred) of 0.73 and 0.77, respectively, for predicting out-ofsample observations. From an ecological perspective, we found that mussel chronologies provided a rich source of information for understanding climate impacts. Responses of mussels to changes in climate and stream ecosystems can be very site- and process-specific, underscoring the complex nature of biotic responses to climate change and the need to understand both regional and local processes in projecting climate impacts on freshwater species.

Conservation at a slow pace: terrestrial gastropods facing fast-changing climate

PubMed Central

Ansart, Armelle

2017-01-01

Abstract The climate is changing rapidly, and terrestrial ectotherms are expected to be particularly vulnerable to changes in temperature and water regime, but also to an increase in extreme weather events in temperate regions. Physiological responses of terrestrial gastropods to climate change are poorly studied. This is surprising, because they are of biodiversity significance among litter-dwelling species, playing important roles in ecosystem function, with numerous species being listed as endangered and requiring efficient conservation management. Through a summary of our ecophysiological work on snail and slug species, we gained some insights into physiological and behavioural responses to climate change that we can organize into the following four threat categories. (i) Winter temperature and snow cover. Terrestrial gastropods use different strategies to survive sub-zero temperatures in buffered refuges, such as the litter or the soil. Absence of the insulating snow cover exposes species to high variability in temperature. The extent of specific cold tolerance might influence the potential of local extinction, but also of invasion. (ii) Drought and high temperature. Physiological responses involve high-cost processes that protect against heat and dehydration. Some species decrease activity periods, thereby reducing foraging and reproduction time. Related costs and physiological limits are expected to increase mortality. (iii) Extreme events. Although some terrestrial gastropod communities can have a good resilience to fire, storms and flooding, an increase in the frequency of those events might lead to community impoverishment. (iv) Habitat loss and fragmentation. Given that terrestrial gastropods are poorly mobile, landscape alteration generally results in an increased risk of local extinction, but responses are highly variable between species, requiring studies at the population level. There is a great need for studies involving non-invasive methods on the plasticity of physiological and behavioural responses and the ability for local adaptation, considering the spatiotemporally heterogeneous climatic landscape, to allow efficient management of ecosystems and conservation of biodiversity. PMID:28852510

Historical and modern disturbance regimes, stand structures, and landscape dynamics in piñon-juniper vegetation of the western United States

USGS Publications Warehouse

Romme, William H.; Allen, Craig D.; Bailey, John D.; Baker, William L.; Bestelmeyer, Brandon T.; Brown, Peter M.; Eisenhart, Karen S.; Floyd, M. Lisa; Huffman, David W.; Jacobs, Brian F.; Miller, Richard F.; Muldavin, Esteban H.; Swetnam, Thomas W.; Tausch, Robin J.; Weisberg, Peter J.

2009-01-01

Piñon–juniper is a major vegetation type in western North America. Effective management of these ecosystems has been hindered by inadequate understanding of 1) the variability in ecosystem structure and ecological processes that exists among the diverse combinations of piñons, junipers, and associated shrubs, herbs, and soil organisms; 2) the prehistoric and historic disturbance regimes; and 3) the mechanisms driving changes in vegetation structure and composition during the past 150 yr. This article summarizes what we know (and don't know) about three fundamentally different kinds of piñon–juniper vegetation. Persistent woodlands are found where local soils, climate, and disturbance regimes are favorable for piñon, juniper, or a mix of both; fires have always been infrequent in these woodlands. Piñon–juniper savannas are found where local soils and climate are suitable for both trees and grasses; it is logical that low-severity fires may have maintained low tree densities before disruption of fire regimes following Euro-American settlement, but information is insufficient to support any confident statements about historical disturbance regimes in these savannas. Wooded shrublands are found where local soils and climate support a shrub community, but trees can increase during moist climatic conditions and periods without disturbance and decrease during droughts and following disturbance. Dramatic increases in tree density have occurred in portions of all three types of piñon–juniper vegetation, although equally dramatic mortality events have also occurred in some areas. The potential mechanisms driving increases in tree density—such as recovery from past disturbance, natural range expansion, livestock grazing, fire exclusion, climatic variability, and CO2 fertilization—generally have not received enough empirical or experimental investigation to predict which is most important in any given location. The intent of this synthesis is 1) to provide a source of information for managers and policy makers; and 2) to stimulate researchers to address the most important unanswered questions.

Conservation at a slow pace: terrestrial gastropods facing fast-changing climate.

PubMed

Nicolai, Annegret; Ansart, Armelle

2017-01-01

The climate is changing rapidly, and terrestrial ectotherms are expected to be particularly vulnerable to changes in temperature and water regime, but also to an increase in extreme weather events in temperate regions. Physiological responses of terrestrial gastropods to climate change are poorly studied. This is surprising, because they are of biodiversity significance among litter-dwelling species, playing important roles in ecosystem function, with numerous species being listed as endangered and requiring efficient conservation management. Through a summary of our ecophysiological work on snail and slug species, we gained some insights into physiological and behavioural responses to climate change that we can organize into the following four threat categories. (i) Winter temperature and snow cover. Terrestrial gastropods use different strategies to survive sub-zero temperatures in buffered refuges, such as the litter or the soil. Absence of the insulating snow cover exposes species to high variability in temperature. The extent of specific cold tolerance might influence the potential of local extinction, but also of invasion. (ii) Drought and high temperature. Physiological responses involve high-cost processes that protect against heat and dehydration. Some species decrease activity periods, thereby reducing foraging and reproduction time. Related costs and physiological limits are expected to increase mortality. (iii) Extreme events. Although some terrestrial gastropod communities can have a good resilience to fire, storms and flooding, an increase in the frequency of those events might lead to community impoverishment. (iv) Habitat loss and fragmentation. Given that terrestrial gastropods are poorly mobile, landscape alteration generally results in an increased risk of local extinction, but responses are highly variable between species, requiring studies at the population level. There is a great need for studies involving non-invasive methods on the plasticity of physiological and behavioural responses and the ability for local adaptation, considering the spatiotemporally heterogeneous climatic landscape, to allow efficient management of ecosystems and conservation of biodiversity.

Providing more informative projections of climate change impact on plant distribution in a mountain environment

NASA Astrophysics Data System (ADS)

Randin, C.; Engler, R.; Pearman, P.; Vittoz, P.; Guisan, A.

2007-12-01

Due to their conic shape and the reduction of area with increasing elevation, mountain ecosystems were early identified as potentially very sensitive to global warming. Moreover, mountain systems may experience unprecedented rates of warming during the next century, two or three times higher than that records of the 20th century. In this context, species distribution models (SDM) have become important tools for rapid assessment of the impact of accelerated land use and climate change on the distribution plant species. In this study, we developed and tested new predictor variables for species distribution models (SDM), specific to current and future geographic projections of plant species in a mountain system, using the Western Swiss Alps as model region. Since meso- and micro-topography are relevant to explain geographic patterns of plant species in mountain environments, we assessed the effect of scale on predictor variables and geographic projections of SDM. We also developed a methodological framework of space-for-time evaluation to test the robustness of SDM when projected in a future changing climate. Finally, we used a cellular automaton to run dynamic simulations of plant migration under climate change in a mountain landscape, including realistic distance of seed dispersal. Results of future projections for the 21st century were also discussed in perspective of vegetation changes monitored during the 20th century. Overall, we showed in this study that, based on the most severe A1 climate change scenario and realistic dispersal simulations of plant dispersal, species extinctions in the Western Swiss Alps could affect nearly one third (28.5%) of the 284 species modeled by 2100. With the less severe B1 scenario, only 4.6% of species are predicted to become extinct. However, even with B1, 54% (153 species) may still loose more than 80% of their initial surface. Results of monitoring of past vegetation changes suggested that plant species can react quickly to the warmer conditions as far as competition is low However, in subalpine grasslands, competition of already present species is probably important and limit establishment of newly arrived species. Results from future simulations also showed that heavy extinctions of alpine plants may start already in 2040, but the latest in 2080. Our study also highlighted the importance of fine scale and regional assessments of climate change impact on mountain vegetation, using more direct predictor variables. Indeed, predictions at the continental scale may fail to predict local refugees or local extinctions, as well as loss of connectivity between local populations. On the other hand, migrations of low-elevation species to higher altitude may be difficult to predict at the local scale.

300 Years of East African Climate Variability from Oxygen Isotopes in a Kenya Coral

NASA Astrophysics Data System (ADS)

Dunbar, R.

2003-04-01

Instrumental records of climate variability from the western Indian Ocean are relatively scarce and short. Here I present a monthly resolution stable isotopic record acquired from a large living coral head (Porites) from the Malindi Marine Reserve, Kenya (3^oS, 40^oE). The annual chronology is precise and is based on exceptionally clear high and low density growth band couplets. The record extends from 1696 to 1996 A.D., making it the longest coral climate record from the Indian Ocean and one of the longest available worldwide. We have analyzed the uppermost portion of the coral colony in triplicate, using 3 separate cores. This upper section, used for calibration purposes, also provides estimates of signal fidelity and noise in the climate recording system internal to the colony. Coral δ18O at this site primarily records SST; linear regression of monthly coral δ18O vs. SST yields a slope of -0.26 ppm δ18O per ^oC, and δ18O explains ˜57% of the SST variance. Additional isotopic variability may result from changes in seawater δ18O due to local runoff or regional evaporation/precipitation balance, but these changes are likely to be small because local rainfall δ18O is not strongly depleted relative to seawater and salinity gradients are small. The coral record indicates a clear warming trend of about 1.5^oC that accelerates in the latest 20th century, superimposed on strong decadal variability that persists throughout the record. In fact, δ18O values in the 1990's exceed the 300 year envelope (they are lower) and correspond with apparently unprecedented coral bleaching in coastal East Africa. The decadal component of the Malindi coral record reflects a regional climate signal spanning much of the western equatorial Indian Ocean. In general, East African SST and rainfall are better correlated with Pacific ENSO indicators than with the Indian Monsoon at all periods (inter-annual through multi-decadal) but the correlation weakens after 1975. One dramatic new result we report here is a strong indication of a major cool and dry period from 1750--1820 A.D. This is the single largest multi-decadal anomaly of the past 300 years and correlates perfectly in time with the historically and anecdotally defined Lapanarat Drought. Our results indicate a strong link between multi-decadal tropical cold SST anomalies And far-reaching continental droughts in East Africa. Causes and links to other climate recording systems will be explored. Interannual-decadal SST variations are strongly coherent with ENSO indices and other ENSO-sensitive coral records on decadal and interannual time scales. The decadal component of the Malindi coral record reflects a regional climate signal spanning much of the western equatorial Indian Ocean. Previous work has argued that this component likely reflects a monsoonal influence. However, decadal variance in both Malindi and Seychelles (Charles et al. 1997) coral records is more strongly coherent with ENSO indices than with the India or East Africa rain indices. The coherency of both coral records with Pacific indicators suggests instead that Indian Ocean variability reflects decadal ENSO-like variability originating in the Pacific. These records don't correlate significantly with the Pacific Decadal Oscillation implying a dominant role for the tropical Pacific (as opposed to extra-tropical regions) as a source of regional decadal variability in the western Indian Ocean. This work confirms that the tropical Pacific can act as an agent of decadal climate variability over a very large spatial scale.

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.

Climate-related relative sea-level changes from Chesapeake Bay, U.S. Atlantic coast

NASA Astrophysics Data System (ADS)

Shaw, Timothy; Horton, Benjamin; Kemp, Andrew; Cahill, Niamh; Mann, Michael; Engelhart, Simon; Kopp, Robert; Brain, Matthew; Clear, Jennifer; Corbett, Reide; Nikitina, Daria; Garcia-Artola, Ane; Walker, Jennifer

2017-04-01

Proxy-based reconstructions of relative sea level (RSL) from the coastlines of the North Atlantic have revealed spatial and temporal variability in the rates of RSL rise during periods of known Late-Holocene climatic variability. Regional driving mechanisms for such variability include glacial isostatic adjustment, static-equilibrium of land-ice changes and/or ocean dynamic effects as well as more localized factors (e.g. sediment compaction and tidal range change). We present a 4000-year RSL reconstruction from salt-marsh sediments of the Chesapeake Bay using a foraminiferal-based transfer function and a composite chronology. A local contemporary training set of foraminifera was developed to calibrate fossil counterparts and provide estimates of paleo marsh elevation with vertical uncertainties of ±0.06m. A composite chronology combining 30 radiocarbon dates, pollen chronohorizons, regional pollution histories, and short-lived radionuclides was placed into a Bayesian age-depth framework yielding low temporal uncertainties averaging 40 years. A compression-only geotechnical model was applied to decompact the RSL record. We coupled the proxy reconstruction with direct observations from nearby tide gauge records before rates of RSL rise were quantified through application of an Errors-In-Variables Integrated Gaussian Process model. The RSL history for Chesapeake Bay shows 6 m of rise since 2000 BCE. Between 2000 BCE and 1300 BCE, rates of RSL increasing to 1.4 mm/yr precede a significant decrease to 0.8 mm/yr at 700 BCE. This minimum coincides with widespread climate cooling identified in multiple paleoclimate archives of the North Atlantic. An increase in the rate of RSL rise to 2.1 mm/yr at 200 CE similarly precedes a decrease in the rate of RSL rise at 1450 CE (1.3 mm/yr) that coincides with the Little Ice Age. Modern rates of RSL rise (3.6 mm/yr) are the fastest observed in the past 4000 years. The temporal length and decadal resolution of the RSL reconstruction further reconciles the response of sea levels to late Holocene climate variability.

Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

NASA Astrophysics Data System (ADS)

Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.

Southern African continental climate since the late Pleistocene: Insights from biomarker analyses of Kalahari salt pan sediments

NASA Astrophysics Data System (ADS)

Belz, Lukas; Schüller, Irka; Wehrmann, Achim; Wilkes, Heinz

2016-04-01

The climate system of sub-tropical southern Africa is mainly controlled by large scale atmospheric and marine circulation processes and, therefore, very sensitive to global climate change. This underlines the importance of paleoenvironmental reconstructions in order to estimate regional implications of current global changes. However, the majority of studies on southern African paleoclimate are based on the investigation of marine sedimentary archives and past climate development especially in continental areas is still poorly understood. This emphasizes the necessity of continental proxy-data from this area. Proxy datasets from local geoarchives especially of the southwestern Kalahari region are still scarce. A main problem is the absence of conventional continental climatic archives, due to the lack of lacustrine systems. In this study we are exploring the utility of sediments from western Kalahari salt pans, i.e. local depressions which are flooded temporarily during rainfall events. An age model based on 14C dating of total organic carbon (TOC) shows evidence that sedimentation predominates over erosional processes with respect to pan formation. Besides the analyses of basic geochemical bulk parameters including TOC, δ13CTOC, total inorganic carbon, δ13CTIC, δ18OTIC, total nitrogen and δ15N, our paleo-climatic approach focuses on reconstruction of local vegetation assemblages to identify changes in the ecosystem. This is pursued using plant biomarkers, particularly leaf wax n-alkanes and n-alcohols and their stable carbon and hydrogen isotopic signatures. Results show prominent shifts in n-alkane and n-alkanol distributions and compound specific carbon isotope values, pointing to changes to a more grass dominated environment during Heinrich Stadial 1 (18.5-14.6 ka BP), while hydrogen isotope values suggest wetter phases during Holocene and LGM. This high variability indicates the local vulnerability to global change.

Pacific Islands Regional Climate Assessment: Building a Framework to Track Physical and Social Indicators of Climate Change Across Pacific Islands

NASA Astrophysics Data System (ADS)

Grecni, Z. N.; Keener, V. W.

2016-12-01

Assessments inform regional and local climate change governance and provide the critical scientific basis for U.S. climate policy. Despite the centrality of scientific information to public discourse and decision making, comprehensive assessments of climate change drivers, impacts, and the vulnerability of human and ecological systems at regional or local scales are often conducted on an ad hoc basis. Methods for sustained assessment and communication of scientific information are diverse and nascent. The Pacific Islands Regional Climate Assessment (PIRCA) is a collaborative effort to assess climate change indicators, impacts, and adaptive capacity of the Hawaiian archipelago and the US-Affiliated Pacific Islands (USAPI). In 2012, PIRCA released the first comprehensive report summarizing the state of scientific knowledge about climate change in the region as a technical input to the U.S. National Climate Assessment. A multi-method evaluation of PIRCA outputs and delivery revealed that the vast majority of key stakeholders view the report as extremely credible and use it as a resource. The current study will present PIRCA's approach to establishing physical and social indicators to track on an ongoing basis, starting with the Republic of the Marshall Islands as an initial location of focus for providing a cross-sectoral indicators framework. Identifying and tracking useful indicators is aimed at sustaining the process of knowledge coproduction with decision makers who seek to better understand the climate variability and change and its impacts on Pacific Island communities.

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

PubMed Central

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

2016-01-01

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901–2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011–2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data. PMID:27275583

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

PubMed

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

2016-01-01

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

Tectonics, orbital forcing, global climate change, and human evolution in Africa: introduction to the African paleoclimate special volume.

PubMed

Maslin, Mark A; Christensen, Beth

2007-11-01

The late Cenozoic climate of Africa is a critical component for understanding human evolution. African climate is controlled by major tectonic changes, global climate transitions, and local variations in orbital forcing. We introduce the special African Paleoclimate Issue of the Journal of Human Evolution by providing a background for and synthesis of the latest work relating to the environmental context for human evolution. Records presented in this special issue suggest that the regional tectonics, appearance of C(4) plants in East Africa, and late Cenozoic global cooling combined to produce a long-term drying trend in East Africa. Of particular importance is the uplift associated with the East African Rift Valley formation, which altered wind flow patterns from a more zonal to more meridinal direction. Results in this volume suggest a marked difference in the climate history of southern and eastern Africa, though both are clearly influenced by the major global climate thresholds crossed in the last 3 million years. Papers in this volume present lake, speleothem, and marine paleoclimate records showing that the East African long-term drying trend is punctuated by episodes of short, alternating periods of extreme wetness and aridity. These periods of extreme climate variability are characterized by the precession-forced appearance and disappearance of large, deep lakes in the East African Rift Valley and paralleled by low and high wind-driven dust loads reaching the adjacent ocean basins. Dating of these records show that over the last 3 million years such periods only occur at the times of major global climatic transitions, such as the intensification of Northern Hemisphere Glaciation (2.7-2.5 Ma), intensification of the Walker Circulation (1.9-1.7 Ma), and the Mid-Pleistocene Revolution (1-0.7 Ma). Authors in this volume suggest this onset occurs as high latitude forcing in both Hemispheres compresses the Intertropical Convergence Zone so that East Africa becomes locally sensitive to precessional forcing, resulting in rapid shifts from wet to dry conditions. These periods of extreme climate variability may have provided a catalyst for evolutionary change and driven key speciation and dispersal events amongst mammals and hominins in Africa. In particular, hominin species seem to differentially originate and go extinct during periods of extreme climate variability. Results presented in this volume may represent the basis of a new theory of early human evolution in Africa.

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.

Vulnerability of island tropical montane cloud forests to climate change, with special reference to East Maui, Hawaii

USGS Publications Warehouse

Loope, Lloyd L.; Giambelluca, Thomas W.

1998-01-01

Island tropical montane cloud forests may be among the most sensitive of the world's ecosystems to global climate change. Measurements in and above a montane cloud forest on East Maui, Hawaii, document steep microclimatic gradients. Relatively small climate-driven shifts in patterns of atmospheric circulation are likely to trigger major local changes in rainfall, cloud cover, and humidity. Increased interannual variability in precipitation and hurricane incidence would provide additional stresses on island biota that are highly vulnerable to disturbance-related invasion of non-native species. Because of the exceptional sensitivity of these microclimates and forests to change, they may provide valuable ‘listening posts’ for detecting the onset of human-induced global climate change.

Complexity of Tropical Pacific Ecosystem and Biogeochemistry: Diurnal to Decadal, Plankters to Penguins

NASA Astrophysics Data System (ADS)

Murtugudde, R. G.; Wang, X.; Valsala, V.; Karnauskas, K. B.

2016-12-01

Tropical Pacific spans nearly 50% of the global tropics allowing to have its own mind in terms of climate variability and physical-biogeochemical interactions. While the El Niño-Southern Oscillation (ENSO) and its flavors get much attention, it is fairly clear by now that any further improvements in ENSO prediction skills and reliability of global warming projections must begin to observe and represent bio-physical interactions in the climate and Earth System models. Coupled climate variability over the tropical Pacific has a global reach with its diurnal to decadal timescales being manifest in ecosystem and biogechemistry. Zonal and meridional contrasts in biogeochemistry across the tropical Pacific is closely related to seasonal variability, ENSO diversity and the PDO. Apparent dominance of ocean dynamic controls on biogeochemistry belies the potential biogeochemical feedbacks on ocean dynamics which may well explain some of the chronic biases in the state-of-the-art climate models. The east Pacific cold-tongue is the most productive open ocean region in the world and home to a unique physical-biogeochmical laboratory, viz., the Galapagos. The Galapagos islands not only control the coupled climate variability via their ability to terminate the equatorial undercurrent but also offer a clear example of a biological loophole in terms of their impact on local upwelling and an expanding penguin habitat in the face of global warming. The complex bio-physical interactions in the cold-tongue and their influence on climate predictions and projections require a holisti thinking on future observing systems. Tropical Pacific offers a natural laboratory for designing a robust and sustained physical-biogeochemical observation system that can effectively bridge climate predictions and projections into a unified framework for subseasonal to multidecadal timescales. Such a system will be a foundation for establishing similar systems over the rest of the World ocean to seemlessly merge climate predictions and projections with the need to constantly monitor climate impacts on marine resources. This talk will focus on the zonal contrasts of the ocean dynamics and biogechemistry across the tropical Pacific to make a case for integrated physical-biogeochemical observations for climate predictions and projections.

Towards a high resolution, integrated hydrology model of North America.

NASA Astrophysics Data System (ADS)

Maxwell, R. M.; Condon, L. E.

2015-12-01

Recent studies demonstrate feedbacks between groundwater dynamics, overland flow, land surface and vegetation processes, and atmospheric boundary layer development that significantly affect local and regional climate across a range of climatic conditions. Furthermore, the type and distribution of vegetation cover alters land-atmosphere water and energy fluxes, as well as runoff generation and overland flow processes. These interactions can result in significant feedbacks on local and regional climate. In mountainous regions, recent research has shown that spatial and temporal variability in annual evapotranspiration, and thus water budgets, is strongly dependent on lateral groundwater flow; however, the full effects of these feedbacks across varied terrain (e.g. from plains to mountains) are not well understood. Here, we present a high-resolution, integrated hydrology model that covers much of continental North America and encompasses the Mississippi and Colorado watersheds. The model is run in a fully-transient manner at hourly temporal resolution incorporating fully-coupled land energy states and fluxes with integrated surface and subsurface hydrology. Connections are seen between hydrologic variables (such as water table depth) and land energy fluxes (such as latent heat) and spatial and temporal scaling is shown to span many orders of magnitude. Using these transient simulations as a proof of concept, we present a vision for future integrated simulation capabilities.

Climate change impact assessment on food security in Indonesia

NASA Astrophysics Data System (ADS)

Ettema, Janneke; Aldrian, Edvin; de Bie, Kees; Jetten, Victor; Mannaerts, Chris

2013-04-01

As Indonesia is the world's fourth most populous country, food security is a persistent challenge. The potential impact of future climate change on the agricultural sector needs to be addressed in order to allow early implementation of mitigation strategies. The complex island topography and local sea-land-air interactions cannot adequately be represented in large scale General Climate Models (GCMs) nor visualized by TRMM. Downscaling is needed. Using meteorological observations and a simple statistical downscaling tool, local future projections are derived from state-of-the-art, large-scale GCM scenarios, provided by the CMIP5 project. To support the agriculture sector, providing information on especially rainfall and temperature variability is essential. Agricultural production forecast is influenced by several rain and temperature factors, such as rainy and dry season onset, offset and length, but also by daily and monthly minimum and maximum temperatures and its rainfall amount. A simple and advanced crop model will be used to address the sensitivity of different crops to temperature and rainfall variability, present-day and future. As case study area, Java Island is chosen as it is fourth largest island in Indonesia but contains more than half of the nation's population and dominates it politically and economically. The objective is to identify regions at agricultural risk due to changing patterns in precipitation and temperature.

Temporal variation in pelagic food chain length in response to environmental change

PubMed Central

Ruiz-Cooley, Rocio I.; Gerrodette, Tim; Fiedler, Paul C.; Chivers, Susan J.; Danil, Kerri; Ballance, Lisa T.

2017-01-01

Climate variability alters nitrogen cycling, primary productivity, and dissolved oxygen concentration in marine ecosystems. We examined the role of this variability (as measured by six variables) on food chain length (FCL) in the California Current (CC) by reconstructing a time series of amino acid–specific δ15N values derived from common dolphins, an apex pelagic predator, and using two FCL proxies. Strong declines in FCL were observed after the 1997–1999 El Niño Southern Oscillation (ENSO) event. Bayesian models revealed longer FCLs under intermediate conditions for surface temperature, chlorophyll concentration, multivariate ENSO index, and total plankton volume but not for hypoxic depth and nitrate concentration. Our results challenge the prevalent paradigm that suggested long-term stability in the food web structure in the CC and, instead, reveal that pelagic food webs respond strongly to disturbances associated with ENSO events, local oceanography, and ongoing changes in climate. PMID:29057322

Cross-continent comparisons reveal differing environmental drivers of growth of the coral reef fish, Lutjanus bohar

NASA Astrophysics Data System (ADS)

Ong, Joyce J. L.; Rountrey, Adam N.; Marriott, Ross J.; Newman, Stephen J.; Meeuwig, Jessica J.; Meekan, Mark G.

2017-03-01

Biochronologies provide important insights into the growth responses of fishes to past variability in physical and biological environments and, in so doing, allow modelling of likely responses to climate change in the future. We examined spatial variability in the key drivers of inter-annual growth patterns of a widespread, tropical snapper, Lutjanus bohar, at similar tropical latitudes on the north-western and north-eastern coasts of the continent of Australia. For this study, we developed biochronologies from otoliths that provided proxies of somatic growth and these were analysed using mixed-effects models to examine the historical drivers of growth. Our analyses demonstrated that growth patterns of fish were driven by different climatic and biological factors in each region, including Pacific Ocean climate indices, regional sea level and the size structure of the fish community. Our results showed that the local oceanographic and biological context of reef systems strongly influenced the growth of L. bohar and that a single age-related growth trend cannot be assumed for separate populations of this species that are likely to experience different environmental conditions. Generalised predictions about the growth response of fishes to climate change will thus require adequate characterisation of the spatial variability in growth determinants likely to be found throughout the range of species that have cosmopolitan distributions.

Land Change Trends in the Great Plains: Linkages to Climate Variability and Socioeconomic Drivers

NASA Astrophysics Data System (ADS)

Drummond, M. A.

2009-12-01

Land use and land cover change have complex linkages to climate variability and change, socioeconomic driving forces, and land management challenges. To assess these land change dynamics and their driving forces in the Great Plains, we compare and contrast contemporary land conversion across seventeen ecoregions using Landsat remote sensing data and statistical analysis. Large area change analysis in agricultural regions is often hampered by the potential for substantial change detection error and the tendency for land conversions to occur in relatively small patches at the local level. To facilitate a regional scale analysis, a statistical sampling design of randomly selected 10-km by 10-km blocks is used in order to efficiently identify the types and rates of land conversions for four time periods between 1972 and 2000, stratified by relatively homogenous ecoregions. Results show a range of rates and processes of land change that vary by ecoregion contingent on the prevailing interactions between socioeconomic and environmental factors such as climate variability, water availability, and land quality. Ecoregions have differential climate and biophysical advantages for agricultural production and other land use change. Human actions further strengthen or dampen the characteristics of change through farm policy, technological advances, economic opportunities, population and demographic shifts, and surface and groundwater irrigation.

Spatiotemporal drought variability of the eastern Tibetan Plateau during the last millennium

NASA Astrophysics Data System (ADS)

Deng, Yang; Gou, Xiaohua; Gao, Linlin; Yang, Meixue; Zhang, Fen

2017-09-01

Tibetan Plateau is the headwater region of many major Asian rivers and very susceptive to climate change. Therefore, knowledge about climate and its spatiotemporal variability in this area is very important for ecological conservation, water resource management and social development. The aim of this study was to reconstruct and analyze the hydroclimate variation on eastern Tibetan Plateau (ETP) over many centuries and explore possible forcing factors on regional hydroclimate variability. We used 118 tree-ring chronologies from ETP to reconstruct the gridded May-July Standardized Precipitation Evapotranspiration Index for the ETP over the last millennium. The reconstruction was developed using an ensemble point-by-point reconstruction method, and a searching region method was used to locate the candidate tree-ring chronologies. The reconstructions have nicely captured the spatial and temporal features of the regional drought variation. The drought variations in south and north of 32.5°N are notably different, which may be related to the divergence influence of North Atlantic Oscillation on the climate systems in the south and north, as well as differences in local climate. Spectral analysis and series comparison suggest that the drought variation in the northeastern Tibetan Plateau has been possibly influenced by solar activity on centurial and longer time scale.

Eastern South African hydroclimate over the past 270,000 years

NASA Astrophysics Data System (ADS)

Simon, Margit H.; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J. C.; Hall, Ian R.

2015-12-01

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique.

Eastern South African hydroclimate over the past 270,000 years.

PubMed

Simon, Margit H; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J C; Hall, Ian R

2015-12-21

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique.

Eastern South African hydroclimate over the past 270,000 years

PubMed Central

Simon, Margit H.; Ziegler, Martin; Bosmans, Joyce; Barker, Stephen; Reason, Chris J.C.; Hall, Ian R.

2015-01-01

Processes that control the hydrological balance in eastern South Africa on orbital to millennial timescales remain poorly understood because proxy records documenting its variability at high resolution are scarce. In this work, we present a detailed 270,000 year-long record of terrestrial climate variability in the KwaZulu-Natal province based on elemental ratios of Fe/K from the southwest Indian Ocean, derived from X-ray fluorescence core scanning. Eastern South African climate variability on these time scales reflects both the long-term effect of regional insolation changes driven by orbital precession and the effects associated with high-latitude abrupt climate forcing over the past two glacial-interglacial cycles, including millennial-scale events not previously identified. Rapid changes towards more humid conditions in eastern South Africa as the Northern Hemisphere entered phases of extreme cooling were potentially driven by a combination of warming in the Agulhas Current and shifts of the subtropical anticyclones. These climate oscillations appear coherent with other Southern Hemisphere records but are anti-phased with respect to the East Asian Monsoon. Numerical modelling results reveal that higher precipitation in the KwaZulu-Natal province during precession maxima is driven by a combination of increased local evaporation and elevated moisture transport into eastern South Africa from the coast of Mozambique. PMID:26686943

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Evaluating interannual variability in speleothem records of North American monsoon rainfall

NASA Astrophysics Data System (ADS)

Truebe, S. A.; Cole, J. E.; Ault, T. R.; Kimbrough, A.; Henderson, G. M.; Barmett, H.; Hlohowskyj, S.

2013-12-01

Speleothems can produce long, high resolution, absolutely-dated records of past climate. They are especially useful for past climate reconstruction in areas such as the southwestern United States, where traditional sources of past climate information (corals, lake or ocean sediments, ice cores) are absent. Here we present two records of Holocene rainfall variability from two Arizona caves less than 40km apart: Cave of the Bells (COB) and Fort Huachuca Cave (FHC), spanning 7000 and 4000 years respectively. Both records show a trend towards more negative oxygen isotope values into the modern era. Extensive monthly monitoring suggests that speleothem oxygen isotope composition is an average of the oxygen isotope composition of the summer North American monsoon (NAM) and winter frontal storms, with a bias towards winter likely due to lack of infiltration of intense monsoon rainfall. This bias is stronger in COB than in FHC. Winter rainfall has had an increasing influence at both sites from the mid-Holocene until the present; in other words, the NAM has been weakening over the past few thousand years, in step with changes in other monsoon systems and Northern Hemisphere insolation. Although the records are similar in overall trend, short-term variability is inconsistent. When providing information to water managers about future rainfall availability in the Southwest, having only millennial-scale information does not help much! To investigate the differences between the two records, we use a combination of approaches, including assessing age model uncertainty and modern climate heterogeneity, and monitoring cave-specific processes that may be overprinting the climate signal. We assess age model uncertainty using a statistical age-modeling program, which allows us to develop many physically plausible time series for the same age-depth data. With this age modeling tool, we critically assess whether particular isotope excursions correspond between speleothems and if they are temporally related to global climate events. However, even correlation and coherence analyses across the suites of time series for each speleothem do not elicit a common high-frequency climate story. We further investigate the discrepancy between cave records by assessing modern climate heterogeneity using historical observations. Climate in the arid Southwest is spatially heterogeneous, especially during the summer monsoon, contributing to the mismatch between these two climate records. Finally, after a decade of monitoring at COB, we recognize that storage and mixing in the epikarst above the cave affect what parts (if any) of the seasonal signal are recorded in a speleothem. In addition to new insights about North American monsoon behavior during the Holocene, the important lesson from these speleothem records is that in caves, because of underlying (overlying?) climate heterogeneity, replication of a common climate signal using oxygen isotopes may be an unattainable goal. The COB and FHC records may record very local climate at their respective locations, overprinted by water storage and mixing in the epikarst. Very local-scale reconstructions of past rainfall variability from speleothems can still be useful and important, if interpreted for what they are.

New insights into the use of stable water isotopes at the northern Antarctic Peninsula as a tool for regional climate studies

NASA Astrophysics Data System (ADS)

Fernandoy, Francisco; Tetzner, Dieter; Meyer, Hanno; Gacitúa, Guisella; Hoffmann, Kirstin; Falk, Ulrike; Lambert, Fabrice; MacDonell, Shelley

2018-03-01

Due to recent atmospheric and oceanic warming, the Antarctic Peninsula is one of the most challenging regions of Antarctica to understand in terms of both local- and regional-scale climate signals. Steep topography and a lack of long-term and in situ meteorological observations complicate the extrapolation of existing climate models to the sub-regional scale. Therefore, new techniques must be developed to better understand processes operating in the region. Isotope signals are traditionally related mainly to atmospheric conditions, but a detailed analysis of individual components can give new insight into oceanic and atmospheric processes. This paper aims to use new isotopic records collected from snow and firn cores in conjunction with existing meteorological and oceanic datasets to determine changes at the climatic scale in the northern extent of the Antarctic Peninsula. In particular, a discernible effect of sea ice cover on local temperatures and the expression of climatic modes, especially the Southern Annular Mode (SAM), is demonstrated. In years with a large sea ice extension in winter (negative SAM anomaly), an inversion layer in the lower troposphere develops at the coastal zone. Therefore, an isotope-temperature relationship (δ-T) valid for all periods cannot be obtained, and instead the δ-T depends on the seasonal variability of oceanic conditions. Comparatively, transitional seasons (autumn and spring) have a consistent isotope-temperature gradient of +0.69 ‰ °C-1. As shown by firn core analysis, the near-surface temperature in the northern-most portion of the Antarctic Peninsula shows a decreasing trend (-0.33 °C year-1) between 2008 and 2014. In addition, the deuterium excess (dexcess) is demonstrated to be a reliable indicator of seasonal oceanic conditions, and therefore suitable to improve a firn age model based on seasonal dexcess variability. The annual accumulation rate in this region is highly variable, ranging between 1060 and 2470 kg m-2 year-1 from 2008 to 2014. The combination of isotopic and meteorological data in areas where data exist is key to reconstruct climatic conditions with a high temporal resolution in polar regions where no direct observations exist.

Participatory data collection and monitoring of agricultural pest dynamics for climate-resilient coffee production using Tiko'n, a generic tool to develop agroecological food web models

NASA Astrophysics Data System (ADS)

Rojas, M.; Malard, J. J.; Adamowski, J. F.; Tuy, H.

2016-12-01

Climate variability impacts agricultural processes through many mechanisms. For example, the proliferation of pests and diseases increases with warmer climate and alternated wind patterns, as longer growing seasons allow pest species to complete more reproductive cycles and changes in the weather patterns alter the stages and rates of development of pests and pathogens. Several studies suggest that enhancing plant diversity and complexity in farming systems, such as in agroforestry systems, reduces the vulnerability of farms to extreme climatic events. On the other hand, other authors have argued that vegetation diversity does not necessarily reduce the incidence of pests and diseases, highlighting the importance of understanding how, where and when it is recommendable to diversify vegetation to improve pest and disease control, and emphasising the need for tools to develop, monitor and evaluate agroecosystems. In order to understand how biodiversity can enhance ecosystem services provided by the agroecosystem in the context of climatic variability, it is important to develop comprehensive models that include the role of trophic chains in the regulation of pests, which can be achieved by integrating crop models with pest-predator models, also known as agroecosystem network (AEN) models. Here we present a methodology for the participatory data collection and monitoring necessary for running Tiko'n, an AEN model that can also be coupled to a crop model such as DSSAT. This methodology aims to combine the local and practical knowledge of farmers with the scientific knowledge of entomologists and agronomists, allowing for the simplification of complex ecological networks of plant and insect interactions. This also increases the acceptability, credibility, and comprehension of the model by farmers, allowing them to understand their relationship with the local agroecosystem and their potential to use key agroecosystem principles such as functional diversity to mitigate climate variability impacts. Preliminary results of a study currently being conducted in a coffee agroforestry system in El Quebracho, Guatemala, will be presented, where the data was directly collected by farmers during eight consecutive months. Finally, future recommendations from lessons learnt during this study will be discussed.

Using Citizen Science Data to Model the Distributions of Common Songbirds of Turkey Under Different Global Climatic Change Scenarios

PubMed Central

Abolafya, Moris; Onmuş, Ortaç; Şekercioğlu, Çağan H.; Bilgin, Raşit

2013-01-01

In this study, we evaluated the potential impact of climate change on the distributions of Turkey’s songbirds in the 21st century by modelling future distributions of 20 resident and nine migratory species under two global climate change scenarios. We combined verified data from an ornithological citizen science initiative (www.kusbank.org) with maximum entropy modeling and eight bioclimatic variables to estimate species distributions and projections for future time periods. Model predictions for resident and migratory species showed high variability, with some species projected to lose and others projected to gain suitable habitat. Our study helps improve the understanding of the current and potential future distributions of Turkey’s songbirds and their responses to climate change, highlights effective strategies to maximize avian conservation efforts in the study region, and provides a model for using citizen science data for biodiversity research in a large developing country with few professional field biologists. Our results demonstrate that climate change will not affect every species equally in Turkey. Expected range reductions in some breeding species will increase the risk of local extinction, whereas others are likely to expand their ranges. PMID:23844151

Using citizen science data to model the distributions of common songbirds of Turkey under different global climatic change scenarios.

PubMed

Abolafya, Moris; Onmuş, Ortaç; Şekercioğlu, Çağan H; Bilgin, Raşit

2013-01-01

In this study, we evaluated the potential impact of climate change on the distributions of Turkey's songbirds in the 21st century by modelling future distributions of 20 resident and nine migratory species under two global climate change scenarios. We combined verified data from an ornithological citizen science initiative (www.kusbank.org) with maximum entropy modeling and eight bioclimatic variables to estimate species distributions and projections for future time periods. Model predictions for resident and migratory species showed high variability, with some species projected to lose and others projected to gain suitable habitat. Our study helps improve the understanding of the current and potential future distributions of Turkey's songbirds and their responses to climate change, highlights effective strategies to maximize avian conservation efforts in the study region, and provides a model for using citizen science data for biodiversity research in a large developing country with few professional field biologists. Our results demonstrate that climate change will not affect every species equally in Turkey. Expected range reductions in some breeding species will increase the risk of local extinction, whereas others are likely to expand their ranges.

Leishmaniasis and Climate Change—Case Study: Argentina

PubMed Central

Salomón, Oscar Daniel; Quintana, María Gabriela; Mastrángelo, Andrea Verónica; Fernández, María Soledad

2012-01-01

Vector-borne diseases closely associated with the environment, such as leishmaniases, have been a usual argument about the deleterious impact of climate change on public health. From the biological point of view interaction of different variables has different and even conflicting effects on the survival of vectors and the probability transmission of pathogens. The results on ecoepidemiology of leishmaniasis in Argentina related to climate variables at different scales of space and time are presented. These studies showed that the changes in transmission due to change or increase in frequency and intensity of climatic instability were expressed through changes in the probability of vector-human reservoir effective contacts. These changes of contact in turn are modulated by both direct effects on the biology and ecology of the organisms involved, as by perceptions and changes in the behavior of the human communities at risk. Therefore, from the perspective of public health and state policy, and taking into account the current nonlinear increased velocity of climate change, we concluded that discussing the uncertainties of large-scale models will have lower impact than to develop-validate mitigation strategies to be operative at local level, and compatibles with sustainable development, conservation biodiversity, and respect for cultural diversity. PMID:22685477

The potential impacts of climate variability and change on health impacts of extreme weather events in the United States.

PubMed Central

Greenough, G; McGeehin, M; Bernard, S M; Trtanj, J; Riad, J; Engelberg, D

2001-01-01

Extreme weather events such as precipitation extremes and severe storms cause hundreds of deaths and injuries annually in the United States. Climate change may alter the frequency, timing, intensity, and duration of these events. Increases in heavy precipitation have occurred over the past century. Future climate scenarios show likely increases in the frequency of extreme precipitation events, including precipitation during hurricanes, raising the risk of floods. Frequencies of tornadoes and hurricanes cannot reliably be projected. Injury and death are the direct health impacts most often associated with natural disasters. Secondary effects, mediated by changes in ecologic systems and public health infrastructure, also occur. The health impacts of extreme weather events hinge on the vulnerabilities and recovery capacities of the natural environment and the local population. Relevant variables include building codes, warning systems, disaster policies, evacuation plans, and relief efforts. There are many federal, state, and local government agencies and nongovernmental organizations involved in planning for and responding to natural disasters in the United States. Future research on health impacts of extreme weather events should focus on improving climate models to project any trends in regional extreme events and as a result improve public health preparedness and mitigation. Epidemiologic studies of health effects beyond the direct impacts of disaster will provide a more accurate measure of the full health impacts and will assist in planning and resource allocation. PMID:11359686

Ecosystem Disturbance Effects on Land Surface Temperature, Forest Carbon Stocks, and Primary Productivity in the Western United States

NASA Astrophysics Data System (ADS)

Cooper, L. A.; Ballantyne, A.; Holden, Z. A.; Landguth, E.

2015-12-01

Disturbance plays an important role in the structure, composition, and nutrient cycling of forest ecosystems. Climate change is resulting in an increase in disturbance frequency and intensity, making it critical that we quantify the physical and chemical impacts of disturbances on forests. The impacts of disturbance are thought to vary widely depending on disturbance type, location, and climate. More specifically, fires, insect infestations, and other types of disturbances differ in their timing, extent, and intensity making it difficult to assess the true impact of disturbances on local energy budgets and carbon cycling. Here, we provide a regional analysis of the impacts of fire, insect attack, and other disturbances on land surface temperature (LST), carbon stocks, and gross primary productivity (GPP). Using disturbances detected with MODIS Enhanced Vegetation Index (EVI) time series between 2002 and 2012, we find that the impacts of disturbance on LST, carbon stocks, and GPP vary widely according to local climate, vegetation, and disturbance type and intensity. Fires resulted in the most distinct impacts on all response variables. Forest responses to insect epidemics were more varied in their magnitude and timing. The results of this study provide an important estimation of the variability of climate and ecosystem responses to disturbance across a large and heterogeneous landscape. With disturbance projected to increase in both frequency and intensity around the globe in the coming years, this information is vitally important to effectively manage forests into the future.

Detecting potential anomalies in projections of rainfall trends and patterns using human observations

NASA Astrophysics Data System (ADS)

Kohfeld, K. E.; Savo, V.; Sillmann, J.; Morton, C.; Lepofsky, D.

2016-12-01

Shifting precipitation patterns are a well-documented consequence of climate change, but their spatial variability is particularly difficult to assess. While the accuracy of global models has increased, specific regional changes in precipitation regimes are not well captured by these models. Typically, researchers who wish to detect trends and patterns in climatic variables, such as precipitation, use instrumental observations. In our study, we combined observations of rainfall by subsistence-oriented communities with several metrics of rainfall estimated from global instrumental records for comparable time periods (1955 - 2005). This comparison was aimed at identifying: 1) which rainfall metrics best match human observations of changes in precipitation; 2) areas where local communities observe changes not detected by global models. The collated observations ( 3800) made by subsistence-oriented communities covered 129 countries ( 1830 localities). For comparable time periods, we saw a substantial correspondence between instrumental records and human observations (66-77%) at the same locations, regardless of whether we considered trends in general rainfall, drought, or extreme rainfall. We observed a clustering of mismatches in two specific regions, possibly indicating some climatic phenomena not completely captured by the currently available global models. Many human observations also indicated an increased unpredictability in the start, end, duration, and continuity of the rainy seasons, all of which may hamper the performance of subsistence activities. We suggest that future instrumental metrics should capture this unpredictability of rainfall. This information would be important for thousands of subsistence-oriented communities in planning, coping, and adapting to climate change.

Connecting Stakeholders and Climate Science: A Summary of Farmer, Rancher, and Forester Climate Data Needs and Climate Change Attitudes

NASA Astrophysics Data System (ADS)

Rango, A.; Crimmins, M.; Elias, E.; Steele, C. M.; Weiss, J. L.

2015-12-01

The mission of the USDA Southwest Regional Climate Hub is to provide farmers, ranchers and forest land owners and managers with information and resources to cope with the impacts of climate change. As such, a clear understanding of landowner needs for weather and climate data and their attitudes about climate change is required. Here we present a summary of results from 17 peer-reviewed articles on studies pertaining to landowner needs and attitudes towards climate change adaptation and mitigation that span much of the continental U.S. and ideally represent a cross-section of different geographies. In general, approximately 75% of landowners and farm advisors believe climate change is occurring, but disagree on the human contribution. Studies found that most farmers were supportive of adaptation responses, but fewer endorsed farm-based greenhouse gas reduction mitigation strategies. Adaptation is often driven by local concerns and requires locally specific strategies. Perceiving weather variability increased belief in human-caused climate change. Presently farmers and ranchers rely on past experience and short-range forecasts (weeks to seasons) whereas some foresters are requesting long-term predictions on the order of years to decades. Foresters indicated that most of them (74%) are presently unable to find needed long-term information. We augment peer-reviewed literature with observations from landowner workshops conducted in Nevada and Arizona during 2014, the first year of Climate Hub operation. To better collect information about climate change needs and attitudes of farmers, ranchers and foresters across the globe, we created a Climate Change Attitudes collection in JournalMap (https://journalmap.org/usda-southwest-regional-climate-hub/climate-change-attitudes). Users anywhere can add articles to this collection, ultimately generating a comprehensive spatial resource in support of adaptation and mitigation efforts on working lands.

North Tropical Atlantic Climate Variability and Model Biases

NASA Astrophysics Data System (ADS)

Yang, Y.

2017-12-01

Remote forcing from El Niño-Southern Oscillation (ENSO) and local ocean-atmosphere feedback are important for climate variability over the North Tropical Atlantic. These two factors are extracted by the ensemble mean and inter-member difference of a 10-member Pacific Ocean-Global Atmosphere (POGA) experiment, in which sea surface temperatures (SSTs) are restored to the observed anomalies over the tropical Pacific but fully coupled to the atmosphere elsewhere. POGA reasonably captures main features of observed North Tropical Atlantic variability. ENSO forced and local North Tropical Atlantic modes (NTAMs) develop with wind-evaporation-SST feedback, explaining one third and two thirds of total variance respectively. Notable biases, however, exist. The seasonality of the simulated NTAM is delayed by one month, due to the late development of the North Atlantic Oscillation (NAO) in the model. A spurious band of enhanced sea surface temperature (SST) variance (SBEV) is identified over the northern equatorial Atlantic in POGA and 14 out of 23 CMIP5 models. The SBEV is especially pronounced in boreal spring and due to the combined effect of both anomalous atmospheric thermal forcing and oceanic vertical upwelling. While the tropical North Atlantic variability is only weakly correlated with the Atlantic Zonal Mode (AZM) in observations, the SBEV in CMIP5 produces conditions that drive and intensify the AZM variability via triggering the Bjerknes feedback. This partially explains why AZM is strong in some CMIP5 models even though the equatorial cold tongue and easterly trades are biased low.

Influence of Climate on PM2.5 Concentrations over Europe : a Meteorological Analysis using a 9-year Model Simulation

NASA Astrophysics Data System (ADS)

Lecoeur, À.; Seigneur, C.; Terray, L.; Pagé, C.

2012-04-01

In the early 1970s, it has been demonstrated that a large number of deaths and health problems are associated with particulate pollution. As a consequence, several governments have set health-based air quality standards to protect public health. Particulate matter with an aerodynamical diameter of 2.5 μg.m-3 or less (PM2.5) is particularly concerned by these measures. As PM2.5 concentrations are strongly dependent on meteorological conditions, it is important to investigate the relationships between PM2.5 and meteorological parameters. This will help to understand the processes at play and anticipate the effects of climate change on PM2.5 air quality. Most of the previous work agree that temperature, wind speed, humidity, rain rate and mixing height are the meteorological variables that impact PM2.5 concentrations the most. A large number of those studies used Global Circulation Models (GCM) and Chemical Transport Models (CTM) and focus on the USA. They typically predict a diminution of PM2.5 concentrations in the future, with some geographical and/or temporal discrepancies, when only the climate evolution is considered. When considering changes in emissions along with climate, no consensus has yet been found. Furthermore, the correlations between PM2.5 concentrations and meteorological variables are often low, which prevents a straightforward analysis of their relationships. In this work, we consider that PM2.5 concentrations depend on both large-scale atmospheric circulation and local meteorological variables. We thus investigate the influence of present climate on PM2.5 concentrations over Europe by representing it using a weather regimes/types approach. We start by exploring the relationships between classical weather regimes, meteorological variables and PM2.5 concentrations over five stations in Europe, using the EMEP air quality database. The pressure at sea level is used in the classification as it effectively describes the atmospheric circulation. We experimentally verify some intuitive results: weather regimes associated with weak (resp. high) precipitation, wind and low (resp. high) temperatures correspond to higher (resp. lower) PM2.5 concentrations. We also observe that rain rate is the variable that impacts PM2.5 concentrations the most. Next, we search for better relationships by adding this second variable to the classification: we therefore build new weather regimes, called weather types. Because of the low number of the EMEP observations, we compute PM2.5 concentrations with the Polyphemus/Polair3D CTM for years between 2000 and 2008 in order to obtain a spatially and temporally complete dataset of PM2.5 concentrations and chemical components, which can be used to relate PM2.5 concentrations to meteorological regimes and specific variables. By classifying both a large-scale variable and a local variable that influence the PM2.5 concentrations and using gridded data of the modeled concentrations of PM2.5, we obtain a more robust analysis. The results of this work will provide the basis to predict the effects of climate change (via the evolution of weather regimes/types frequencies) on PM2.5 chemical composition and concentrations.

Regional climate science: lessons and opportunities

NASA Astrophysics Data System (ADS)

Mote, P. W.; Miles, E. L.; Whitely Binder, L.

2008-12-01

Since its founding in 1995, the Climate Impacts Group (CIG) at the University of Washington (UW) has achieved remarkable success at translating global- and regional-scale science into forms and products that are useful to, and used by, decision-makers. From GCM scenarios to research on the connection between global climate patterns and locally important factors like floods and wildfires, CIG's strong physical science foundation is matched by a vigorous and successful outreach program. As a result, CIG and its partner the Office of Washington State Climatologist at UW have made substantial progress at bridging the gap between climate science and decision-making, and are deeply involved in advising all levels of government and many business interests on adapting to climate variability and change. This talk will showcase some of the specific activities and tools, describe lessons learned, and illustrate how such efforts fit into a "National Climate Service."

Carbon pollution increases health inequities: lessons in resilience from the most vulnerable.

PubMed

Ebi, Kristie L; Fawcett, Stephen B; Spiegel, Jerry; Tovalin, Horacio

2016-09-01

Climate change is a social justice as well as an environmental issue. The magnitude and pattern of changes in weather and climate variables are creating differential exposures, vulnerabilities, and health risks that increase stress on health systems while exacerbating existing and creating new health inequities. Examples from national and local health adaptation projects highlight that developing partnerships across sectors and levels are critical for building climate-resilient health systems and communities. Strengthening current and implementing new health interventions, such as using environmental information to develop early warning systems, can be effective in protecting the most vulnerable. However, not all projected risks of climate change can be avoided by climate policies and programs, so health system strengthening is also critical. Applying a health inequity lens can reduce current vulnerabilities while building resilience to longer-term climate change. Taking inequities into account is critical if societies are to effectively prepare for and manage the challenges ahead.

Investigating the case of human nose shape and climate adaptation

PubMed Central

Zaidi, Arslan A.; Claes, Peter; McEcoy, Brian; Shriver, Mark D.

2017-01-01

The evolutionary reasons for variation in nose shape across human populations have been subject to continuing debate. An import function of the nose and nasal cavity is to condition inspired air before it reaches the lower respiratory tract. For this reason, it is thought the observed differences in nose shape among populations are not simply the result of genetic drift, but may be adaptations to climate. To address the question of whether local adaptation to climate is responsible for nose shape divergence across populations, we use Qst–Fst comparisons to show that nares width and alar base width are more differentiated across populations than expected under genetic drift alone. To test whether this differentiation is due to climate adaptation, we compared the spatial distribution of these variables with the global distribution of temperature, absolute humidity, and relative humidity. We find that width of the nares is correlated with temperature and absolute humidity, but not with relative humidity. We conclude that some aspects of nose shape may indeed have been driven by local adaptation to climate. However, we think that this is a simplified explanation of a very complex evolutionary history, which possibly also involved other non-neutral forces such as sexual selection. PMID:28301464

Investigating the case of human nose shape and climate adaptation.

PubMed

Zaidi, Arslan A; Mattern, Brooke C; Claes, Peter; McEvoy, Brian; Hughes, Cris; Shriver, Mark D

2017-03-01

The evolutionary reasons for variation in nose shape across human populations have been subject to continuing debate. An import function of the nose and nasal cavity is to condition inspired air before it reaches the lower respiratory tract. For this reason, it is thought the observed differences in nose shape among populations are not simply the result of genetic drift, but may be adaptations to climate. To address the question of whether local adaptation to climate is responsible for nose shape divergence across populations, we use Qst-Fst comparisons to show that nares width and alar base width are more differentiated across populations than expected under genetic drift alone. To test whether this differentiation is due to climate adaptation, we compared the spatial distribution of these variables with the global distribution of temperature, absolute humidity, and relative humidity. We find that width of the nares is correlated with temperature and absolute humidity, but not with relative humidity. We conclude that some aspects of nose shape may indeed have been driven by local adaptation to climate. However, we think that this is a simplified explanation of a very complex evolutionary history, which possibly also involved other non-neutral forces such as sexual selection.

Importance of climatological downscaling and plant phenology for red deer in heterogeneous landscapes

PubMed Central

Pettorelli, Nathalie; Mysterud, Atle; Yoccoz, Nigel G; Langvatn, Rolf; Stenseth, Nils Chr

2005-01-01

Understanding how climate influences ecosystems represents a challenge in ecology and natural resource management. Although we know that climate affects plant phenology and herbivore performances at any single site, no study has directly coupled the topography–climate interaction (i.e. the climatological downscaling process) with large-scale vegetation dynamics and animal performances. Here we show how climatic variability (measured by the North Atlantic oscillation ‘NAO’) interacts with local topography in determining the vegetative greenness (as measured by the normalized difference vegetation index ‘NDVI’) and the body masses and seasonal movements of red deer (Cervus elaphus) in Norway. Warm springs induced an earlier onset of vegetation, resulting in earlier migration and higher body masses. Increasing values of the winter-NAO corresponded to less snow at low altitude (warmer, more precipitation results in more rain), but more snow at high altitude (colder, more precipitation corresponds to more snow) relative to winters with low winter-NAO. An increasing NAO thus results in a spatially more variable phenology, offering migrating deer an extended period with access to high-quality forage leading to increased body mass. Our results emphasize the importance of incorporating spring as well as the interaction between winter climate and topography when aiming at understanding how plant and animal respond to climate change. PMID:16243701

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

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.

Dynamical malaria models reveal how immunity buffers effect of climate variability.

PubMed

Laneri, Karina; Paul, Richard E; Tall, Adama; Faye, Joseph; Diene-Sarr, Fatoumata; Sokhna, Cheikh; Trape, Jean-François; Rodó, Xavier

2015-07-14

Assessing the influence of climate on the incidence of Plasmodium falciparum malaria worldwide and how it might impact local malaria dynamics is complex and extrapolation to other settings or future times is controversial. This is especially true in the light of the particularities of the short- and long-term immune responses to infection. In sites of epidemic malaria transmission, it is widely accepted that climate plays an important role in driving malaria outbreaks. However, little is known about the role of climate in endemic settings where clinical immunity develops early in life. To disentangle these differences among high- and low-transmission settings we applied a dynamical model to two unique adjacent cohorts of mesoendemic seasonal and holoendemic perennial malaria transmission in Senegal followed for two decades, recording daily P. falciparum cases. As both cohorts are subject to similar meteorological conditions, we were able to analyze the relevance of different immunological mechanisms compared with climatic forcing in malaria transmission. Transmission was first modeled by using similarly unique datasets of entomological inoculation rate. A stochastic nonlinear human-mosquito model that includes rainfall and temperature covariates, drug treatment periods, and population variability is capable of simulating the complete dynamics of reported malaria cases for both villages. We found that under moderate transmission intensity climate is crucial; however, under high endemicity the development of clinical immunity buffers any effect of climate. Our models open the possibility of forecasting malaria from climate in endemic regions but only after accounting for the interaction between climate and immunity.

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.

Improving Empirical Approaches to Estimating Local Greenhouse Gas Emissions

NASA Astrophysics Data System (ADS)

Blackhurst, M.; Azevedo, I. L.; Lattanzi, A.

2016-12-01

Evidence increasingly indicates our changing climate will have significant global impacts on public health, economies, and ecosystems. As a result, local governments have become increasingly interested in climate change mitigation. In the U.S., cities and counties representing nearly 15% of the domestic population plan to reduce 300 million metric tons of greenhouse gases over the next 40 years (or approximately 1 ton per capita). Local governments estimate greenhouse gas emissions to establish greenhouse gas mitigation goals and select supporting mitigation measures. However, current practices produce greenhouse gas estimates - also known as a "greenhouse gas inventory " - of empirical quality often insufficient for robust mitigation decision making. Namely, current mitigation planning uses sporadic, annual, and deterministic estimates disaggregated by broad end use sector, obscuring sources of emissions uncertainty, variability, and exogeneity that influence mitigation opportunities. As part of AGU's Thriving Earth Exchange, Ari Lattanzi of City of Pittsburgh, PA recently partnered with Dr. Inez Lima Azevedo (Carnegie Mellon University) and Dr. Michael Blackhurst (University of Pittsburgh) to improve the empirical approach to characterizing Pittsburgh's greenhouse gas emissions. The project will produce first-order estimates of the underlying sources of uncertainty, variability, and exogeneity influencing Pittsburgh's greenhouse gases and discuss implications of mitigation decision making. The results of the project will enable local governments to collect more robust greenhouse gas inventories to better support their mitigation goals and improve measurement and verification efforts.

Dynamic Topography and Sea Level Anomalies of the Southern Ocean: Variability and Teleconnections

NASA Astrophysics Data System (ADS)

Armitage, Thomas W. K.; Kwok, Ron; Thompson, Andrew F.; Cunningham, Glenn

2018-01-01

This study combines sea surface height (SSH) estimates of the ice-covered Southern Ocean with conventional open-ocean SSH estimates from CryoSat-2 to produce monthly composites of dynamic ocean topography (DOT) and sea level anomaly (SLA) on a 50 km grid spanning 2011-2016. This data set reveals the full Southern Ocean SSH seasonal cycle for the first time; there is an antiphase relationship between sea level on the Antarctic continental shelf and the deeper basins, with coastal SSH highest in autumn and lowest in spring. As a result of this pattern of seasonal SSH variability, the barotropic component of the Antarctic Slope Current (ASC) has speeds that are regionally up to twice as fast in the autumn. Month-to-month circulation variability of the Ross and Weddell Gyres is strongly influenced by the local wind field, and is correlated with the local wind curl (Ross: -0.58; Weddell: -0.67). SSH variability is linked to both the Southern Oscillation and the Southern Annular Mode, dominant modes of southern hemisphere climate variability. In particular, during the strong 2015-2016 El Niño, a sustained negative coastal SLA of up to -6 cm, implying a weakening of the ASC, was observed in the Pacific sector of the Southern Ocean. The ability to examine sea level variability in the seasonally ice-covered regions of the Southern Ocean—climatically important regions with an acute sparsity of data—makes this new merged sea level record of particular interest to the Southern Ocean oceanography and glaciology communities.

Climate and Non-Climate Drivers of Dengue Epidemics in Southern Coastal Ecuador

PubMed Central

Stewart-Ibarra, Anna M.; Lowe, Rachel

2013-01-01

We report a statistical mixed model for assessing the importance of climate and non-climate drivers of interannual variability in dengue fever in southern coastal Ecuador. Local climate data and Pacific sea surface temperatures (Oceanic Niño Index [ONI]) were used to predict dengue standardized morbidity ratios (SMRs; 1995–2010). Unobserved confounding factors were accounted for using non-structured yearly random effects. We found that ONI, rainfall, and minimum temperature were positively associated with dengue, with more cases of dengue during El Niño events. We assessed the influence of non-climatic factors on dengue SMR using a subset of data (2001–2010) and found that the percent of households with Aedes aegypti immatures was also a significant predictor. Our results indicate that monitoring the climate and non-climate drivers identified in this study could provide some predictive lead for forecasting dengue epidemics, showing the potential to develop a dengue early-warning system in this region. PMID:23478584

A Decision Analysis Tool for Climate Impacts, Adaptations, and Vulnerabilities

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

Omitaomu, Olufemi A; Parish, Esther S; Nugent, Philip J

Climate change related extreme events (such as flooding, storms, and drought) are already impacting millions of people globally at a cost of billions of dollars annually. Hence, there are urgent needs for urban areas to develop adaptation strategies that will alleviate the impacts of these extreme events. However, lack of appropriate decision support tools that match local applications is limiting local planning efforts. In this paper, we present a quantitative analysis and optimization system with customized decision support modules built on geographic information system (GIS) platform to bridge this gap. This platform is called Urban Climate Adaptation Tool (Urban-CAT). Formore » all Urban-CAT models, we divide a city into a grid with tens of thousands of cells; then compute a list of metrics for each cell from the GIS data. These metrics are used as independent variables to predict climate impacts, compute vulnerability score, and evaluate adaptation options. Overall, the Urban-CAT system has three layers: data layer (that contains spatial data, socio-economic and environmental data, and analytic data), middle layer (that handles data processing, model management, and GIS operation), and application layer (that provides climate impacts forecast, adaptation optimization, and site evaluation). The Urban-CAT platform can guide city and county governments in identifying and planning for effective climate change adaptation strategies.« less

Mesoscale disturbance and ecological response to decadal climatic variability in the American Southwest

USGS Publications Warehouse

Swetnam, T.W.; Betancourt, J.L.

1998-01-01

Ecological responses to climatic variability in the Southwest include regionally synchronized fires, insect outbreaks, and pulses in tree demography (births and deaths). Multicentury, tree-ring reconstructions of drought, disturbance history, and tree demography reveal climatic effects across scales, from annual to decadal, and from local (<102 km2) to mesoscale (104-106 km2). Climate-disturbance relations are more variable and complex than previously assumed. During the past three centuries, mesoscale outbreaks of the western spruce budworm (Choristoneura occidentalis) were associated with wet, not dry episodes, contrary to conventional wisdom. Regional fires occur during extreme droughts but, in some ecosystems, antecedent wet conditions play a secondary role by regulating accumulation of fuels. Interdecadal changes in fire-climate associations parallel other evidence for shifts in the frequency or amplitude of the Southern Oscillation (SO) during the past three centuries. High interannual, fire-climate correlations (r = 0.7 to 0.9) during specific decades (i.e., circa 1740-80 and 1830-60) reflect periods of high amplitude in the SO and rapid switching from extreme wet to dry years in the Southwest, thereby entraining fire occurrence across the region. Weak correlations from 1780 to 1830 correspond with a decrease in SO frequency or amplitude inferred from independent tree-ring width, ice core, and coral isotope reconstructions. Episodic dry and wet episodes have altered age structures and species composition of woodland and conifer forests. The scarcity of old, living conifers established before circa 1600 suggests that the extreme drought of 1575-95 had pervasive effects on tree populations. The most extreme drought of the past 400 years occurred in the mid-twentieth century (1942-57). This drought resulted in broadscale plant dieoffs in shrublands, woodlands, and forests and accelerated shrub invasion of grasslands. Drought conditions were broken by the post-1976 shift to the negative SO phase and wetter cool seasons in the Southwest. The post-1976 period shows up as an unprecedented surge in tree-ring growth within millennia-length chronologies. This unusual episode may have produced a pulse in tree recruitment and improved rangeland conditions (e.g., higher grass production), though additional study is needed to disentangle the interacting roles of land use and climate. The 1950s drought and the post-1976 wet period and their aftermaths offer natural experiments to study long-term ecosystem response to interdecadal climate variability.Ecological responses to climatic variability in the Southwest include regionally synchronized fires, insect outbreaks, and pulses in tree demography (births and deaths). Multicentury, tree-ring reconstructions of drought, disturbance history, and tree demography reveal climatic effects across scales, from annual to decadal, and from local (<102 km2) to mesoscale (104-106 km2). Climate-disturbance relations are more variable and complex than previously assumed. During the past three centuries, mesoscale outbreaks of the western spruce budworm (Choristoneura occidentalis) were associated with wet, not dry episodes, contrary to conventional wisdom. Regional fires occur during extreme droughts but, in some ecosystems, antecedent wet conditions play a secondary role by regulating accumulation of fuels. Interdecadal changes in fire-climate associations parallel other evidence for shifts in the frequency or amplitude of the Southern Oscillation (SO) during the past three centuries. High interannual, fire-climate correlations (r = 0.7 to 0.9) during specific decades (i.e., circa 1740-80 and 1830-60) reflect periods of high amplitude in the SO and rapid switching from extreme wet to dry years in the Southwest, thereby entraining fire occurrence across the region. Weak correlations from 1780 to 1830 correspond with a decrease in SO frequency or amplitude inferred from independent tree-ring width, ic

Urban Heat Wave Vulnerability Analysis Considering Climate Change

NASA Astrophysics Data System (ADS)

JE, M.; KIM, H.; Jung, S.

2017-12-01

Much attention has been paid to thermal environments in Seoul City in South Korea since 2016 when the worst heatwave in 22 years. It is necessary to provide a selective measure by singling out vulnerable regions in advance to cope with the heat wave-related damage. This study aims to analyze and categorize vulnerable regions of thermal environments in the Seoul and analyzes and discusses the factors and risk factors for each type. To do this, this study conducted the following processes: first, based on the analyzed various literature reviews, indices that can evaluate vulnerable regions of thermal environment are collated. The indices were divided into climate exposure index related to temperature, sensitivity index including demographic, social, and economic indices, and adaptation index related to urban environment and climate adaptation policy status. Second, significant variables were derived to evaluate a vulnerable region of thermal environment based on the summarized indices in the above. this study analyzed a relationship between the number of heat-related patients in Seoul and variables that affected the number using multi-variate statistical analysis to derive significant variables. Third, the importance of each variable was calculated quantitatively by integrating the statistical analysis results and analytic hierarchy process (AHP) method. Fourth, a distribution of data for each index was identified based on the selected variables and indices were normalized and overlapped. Fifth, For the climate exposure index, evaluations were conducted as same as the current vulnerability evaluation method by selecting future temperature of Seoul predicted through the representative concentration pathways (RCPs) climate change scenarios as an evaluation variable. The results of this study can be utilized as foundational data to establish a countermeasure against heatwave in Seoul. Although it is limited to control heatwave occurrences itself completely, improvements on environment for heatwave alleviation and response can be done. In particular, if vulnerable regions of heatwave can be identified and managed in advance, the study results are expected to be utilized as a basis of policy utilization in local communities accordingly.

Impact of socio-demographic factors on the mitigating actions for climate change: a path analysis with mediating effects of attitudinal variables.

PubMed

Masud, Muhammad Mehedi; Akhatr, Rulia; Nasrin, Shamima; Adamu, Ibrahim Mohammed

2017-12-01

Socio-demographic factors play a significant role in increasing the individual's climate change awareness and in setting a favorable individual attitude towards its mitigation. To better understand how the adversative effects of climate change can be mitigated, this study attempts to investigate the impact of socio-demographic factors on the mitigating actions of the individuals (MAOI) on climate change. Qualitative data were collected from a face-to-face survey of 360 respondents in the Kuala Lumpur region of Malaysia through a close-ended questionnaire. Analysis was conducted on the mediating effects of attitudinal variables through the path model by using the SEM. Findings indicate that the socio-demographic factors such as gender, age, education, income, and ethnicity can greatly influence the individual's awareness, attitude, risk perception, and knowledge of climate change issues. The results drawn from this study also revealed that the attitudinal factors act as a mediating effect between the socio-demographic factors and the MAOI, thereby, indicating that both the socio-demographic factors and the attitudinal factors have significant effects on the MAOI towards climate change. The outcome of this study can help policy makers and other private organizations to decide on the appropriate actions to take in managing climate change effects. These actions which encompass improving basic climate change education and making the public more aware of the local dimensions of climate change are important for harnessing public engagement and support that can also stimulate climate change awareness and promote mitigating actions to n protect the environment from the impact of climate change.

Future Temperatures and Precipitations in the Arid Northern-Central Chile: A Multi-Model Downscaling Approach

NASA Astrophysics Data System (ADS)

Souvignet, M.; Heinrich, J.

2010-03-01

Downscaling of global climate outputs is necessary to transfer projections of potential climate change scenarios to local levels. This is of special interest to dry mountainous areas, which are particularly vulnerable to climate change due to risks of reduced freshwater availability. These areas play a key role for hydrology since they usually receive the highest local precipitation rates stored in form of snow and glaciers. In the central-northern Chile (Norte Chico, 26-33ºS), where agriculture still serves as a backbone of the economy as well as ensures the well being of people, the knowledge of water resources availability is essential. The region is characterised by a semiarid climate with a mean annual precipitation inferior to 100mm. Moreover, the local climate is also highly influenced by the ENSO phenomenon, which accounts for the strong inter-annual variability in precipitation patterns. Although historical and spatially extensive precipitation data in the headwaters of the basins in this region are not readily available, records at coastal stations show worrisome trends. For instance, the average precipitation in La Serena, the most important city located in the Coquimbo Region, has decreased dramatically in the past 100 years. The 30-year monthly average has decreased from 170 mm in the early 20th century to values less than 80 mm nowadays. Climate Change is expected to strengthen this pattern in the region, and therefore strongly influence local hydrological patterns. The objectives of this study are i) to develop climate change scenarios (2046-2099) for the Norte Chico using multi-model predictions in terms of temperatures and precipitations, and ii) to compare the efficiency of two downscaling techniques in arid mountainous regions. In addition, this study aims at iii) providing decision makers with sound analysis of potential impact of Climate Change on streamflow in the region. For the present study, future local climate scenarios were developed for maximum, minimum temperature and precipitation in the research area based on four different General Circulation Models (GCMs). On the first hand, the Statistical Downscaling Model (SDSM) was used. This model is based on a multiple linear regression method and is best described as a hybrid of the stochastic weather generator and transfer function methods. One common advantage of statistical downscaling is that it ensures the maintenance of local spatial and temporal variability in generating realistic data time series. On the other hand and for comparison purposes, the Change Factor method was used. This methodology is relatively straightforward and ideal for rapid climate change assessment. The outputs of the HadCM3, CGCM3.1, GDFL-CM2 and MRI-CGCM2.3.2 A1 and B2 scenarios were downscaled with both methodologies and thereafter compared by means of several hydro-meteorological indices for a 55-years period (2045-2099). Preliminary results indicate that local temperatures are expected to rise in the region, whereas precipitations may decrease. However, minimum and maximum temperatures might increase at a faster rate at higher altitude areas. In addition, the Cordillera mountain range may encounter and longer winters with a dramatic decrease of icing days (Tmax<0°C). As for precipitation, both SRES scenarios for all models return a diminishing tendency, though the A2 scenario results show a faster decrease rate. Results indicate potential strong inter-seasonal and inter-annual perturbations in Rainfall in the region. Consequently, the Norte Chico will possibly see its streamflow strongly impacted with a resulting high variability at the seasonal and inter-annual level. A probabilistic analysis of the projections of the four GCMs provided a better representation of uncertainties linked with downscaled scenarios. Whereas maximum and minimum temperatures were accurately simulated by both downscaling methods, precipitation simulations returned weaker results. SDSM proved to have a poor ability to simulate extreme rainfall events and few conclusions could be drawn with respect to future occurrences of ENSO phenomena. On the other hand, the change factor method reproduced comparatively better historical precipitations. Despite all sources of error and uncertainties, which must be taken into account when handling the projections, this study addresses an issue that goes beyond local concerns and aims at developing a better understanding of impacts of climate change in fragile environments such as the arid and semiarid transition zone of north-central Chile. Its additional applied component goes therefore beyond the classical comparative study and aims at supporting stakeholders in their processes of decision making.

Past climates primary productivity changes in the Indian Ocean

NASA Astrophysics Data System (ADS)

Le Mézo, P. K.; Kageyama, M.; Bopp, L.; Beaufort, L.; Braconnot, P.; Bassinot, F. C.

2016-02-01

Organic climate recorders, e.g., coccolithophorids and foraminifera, are widely used to reconstruct past climate conditions, such as the Indian monsoon intensity and variability, since they are sensitive to climate-induced fluctuations of their environment. In the Indian Ocean, it is commonly accepted that a stronger summer monsoon will enhance productivity in the Arabian Sea and therefore the amount of organisms in a sediment core should reflect monsoon intensity. In this study, we use the coupled Earth System Model IPSLCM5A, which has a biogeochemical component PISCES that simulates primary production. We use 8 climate simulations of the IPSL-CM5A model, from -72kyr BP climate conditions to a preindustrial state. Our simulations have different orbital forcing (precession, obliquity and eccentricity), greenhouse gas concentrations as well as different ice sheet covers. The objective of this work is to characterize the mechanisms behind the changes in primary productivity between the different time periods. Our model shows that in climates where monsoon is enhanced (due to changes in precession) we do not necessarily see an increase in summer productivity in the Arabian Sea, and inversely. It seems that the glacial-interglacial state of the simulation is important in driving productivity changes in this region of the world. We try to explain the changes in productivity in the Arabian Sea with the local climate and then to link the changes in local climate to large scale atmospheric forcing and commonly used Indian monsoon definitions.

Local-scale models reveal ecological niche variability in amphibian and reptile communities from two contrasting biogeographic regions

PubMed Central

Santos, Xavier; Felicísimo, Ángel M.

2016-01-01

Ecological Niche Models (ENMs) are widely used to describe how environmental factors influence species distribution. Modelling at a local scale, compared to a large scale within a high environmental gradient, can improve our understanding of ecological species niches. The main goal of this study is to assess and compare the contribution of environmental variables to amphibian and reptile ENMs in two Spanish national parks located in contrasting biogeographic regions, i.e., the Mediterranean and the Atlantic area. The ENMs were built with maximum entropy modelling using 11 environmental variables in each territory. The contributions of these variables to the models were analysed and classified using various statistical procedures (Mann–Whitney U tests, Principal Components Analysis and General Linear Models). Distance to the hydrological network was consistently the most relevant variable for both parks and taxonomic classes. Topographic variables (i.e., slope and altitude) were the second most predictive variables, followed by climatic variables. Differences in variable contribution were observed between parks and taxonomic classes. Variables related to water availability had the larger contribution to the models in the Mediterranean park, while topography variables were decisive in the Atlantic park. Specific response curves to environmental variables were in accordance with the biogeographic affinity of species (Mediterranean and non-Mediterranean species) and taxonomy (amphibians and reptiles). Interestingly, these results were observed for species located in both parks, particularly those situated at their range limits. Our findings show that ecological niche models built at local scale reveal differences in habitat preferences within a wide environmental gradient. Therefore, modelling at local scales rather than assuming large-scale models could be preferable for the establishment of conservation strategies for herptile species in natural parks. PMID:27761304

Varying geospatial analyses to assess climate risk and adaptive capacity in a hotter, drier Southwestern United States

NASA Astrophysics Data System (ADS)

Elias, E.; Reyes, J. J.; Steele, C. M.; Rango, A.

2017-12-01

Assessing vulnerability of agricultural systems to climate variability and change is vital in securing food systems and sustaining rural livelihoods. Farmers, ranchers, and forest landowners rely on science-based, decision-relevant, and localized information to maintain production, ecological viability, and economic returns. This contribution synthesizes a collection of research on the future of agricultural production in the American Southwest (SW). Research was based on a variety of geospatial methodologies and datasets to assess the vulnerability of rangelands and livestock, field crops, specialty crops, and forests in the SW to climate-risk and change. This collection emerged from the development of regional vulnerability assessments for agricultural climate-risk by the U.S. Department of Agriculture (USDA) Climate Hub Network, established to deliver science-based information and technologies to enable climate-informed decision-making. Authors defined vulnerability differently based on their agricultural system of interest, although each primarily focuses on biophysical systems. We found that an inconsistent framework for vulnerability and climate risk was necessary to adequately capture the diversity, variability, and heterogeneity of SW landscapes, peoples, and agriculture. Through the diversity of research questions and methodologies, this collection of articles provides valuable information on various aspects of SW vulnerability. All articles relied on geographic information systems technology, with highly variable levels of complexity. Agricultural articles used National Agricultural Statistics Service data, either as tabular county level summaries or through the CropScape cropland raster datasets. Most relied on modeled historic and future climate information, but with differing assumptions regarding spatial resolution and temporal framework. We assert that it is essential to evaluate climate risk using a variety of complementary methodologies and perspectives. In addition, we found that spatial analysis supports informed adaptation, within and outside the SW United States. The persistence and adaptive capacity of agriculture in the water-limited Southwest serves as an instructive example and may offer solutions to reduce future climate risk.

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

PubMed

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

2016-01-01

In the Mediterranean region, the widely predicted rise in temperature, change in the precipitation pattern, and increase in the frequency of extreme climatic events are expected to alter the shape of ecological communities and to affect plant physiological processes that regulate ecosystem functioning. Although change in the mean values are important, there is increasing evidence that plant distribution, survival, and productivity respond to extremes rather than to the average climatic condition. The present study aims to assess the effects of both mean and extreme climatic conditions on radial growth and functional anatomical traits using long-term tree-ring time series of two co-existing Quercus spp. from a drought-prone site in Southern Italy. In particular, this is the first attempt to apply the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) technique and Bayesian modeling procedures to xylem traits data set, with the aim of (i) detecting non-linear long-term responses to climate and (ii) exploring relationships between climate extreme and xylem traits variability in terms of probability of occurrence. This study demonstrates the usefulness of long-term xylem trait chronologies as records of environmental conditions at annual resolution. Statistical analyses revealed that most of the variability in tree-ring width and specific hydraulic conductivity might be explained by cambial age. Additionally, results highlighted appreciable relationships between xylem traits and climate variability more than tree-ring width, supporting also the evidence that the plant hydraulic traits are closely linked to local climate extremes rather than average climatic conditions. We reported that the probability of extreme departure in specific hydraulic conductivity (Ks) rises at extreme values of Standardized Precipitation Index (SPI). Therefore, changing frequency or intensity of extreme events might overcome the adaptive limits of vascular transport, resulting in substantial reduction of hydraulic functionality and, hence increased incidence of xylem dysfunctions.

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

PubMed Central

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

2016-01-01

In the Mediterranean region, the widely predicted rise in temperature, change in the precipitation pattern, and increase in the frequency of extreme climatic events are expected to alter the shape of ecological communities and to affect plant physiological processes that regulate ecosystem functioning. Although change in the mean values are important, there is increasing evidence that plant distribution, survival, and productivity respond to extremes rather than to the average climatic condition. The present study aims to assess the effects of both mean and extreme climatic conditions on radial growth and functional anatomical traits using long-term tree-ring time series of two co-existing Quercus spp. from a drought-prone site in Southern Italy. In particular, this is the first attempt to apply the Generalized Additive Model for Location, Scale, and Shape (GAMLSS) technique and Bayesian modeling procedures to xylem traits data set, with the aim of (i) detecting non-linear long-term responses to climate and (ii) exploring relationships between climate extreme and xylem traits variability in terms of probability of occurrence. This study demonstrates the usefulness of long-term xylem trait chronologies as records of environmental conditions at annual resolution. Statistical analyses revealed that most of the variability in tree-ring width and specific hydraulic conductivity might be explained by cambial age. Additionally, results highlighted appreciable relationships between xylem traits and climate variability more than tree-ring width, supporting also the evidence that the plant hydraulic traits are closely linked to local climate extremes rather than average climatic conditions. We reported that the probability of extreme departure in specific hydraulic conductivity (Ks) rises at extreme values of Standardized Precipitation Index (SPI). Therefore, changing frequency or intensity of extreme events might overcome the adaptive limits of vascular transport, resulting in substantial reduction of hydraulic functionality and, hence increased incidence of xylem dysfunctions. PMID:27532008

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

NASA Astrophysics Data System (ADS)

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

2007-05-01

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

Decision-support tools for Extreme Weather and Climate Events in the Northeast United States

NASA Astrophysics Data System (ADS)

Kumar, S.; Lowery, M.; Whelchel, A.

2013-12-01

Decision-support tools were assessed for the 2013 National Climate Assessment technical input document, "Climate Change in the Northeast, A Sourcebook". The assessment included tools designed to generate and deliver actionable information to assist states and highly populated urban and other communities in assessment of climate change vulnerability and risk, quantification of effects, and identification of adaptive strategies in the context of adaptation planning across inter-annual, seasonal and multi-decadal time scales. State-level adaptation planning in the Northeast has generally relied on qualitative vulnerability assessments by expert panels and stakeholders, although some states have undertaken initiatives to develop statewide databases to support vulnerability assessments by urban and local governments, and state agencies. The devastation caused by Superstorm Sandy in October 2012 has raised awareness of the potential for extreme weather events to unprecedented levels and created urgency for action, especially in coastal urban and suburban communities that experienced pronounced impacts - especially in New Jersey, New York and Connecticut. Planning approaches vary, but any adaptation and resiliency planning process must include the following: - Knowledge of the probable change in a climate variable (e.g., precipitation, temperature, sea-level rise) over time or that the climate variable will attain a certain threshold deemed to be significant; - Knowledge of intensity and frequency of climate hazards (past, current or future events or conditions with potential to cause harm) and their relationship with climate variables; - Assessment of climate vulnerabilities (sensitive resources, infrastructure or populations exposed to climate-related hazards); - Assessment of relative risks to vulnerable resources; - Identification and prioritization of adaptive strategies to address risks. Many organizations are developing decision-support tools to assist in the urban planning process by addressing some of these needs. In this paper we highlight the decision tools available today, discuss their application in selected case studies, and present a gap analysis with opportunities for innovation and future work.

Spatial and temporal expression of vegetation and atmospheric variability from stable carbon and nitrogen isotope analysis of bat guano in the southern United States

NASA Astrophysics Data System (ADS)

Wurster, Christopher M.; McFarlane, Donald A.; Bird, Michael I.

2007-07-01

Stable isotopes of faeces contain information related to the animals feeding ecology. The use of stable isotope values from subfossil faeces as a palaeoenvironmental indicator depends on how faithfully the animal records their local environment. Here we present insectivorous bat guano δ 13C and δ 15N values from a precipitation gradient across the southern United States and northern Mexico to compare with local vegetation and climate. We find δ 13C values to be an excellent predictor of expected C 4/CAM vegetation, indicating that the bats are non-selective in their diet. Moreover, we find bat guano δ 13C values to be strongly correlated with summer precipitation amount and winter precipitation ratio. We also find evidence for a significant relationship with mean annual temperature. In general, we do not find δ 15N values to be related to any parameters along the climatic gradient we examined. Additionally, we measured δ 13C and δ 15N values of bulk guano deposited annually from 1968 to 1987 in a varved guano deposit at Eagle Creek Cave, Arizona. Neither δ 13C nor δ 15N values were significantly related to various local meteorological variables; however, we found δ 13C values of guano to be significantly related to drought and to the North American Monsoon indicating bat guano δ 13C values preserve an interpretable record of large-scale atmospheric variability.

Landscape genomic analysis of candidate genes for climate adaptation in a California endemic oak, Quercus lobata.

PubMed

Sork, Victoria L; Squire, Kevin; Gugger, Paul F; Steele, Stephanie E; Levy, Eric D; Eckert, Andrew J

2016-01-01

The ability of California tree populations to survive anthropogenic climate change will be shaped by the geographic structure of adaptive genetic variation. Our goal is to test whether climate-associated candidate genes show evidence of spatially divergent selection in natural populations of valley oak, Quercus lobata, as preliminary indication of local adaptation. Using DNA from 45 individuals from 13 localities across the species' range, we sequenced portions of 40 candidate genes related to budburst/flowering, growth, osmotic stress, and temperature stress. Using 195 single nucleotide polymorphisms (SNPs), we estimated genetic differentiation across populations and correlated allele frequencies with climate gradients using single-locus and multivariate models. The top 5% of FST estimates ranged from 0.25 to 0.68, yielding loci potentially under spatially divergent selection. Environmental analyses of SNP frequencies with climate gradients revealed three significantly correlated SNPs within budburst/flowering genes and two SNPs within temperature stress genes with mean annual precipitation, after controlling for multiple testing. A redundancy model showed a significant association between SNPs and climate variables and revealed a similar set of SNPs with high loadings on the first axis. In the RDA, climate accounted for 67% of the explained variation, when holding climate constant, in contrast to a putatively neutral SSR data set where climate accounted for only 33%. Population differentiation and geographic gradients of allele frequencies in climate-associated functional genes in Q. lobata provide initial evidence of adaptive genetic variation and background for predicting population response to climate change. © 2016 Botanical Society of America.

Use of Machine Learning Techniques for Iidentification of Robust Teleconnections to East African Rainfall Variability in Observations and Models

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, Franklin R.; Funk, Chris

2014-01-01

Providing advance warning of East African rainfall variations is a particular focus of several groups including those participating in the Famine Early Warming Systems Network. Both seasonal and long-term model projections of climate variability are being used to examine the societal impacts of hydrometeorological variability on seasonal to interannual and longer time scales. The NASA / USAID SERVIR project, which leverages satellite and modeling-based resources for environmental decision making in developing nations, is focusing on the evaluation of both seasonal and climate model projections to develop downscaled scenarios for using in impact modeling. The utility of these projections is reliant on the ability of current models to capture the embedded relationships between East African rainfall and evolving forcing within the coupled ocean-atmosphere-land climate system. Previous studies have posited relationships between variations in El Niño, the Walker circulation, Pacific decadal variability (PDV), and anthropogenic forcing. This study applies machine learning methods (e.g. clustering, probabilistic graphical model, nonlinear PCA) to observational datasets in an attempt to expose the importance of local and remote forcing mechanisms of East African rainfall variability. The ability of the NASA Goddard Earth Observing System (GEOS5) coupled model to capture the associated relationships will be evaluated using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations.

Impacts of climate change on mangrove ecosystems: A region by region overview

USGS Publications Warehouse

Ward, Raymond D.; Friess, Daniel A.; Day, Richard H.; MacKenzie, Richard A.

2016-01-01

Inter-related and spatially variable climate change factors including sea level rise, increased storminess, altered precipitation regime and increasing temperature are impacting mangroves at regional scales. This review highlights extreme regional variation in climate change threats and impacts, and how these factors impact the structure of mangrove communities, their biodiversity and geomorphological setting. All these factors interplay to determine spatially variable resiliency to climate change impacts, and because mangroves are varied in type and geographical location, these systems are good models for understanding such interactions at different scales. Sea level rise is likely to influence mangroves in all regions although local impacts are likely to be more varied. Changes in the frequency and intensity of storminess are likely to have a greater impact on N and Central America, Asia, Australia, and East Africa than West Africa and S. America. This review also highlights the numerous geographical knowledge gaps of climate change impacts, with some regions particularly understudied (e.g., Africa and the Middle East). While there has been a recent drive to address these knowledge gaps especially in South America and Asia, further research is required to allow researchers to tease apart the processes that influence both vulnerability and resilience to climate change. A more globally representative view of mangroves would allow us to better understand the importance of mangrove type and landscape setting in determining system resiliency to future climate change.

Citizen Science: Participatory Monitoring of Water Resources Management in Mustang District, Nepal

NASA Astrophysics Data System (ADS)

Regmi, S.; Bhusal, J.; Gurung, P.; Ochoa-Tocachi, B. F.; Buytaert, W.

2016-12-01

Abstract The Mustang region of the Himalayas has unique geographical and climatic features. This region is characterized by a cold-arid climate with total annual precipitation of less than 300mm. Agriculture and livestock grazing lands are the major ecosystem services, which support directly the livelihoods of local populations yet, are strongly determined by low water availability. As a result, optimizing water resources management is paramount to support local development, but this is severely complicated by the lack of information about water availability. This problem is further aggravated by increasing pressure on the social, physical and climatic environments. In order to support the management of scarce water in irrigation and domestic uses, stream flow and precipitation monitoring networks were established using a participatory approach under the principle of citizen science. Data collection, and the following interpretation and application of the co-generated knowledge relies on local users, whereas the establishment of the system, knowledge co-generation, and development of application tools particularly is part of a collaboration of members of the general public with professional scientists. We show how the resulting data enable local users to quantify the water balance in the area and reduce the uncertainty associated to data-scarcity, which leads to the generation of useable information about water availability for irrigation, livestock grazing, and domestic demand. We contrast the current scenario of water use, under different conditions of natural variability and environmental change, with an optimized water management strategy generated and agreed with local users. This approach contributes to an optimal use of water, to an improvement in ecosystem services supporting to livelihood development and economic progress of local populations. Key words: ecosystem services, climate change, water balance, knowledge generation, irrigation

Observations, inferences, and mechanisms of the Atlantic Meridional Overturning Circulation: A review

NASA Astrophysics Data System (ADS)

Buckley, Martha W.; Marshall, John

2016-03-01

This is a review about the Atlantic Meridional Overturning Circulation (AMOC), its mean structure, temporal variability, controlling mechanisms, and role in the coupled climate system. The AMOC plays a central role in climate through its heat and freshwater transports. Northward ocean heat transport achieved by the AMOC is responsible for the relative warmth of the Northern Hemisphere compared to the Southern Hemisphere and is thought to play a role in setting the mean position of the Intertropical Convergence Zone north of the equator. The AMOC is a key means by which heat anomalies are sequestered into the ocean's interior and thus modulates the trajectory of climate change. Fluctuations in the AMOC have been linked to low-frequency variability of Atlantic sea surface temperatures with a host of implications for climate variability over surrounding landmasses. On intra-annual timescales, variability in AMOC is large and primarily reflects the response to local wind forcing; meridional coherence of anomalies is limited to that of the wind field. On interannual to decadal timescales, AMOC changes are primarily geostrophic and related to buoyancy anomalies on the western boundary. A pacemaker region for decadal AMOC changes is located in a western "transition zone" along the boundary between the subtropical and subpolar gyres. Decadal AMOC anomalies are communicated meridionally from this region. AMOC observations, as well as the expanded ocean observational network provided by the Argo array and satellite altimetry, are inspiring efforts to develop decadal predictability systems using coupled atmosphere-ocean models initialized by ocean data.

Remote sensing of ecosystem vulnerability: Assessing climate-vegetation-livestock interactions in Mongolia

NASA Astrophysics Data System (ADS)

Kang, S.; Hong, S. Y.

2015-12-01

Stock breeding is a major economic sector of Mongolia, supporting unique cultural and social identity. In spite of its long history, contemporary pastoralism increases interventions on climate-vegetation interactions substantially, which results in negative feedbacks to livestock sector. This presentation draws an attention how natural processes of climate and vegetation interact with livestock dynamics. Massive loss of livestock and wildlife animal during winter seasons (dzud) is an endemic climatic disaster in the Central Asia grasslands but the mechanisms are not well understood yet. Recent national-wide sever Dzud occurred during 2009-2010 winter in Mongolia. The dzud mechanisms were investigated by developing a schematic mechanism model on climate-vegetation-livestock interactions and applying it for quantitative statistical analysis. Various remote sensing products were integrated to prepare the status and process variables of the schematic model, including daily temperature, precipitation, evapotranspiration, and primary production and biomass for a period from 2003 to 2010. At a lower level of administration (i.e., 'soum' generally larger than 1000 km2), stepwise multiple regression analysis was conducted to find significant factors of inter-annual livestock change. As results, linear regression models were successfully produced at 70% of soums. Summer and winter variables appeared equally important in controlling livestock dynamics. The primary factor of each soum showed certain regional patterns incident well with climate severity and foraging resource availability (e.g. temperature in north, dryness in south, and NDVI in middle). Regional pattern of herbaceous biodiversity depends on both climate and disturbance (i.e. fire and grazing) gradients but the livestock grazing effect appeared localized normally within 1.5 km from livestock shelter or wells. At a local-scale (i.e. family level smaller than 100 km2), species composition seems to provide useful indicator of grazing pressure, while climate and fire disturbance determined regional pattern of vegetation biodiversity. The results provide a useful premise to devise a satellite-based assessment tool for foraging resource availability and biological regime shift by grazing and climate change in future study.

Effects of topography on simulated net primary productivity at landscape scale.

PubMed

Chen, X F; Chen, J M; An, S Q; Ju, W M

2007-11-01

Local topography significantly affects spatial variations of climatic variables and soil water movement in complex terrain. Therefore, the distribution and productivity of ecosystems are closely linked to topography. Using a coupled terrestrial carbon and hydrological model (BEPS-TerrainLab model), the topographic effects on the net primary productivity (NPP) are analyzed through four modelling experiments for a 5700 km(2) area in Baohe River basin, Shaanxi Province, northwest of China. The model was able to capture 81% of the variability in NPP estimated from tree rings, with a mean relative error of 3.1%. The average NPP in 2003 for the study area was 741 gCm(-2)yr(-1) from a model run including topographic effects on the distributions of climate variables and lateral flow of ground water. Topography has considerable effect on NPP, which peaks near 1350 m above the sea level. An elevation increase of 100 m above this level reduces the average annual NPP by about 25 gCm(-2). The terrain aspect gives rise to a NPP change of 5% for forests located below 1900 m as a result of its influence on incident solar radiation. For the whole study area, a simulation totally excluding topographic effects on the distributions of climatic variables and ground water movement overestimated the average NPP by 5%.

Forecasting Distributional Responses of Limber Pine to Climate Change at Management-Relevant Scales in Rocky Mountain National Park

PubMed Central

Monahan, William B.; Cook, Tammy; Melton, Forrest; Connor, Jeff; Bobowski, Ben

2013-01-01

Resource managers at parks and other protected areas are increasingly expected to factor climate change explicitly into their decision making frameworks. However, most protected areas are small relative to the geographic ranges of species being managed, so forecasts need to consider local adaptation and community dynamics that are correlated with climate and affect distributions inside protected area boundaries. Additionally, niche theory suggests that species' physiological capacities to respond to climate change may be underestimated when forecasts fail to consider the full breadth of climates occupied by the species rangewide. Here, using correlative species distribution models that contrast estimates of climatic sensitivity inferred from the two spatial extents, we quantify the response of limber pine (Pinus flexilis) to climate change in Rocky Mountain National Park (Colorado, USA). Models are trained locally within the park where limber pine is the community dominant tree species, a distinct structural-compositional vegetation class of interest to managers, and also rangewide, as suggested by niche theory. Model forecasts through 2100 under two representative concentration pathways (RCP 4.5 and 8.5 W/m2) show that the distribution of limber pine in the park is expected to move upslope in elevation, but changes in total and core patch area remain highly uncertain. Most of this uncertainty is biological, as magnitudes of projected change are considerably more variable between the two spatial extents used in model training than they are between RCPs, and novel future climates only affect local model predictions associated with RCP 8.5 after 2091. Combined, these results illustrate the importance of accounting for unknowns in species' climatic sensitivities when forecasting distributional scenarios that are used to inform management decisions. We discuss how our results for limber pine may be interpreted in the context of climate change vulnerability and used to help guide adaptive management. PMID:24391742

Forecasting distributional responses of limber pine to climate change at management-relevant scales in Rocky Mountain National Park.

PubMed

Monahan, William B; Cook, Tammy; Melton, Forrest; Connor, Jeff; Bobowski, Ben

2013-01-01

Resource managers at parks and other protected areas are increasingly expected to factor climate change explicitly into their decision making frameworks. However, most protected areas are small relative to the geographic ranges of species being managed, so forecasts need to consider local adaptation and community dynamics that are correlated with climate and affect distributions inside protected area boundaries. Additionally, niche theory suggests that species' physiological capacities to respond to climate change may be underestimated when forecasts fail to consider the full breadth of climates occupied by the species rangewide. Here, using correlative species distribution models that contrast estimates of climatic sensitivity inferred from the two spatial extents, we quantify the response of limber pine (Pinus flexilis) to climate change in Rocky Mountain National Park (Colorado, USA). Models are trained locally within the park where limber pine is the community dominant tree species, a distinct structural-compositional vegetation class of interest to managers, and also rangewide, as suggested by niche theory. Model forecasts through 2100 under two representative concentration pathways (RCP 4.5 and 8.5 W/m(2)) show that the distribution of limber pine in the park is expected to move upslope in elevation, but changes in total and core patch area remain highly uncertain. Most of this uncertainty is biological, as magnitudes of projected change are considerably more variable between the two spatial extents used in model training than they are between RCPs, and novel future climates only affect local model predictions associated with RCP 8.5 after 2091. Combined, these results illustrate the importance of accounting for unknowns in species' climatic sensitivities when forecasting distributional scenarios that are used to inform management decisions. We discuss how our results for limber pine may be interpreted in the context of climate change vulnerability and used to help guide adaptive management.

On the Onset of the Rainy Season in Amazonia: WHAT the Observations Show, and Why the Biases in Climate Models?

NASA Astrophysics Data System (ADS)

Marengo, J. A.; Alves, L. M.; Fu, R.

2014-12-01

The onset of the Amazon rainy season shows a large temporal and spatial variability, delays on the date of the onset will have strong impacts on local agriculture, hydroelectric power generation as well as on the hydrology of large rivers. Two "once-in-a-century" droughts occurred in 2005 and 2010, and it was shown that in those events the rainy season started later than normal, and also that on the last 10 years the dry season has increased in length by about one month. These events highlight the urgency for improving our understanding and capability to model onset of the rainy season and drought variability, for the present and future. Most studies have attributed the variability of the rainy season onset over Amazonia to the variability of the tropical oceans whether other factors, such as climate change, land use and aerosols also contribute to the variability are not clear.. Global climate models run on seasonal climate forecast mode still show large uncertainties on the prediction of onset of seasonal rains. As for climate change, the CMIP3 and CMIP5 appear to underestimate the past variability, and also project virtually no future change of the onset of rainy season over the Amazon even when they are forced by strong greenhouse forcing under the RCP8.5 emission scenario. Why these models underestimate the variability of the rainy season onset, and whether this bias implies an underestimate of sensitivity of their dry season length to anthropogenic radiative forcing remain unclear. This FAPESP DOE grant 2013/50538 aims to explore use of the measurements provided by the Atmospheric Radiation Measurement (ARM) Mobile Facilities (AMF)-GoAmazon and the Cloud processes of the main precipitation systems in Brazil (CHUVA) Field Experiments, along with global and regional model experiments, to explore the sources of the above described uncertainty. The project will address several issues, i.e. the inadequate representation of the types of convection (i.e., maritime versus continental) and their relationships to aerosols, land surface and atmospheric circulation as represented in climate models We will present our initial results addressing the factors that control the variability of the wet season onset over Amazonia, the influence of convective types on atmospheric diabatic heating based on GoAmazon and CHUVA.

Assessing Mammal Exposure to Climate Change in the Brazilian Amazon.

PubMed

Ribeiro, Bruno R; Sales, Lilian P; De Marco, Paulo; Loyola, Rafael

2016-01-01

Human-induced climate change is considered a conspicuous threat to biodiversity in the 21st century. Species' response to climate change depends on their exposition, sensitivity and ability to adapt to novel climates. Exposure to climate change is however uneven within species' range, so that some populations may be more at risk than others. Identifying the regions most exposed to climate change is therefore a first and pivotal step on determining species' vulnerability across their geographic ranges. Here, we aimed at quantifying mammal local exposure to climate change across species' ranges. We identified areas in the Brazilian Amazon where mammals will be critically exposed to non-analogue climates in the future with different variables predicted by 15 global circulation climate forecasts. We also built a null model to assess the effectiveness of the Amazon protected areas in buffering the effects of climate change on mammals, using an innovative and more realistic approach. We found that 85% of species are likely to be exposed to non-analogue climatic conditions in more than 80% of their ranges by 2070. That percentage is even higher for endemic mammals; almost all endemic species are predicted to be exposed in more than 80% of their range. Exposure patterns also varied with different climatic variables and seem to be geographically structured. Western and northern Amazon species are more likely to experience temperature anomalies while northeastern species will be more affected by rainfall abnormality. We also observed an increase in the number of critically-exposed species from 2050 to 2070. Overall, our results indicate that mammals might face high exposure to climate change and that protected areas will probably not be efficient enough to avert those impacts.

Assessing Mammal Exposure to Climate Change in the Brazilian Amazon

PubMed Central

Ribeiro, Bruno R.; Sales, Lilian P.; De Marco, Paulo; Loyola, Rafael

2016-01-01

Human-induced climate change is considered a conspicuous threat to biodiversity in the 21st century. Species’ response to climate change depends on their exposition, sensitivity and ability to adapt to novel climates. Exposure to climate change is however uneven within species’ range, so that some populations may be more at risk than others. Identifying the regions most exposed to climate change is therefore a first and pivotal step on determining species’ vulnerability across their geographic ranges. Here, we aimed at quantifying mammal local exposure to climate change across species’ ranges. We identified areas in the Brazilian Amazon where mammals will be critically exposed to non-analogue climates in the future with different variables predicted by 15 global circulation climate forecasts. We also built a null model to assess the effectiveness of the Amazon protected areas in buffering the effects of climate change on mammals, using an innovative and more realistic approach. We found that 85% of species are likely to be exposed to non-analogue climatic conditions in more than 80% of their ranges by 2070. That percentage is even higher for endemic mammals; almost all endemic species are predicted to be exposed in more than 80% of their range. Exposure patterns also varied with different climatic variables and seem to be geographically structured. Western and northern Amazon species are more likely to experience temperature anomalies while northeastern species will be more affected by rainfall abnormality. We also observed an increase in the number of critically-exposed species from 2050 to 2070. Overall, our results indicate that mammals might face high exposure to climate change and that protected areas will probably not be efficient enough to avert those impacts. PMID:27829036

Climate change adaptation strategies and mitigation policies

NASA Astrophysics Data System (ADS)

García Fernández, Cristina

2015-04-01

The pace of climate change and the consequent warming of the Earth's surface is increasing vulnerability and decreasing adaptive capacity. Achieving a successful adaptation depends on the development of technology, institutional organization, financing availability and the exchange of information. Populations living in arid and semi-arid zones, low-lying coastal areas, land with water shortages or at risk of overflow or small islands are particularly vulnerable to climate change. Due to increasing population density in sensitive areas, some regions have become more vulnerable to events such as storms, floods and droughts, like the river basins and coastal plains. Human activities have fragmented and increased the vulnerability of ecosystems, which limit both, their natural adaptation and the effectiveness of the measures adopted. Adaptation means to carry out the necessary modifications for society to adapt to new climatic conditions in order to reduce their vulnerability to climate change. Adaptive capacity is the ability of a system to adjust to climate change (including climate variability and extremes) and to moderate potential damages, to take advantage of opportunities or face the consequences. Adaptation reduces the adverse impacts of climate change and enhance beneficial impacts, but will not prevent substantial cost that are produced by all damages. The performances require adaptation actions. These are defined and implemented at national, regional or local levels since many of the impacts and vulnerabilities depend on the particular economic, geographic and social circumstances of each country or region. We will present some adaptation strategies at national and local level and revise some cases of its implementation in several vulnerable areas. However, adaptation to climate change must be closely related to mitigation policies because the degree of change planned in different climatic variables is a function of the concentration levels that are achieved by greenhouse gases in the atmosphere. Mitigation and adaptation are therefore complementary actions. In the long term, climate change without mitigation measures will likely exceed the adaptive capacity of natural, managed and human systems. Early adoption of mitigation measures would break the dependence on carbon-intensive infrastructures and reduce adaptation needs to climate change. It also can save on adaptation cost. Therefore mitigation is the key objective of the global warming problem but little is being done in this field. We will present some proposals of "preventive economically efficient" policies at a global and regional level which will constitute the complement to the adaptation aspect.

Elucidating dynamic responses of North Pacific fish populations to climatic forcing: Influence of life-history strategy

NASA Astrophysics Data System (ADS)

Yatsu, A.; Aydin, K. Y.; King, J. R.; McFarlane, G. A.; Chiba, S.; Tadokoro, K.; Kaeriyama, M.; Watanabe, Y.

2008-05-01

In order to explore mechanistic linkages between low-frequency ocean/climate variability, and fish population responses, we undertook comparative studies of time-series of recruitment-related productivity and the biomass levels of fish stocks representing five life-history strategies in the northern North Pacific between the 1950s and the present. We selected seven species: Japanese sardine ( Sardinopus melanostictus) and California sardine ( Sardinopus sagax) (opportunistic strategists), walleye pollock ( Theragra chalcogramma, intermediate strategist), pink salmon ( Oncorhynchus gorbuscha, salmonic strategist), sablefish ( Anoplopoma fimbria) and Pacific halibut ( Hippoglossus stenolepis) (periodic strategists) and spiny dogfish ( Squalus acanthias, equilibrium strategist). The responses in terms of productivity of sardine, pink salmon, sablefish and halibut to climatic regime shifts were generally immediate, delayed, or no substantial responses depending on the particular regime shift year and fish stock (population). In walleye pollock, there were some periods of high productivity and low productivity, but not coincidental to climatic regime shifts, likely due to indirect climate forcing impacts on both bottom-up and top-down processes. Biomass of zooplankton and all fish stocks examined, except for spiny dogfish whose data were limited, indicated a decadal pattern with the most gradual changes in periodic strategists and most intensive and rapid changes in opportunistic strategists. Responses of sardine productivity to regime shifts were the most intense, probably due to the absence of density-dependent effects and the availability of refuges from predators when sardine biomass was extremely low. Spiny dogfish were least affected by environmental variability. Conversely, spiny dogfish are likely to withstand only modest harvest rates due to their very low intrinsic rate of increase. Thus, each life-history strategy type had a unique response to climatic forcing, owing to their inherent biological traits such as mode, frequency and intensity of reproduction, early life style, age of maturity and longevity. On the other hand, responses of different stocks within a species to climatic regime shifts were unique to each local region, because large-scale climatic forcings are modulated by local physical, chemical and biological processes. The observed response time or absence of response in recruitment-related fish productivity to climatic regime shifts may be influenced by (1) local environmental conditions (immediate, with a delay or no effects), (2) phenological shifts in zooplankton life-history (immediate or with a delay), and (3) stochastic episodic events in both top-down and bottom-up processes (immediate, with a delay or no effects).

An index-based method to assess risks of climate-related hazards in coastal zones: The case of Tetouan

NASA Astrophysics Data System (ADS)

Satta, Alessio; Snoussi, Maria; Puddu, Manuela; Flayou, Latifa; Hout, Radouane

2016-06-01

The regional risk assessment carried out within the ClimVar & ICZM Project identified the coastal zone of Tetouan as a hotspot of the Mediterranean Moroccan coast and so it was chosen for the application of the Multi-Scale Coastal Risk Index for Local Scale (CRI-LS). The local scale approach provides a useful tool for local coastal planning and management by exploring the effects and the extensions of the hazards and combining hazard, vulnerability and exposure variables in order to identify areas where the risk is relatively high. The coast of Tetouan is one of the coastal areas that have been most rapidly and densely urbanized in Morocco and it is characterized by an erosive shoreline. Local authorities are facing the complex task of balancing development and managing coastal risks, especially coastal erosion and flooding, and then be prepared to the unavoidable impacts of climate change. The first phase of the application of the CRI-LS methodology to Tetouan consisted of defining the coastal hazard zone, which results from the overlaying of the erosion hazard zone and the flooding hazard zone. Nineteen variables were chosen to describe the Hazards, Vulnerability and Exposure factors. The scores corresponding to each variable were calculated and the weights assigned through an expert judgement elicitation. The resulting values are hosted in a geographic information system (GIS) platform that enables the individual variables and aggregated risk scores to be color-coded and mapped across the coastal hazard zone. The results indicated that 10% and 27% of investigated littoral fall under respectively very high and high vulnerability because of combination of high erosion rates with high capital land use. The risk map showed that some areas, especially the flood plains of Restinga, Smir and Martil-Alila, with distances over 5 km from the coast, are characterized by high levels of risk due to the low topography of the flood plains and to the high values of exposure. The CRI-LS provides a set of maps that allow identifying areas within the coastal hazard zone with relative higher risk from climate-related hazards. The method can be used to support coastal planning and management process in selecting the most suitable adaptation measures.

Simulating changes in ecosystem structure and composition in response to climate change: a case study focused on tropical nitrogen-fixing trees (Invited)

NASA Astrophysics Data System (ADS)

Medvigy, D.; Levy, J.; Xu, X.; Batterman, S. A.; Hedin, L.

2013-12-01

Ecosystems, by definition, involve a community of organisms. These communities generally exhibit heterogeneity in their structure and composition as a result of local variations in climate, soil, topography, disturbance history, and other factors. Climate-driven shifts in ecosystems will likely include an internal re-organization of community structure and composition and as well as the introduction of novel species. In terms of vegetation, this ecosystem heterogeneity can occur at relatively small scales, sometimes of the order of tens of meters or even less. Because this heterogeneous landscape generally has a variable and nonlinear response to environmental perturbations, it is necessary to carefully aggregate the local competitive dynamics between individual plants to the large scales of tens or hundreds of kilometers represented in climate models. Accomplishing this aggregation in a computationally efficient way has proven to be an extremely challenging task. To meet this challenge, the Ecosystem Demography 2 (ED2) model statistically characterizes a distribution of local resource environments, and then simulates the competition between individuals of different sizes and species (or functional groupings). Within this framework, it is possible to explicitly simulate the impacts of climate change on ecosystem structure and composition, including both internal re-organization and the introduction of novel species or functional groups. This presentation will include several illustrative applications of the evolution of ecosystem structure and composition under climate change. One application pertains to the role of nitrogen-fixing species in tropical forests. Will increasing CO2 concentrations increase the demand for nutrients and perhaps give a competitive edge to nitrogen-fixing species? Will potentially warmer and drier conditions make some tropical forests more water-limited, reducing the demand for nitrogen, thereby giving a competitive advantage to non-nitrogen-fixing species? Will the response of nitrogen-fixing species to climate change be sensitive to local disturbance histories?

Oscar: a portable prototype system for the study of climate variability

NASA Astrophysics Data System (ADS)

Madonna, Fabio; Rosoldi, Marco; Amato, Francesco

2015-04-01

The study of the techniques for the exploitation of solar energy implies the knowledge of nature, ecosystem, biological factors and local climate. Clouds, fog, water vapor, and the presence of large concentrations of dust can significantly affect the way to exploit the solar energy. Therefore, a quantitative characterization of the impact of climate variability at the regional scale is needed to increase the efficiency and sustainability of the energy system. OSCAR (Observation System for Climate Application at Regional scale) project, funded in the frame of the PO FESR 2007-2013, aims at the design of a portable prototype system for the study of correlations among the trends of several Essential Climate Variables (ECVs) and the change in the amount of solar irradiance at the ground level. The final goal of this project is to provide a user-friendly low cost solution for the quantification of the impact of regional climate variability on the efficiency of solar cell and concentrators to improve the exploitation of natural sources. The prototype has been designed on the basis of historical measurements performed at CNR-IMAA Atmospheric Observatory (CIAO). Measurements from satellite and data from models have been also considered as ancillary to the study, above all, to fill in the gaps of existing datasets. In this work, the results outcome from the project activities will be presented. The results include: the design and implementation of the prototype system; the development of a methodology for the estimation of the impact of climate variability, mainly due to aerosol, cloud and water vapor, on the solar irradiance using the integration of the observations potentially provided by prototype; the study of correlation between the surface radiation, precipitation and aerosols transport. In particular, a statistical study will be presented to assess the impact of the atmosphere on the solar irradiance at the ground, quantifying the contribution due to aerosol and clouds and separating their effect on the direct and the diffuse components of the solar radiation. This also aims to provide recommendations to the manufacturer of the devices used to exploit solar radiation.

Reconstructing medieval climate in the tropical North Atlantic with corals from Anegada, British Virgin Islands

NASA Astrophysics Data System (ADS)

Kilbourne, K. H.; Xu, Y. Y.

2014-12-01

Resolving the patterns of climate variability during the Medieval Climate Anomaly (MCA) is key for exploring forced versus unforced variability during the last 1000 years. Tropical Atlantic climate is currently not well resolved during the MCA despite it being an important source of heat and moisture to the climate system today. To fill this data gap, we collected cores from Diploria strigosa corals brought onto the low-lying island of Anegada, British Virgin Islands (18.7˚N, 64.3˚S) during an overwash event and use paired analysis of Sr/Ca and δ18O in the skeletal aragonite to explore climate in the tropical Atlantic at the end of the MCA. The three sub-fossil corals used in this analysis overlap temporally and together span the years 1256-1372 C.E. An assessment of three modern corals from the study site indicates that the most robust features of climate reconstructions using Sr/Ca and δ18O in this species are the seasonal cycle and inter-annual variability. The modern seasonal temperature range is 2.8 degrees Celsius and the similarity between the modern and sub-fossil coral Sr/Ca indicates a similar range during the MCA. Today seasonal salinity changes locally are driven in large part by the migration of a regional salinity front. The modern corals capture the related large seasonal seawater δ18O change, but the sub-fossil corals indicate stable seawater δ18O throughout the year, supporting the idea that this site remained on one side of the salinity front continuously throughout the year. Inter-annual variability in the region is influenced by the cross-equatorial SST gradient, the North Atlantic Oscillation and ENSO. Gridded instrumental SST from the area surrounding Anegada and coral geochemical records from nearby Puerto Rico demonstrate concentrations of variance in specific frequency bands associated with these phenomena. The sub-fossil coral shows no concentration of variance in the modern ENSO frequency band, consistent with reduced ENSO variability found in central Pacific corals growing at the same time.

From GCM grid cell to agricultural plot: scale issues affecting modelling of climate impact

PubMed Central

Baron, Christian; Sultan, Benjamin; Balme, Maud; Sarr, Benoit; Traore, Seydou; Lebel, Thierry; Janicot, Serge; Dingkuhn, Michael

2005-01-01

General circulation models (GCM) are increasingly capable of making relevant predictions of seasonal and long-term climate variability, thus improving prospects of predicting impact on crop yields. This is particularly important for semi-arid West Africa where climate variability and drought threaten food security. Translating GCM outputs into attainable crop yields is difficult because GCM grid boxes are of larger scale than the processes governing yield, involving partitioning of rain among runoff, evaporation, transpiration, drainage and storage at plot scale. This study analyses the bias introduced to crop simulation when climatic data is aggregated spatially or in time, resulting in loss of relevant variation. A detailed case study was conducted using historical weather data for Senegal, applied to the crop model SARRA-H (version for millet). The study was then extended to a 10°N–17° N climatic gradient and a 31 year climate sequence to evaluate yield sensitivity to the variability of solar radiation and rainfall. Finally, a down-scaling model called LGO (Lebel–Guillot–Onibon), generating local rain patterns from grid cell means, was used to restore the variability lost by aggregation. Results indicate that forcing the crop model with spatially aggregated rainfall causes yield overestimations of 10–50% in dry latitudes, but nearly none in humid zones, due to a biased fraction of rainfall available for crop transpiration. Aggregation of solar radiation data caused significant bias in wetter zones where radiation was limiting yield. Where climatic gradients are steep, these two situations can occur within the same GCM grid cell. Disaggregation of grid cell means into a pattern of virtual synoptic stations having high-resolution rainfall distribution removed much of the bias caused by aggregation and gave realistic simulations of yield. It is concluded that coupling of GCM outputs with plot level crop models can cause large systematic errors due to scale incompatibility. These errors can be avoided by transforming GCM outputs, especially rainfall, to simulate the variability found at plot level. PMID:16433096

WaterWorld, a spatial hydrological model applied at scales from local to global: key challenges to local application

NASA Astrophysics Data System (ADS)

Burke, Sophia; Mulligan, Mark

2017-04-01

WaterWorld is a widely used spatial hydrological policy support system. The last user census indicates regular use by 1029 institutions across 141 countries. A key feature of WaterWorld since 2001 is that it comes pre-loaded with all of the required data for simulation anywhere in the world at a 1km or 1 ha resolution. This means that it can be easily used, without specialist technical ability, to examine baseline hydrology and the impacts of scenarios for change or management interventions to support policy formulation, hence its labelling as a policy support system. WaterWorld is parameterised by an extensive global gridded database of more than 600 variables, developed from many sources, since 1998, the so-called simTerra database. All of these data are available globally at 1km resolution and some variables (terrain, land cover, urban areas, water bodies) are available globally at 1ha resolution. If users have access to better data than is pre-loaded, they can upload their own data. WaterWorld is generally applied at the national or basin scale at 1km resolution, or locally (for areas of <10,000km2) at 1ha resolution, though continental (1km resolution) and global (10km resolution) applications are possible so it is a model with local to global applications. WaterWorld requires some 140 maps to run including monthly climate data, land cover and use, terrain, population, water bodies and more. Whilst publically-available terrain and land cover data are now well developed for local scale application, climate and land use data remain a challenge, with most global products being available at 1km or 10km resolution or worse, which is rather coarse for local application. As part of the EartH2Observe project we have used WFDEI (WATCH Forcing Data methodology applied to ERA-Interim data) at 1km resolution to provide an alternative input to WaterWorld's preloaded climate data. Here we examine the impacts of that on key hydrological outputs: water balance, water quality and outline the remaining challenges of using datasets like these for local scale application.

Improving High-Resolution Weather Forecasts Using the Weather Research and Forecasting (WRF) Model with an Updated Kain–Fritsch Scheme

EPA Science Inventory

Efforts to improve the prediction accuracy of high-resolution (1–10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at ...

Chronology for fluctuations in late Pleistocene Sierra Nevada glaciers and lakes

USGS Publications Warehouse

Phillips, F.M.; Zreda, M.G.; Benson, L.V.; Plummer, M.A.; Elmore, D.; Sharma, Prakash

1996-01-01

Mountain glaciers, because of their small size, are usually close to equilibrium with the local climate and thus should provide a test of whether temperature oscillations in Greenland late in the last glacial period are part of global-scale climate variability or are restricted to the North Atlantic region. Correlation of cosmogenic chlorine-36 dates on Sierra Nevada moraines with a continuous radiocarbon-dated sediment record from nearby Owens Lake shows that Sierra Nevada glacial advances were associated with Heinrich events 5, 3, 2, and 1.

Influence of climate on the presence of colour polymorphism in two montane reptile species.

PubMed

Broennimann, Olivier; Ursenbacher, Sylvain; Meyer, Andreas; Golay, Philippe; Monney, Jean-Claude; Schmocker, Hans; Guisan, Antoine; Dubey, Sylvain

2014-11-01

The coloration of ectotherms plays an important role in thermoregulation processes. Dark individuals should heat up faster and be able to reach a higher body temperature than light individuals and should therefore have benefits in cool areas. In central Europe, montane local populations of adder (Vipera berus) and asp viper (Vipera aspis) exhibit a varying proportion of melanistic individuals. We tested whether the presence of melanistic V. aspis and V. berus could be explained by climatic conditions. We measured the climatic niche position and breadth of monomorphic (including strictly patterned individuals) and polymorphic local populations, calculated their niche overlap and tested for niche equivalency and similarity. In accordance with expectations, niche overlap between polymorphic local populations of both species is high, and even higher than that of polymorphic versus monomorphic montane local populations of V. aspis, suggesting a predominant role of melanism in determining the niche of ectothermic vertebrates. However, unexpectedly, the niche of polymorphic local populations of both species is narrower than that of monomorphic ones, indicating that colour polymorphism does not always enable the exploitation of a greater variability of resources, at least at the intraspecific level. Overall, our results suggest that melanism might be present only when the thermoregulatory benefit is higher than the cost of predation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Seasonality in cholera dynamics: A rainfall-driven model explains the wide range of patterns in endemic areas

NASA Astrophysics Data System (ADS)

Baracchini, Theo; King, Aaron A.; Bouma, Menno J.; Rodó, Xavier; Bertuzzo, Enrico; Pascual, Mercedes

2017-10-01

Seasonal patterns in cholera dynamics exhibit pronounced variability across geographical regions, showing single or multiple peaks at different times of the year. Although multiple hypotheses related to local climate variables have been proposed, an understanding of this seasonal variation remains incomplete. The historical Bengal region, which encompasses the full range of cholera's seasonality observed worldwide, provides a unique opportunity to gain insights on underlying environmental drivers. Here, we propose a mechanistic, rainfall-temperature driven, stochastic epidemiological model which explicitly accounts for the fluctuations of the aquatic reservoir, and analyze with this model the historical dataset of cholera mortality in the Bengal region. Parameters are inferred with a recently developed sequential Monte Carlo method for likelihood maximization in partially observed Markov processes. Results indicate that the hydrological regime is a major driver of the seasonal dynamics of cholera. Rainfall tends to buffer the propagation of the disease in wet regions due to the longer residence times of water in the environment and an associated dilution effect, whereas it enhances cholera resurgence in dry regions. Moreover, the dynamics of the environmental water reservoir determine whether the seasonality is unimodal or bimodal, as well as its phase relative to the monsoon. Thus, the full range of seasonal patterns can be explained based solely on the local variation of rainfall and temperature. Given the close connection between cholera seasonality and environmental conditions, a deeper understanding of the underlying mechanisms would allow the better management and planning of public health policies with respect to climate variability and climate change.

Multiscale climate emulator of multimodal wave spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, Ana; Hegermiller, Christie A.; Antolinez, Jose A. A.; Camus, Paula; Vitousek, Sean; Ruggiero, Peter; Barnard, Patrick L.; Erikson, Li H.; Tomás, Antonio; Mendez, Fernando J.

2017-02-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this complex problem tractable using computationally expensive numerical models. So far, the skill of statistical-downscaling model-based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Multiscale Climate Emulator of Multimodal Wave Spectra: MUSCLE-spectra

NASA Astrophysics Data System (ADS)

Rueda, A.; Hegermiller, C.; Alvarez Antolinez, J. A.; Camus, P.; Vitousek, S.; Ruggiero, P.; Barnard, P.; Erikson, L. H.; Tomas, A.; Mendez, F. J.

2016-12-01

Characterization of multimodal directional wave spectra is important for many offshore and coastal applications, such as marine forecasting, coastal hazard assessment, and design of offshore wave energy farms and coastal structures. However, the multivariate and multiscale nature of wave climate variability makes this problem complex yet tractable using computationally-expensive numerical models. So far, the skill of statistical-downscaling models based parametric (unimodal) wave conditions is limited in large ocean basins such as the Pacific. The recent availability of long-term directional spectral data from buoys and wave hindcast models allows for development of stochastic models that include multimodal sea-state parameters. This work introduces a statistical-downscaling framework based on weather types to predict multimodal wave spectra (e.g., significant wave height, mean wave period, and mean wave direction from different storm systems, including sea and swells) from large-scale atmospheric pressure fields. For each weather type, variables of interest are modeled using the categorical distribution for the sea-state type, the Generalized Extreme Value (GEV) distribution for wave height and wave period, a multivariate Gaussian copula for the interdependence between variables, and a Markov chain model for the chronology of daily weather types. We apply the model to the Southern California coast, where local seas and swells from both the Northern and Southern Hemispheres contribute to the multimodal wave spectrum. This work allows attribution of particular extreme multimodal wave events to specific atmospheric conditions, expanding knowledge of time-dependent, climate-driven offshore and coastal sea-state conditions that have a significant influence on local nearshore processes, coastal morphology, and flood hazards.

Sensitivity of Statistical Downscaling Techniques to Reanalysis Choice and Implications for Regional Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Manzanas, R., Sr.; Brands, S.; San Martin, D., Sr.; Gutiérrez, J. M., Sr.

2014-12-01

This work shows that local-scale climate projections obtained by means of statistical downscaling are sensitive to the choice of reanalysis used for calibration. To this aim, a Generalized Linear Model (GLM) approach is applied to downscale daily precipitation in the Philippines. First, the GLMs are trained and tested -under a cross-validation scheme- separately for two distinct reanalyses (ERA-Interim and JRA-25) for the period 1981-2000. When the observed and downscaled time-series are compared, the attained performance is found to be sensitive to the reanalysis considered if climate change signal bearing variables (temperature and/or specific humidity) are included in the predictor field. Moreover, performance differences are shown to be in correspondence with the disagreement found between the raw predictors from the two reanalyses. Second, the regression coefficients calibrated either with ERA-Interim or JRA-25 are subsequently applied to the output of a Global Climate Model (MPI-ECHAM5) in order to assess the sensitivity of local-scale climate change projections (up to 2100) to reanalysis choice. In this case, the differences detected in present climate conditions are considerably amplified, leading to "delta-change" estimates differing by up to a 35% (on average for the entire country) depending on the reanalysis used for calibration. Therefore, reanalysis choice is shown to importantly contribute to the uncertainty of local-scale climate change projections, and, consequently, should be treated with equal care as other, well-known, sources of uncertainty -e.g., the choice of the GCM and/or downscaling method.- Implications of the results for the entire tropics, as well as for the Model Output Statistics downscaling approach are also briefly discussed.

An Alexandrium Spp. Cyst Record from Sequim Bay, Washington State, USA, and its Relation to Past Climate Variability(1).

PubMed

Feifel, Kirsten M; Moore, Stephanie K; Horner, Rita A

2012-06-01

Since the 1970s, Puget Sound, Washington State, USA, has experienced an increase in detections of paralytic shellfish toxins (PSTs) in shellfish due to blooms of the harmful dinoflagellate Alexandrium. Natural patterns of climate variability, such as the Pacific Decadal Oscillation (PDO), and changes in local environmental factors, such as sea surface temperature (SST) and air temperature, have been linked to the observed increase in PSTs. However, the lack of observations of PSTs in shellfish prior to the 1950s has inhibited statistical assessments of longer-term trends in climate and environmental conditions on Alexandrium blooms. After a bloom, Alexandrium cells can enter a dormant cyst stage, which settles on the seafloor and then becomes entrained into the sedimentary record. In this study, we created a record of Alexandrium spp. cysts from a sediment core obtained from Sequim Bay, Puget Sound. Cyst abundances ranged from 0 to 400 cysts · cm(-3) and were detected down-core to a depth of 100 cm, indicating that Alexandrium has been present in Sequim Bay since at least the late 1800s. The cyst record allowed us to statistically examine relationships with available environmental parameters over the past century. Local air temperature and sea surface temperature were positively and significantly correlated with cyst abundances from the late 1800s to 2005; no significant relationship was found between PDO and cyst abundances. This finding suggests that local environmental variations more strongly influence Alexandrium population dynamics in Puget Sound when compared to large-scale changes. © 2012 Phycological Society of America.

Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

NASA Astrophysics Data System (ADS)

Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul

2018-01-01

Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.

Retrospective Analysis of Low Flows at Headwater Watersheds in Wyoming

NASA Astrophysics Data System (ADS)

Voutchkova, D. D.; Miller, S. N.

2016-12-01

Understanding summer low-flow variability and change in the mountainous West has important implications for water allocations downstream and for maintaining water availability for drinking water supply, reservoir storage, industrial, agricultural, and ecological needs. Wildfires and insect infestations are classical disturbance hydrology topics. It is unclear, however, what are their effects on streamflow and in particular low-flows, when vegetation disturbances are overlapping in time and combined with highly variable and potentially changing local climate. The purpose of this study, therefore, is to quantify changes in low-flows resulting from disturbance in headwater streams. Here we present a retrospective analysis based on: (1) 49-75 complete water years (wy) of daily streamflow data (USGS) for 14 high-elevation headwater watersheds with varying areas (60-1730 km2, 86-100% of watershed area >2000masl) and evergreen forest cover (15-82%), (2) 25-36 complete wy of daily snow-water equivalent accumulation (SWE) and precipitation data from Wyoming SNOTEL stations, (3) burned area boundaries for 20wy (MTBS project), (4) aerial surveys by R1, R2, R4 Forest Service Regions for 18wy (data on tree mortality). We quantify the change in various low-flow characteristics (e.g. post-snowmelt baseflow, Q90 and Q95, 3-,7-, 30- and 90-day annual minima etc.) while accounting for local inter- and multi-annual climate variability by using SWE accumulation data, as it integrates both temperature and precipitation changes. Our approach differs from typical before-after field-based investigation for paired watersheds, as it provides a synthesis over large temporal and spatial scales, resulting in spectrum of possible hydrologic responses due to varying disturbance severity. Quantifying the changes in low-flows and low-flow variability will improve our understanding and will facilitate water management and planning at local state-wide level.

Strong sensitivity of Pine Island ice-shelf melting to climatic variability.

PubMed

Dutrieux, Pierre; De Rydt, Jan; Jenkins, Adrian; Holland, Paul R; Ha, Ho Kyung; Lee, Sang Hoon; Steig, Eric J; Ding, Qinghua; Abrahamsen, E Povl; Schröder, Michael

2014-01-10

Pine Island Glacier has thinned and accelerated over recent decades, significantly contributing to global sea-level rise. Increased oceanic melting of its ice shelf is thought to have triggered those changes. Observations and numerical modeling reveal large fluctuations in the ocean heat available in the adjacent bay and enhanced sensitivity of ice-shelf melting to water temperatures at intermediate depth, as a seabed ridge blocks the deepest and warmest waters from reaching the thickest ice. Oceanic melting decreased by 50% between January 2010 and 2012, with ocean conditions in 2012 partly attributable to atmospheric forcing associated with a strong La Niña event. Both atmospheric variability and local ice shelf and seabed geometry play fundamental roles in determining the response of the Antarctic Ice Sheet to climate.

A local scale assessment of the climate change sensitivity of snow in Pyrenean ski resorts

NASA Astrophysics Data System (ADS)

Pesado, Cristina; Pons, Marc; Vilella, Marc; López-Moreno, Juan Ignacio

2016-04-01

The Pyrenees host one of the largest ski area in Europe after the Alps that encompasses the mountain area of the south of France, the north of Spain and the small country of Andorra. In this region, winter tourism is one of the main source of income and driving force of local development on these mountain communities. However, this activity was identified as one of the most vulnerable to a future climate change due to the projected decrease of natural snow and snowmaking capacity. However, within the same ski resorts different areas showed to have a very different vulnerability within the same resort based on the geographic features of the area and the technical management of the slopes. Different areas inside a same ski resort could have very different vulnerability to future climate change based on aspect, steepness or elevation. Furthermore, the technical management of ski resorts, such as snowmaking and grooming were identified to have a significant impact on the response of the snowpack in a warmer climate. In this line, two different ski resorts were deeply analyzed taken into account both local geographical features as well as the effect of the technical management of the runs. Principal Component Analysis was used to classify the main areas of the resort based on the geographic features (elevation, aspect and steepness) and identify the main representative areas with different local features. Snow energy and mass balance was simulated in the different representative areas using the Cold Regions Hydrological Model (CRHM) assuming different magnitudes of climate warming (increases of 2°C and 4°C in the mean winter temperature) both in natural conditions and assuming technical management of the slopes. Theses first results showed the different sensitivity and vulnerability to climate changes based on the local geography of the resort and the management of the ski runs, showing the importance to include these variables when analyzing the local vulnerability of a ski resort and the potential adaptation measures in each particular case.

Projecting climate effects on birds and reptiles of the Southwestern United States

USGS Publications Warehouse

van Riper, Charles; Hatten, James R.; Giermakowski, J. Tomasz; Mattson, David; Holmes, Jennifer A.; Johnson, Matthew J.; Nowak, Erika M.; Ironside, Kirsten; Peters, Michael; Heinrich, Paul; Cole, K.L.; Truettner, C.; Schwalbe, Cecil R.

2014-01-01

We modeled the current and future breeding ranges of seven bird and five reptile species in the Southwestern United States with sets of landscape, biotic (plant), and climatic global circulation model (GCM) variables. For modeling purposes, we used PRISM data to characterize the climate of the Western United States between 1980 and 2009 (baseline for birds) and between 1940 and 2009 (baseline for reptiles). In contrast, we used a pre-selected set of GCMs that are known to be good predictors of southwestern climate (five individual and one ensemble GCM), for the A1B emission scenario, to characterize future climatic conditions in three time periods (2010–39; 2040–69; and, 2070–99). Our modeling approach relied on conceptual models for each target species to inform selection of candidate explanatory variables and to interpret the ecological meaning of developed probabilistic distribution models. We employed logistic regression and maximum entropy modeling techniques to create a set of probabilistic models for each target species. We considered climatic, landscape, and plant variables when developing and testing our probabilistic models. Climatic variables included the maximum and minimum mean monthly and seasonal temperature and precipitation for three time periods. Landscape features included terrain ruggedness and insolation. We also considered plant species distributions as candidate explanatory variables where prior ecological knowledge implicated a strong association between a plant and animal species. Projected changes in range varied widely among species, from major losses to major gains. Breeding bird ranges exhibited greater expansions and contractions than did reptile species. We project range losses for Williamson’s sapsucker and pygmy nuthatch of a magnitude that could move these two species close to extinction within the next century. Although both species currently have a relatively limited distribution, they can be locally common, and neither are presently considered candidates for prospective endangerment. We project range losses of over 40 percent, from its current extent of occurrence, for the plateau striped whiptail, Arizona black rattlesnake, and common lesser earless lizard. Currently, these reptile species are thought to be common or at least locally abundant throughout their ranges. The total contribution of plants in each distribution model was very small, but models that contained at least one plant always outperformed models with only physical variables (climatic or landscape). The magnitude of change in projected range increased further into the future, especially when a plant was in the model. Among bird species, those that had the strongest association with a landscape feature during the breeding season, such as terrain ruggedness and insolation, exhibited the smallest contractions in projected breeding range in the future. In contrast, bird species that had weak associations with landscape features, but strong climatic associations, suffered the greatest breeding range contractions. Thus, landscape effects appeared to buffer some of the negative effects of climate change for some species. Among bird species, magnitude of change in projected breeding range was positively related to the annual average temperature of their baseline distribution, thus species with the warmest breeding ranges exhibited the greatest changes in future breeding ranges. This pattern was not evident for reptiles, but might exist if additional species were included in the model. Our results provide managers with a series of projected range maps that will enable scientists, concerned citizens, and wildlife managers to identify what the potential effects of climate change will be on bird and reptile distributions in the Western United States. We hope that our results can be used in proactive ways to mitigate some of the potential effects of climate change on selected species.

Effect of Climate Change on Mediterranean Winter Ranges of Two Migratory Passerines.

PubMed

Tellería, José L; Fernández-López, Javier; Fandos, Guillermo

2016-01-01

We studied the effect of climate change on the distribution of two insectivorous passerines (the meadow pipit Anthus pratensis and the chiffchaff Phylloscopus collybita) in wintering grounds of the Western Mediterranean basin. In this region, precipitation and temperature can affect the distribution of these birds through direct (thermoregulation costs) or indirect effects (primary productivity). Thus, it can be postulated that projected climate changes in the region will affect the extent and suitability of their wintering grounds. We studied pipit and chiffchaff abundance in several hundred localities along a belt crossing Spain and Morocco and assessed the effects of climate and other geographical and habitat predictors on bird distribution. Multivariate analyses reported a positive effect of temperature on the present distribution of the two species, with an additional effect of precipitation on the meadow pipit. These climate variables were used with Maxent to model the occurrence probabilities of species using ring recoveries as presence data. Abundance and occupancy of the two species in the study localities adjusted to the distribution models, with more birds in sectors of high climate suitability. After validation, these models were used to forecast the distribution of climate suitability according to climate projections for 2050-2070 (temperature increase and precipitation reduction). Results show an expansion of climatically suitable sectors into the highlands by the effect of warming on the two species, and a retreat of the meadow pipit from southern sectors related to rain reduction. The predicted patterns show a mean increase in climate suitability for the two species due to the warming of the large highland expanses typical of the western Mediterranean.

Development of hi-resolution regional climate scenarios in Japan by statistical downscaling

NASA Astrophysics Data System (ADS)

Dairaku, K.

2016-12-01

Climate information and services for Impacts, Adaptation and Vulnerability (IAV) Assessments are of great concern. To meet with the needs of stakeholders such as local governments, a Japan national project, Social Implementation Program on Climate Change Adaptation Technology (SI-CAT), launched in December 2015. It develops reliable technologies for near-term climate change predictions. Multi-model ensemble regional climate scenarios with 1km horizontal grid-spacing over Japan are developed by using CMIP5 GCMs and a statistical downscaling method to support various municipal adaptation measures appropriate for possible regional climate changes. A statistical downscaling method, Bias Correction Spatial Disaggregation (BCSD), is employed to develop regional climate scenarios based on CMIP5 RCP8.5 five GCMs (MIROC5, MRI-CGCM3, GFDL-CM3, CSIRO-Mk3-6-0, HadGEM2-ES) for the periods of historical climate (1970-2005) and near future climate (2020-2055). Downscaled variables are monthly/daily precipitation and temperature. File format is NetCDF4 (conforming to CF1.6, HDF5 compression). Developed regional climate scenarios will be expanded to meet with needs of stakeholders and interface applications to access and download the data are under developing. Statistical downscaling method is not necessary to well represent locally forced nonlinear phenomena, extreme events such as heavy rain, heavy snow, etc. To complement the statistical method, dynamical downscaling approach is also combined and applied to some specific regions which have needs of stakeholders. The added values of statistical/dynamical downscaling methods compared with parent GCMs are investigated.

Effects of Hydrological Parameters on Palm Oil Fresh Fruit Bunch Yield)

NASA Astrophysics Data System (ADS)

Nda, M.; Adnan, M. S.; Suhadak, M. A.; Zakaria, M. S.; Lopa, R. T.

2018-04-01

Climate change effects and variability have been studied by many researchers in diverse geophysical fields. Malaysia produces large volume of palm oil, the effects of climate change on hydrological parameters (rainfall and precipitation) could have adverse effects on palm oil fresh fruit bunch (FFB) production with implications at both local and international market. It is important to understand the effects of climate change on crop yield to adopt new cultivation techniques and guaranteeing food security globally. Based on this background, the paper’s objective is to investigate the effects of rainfall and temperature pattern on crop yield (FFB) within five years period (2013 - 2017) at Batu Pahat District. The Man - Kendall rank technique (trend test) and statistical analyses (correlation and regression) were applied to the dataset used for the study. The results reveal that there are variabilities in rainfall and temperature from one month to the other and the statistical analysis reveals that the hydrological parameters have an insignificant effect on crop yield.