Processes Understanding of Decadal Climate Variability

NASA Astrophysics Data System (ADS)

Prömmel, Kerstin; Cubasch, Ulrich

2016-04-01

The realistic representation of decadal climate variability in the models is essential for the quality of decadal climate predictions. Therefore, the understanding of those processes leading to decadal climate variability needs to be improved. Several of these processes are already included in climate models but their importance has not yet completely been clarified. The simulation of other processes requires sometimes a higher resolution of the model or an extension by additional subsystems. This is addressed within one module of the German research program "MiKlip II - Decadal Climate Predictions" (http://www.fona-miklip.de/en/) with a focus on the following processes. Stratospheric processes and their impact on the troposphere are analysed regarding the climate response to aerosol perturbations caused by volcanic eruptions and the stratospheric decadal variability due to solar forcing, climate change and ozone recovery. To account for the interaction between changing ozone concentrations and climate a computationally efficient ozone chemistry module is developed and implemented in the MiKlip prediction system. The ocean variability and air-sea interaction are analysed with a special focus on the reduction of the North Atlantic cold bias. In addition, the predictability of the oceanic carbon uptake with a special emphasis on the underlying mechanism is investigated. This addresses a combination of physical, biological and chemical processes.

Does climate variability influence the demography of wild primates? Evidence from long-term life-history data in seven species.

PubMed

Campos, Fernando A; Morris, William F; Alberts, Susan C; Altmann, Jeanne; Brockman, Diane K; Cords, Marina; Pusey, Anne; Stoinski, Tara S; Strier, Karen B; Fedigan, Linda M

2017-11-01

Earth's rapidly changing climate creates a growing need to understand how demographic processes in natural populations are affected by climate variability, particularly among organisms threatened by extinction. Long-term, large-scale, and cross-taxon studies of vital rate variation in relation to climate variability can be particularly valuable because they can reveal environmental drivers that affect multiple species over extensive regions. Few such data exist for animals with slow life histories, particularly in the tropics, where climate variation over large-scale space is asynchronous. As our closest relatives, nonhuman primates are especially valuable as a resource to understand the roles of climate variability and climate change in human evolutionary history. Here, we provide the first comprehensive investigation of vital rate variation in relation to climate variability among wild primates. We ask whether primates are sensitive to global changes that are universal (e.g., higher temperature, large-scale climate oscillations) or whether they are more sensitive to global change effects that are local (e.g., more rain in some places), which would complicate predictions of how primates in general will respond to climate change. To address these questions, we use a database of long-term life-history data for natural populations of seven primate species that have been studied for 29-52 years to investigate associations between vital rate variation, local climate variability, and global climate oscillations. Associations between vital rates and climate variability varied among species and depended on the time windows considered, highlighting the importance of temporal scale in detection of such effects. We found strong climate signals in the fertility rates of three species. However, survival, which has a greater impact on population growth, was little affected by climate variability. Thus, we found evidence for demographic buffering of life histories, but also evidence of mechanisms by which climate change could affect the fates of wild primates. © 2017 John Wiley & Sons Ltd.

The Climate Variability & Predictability (CVP) Program at NOAA - Observing and Understanding Processes Affecting the Propagation of Intraseasonal Oscillations in the Maritime Continent Region

NASA Astrophysics Data System (ADS)

Lucas, S. E.

2017-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). In 2017, the CVP Program had a call for proposals focused on observing and understanding processes affecting the propagation of intraseasonal oscillations in the Maritime Continent region. This poster will present the recently funded CVP projects, the expected scientific outcomes, the geographic areas of their work in the Maritime Continent region, and the collaborations with the Office of Naval Research, Indonesian Agency for Meteorology, Climatology and Geophysics (BMKG), Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and other partners.

The Space-Time Variation of Global Crop Yields, Detecting Simultaneous Outliers and Identifying the Teleconnections with Climatic Patterns

NASA Astrophysics Data System (ADS)

Najafi, E.; Devineni, N.; Pal, I.; Khanbilvardi, R.

2017-12-01

An understanding of the climate factors that influence the space-time variability of crop yields is important for food security purposes and can help us predict global food availability. In this study, we address how the crop yield trends of countries globally were related to each other during the last several decades and the main climatic variables that triggered high/low crop yields simultaneously across the world. Robust Principal Component Analysis (rPCA) is used to identify the primary modes of variation in wheat, maize, sorghum, rice, soybeans, and barley yields. Relations between these modes of variability and important climatic variables, especially anomalous sea surface temperature (SSTa), are examined from 1964 to 2010. rPCA is also used to identify simultaneous outliers in each year, i.e. systematic high/low crop yields across the globe. The results demonstrated spatiotemporal patterns of these crop yields and the climate-related events that caused them as well as the connection of outliers with weather extremes. We find that among climatic variables, SST has had the most impact on creating simultaneous crop yields variability and yield outliers in many countries. An understanding of this phenomenon can benefit global crop trade networks.

Climate Change: Potential Effects on Demands for US Military Humanitarian Assistance and Disaster Response

DTIC Science & Technology

2010-11-01

As we do not fully understand how decision-makers will approach future climate- induced requirements, gaming provides a tool for better understanding...result in the need for humanitarian response missions. Those cases involve not only the stress induced by the natural environment, but also the...natural cyclic variability and a warming- induced variability. The pri- mary variability related to SST involves the strength of the storms, rather

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

Treesearch

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

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...

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern US

USGS Publications Warehouse

Gremer, Jennifer; Bradford, John B.; Munson, Seth M.; Duniway, Michael C.

2015-01-01

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20 to 56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40 to 60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands.

Desert grassland responses to climate and soil moisture suggest divergent vulnerabilities across the southwestern United States.

PubMed

Gremer, Jennifer R; Bradford, John B; Munson, Seth M; Duniway, Michael C

2015-11-01

Climate change predictions include warming and drying trends, which are expected to be particularly pronounced in the southwestern United States. In this region, grassland dynamics are tightly linked to available moisture, yet it has proven difficult to resolve what aspects of climate drive vegetation change. In part, this is because it is unclear how heterogeneity in soils affects plant responses to climate. Here, we combine climate and soil properties with a mechanistic soil water model to explain temporal fluctuations in perennial grass cover, quantify where and the degree to which incorporating soil water dynamics enhances our ability to understand temporal patterns, and explore the potential consequences of climate change by assessing future trajectories of important climate and soil water variables. Our analyses focused on long-term (20-56 years) perennial grass dynamics across the Colorado Plateau, Sonoran, and Chihuahuan Desert regions. Our results suggest that climate variability has negative effects on grass cover, and that precipitation subsidies that extend growing seasons are beneficial. Soil water metrics, including the number of dry days and availability of water from deeper (>30 cm) soil layers, explained additional grass cover variability. While individual climate variables were ranked as more important in explaining grass cover, collectively soil water accounted for 40-60% of the total explained variance. Soil water conditions were more useful for understanding the responses of C3 than C4 grass species. Projections of water balance variables under climate change indicate that conditions that currently support perennial grasses will be less common in the future, and these altered conditions will be more pronounced in the Chihuahuan Desert and Colorado Plateau. We conclude that incorporating multiple aspects of climate and accounting for soil variability can improve our ability to understand patterns, identify areas of vulnerability, and predict the future of desert grasslands. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

The CESM Large Ensemble Project: Inspiring New Ideas and Understanding

NASA Astrophysics Data System (ADS)

Kay, J. E.; Deser, C.

2016-12-01

While internal climate variability is known to affect climate projections, its influence is often underappreciated and confused with model error. Why? In general, modeling centers contribute a small number of realizations to international climate model assessments [e.g., phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. As a result, model error and internal climate variability are difficult, and at times impossible, to disentangle. In response, the Community Earth System Model (CESM) community designed the CESM Large Ensemble (CESM-LE) with the explicit goal of enabling assessment of climate change in the presence of internal climate variability. All CESM-LE simulations use a single CMIP5 model (CESM with the Community Atmosphere Model, version 5). The core simulations replay the twenty to twenty-first century (1920-2100) 40+ times under historical and representative concentration pathway 8.5 external forcing with small initial condition differences. Two companion 2000+-yr-long preindustrial control simulations (fully coupled, prognostic atmosphere and land only) allow assessment of internal climate variability in the absence of climate change. Comprehensive outputs, including many daily fields, are available as single-variable time series on the Earth System Grid for anyone to use. Examples of scientists and stakeholders that are using the CESM-LE outputs to help interpret the observational record, to understand projection spread and to plan for a range of possible futures influenced by both internal climate variability and forced climate change will be highlighted the presentation.

Identifying Decadal to Multi-decadal Variability in the Pacific by Empirical Mode Decomposition

NASA Astrophysics Data System (ADS)

Sommers, L. A.; Hamlington, B.; Cheon, S. H.

2016-12-01

Large scale climate variability in the Pacific Ocean like that associated with ENSO and the Pacific Decadal Oscillation (PDO) has been shown to have a significant impact on climate and sea level across a range of timescales. The changes related to these climate signals have worldwide impacts on fisheries, weather, and precipitation patterns among others. Understanding these inter-annual to multi-decadal oscillations is imperative to longer term climate forecasts and understanding how climate will behave, and its effect on changes in sea level. With a 110-year reconstruction of sea level, we examine decadal to multi-decadal variability seen in the sea level fluctuations in the Pacific Ocean. Using empirical mode decomposition (EMD), we break down regional sea level into a series of intrinsic mode functions (IMFs) and attempt attribution of these IMFs to specific climate modes of variability. In particular, and not unexpectedly, we identify IMFs associated with the PDO, finding correlations between the PDO Index and IMFs in the Pacific Ocean upwards of 0.6-0.8 over the 110-year reconstructed record. Perhaps more significantly, we also find evidence of a longer multi-decadal signal ( 50-60 years) in the higher order IMFs. This lower frequency variability has been suggested in previous literature as influencing GMSL, but here we find a regional pattern associated with this multi-decadal signal. By identifying and separating these periodic climate signals, we can gain a better understanding of how the sea level variability associated with these modes can impact sea level on short timescales and serve to exacerbate the effects of long-term sea level change.

Quantitative approaches in climate change ecology

PubMed Central

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

2011-01-01

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

Medieval Warm Period Archives Preserved in Limpet Shells (Patella Vulgata) From Viking Deposits, United Kingdom

NASA Astrophysics Data System (ADS)

Mobilia, M.; Surge, D.

2008-12-01

The Medieval Warm Period (700-1100 YBP) represents a recent period of warm climate, and as such provides a powerful comparison to today's continuing warming trend. However, the spatial and temporal variability inherent in the Medieval Warm Period (MWP) makes it difficult to differentiate between global climate trends and regional variability. The continued study of this period will allow for the better understanding of temperature variability, both regional and global, during this climate interval. Our study is located in the Orkney Islands, Scotland, which is a critical area to understand climate dynamics. The North Atlantic Oscillation and Gulf Stream heavily influence climate in this region, and the study of climate intervals during the MWP will improve our understanding of the behavior of these climate mechanisms during this interval. Furthermore, the vast majority of the climate archive has been derived from either deep marine or arctic environments. Studying a coastal environment will offer valuable insight into the behavior of maritime climate during the MWP. Estimated seasonal sea surface temperature data were derived through isotopic analysis of limpet shells (Patella vulgata). Analysis of modern shells confirms that growth temperature tracks seasonal variation in ambient water temperature. Preliminary data from MWP shells record a seasonal temperature range comparable to that observed in the modern temperature data. We will extend the range of temperature data from the 10th through 14th centuries to advance our knowledge of seasonal temperature variability during the late Holocene.

Developing a historical climatology of Wales from Welsh and English language sources

NASA Astrophysics Data System (ADS)

MacDonald, N.; Davies, S. J.; Jones, C. A.; Charnell-White, C.

2009-04-01

Historical documentary records are recognised as valuable in understanding long term climate variability. In the UK, the Central England Temperature Series (1772- ) and the Lamb weather catalogue (1861- ) provide a detailed climate record for England, but the value of these archives in Wales and Scotland is more limited, though some long term instrumental series exist, particularly for cities such as Cardiff. The spatial distance from the central England area and a lower density of instrumental stations in Wales has limited understanding of climate variability during the instrumental period (~1750- ). This paper illustrates that historical documentary records represent a considerable resource, that to date have been underutilised in developing a more complete understanding of past weather and climate within many parts of Western Europe.

Exploiting temporal variability to understand tree recruitment response to climate change

Treesearch

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

2007-01-01

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

National climate assessment technical report on the impacts of climate and land use and land cover change

Treesearch

Thomas Loveland; Rezaul Mahmood; Toral Patel-Weynand; Krista Karstensen; Kari Beckendorf; Norman Bliss; Andrew Carleton

2012-01-01

This technical report responds to the recognition by the U.S. Global Change Research Program (USGCRP) and the National Climate Assessment (NCA) of the importance of understanding how land use and land cover (LULC) affects weather and climate variability and change and how that variability and change affects LULC. Current published, peer-reviewed, scientific literature...

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.

"What Controls the Structure and Stability of the Ocean Meridional Overturning Circulation: Implications for Abrupt Climate Change?"

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

Fedorov, Alexey

2013-11-23

The central goal of this research project is to understand the properties of the ocean meridional overturning circulation (MOC) – a topic critical for understanding climate variability and stability on a variety of timescales (from decadal to centennial and longer). Specifically, we have explored various factors that control the MOC stability and decadal variability in the Atlantic and the ocean thermal structure in general, including the possibility abrupt climate change. We have also continued efforts on improving the performance of coupled ocean-atmosphere GCMs.

Vulnerability of white spruce tree growth in interior Alaska in response to climate variability: dendrochronological, demographic, and experimental perspectives

Treesearch

A.D. McGuire; R.W. Ruess; A. Lloyd; J. Yarie; J.S. Clein; G.P. Juday

2010-01-01

This paper integrates dendrochronological, demographic, and experimental perspectives to improve understanding of the response of white spruce (Picea glauca (Moench) Voss) tree growth to climatic variability in interior Alaska. The dendrochronological analyses indicate that climate warming has led to widespread declines in white spruce growth...

Climate change/variability science and adaptive strategies for state and regional transportation decision making.

DOT National Transportation Integrated Search

2010-04-01

The objective of this study was to generate a baseline understanding of current policy responses to climate : change/variability at the state and regional transportation-planning and -decision levels. Specifically, : researchers were interested in th...

Global Climate Change: Valuable Insights from Concordant and Discordant Ice Core Histories

NASA Astrophysics Data System (ADS)

Mosley-Thompson, E.; Thompson, L. G.; Porter, S. E.; Goodwin, B. P.; Wilson, A. B.

2014-12-01

Earth's ice cover is responding to the ongoing large-scale warming driven in part by anthropogenic forces. The highest tropical and subtropical ice fields are dramatically shrinking and/or thinning and unique climate histories archived therein are now threatened, compromised or lost. Many ice fields in higher latitudes are also experiencing and recording climate system changes although these are often manifested in less evident and spectacular ways. The Antarctic Peninsula (AP) has experienced a rapid, widespread and dramatic warming over the last 60 years. Carefully selected ice fields in the AP allow reconstruction of long histories of key climatic variables. As more proxy climate records are recovered it is clear they reflect a combination of expected and unexpected responses to seemingly similar climate forcings. Recently acquired temperature and precipitation histories from the Bruce Plateau are examined within the context provided by other cores recently collected in the AP. Understanding the differences and similarities among these records provides a better understanding of the forces driving climate variability in the AP over the last century. The Arctic is also rapidly warming. The δ18O records from the Bona-Churchill and Mount Logan ice cores from southeast Alaska and southwest Yukon Territory, respectively, do not record this strong warming. The Aleutian Low strongly influences moisture transport to this geographically complex region, yet its interannual variability is preserved differently in these cores located just 110 km apart. Mount Logan is very sensitive to multi-decadal to multi-centennial climate shifts in the tropical Pacific while low frequency variability on Bona-Churchill is more strongly connected to Western Arctic sea ice extent. There is a natural tendency to focus more strongly on commonalities among records, particularly on regional scales. However, it is also important to investigate seemingly poorly correlated records, particularly those from geographically complex settings that appear to be dominated by similar large-scale climatological processes. Better understanding of the spatially and temporally diverse responses in such regions will expand our understanding of the mechanisms forcing climate variability in meteorologically complex environments.

A Generalized Stability Analysis of the AMOC in Earth System Models: Implication for Decadal Variability and Abrupt Climate Change

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

Fedorov, Alexey V.

2015-01-14

The central goal of this research project was to understand the mechanisms of decadal and multi-decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) as related to climate variability and abrupt climate change within a hierarchy of climate models ranging from realistic ocean models to comprehensive Earth system models. Generalized Stability Analysis, a method that quantifies the transient and asymptotic growth of perturbations in the system, is one of the main approaches used throughout this project. The topics we have explored range from physical mechanisms that control AMOC variability to the factors that determine AMOC predictability in the Earth systemmore » models, to the stability and variability of the AMOC in past climates.« less

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

PubMed Central

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

2013-01-01

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

Climate change adaptation and mitigation options a guide for natural resource managers in southern forest ecosystems

Treesearch

James M. Vose; Kier D. Klepzig

2014-01-01

The rapid pace of climate change and its direct and indirect effects on forest ecosystems present a pressing need for better scientific understanding and the development of new science-management partnerships. Understanding the effects of stressors and disturbances (including climatic variability), and developing and testing science-based management options to deal...

Intraseasonal Variability in the Atmosphere-Ocean Climate System. Second Edition

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Waliser, Duane E.

2011-01-01

Understanding and predicting the intraseasonal variability (ISV) of the ocean and atmosphere is crucial to improving long-range environmental forecasts and the reliability of climate change projections through climate models. This updated, comprehensive and authoritative second edition has a balance of observation, theory and modeling and provides a single source of reference for all those interested in this important multi-faceted natural phenomenon and its relation to major short-term climatic variations.

Towards the Prediction of Decadal to Centennial Climate Processes in the Coupled Earth System Model

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

Liu, Zhengyu; Kutzbach, J.; Jacob, R.

2011-12-05

In this proposal, we have made major advances in the understanding of decadal and long term climate variability. (a) We performed a systematic study of multidecadal climate variability in FOAM-LPJ and CCSM-T31, and are starting exploring decadal variability in the IPCC AR4 models. (b) We develop several novel methods for the assessment of climate feedbacks in the observation. (c) We also developed a new initialization scheme DAI (Dynamical Analogue Initialization) for ensemble decadal prediction. (d) We also studied climate-vegetation feedback in the observation and models. (e) Finally, we started a pilot program using Ensemble Kalman Filter in CGCM for decadalmore » climate prediction.« less

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

PubMed

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

2016-08-01

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

Exploring objective climate classification for the Himalayan arc and adjacent regions using gridded data sources

NASA Astrophysics Data System (ADS)

Forsythe, N.; Blenkinsop, S.; Fowler, H. J.

2015-05-01

A three-step climate classification was applied to a spatial domain covering the Himalayan arc and adjacent plains regions using input data from four global meteorological reanalyses. Input variables were selected based on an understanding of the climatic drivers of regional water resource variability and crop yields. Principal component analysis (PCA) of those variables and k-means clustering on the PCA outputs revealed a reanalysis ensemble consensus for eight macro-climate zones. Spatial statistics of input variables for each zone revealed consistent, distinct climatologies. This climate classification approach has potential for enhancing assessment of climatic influences on water resources and food security as well as for characterising the skill and bias of gridded data sets, both meteorological reanalyses and climate models, for reproducing subregional climatologies. Through their spatial descriptors (area, geographic centroid, elevation mean range), climate classifications also provide metrics, beyond simple changes in individual variables, with which to assess the magnitude of projected climate change. Such sophisticated metrics are of particular interest for regions, including mountainous areas, where natural and anthropogenic systems are expected to be sensitive to incremental climate shifts.

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

PubMed Central

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

2014-01-01

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

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

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

Fedorov, Alexey

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

NASA Astrophysics Data System (ADS)

Deal, Eric; Braun, Jean

2017-04-01

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

Climate variability and 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.

Leveraging federal science data and tools to help communities & business build climate resilience

NASA Astrophysics Data System (ADS)

Herring, D.

2016-12-01

Decision-makers in every sector and region of the United States are seeking actionable science-based information to help them understand and manage their climate-related risks. Translating data, tools and information from the domain of climate science to the domains of municipal, social, and economic decision-making raises complex questions—e.g., how to communicate causes and impacts of climate variability and change; how to show projections of plausible future climate scenarios; how to characterize and quantify vulnerabilities, risks, and opportunities facing communities and businesses; and how to make and implement "win-win" adaptation plans. These are the types of challenges being addressed by a public-private partnership of federal agencies, academic institutions, non-governmental organizations, and private businesses that are contributing to the development of the U.S. Climate Resilience Toolkit (toolkit.climate.gov), a new website designed to help people build resilience to extreme events caused by both natural climate variability and long-term climate change. The site's Climate Explorer is designed to help people understand potential climate conditions over the course of this century. It offers easy access to downloadable maps, graphs, and data tables of observed and projected temperature, precipitation and other decision-relevant climate variables dating back to 1950 and out to 2100. Of course, climate change is only one of many variables affecting decisions about the future so the Toolkit also ties climate information to a wide range of other relevant tools and information to help users to explore their vulnerabilities and risks. In this session, we will describe recent enhancements to the Toolkit, lessons learned from user engagements, and evidence that our approach of coupling scientific information with actionable decision-making processes is helping Americans build resilience to climate-related impacts.

Pacific Decadal Variability and Central Pacific Warming El Niño in a Changing Climate

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

Di Lorenzo, Emanuele

This research aimed at understanding the dynamics controlling decadal variability in the Pacific Ocean and its interactions with global-scale climate change. The first goal was to assess how the dynamics and statistics of the El Niño Southern Oscillation and the modes of Pacific decadal variability are represented in global climate models used in the IPCC. The second goal was to quantify how decadal dynamics are projected to change under continued greenhouse forcing, and determine their significance in the context of paleo-proxy reconstruction of long-term climate.

DOE Contribution to the 2015 US CLIVAR Project Office Budget

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

DeWeaver, Eric; Patterson, Michael

The primary goal of the US Climate Variability and Predictability (CLIVAR) Project Office is to enable science community planning and implementation of research to understand and predict climate variability and change on intraseasonal-to-centennial timescales, through observations and modeling with emphasis on the role of the ocean and its interaction with other elements of the Earth system, and to serve the climate community and society through the coordination and facilitation of research on outstanding climate questions.

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

USGS Publications Warehouse

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Promoting Climate Literacy and Conceptual Understanding among In-service Secondary Science Teachers requires an Epistemological Perspective

NASA Astrophysics Data System (ADS)

Bhattacharya, D.; Forbes, C.; Roehrig, G.; Chandler, M. A.

2017-12-01

Promoting climate literacy among in-service science teachers necessitates an understanding of fundamental concepts about the Earth's climate System (USGCRP, 2009). Very few teachers report having any formal instruction in climate science (Plutzer et al., 2016), therefore, rather simple conceptions of climate systems and their variability exist, which has implications for students' science learning (Francies et al., 1993; Libarkin, 2005; Rebich, 2005). This study uses the inferences from a NASA Innovations in Climate Education (NICE) teacher professional development program (CYCLES) to establish the necessity for developing an epistemological perspective among teachers. In CYCLES, 19 middle and high school (male=8, female=11) teachers were assessed for their understanding of global climate change (GCC). A qualitative analysis of their concept maps and an alignment of their conceptions with the Essential Principles of Climate Literacy (NOAA, 2009) demonstrated that participants emphasized on EPCL 1, 3, 6, 7 focusing on the Earth system, atmospheric, social and ecological impacts of GCC. However, EPCL 4 (variability in climate) and 5 (data-based observations and modeling) were least represented and emphasized upon. Thus, participants' descriptions about global climatic patterns were often factual rather than incorporating causation (why the temperatures are increasing) and/or correlation (describing what other factors might influence global temperatures). Therefore, engaging with epistemic dimensions of climate science to understand the processes, tools, and norms through which climate scientists study the Earth's climate system (Huxter et al., 2013) is critical for developing an in-depth conceptual understanding of climate. CLiMES (Climate Modeling and Epistemology of Science), a NSF initiative proposes to use EzGCM (EzGlobal Climate Model) to engage students and teachers in designing and running simulations, performing data processing activities, and analyzing computational models to develop their own evidence-based claims about the Earth's climate system. We describe how epistemological investigations can be conducted using EzGCM to bring the scientific process and authentic climate science practice to middle and high school classrooms.

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

USGS Publications Warehouse

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

2016-01-01

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

Solar Spectral Irradiance and Climate

NASA Technical Reports Server (NTRS)

Pilewskie, P.; Woods, T.; Cahalan, R.

2012-01-01

Spectrally resolved solar irradiance is recognized as being increasingly important to improving our understanding of the manner in which the Sun influences climate. There is strong empirical evidence linking total solar irradiance to surface temperature trends - even though the Sun has likely made only a small contribution to the last half-century's global temperature anomaly - but the amplitudes cannot be explained by direct solar heating alone. The wavelength and height dependence of solar radiation deposition, for example, ozone absorption in the stratosphere, absorption in the ocean mixed layer, and water vapor absorption in the lower troposphere, contribute to the "top-down" and "bottom-up" mechanisms that have been proposed as possible amplifiers of the solar signal. New observations and models of solar spectral irradiance are needed to study these processes and to quantify their impacts on climate. Some of the most recent observations of solar spectral variability from the mid-ultraviolet to the near-infrared have revealed some unexpected behavior that was not anticipated prior to their measurement, based on an understanding from model reconstructions. The atmospheric response to the observed spectral variability, as quantified in climate model simulations, have revealed similarly surprising and in some cases, conflicting results. This talk will provide an overview on the state of our understanding of the spectrally resolved solar irradiance, its variability over many time scales, potential climate impacts, and finally, a discussion on what is required for improving our understanding of Sun-climate connections, including a look forward to future observations.

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.

Convergence of Dynamic Vegetation Net Productivity Responses to Precipitation Variability from 10 Years of MODIS EVI

USDA-ARS?s Scientific Manuscript database

According to Global Climate Models (GCMs) the occurrence of extreme events of precipitation will be more frequent in the future. Therefore, important challenges arise regarding climate variability, which are mainly related to the understanding of ecosystem responses to changes in precipitation patte...

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

USDA-ARS?s Scientific Manuscript database

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

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.

Describing rainfall in northern Australia using multiple climate indices

NASA Astrophysics Data System (ADS)

Wilks Rogers, Cassandra Denise; Beringer, Jason

2017-02-01

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

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.

Northwest Regional Climate Assessment

NASA Technical Reports Server (NTRS)

Lipschultz, Fred

2011-01-01

Objectives are to establish a continuing, inclusive National process that: 1) synthesizes relevant science and information 2) increases understanding of what is known & not known 3) identifies information needs related to preparing for climate variability and change, and reducing climate impacts and vulnerability 4) evaluates progress of adaptation & mitigation activities 5) informs science priorities 6) builds assessment capacity in regions and sectors 7) builds understanding & skilled use of findings

Climate Variability, Climate Change and Social Vulnerability in the Semi-arid Tropics

NASA Astrophysics Data System (ADS)

Ribot, Jesse C.; Rocha Magalhaes, Antonio; Panagides, Stahis

1996-06-01

Climate changes can trigger events that lead to mass migration, hunger, and even famine. Rather than focus on the impacts that result from climatic fluctuations, the authors look at the underlying conditions that cause social vulnerability. Once we understand why individuals, households, nations, and regions are vulnerable, and how they have buffered themselves against climatic and environmental shifts, then present and future vulnerability can be redressed. By using case studies from across the globe, the authors explore past experiences with climate variability, and the likely effects of--and the possible policy responses to--the types of climatic events that global warming might bring.

The Role of Climate Covariability on Crop Yields in the Conterminous United States

DOE PAGES

Leng, Guoyong; Zhang, Xuesong; Huang, Maoyi; ...

2016-09-12

The covariability of temperature (T), precipitation (P) and radiation (R) is an important aspect in understanding the climate influence on crop yields. Here in this paper, we analyze county-level corn and soybean yields and observed climate for the period 1983–2012 to understand how growing-season (June, July and August) mean T, P and R influence crop yields jointly and in isolation across the CONterminous United States (CONUS). Results show that nationally averaged corn and soybean yields exhibit large interannual variability of 21% and 22%, of which 35% and 32% can be significantly explained by T and P, respectively. By including R,more » an additional of 5% in variability can be explained for both crops. Using partial regression analyses, we find that studies that ignore the covariability among T, P, and R can substantially overestimate the sensitivity of crop yields to a single climate factor at the county scale. Further analyses indicate large spatial variation in the relative contributions of different climate variables to the variability of historical corn and soybean yields. Finally, the structure of the dominant climate factors did not change substantially over 1983–2012, confirming the robustness of the findings, which have important implications for crop yield prediction and crop model validations.« less

Climate variability and vulnerability to climate change: a review

PubMed Central

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

2014-01-01

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

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

PubMed

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

2017-06-01

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

Implications of climate variability for monitoring the effectiveness of global mercury policy

NASA Astrophysics Data System (ADS)

Giang, A.; Monier, E.; Couzo, E. A.; Pike-thackray, C.; Selin, N. E.

2016-12-01

We investigate how climate variability affects ability to detect policy-related anthropogenic changes in mercury emissions in wet deposition monitoring data using earth system and atmospheric chemistry modeling. The Minamata Convention, a multilateral environmental agreement that aims to protect human health and the environment from anthropogenic emissions and releases of mercury, includes provisions for monitoring treaty effectiveness. Because meteorology can affect mercury chemistry and transport, internal variability is an important contributor to uncertainty in how effective policy may be in reducing the amount of mercury entering ecosystems through wet deposition. We simulate mercury chemistry using the GEOS-Chem global transport model to assess the influence of meteorology in the context of other uncertainties in mercury cycling and policy. In these simulations, we find that interannual variability in meteorology may be a dominant contributor to the spatial pattern and magnitude of historical regional wet deposition trends. To further assess the influence of climate variability in the GEOS-Chem mercury simulation, we use a 5-member ensemble of meteorological fields from the MIT Integrated Global System Model under present and future climate. Each member involves randomly initialized 20 year simulations centered around 2000 and 2050 (under a no-policy and a climate stabilization scenario). Building on previous efforts to understand climate-air quality interactions for ground-level O3 and particulate matter, we estimate from the ensemble the range of trends in mercury wet deposition given natural variability, and, to extend our previous results on regions that are sensitive to near-source vs. remote anthropogenic signals, we identify geographic regions where mercury wet deposition is most sensitive to this variability. We discuss how an improved understanding of natural variability can inform the Conference of Parties on monitoring strategy and policy ambition.

North Atlantic climate variability: The role of the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Hurrell, James W.; Deser, Clara

2009-08-01

Marine ecosystems are undergoing rapid change at local and global scales. To understand these changes, including the relative roles of natural variability and anthropogenic effects, and to predict the future state of marine ecosystems requires quantitative understanding of the physics, biogeochemistry and ecology of oceanic systems at mechanistic levels. Central to this understanding is the role played by dominant patterns or "modes" of atmospheric and oceanic variability, which orchestrate coherent variations in climate over large regions with profound impacts on ecosystems. We review the spatial structure of extratropical climate variability over the Northern Hemisphere and, specifically, focus on modes of climate variability over the extratropical North Atlantic. A leading pattern of weather and climate variability over the Northern Hemisphere is the North Atlantic Oscillation (NAO). The NAO refers to a redistribution of atmospheric mass between the Arctic and the subtropical Atlantic, and swings from one phase to another producing large changes in surface air temperature, winds, storminess and precipitation over the Atlantic as well as the adjacent continents. The NAO also affects the ocean through changes in heat content, gyre circulations, mixed layer depth, salinity, high latitude deep water formation and sea ice cover. Thus, indices of the NAO have become widely used to document and understand how this mode of variability alters the structure and functioning of marine ecosystems. There is no unique way, however, to define the NAO. Several approaches are discussed including both linear (e.g., principal component analysis) and nonlinear (e.g., cluster analysis) techniques. The former, which have been most widely used, assume preferred atmospheric circulation states come in pairs, in which anomalies of opposite polarity have the same spatial structure. In contrast, nonlinear techniques search for recurrent patterns of a specific amplitude and sign. They reveal, for instance, spatial asymmetries between different phases of the NAO that are likely important for ecological studies. It also follows that there is no universally accepted index to describe the temporal evolution of the NAO. Several of the most common measures are presented and compared. All reveal that there is no preferred time scale of variability for the NAO: large changes occur from one winter to the next and from one decade to the next. There is also a large amount of within-season variability in the patterns of atmospheric circulation of the North Atlantic, so that most winters cannot be characterized solely by a canonical NAO structure. A better understanding of how the NAO responds to external forcing, including sea surface temperature changes in the tropics, stratospheric influences, and increasing greenhouse gas concentrations, is crucial to the current debate on climate variability and change.

North Atlantic climate variability: The role of the North Atlantic Oscillation

NASA Astrophysics Data System (ADS)

Hurrell, James W.; Deser, Clara

2010-02-01

Marine ecosystems are undergoing rapid change at local and global scales. To understand these changes, including the relative roles of natural variability and anthropogenic effects, and to predict the future state of marine ecosystems requires quantitative understanding of the physics, biogeochemistry and ecology of oceanic systems at mechanistic levels. Central to this understanding is the role played by dominant patterns or "modes" of atmospheric and oceanic variability, which orchestrate coherent variations in climate over large regions with profound impacts on ecosystems. We review the spatial structure of extratropical climate variability over the Northern Hemisphere and, specifically, focus on modes of climate variability over the extratropical North Atlantic. A leading pattern of weather and climate variability over the Northern Hemisphere is the North Atlantic Oscillation (NAO). The NAO refers to a redistribution of atmospheric mass between the Arctic and the subtropical Atlantic, and swings from one phase to another producing large changes in surface air temperature, winds, storminess and precipitation over the Atlantic as well as the adjacent continents. The NAO also affects the ocean through changes in heat content, gyre circulations, mixed layer depth, salinity, high latitude deep water formation and sea ice cover. Thus, indices of the NAO have become widely used to document and understand how this mode of variability alters the structure and functioning of marine ecosystems. There is no unique way, however, to define the NAO. Several approaches are discussed including both linear (e.g., principal component analysis) and nonlinear (e.g., cluster analysis) techniques. The former, which have been most widely used, assume preferred atmospheric circulation states come in pairs, in which anomalies of opposite polarity have the same spatial structure. In contrast, nonlinear techniques search for recurrent patterns of a specific amplitude and sign. They reveal, for instance, spatial asymmetries between different phases of the NAO that are likely important for ecological studies. It also follows that there is no universally accepted index to describe the temporal evolution of the NAO. Several of the most common measures are presented and compared. All reveal that there is no preferred time scale of variability for the NAO: large changes occur from one winter to the next and from one decade to the next. There is also a large amount of within-season variability in the patterns of atmospheric circulation of the North Atlantic, so that most winters cannot be characterized solely by a canonical NAO structure. A better understanding of how the NAO responds to external forcing, including sea surface temperature changes in the tropics, stratospheric influences, and increasing greenhouse gas concentrations, is crucial to the current debate on climate variability and change.

Changes in Intense Precipitation Events in West Africa and the central U.S. under Global Warming

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

Cook, Kerry H.; Vizy, Edward

The purpose of the proposed project is to improve our understanding of the physical processes and large-scale connectivity of changes in intense precipitation events (high rainfall rates) under global warming in West Africa and the central U.S., including relationships with low-frequency modes of variability. This is in response to the requested subject area #2 “simulation of climate extremes under a changing climate … to better quantify the frequency, duration, and intensity of extreme events under climate change and elucidate the role of low frequency climate variability in modulating extremes.” We will use a regional climate model and emphasize an understandingmore » of the physical processes that lead to an intensification of rainfall. The project objectives are as follows: 1. Understand the processes responsible for simulated changes in warm-season rainfall intensity and frequency over West Africa and the Central U.S. associated with greenhouse gas-induced global warming 2. Understand the relationship between changes in warm-season rainfall intensity and frequency, which generally occur on regional space scales, and the larger-scale global warming signal by considering modifications of low-frequency modes of variability. 3. Relate changes simulated on regional space scales to global-scale theories of how and why atmospheric moisture levels and rainfall should change as climate warms.« less

NASA Scientific Forum on Climate Variability and Global Change: UNISPACE 3

NASA Technical Reports Server (NTRS)

Schiffer, Robert A.; Unninayar, Sushel

1999-01-01

The Forum on Climate Variability and Global Change is intended to provide a glimpse into some of the advances made in our understanding of key scientific and environmental issues resulting primarily from improved observations and modeling on a global basis. This publication contains the papers presented at the forum.

Historic Hydroclimatic Variability in Northern Mexico

Treesearch

José Villanueva-Diaz; J. Cerano-Paredes; D.W. Stahle; B. H. Luckman; M.D. Therrell; M.K. Cleaveland; G. Gutierrez-Garcia

2006-01-01

The understanding of historic hydroclimatic variability is basic to plan for a proper management of limited water resources in northern Mexico. The objective of this study was to develop a network of tree-ring chronologies for climate reconstruction and to analyze the influence of circulatory patterns, such as ENSO. Climatic sensitive treering chronologies were...

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

USDA-ARS?s Scientific Manuscript database

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

The Hydrological Response of Snowmelt Dominated Catchments to Climate Change

NASA Astrophysics Data System (ADS)

Arrigoni, A. S.; Moore, J. N.

2007-12-01

Hydrological systems dominated by snowmelt discharge contribute greater than half the freshwater resource available to the western United States. Globally, the contribution of mountain discharge to total runoff is twice the expected for their geographical coverage. Therefore, snowmelt dominated mountain catchments have proportionally a more prominent role than other systems to our freshwater resource. A changing climate, or even a more variable climate, could have a significant impact on these systems, and consequently on our freshwater resource. Ergo, a better understanding of how changes and variations in climate will influence mountain catchments is a necessity for improving future water management under predicted/proposed climate change. The research presented here is a first order analysis to improve our understanding of these systems by monitoring and analyzing high mountain catchments along the entirety of the Mission Mountain Front, Montana USA. The Mission Mountain Range is an ideal location for conducting this research as it runs directly north to south with elevations progressively increasing from 7600 feet in the northern section, to over 9700 feet at the southern end. The lower elevation catchments will be used as surrogates for variable climate change, while the high elevation catchments will be used as surrogates for a more stable, cooler, climate regime. We use a combination of USGS and Tribal stream gauges, as well as stage gauge loggers in the headwaters of the catchments, SNOTEL datasets, and weather station datasets. This information is used to determine if, how, and why the snowmelt hydrographs vary between catchments, within the catchments between the upper and lower segments, and the dominant driver or drivers of the hydrograph form in relation to changing climatic variables such as temperature and precipitation. This research will improve current comprehension of how mountain catchments respond to climatic variables, and additionally will expand upon the current understanding of general catchment hydrology.

Understanding the Changes in Global Crop Yields Through Changes in Climate and Technology

NASA Astrophysics Data System (ADS)

Najafi, Ehsan; Devineni, Naresh; Khanbilvardi, Reza M.; Kogan, Felix

2018-03-01

During the last few decades, the global agricultural production has risen and technology enhancement is still contributing to yield growth. However, population growth, water crisis, deforestation, and climate change threaten the global food security. An understanding of the variables that caused past changes in crop yields can help improve future crop prediction models. In this article, we present a comprehensive global analysis of the changes in the crop yields and how they relate to different large-scale and regional climate variables, climate change variables and technology in a unified framework. A new multilevel model for yield prediction at the country level is developed and demonstrated. The structural relationships between average yield and climate attributes as well as trends are estimated simultaneously. All countries are modeled in a single multilevel model with partial pooling to automatically group and reduce estimation uncertainties. El Niño-southern oscillation (ENSO), Palmer drought severity index (PDSI), geopotential height anomalies (GPH), historical carbon dioxide (CO2) concentration and country-based time series of GDP per capita as an approximation of technology measurement are used as predictors to estimate annual agricultural crop yields for each country from 1961 to 2013. Results indicate that these variables can explain the variability in historical crop yields for most of the countries and the model performs well under out-of-sample verifications. While some countries were not generally affected by climatic factors, PDSI and GPH acted both positively and negatively in different regions for crop yields in many countries.

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.

Modeling impacts of CO2, ozone, and climate change on tree growth

Treesearch

George E. Host; Gary W. Theseira; J. G. Isebrands

1996-01-01

Understanding the influence of ozone, CO2, and changing climatic regimes on basic plant physiological processes is essential for predicting the response of forest ecosystems. To understand the relationships among these interacting factors, in the face of genetic and other environmental variability, requires a means of synthesis. Physiological...

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

Treesearch

Rachel Loehman

2010-01-01

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

Solar variability, weather, and climate

NASA Technical Reports Server (NTRS)

1982-01-01

Advances in the understanding of possible effects of solar variations on weather and climate are most likely to emerge by addressing the subject in terms of fundamental physical principles of atmospheric sciences and solar-terrestrial physis. The limits of variability of solar inputs to the atmosphere and the depth in the atmosphere to which these variations have significant effects are determined.

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

Treesearch

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

2013-01-01

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

Impacts of Considering Climate Variability on Investment Decisions in Ethiopia

NASA Astrophysics Data System (ADS)

Strzepek, K.; Block, P.; Rosegrant, M.; Diao, X.

2005-12-01

In Ethiopia, climate extremes, inducing droughts or floods, are not unusual. Monitoring the effects of these extremes, and climate variability in general, is critical for economic prediction and assessment of the country's future welfare. The focus of this study involves adding climate variability to a deterministic, mean climate-driven agro-economic model, in an attempt to understand its effects and degree of influence on general economic prediction indicators for Ethiopia. Four simulations are examined, including a baseline simulation and three investment strategies: simulations of irrigation investment, roads investment, and a combination investment of both irrigation and roads. The deterministic model is transformed into a stochastic model by dynamically adding year-to-year climate variability through climate-yield factors. Nine sets of actual, historic, variable climate data are individually assembled and implemented into the 12-year stochastic model simulation, producing an ensemble of economic prediction indicators. This ensemble allows for a probabilistic approach to planning and policy making, allowing decision makers to consider risk. The economic indicators from the deterministic and stochastic approaches, including rates of return to investments, are significantly different. The predictions of the deterministic model appreciably overestimate the future welfare of Ethiopia; the predictions of the stochastic model, utilizing actual climate data, tend to give a better semblance of what may be expected. Inclusion of climate variability is vital for proper analysis of the predictor values from this agro-economic model.

Speciation within Columnea section Angustiflora (Gesneriaceae): islands, pollinators and climate.

PubMed

Schulte, Lacie J; Clark, John L; Novak, Stephen J; Jeffries, Shandra K; Smith, James F

2015-03-01

Despite many advances in evolutionary biology, understanding the proximate mechanisms that lead to speciation for many taxonomic groups remains elusive. Phylogenetic analyses provide a means to generate well-supported estimates of species relationships. Understanding how genetic isolation (restricted gene flow) occurred in the past requires not only a well-supported molecular phylogenetic analysis, but also an understanding of when character states that define species may have changed. In this study, phylogenetic trees resolve species level relationships for fourteen of the fifteen species within Columnea section Angustiflorae (Gesneriaceae). The distributions of sister species pairs are compared and ancestral character states are reconstructed using Bayesian stochastic mapping. Climate variables were also assessed and shifts in ancestral climate conditions were mapped using SEEVA. The relationships between morphological character states and climate variables were assessed with correlation analyses. These results indicate that species in section Angustiflorae have likely diverged as a result of allopatric, parapatric, and sympatric speciation, with both biotic and abiotic forces driving morphological and phenological divergence. Copyright © 2015 Elsevier Inc. All rights reserved.

Vulnerability to Climate Change in Rural Saskatchewan: Case Study of the Rural Municipality of Rudy No. 284

ERIC Educational Resources Information Center

Pittman, Jeremy; Wittrock, Virginia; Kulshreshtha, Surendra; Wheaton, Elaine

2011-01-01

With the likelihood of future changes in climate and climate variability, it is important to understand how human systems may be vulnerable. Rural communities in Saskatchewan having agricultural-based economies are particularly dependent on climate and could be among the most vulnerable human systems in Canada. Future changes in climate are likely…

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Advances in Understanding Decadal Climate Variability

NASA Technical Reports Server (NTRS)

Busalaacchi, Antonio J.

1998-01-01

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

Advances in Understanding Decadal Climate Variability

NASA Technical Reports Server (NTRS)

Busalacchi, Antonio J.

1999-01-01

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

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

NASA Astrophysics Data System (ADS)

Yudawati Cahyarini, Sri; Henrizan, Marfasran

2018-02-01

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

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.

Regime Behavior in Paleo-Reconstructed Streamflow: Attributions to Atmospheric Dynamics, Synoptic Circulation and Large-Scale Climate Teleconnection Patterns

NASA Astrophysics Data System (ADS)

Ravindranath, A.; Devineni, N.

2017-12-01

Studies have shown that streamflow behavior and dynamics have a significant link with climate and climate variability. Patterns of persistent regime behavior from extended streamflow records in many watersheds justify investigating large-scale climate mechanisms as potential drivers of hydrologic regime behavior and streamflow variability. Understanding such streamflow-climate relationships is crucial to forecasting/simulation systems and the planning and management of water resources. In this study, hidden Markov models are used with reconstructed streamflow to detect regime-like behaviors - the hidden states - and state transition phenomena. Individual extreme events and their spatial variability across the basin are then verified with the identified states. Wavelet analysis is performed to examine the signals over time in the streamflow records. Joint analyses of the climatic data in the 20th century and the identified states are undertaken to better understand the hydroclimatic connections within the basin as well as important teleconnections that influence water supply. Compositing techniques are used to identify atmospheric circulation patterns associated with identified states of streamflow. The grouping of such synoptic patterns and their frequency are then examined. Sliding time-window correlation analysis and cross-wavelet spectral analysis are performed to establish the synchronicity of basin flows to the identified synoptic and teleconnection patterns. The Missouri River Basin (MRB) is examined in this study, both as a means of better understanding the synoptic climate controls in this important watershed and as a case study for the techniques developed here. Initial wavelet analyses of reconstructed streamflow at major gauges in the MRB show multidecadal cycles in regime behavior.

Earth Radiation Budget Science, 1978. [conferences

NASA Technical Reports Server (NTRS)

1978-01-01

An earth radiation budget satellite system planned in order to understand climate on various temporal and spatial scales is considered. Topics discussed include: climate modeling, climate diagnostics, radiation modeling, radiation variability and correlation studies, cloudiness and the radiation budget, and radiation budget and related measurements in 1985 and beyond.

Impact of Holocene climate variability on Arctic vegetation

NASA Astrophysics Data System (ADS)

Gajewski, K.

2015-10-01

This paper summarizes current knowledge about the postglacial history of the vegetation of the Canadian Arctic Archipelago (CAA) and Greenland. Available pollen data were used to understand the initial migration of taxa across the Arctic, how the plant biodiversity responded to Holocene climate variability, and how past climate variability affected primary production of the vegetation. Current evidence suggests that most of the flora arrived in the area during the Holocene from Europe or refugia south or west of the region immediately after local deglaciation, indicating rapid dispersal of propagules to the region from distant sources. There is some evidence of shrub species arriving later in Greenland, but it is not clear if this is dispersal limited or a response to past climates. Subsequent climate variability had little effect on biodiversity across the CAA, with some evidence of local extinctions in areas of Greenland in the late Holocene. The most significant impact of climate changes is on vegetation density and/or plant production.

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960–2006

PubMed Central

Mantilla, Gilma; Oliveros, Hugo; Barnston, Anthony G

2009-01-01

Background Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. Methods Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. Results The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. Conclusion Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960–2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models. PMID:19133152

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.

Women's role in adapting to climate change and variability

NASA Astrophysics Data System (ADS)

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

2008-04-01

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

Fine-scale variability in growth-climate relationships of Douglas-fir, North Cascade Range, Washington.

Treesearch

Michael J. Case; David L. Peterson

2005-01-01

Information about the sensitivity to climate of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) is valuable because it will allow forest managers to maximize growth, better understand how carbon sequestration may change over time, and better model and predict future ecosystem responses to climatic change. We examined the effects of climatic...

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.

Prerequisites for understanding climate-change impacts on northern prairie wetlands

USGS Publications Warehouse

Anteau, Michael J.; Wiltermuth, Mark T.; Post van der Burg, Max; Pearse, Aaron T.

2016-01-01

The Prairie Pothole Region (PPR) contains ecosystems that are typified by an extensive matrix of grasslands and depressional wetlands, which provide numerous ecosystem services. Over the past 150 years the PPR has experienced numerous landscape modifications resulting in agricultural conversion of 75–99 % of native prairie uplands and drainage of 50–90 % of wetlands. There is concern over how and where conservation dollars should be spent within the PPR to protect and restore wetland basins to support waterbird populations that will be robust to a changing climate. However, while hydrological impacts of landscape modifications appear substantial, they are still poorly understood. Previous modeling efforts addressing impacts of climate change on PPR wetlands have yet to fully incorporate interacting or potentially overshadowing impacts of landscape modification. We outlined several information needs for building more informative models to predict climate change effects on PPR wetlands. We reviewed how landscape modification influences wetland hydrology and present a conceptual model to describe how modified wetlands might respond to climate variability. We note that current climate projections do not incorporate cyclical variability in climate between wet and dry periods even though such dynamics have shaped the hydrology and ecology of PPR wetlands. We conclude that there are at least three prerequisite steps to making meaningful predictions about effects of climate change on PPR wetlands. Those evident to us are: 1) an understanding of how physical and watershed characteristics of wetland basins of similar hydroperiods vary across temperature and moisture gradients; 2) a mechanistic understanding of how wetlands respond to climate across a gradient of anthropogenic modifications; and 3) improved climate projections for the PPR that can meaningfully represent potential changes in climate variability including intensity and duration of wet and dry periods. Once these issues are addressed, we contend that modeling efforts will better inform and quantify ecosystem services provided by wetlands to meet needs of waterbird conservation and broader societal interests such as flood control and water quality.

Climate reddening increases the chance of critical transitions

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

Disentangling the effects of climate variability and functional change on ecosystem carbon dynamics using semi-empirical modelling

NASA Astrophysics Data System (ADS)

Wu, J.; van der Linden, L.; Lasslop, G.; Carvalhais, N.; Pilegaard, K.; Beier, C.; Ibrom, A.

2012-04-01

The ecosystem carbon balance is affected by both external climatic forcing (e.g. solar radiation, air temperature and humidity) and internal dynamics in the ecosystem functional properties (e.g. canopy structure, leaf photosynthetic capacity and carbohydrate reserve). In order to understand to what extent and at which temporal scale, climatic variability and functional changes regulated the interannual variation (IAV) in the net ecosystem exchange of CO2 (NEE), data-driven analysis and semi-empirical modelling (Lasslop et al. 2010) were performed based on a 13 year NEE record in a temperate deciduous forest (Pilegaard et al 2011, Wu et al. 2012). We found that the sensitivity of carbon fluxes to climatic variability was significantly higher at shorter than at longer time scales and changed seasonally. This implied that the changing distribution of climate anomalies during the vegetation period could have stronger impacts on future ecosystem carbon balances than changes in average climate. At the annual time scale, approximately 80% of the interannual variability in NEE was attributed to the variation in the model parameters, indicating the observed IAV in the carbon dynamics at the investigated site was dominated by changes in ecosystem functioning. In general this study showed the need for understanding the mechanisms of ecosystem functional change. The method can be applied at other sites to explore ecosystem behavior across different plant functional types and climate gradients. Incorporating ecosystem functional change into process based models will reduce the uncertainties in long-term predictions of ecosystem carbon balances in global climate change projections. Acknowledgements. This work was supported by the EU FP7 project CARBO-Extreme, the DTU Climate Centre and the Danish national project ECOCLIM (Danish Council for Strategic Research).

External forcing as a metronome for Atlantic multidecadal variability

NASA Astrophysics Data System (ADS)

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

2010-10-01

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

1996-2007 Interannual Spatio-Temporal Variability in Snowmelt in Two Montane Watersheds

NASA Astrophysics Data System (ADS)

Jepsen, S. M.; Molotch, N. P.; Rittger, K. E.

2009-12-01

Snowmelt is a primary water source for ecosystems within, and urban/agricultural centers near, mountain regions. Stream chemistry from montane catchments is controlled by the flowpaths of water from snowmelt and the timing and duration of snow coverage. A process level understanding of the variability in these processes requires an understanding of the effect of changing climate and anthropogenic loading on spatio-temporal snowmelt patterns. With this as our objective, we are applying a snow reconstruction model to two well-studied montane watersheds, Tokopah Basin (TOK), California and Green Lakes Valley (GLV), Colorado, to examine interannual variability in the timing and location of snowmelt in response to variable climate conditions during the period from 1996 to 2007. The reconstruction model back solves for snowmelt by combining surface energy fluxes, inferred from meteorological data, with sequences of melt season snow images derived from satellite data (i.e., snowmelt depletion curves). Preliminary model results for 2002 were tested against measured snow water equivalent (SWE) and hydrograph data for the two watersheds. The computed maximum SWE averaged over TOK and GLV were 94 cm (~+17% error) and 50.2 cm (~+1% error), respectively. We present an analysis of interannual variability in these errors, in addition to reconstructed snowmelt maps over different land cover types under changing climate conditions between 1996-2007, focusing on the variability with interannual variation in climate.

Quantifying Livestock Heat Stress Impacts in the Sahel

NASA Astrophysics Data System (ADS)

Broman, D.; Rajagopalan, B.; Hopson, T. M.

2014-12-01

Livestock heat stress, especially in regions of the developing world with limited adaptive capacity, has a largely unquantified impact on food supply. Though dominated by ambient air temperature, relative humidity, wind speed, and solar radiation all affect heat stress, which can decrease livestock growth, milk production, reproduction rates, and mortality. Indices like the thermal-humidity index (THI) are used to quantify the heat stress experienced from climate variables. Livestock experience differing impacts at different index critical thresholds that are empirically determined and specific to species and breed. This lack of understanding has been highlighted in several studies with a limited knowledge of the critical thresholds of heat stress in native livestock breeds, as well as the current and future impact of heat stress,. As adaptation and mitigation strategies to climate change depend on a solid quantitative foundation, this knowledge gap has limited such efforts. To address the lack of study, we have investigated heat stress impacts in the pastoral system of Sub-Saharan West Africa. We used a stochastic weather generator to quantify both the historic and future variability of heat stress. This approach models temperature, relative humidity, and precipitation, the climate variables controlling heat stress. Incorporating large-scale climate as covariates into this framework provides a better historical fit and allows us to include future CMIP5 GCM projections to examine the climate change impacts on heat stress. Health and production data allow us to examine the influence of this variability on livestock directly, and are considered in conjunction with the confounding impacts of fodder and water access. This understanding provides useful information to decision makers looking to mitigate the impacts of climate change and can provide useful seasonal forecasts of heat stress risk. A comparison of the current and future heat stress conditions based on climate variables for West Africa will be presented, An assessment of current and future risk was obtained by linking climatic heat stress to cattle health and production. Seasonal forecasts of heat stress are also provided by modeling the heat stress climate variables using persistent large-scale climate features.

SimilarityExplorer: A visual inter-comparison tool for multifaceted climate data

Treesearch

J. Poco; A. Dasgupta; Y. Wei; W. Hargrove; C. Schwalm; R. Cook; E. Bertini; C. Silva

2014-01-01

Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, for example, simulations of photosynthesis and respiration, using algorithms...

Satellite Observations of the Effect of Natural and Anthropogenic Aerosols on Clouds

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2006-01-01

Our knowledge of atmospheric aerosols (smoke, pollution, dust or sea salt particles, small enough to be suspended in the air), their evolution, composition, variability in space and time and interaction with clouds and precipitation is still lacking despite decades of research. Understanding the global aerosol system is critical to quantifying anthropogenic climate change, to determine climate sensitivity from observations and to understand the hydrological cycle. While a single instrument was used to demonstrate 50 years ago that the global CO2 levels are rising, posing threat of global warming, we need an array of satellites and field measurements coupled with chemical transport models to understand the global aerosol system. This complexity of the aerosol problem results from their short lifetime (1 week) and variable chemical composition. A new generation of satellites provides exciting opportunities to measure the global distribution of aerosols, distinguishing natural from anthropogenic aerosol and measuring their interaction with clouds and climate.

Ground Water and Climate Change

NASA Technical Reports Server (NTRS)

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

Ground water and climate change

USGS Publications Warehouse

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

2012-01-01

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

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.

Virtual water trade in the Roman Mediterranean

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

A Vulnerability Assessment of Fish and Invertebrates to Climate Change on the Northeast U.S. Continental Shelf.

PubMed

Hare, Jonathan A; Morrison, Wendy E; Nelson, Mark W; Stachura, Megan M; Teeters, Eric J; Griffis, Roger B; Alexander, Michael A; Scott, James D; Alade, Larry; Bell, Richard J; Chute, Antonie S; Curti, Kiersten L; Curtis, Tobey H; Kircheis, Daniel; Kocik, John F; Lucey, Sean M; McCandless, Camilla T; Milke, Lisa M; Richardson, David E; Robillard, Eric; Walsh, Harvey J; McManus, M Conor; Marancik, Katrin E; Griswold, Carolyn A

2016-01-01

Climate change and decadal variability are impacting marine fish and invertebrate species worldwide and these impacts will continue for the foreseeable future. Quantitative approaches have been developed to examine climate impacts on productivity, abundance, and distribution of various marine fish and invertebrate species. However, it is difficult to apply these approaches to large numbers of species owing to the lack of mechanistic understanding sufficient for quantitative analyses, as well as the lack of scientific infrastructure to support these more detailed studies. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species with existing information. These methods combine the exposure of a species to a stressor (climate change and decadal variability) and the sensitivity of species to the stressor. These two components are then combined to estimate an overall vulnerability. Quantitative data are used when available, but qualitative information and expert opinion are used when quantitative data is lacking. Here we conduct a climate vulnerability assessment on 82 fish and invertebrate species in the Northeast U.S. Shelf including exploited, forage, and protected species. We define climate vulnerability as the extent to which abundance or productivity of a species in the region could be impacted by climate change and decadal variability. We find that the overall climate vulnerability is high to very high for approximately half the species assessed; diadromous and benthic invertebrate species exhibit the greatest vulnerability. In addition, the majority of species included in the assessment have a high potential for a change in distribution in response to projected changes in climate. Negative effects of climate change are expected for approximately half of the species assessed, but some species are expected to be positively affected (e.g., increase in productivity or move into the region). These results will inform research and management activities related to understanding and adapting marine fisheries management and conservation to climate change and decadal variability.

A Vulnerability Assessment of Fish and Invertebrates to Climate Change on the Northeast U.S. Continental Shelf

PubMed Central

Hare, Jonathan A.; Morrison, Wendy E.; Nelson, Mark W.; Stachura, Megan M.; Teeters, Eric J.; Griffis, Roger B.; Alexander, Michael A.; Scott, James D.; Alade, Larry; Bell, Richard J.; Chute, Antonie S.; Curti, Kiersten L.; Curtis, Tobey H.; Kircheis, Daniel; Kocik, John F.; Lucey, Sean M.; McCandless, Camilla T.; Milke, Lisa M.; Richardson, David E.; Robillard, Eric; Walsh, Harvey J.; McManus, M. Conor; Marancik, Katrin E.; Griswold, Carolyn A.

2016-01-01

Climate change and decadal variability are impacting marine fish and invertebrate species worldwide and these impacts will continue for the foreseeable future. Quantitative approaches have been developed to examine climate impacts on productivity, abundance, and distribution of various marine fish and invertebrate species. However, it is difficult to apply these approaches to large numbers of species owing to the lack of mechanistic understanding sufficient for quantitative analyses, as well as the lack of scientific infrastructure to support these more detailed studies. Vulnerability assessments provide a framework for evaluating climate impacts over a broad range of species with existing information. These methods combine the exposure of a species to a stressor (climate change and decadal variability) and the sensitivity of species to the stressor. These two components are then combined to estimate an overall vulnerability. Quantitative data are used when available, but qualitative information and expert opinion are used when quantitative data is lacking. Here we conduct a climate vulnerability assessment on 82 fish and invertebrate species in the Northeast U.S. Shelf including exploited, forage, and protected species. We define climate vulnerability as the extent to which abundance or productivity of a species in the region could be impacted by climate change and decadal variability. We find that the overall climate vulnerability is high to very high for approximately half the species assessed; diadromous and benthic invertebrate species exhibit the greatest vulnerability. In addition, the majority of species included in the assessment have a high potential for a change in distribution in response to projected changes in climate. Negative effects of climate change are expected for approximately half of the species assessed, but some species are expected to be positively affected (e.g., increase in productivity or move into the region). These results will inform research and management activities related to understanding and adapting marine fisheries management and conservation to climate change and decadal variability. PMID:26839967

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Effects of climatic factors and ecosystem responses on the inter-annual variability of evapotranspiration in a coniferous plantation in subtropical China.

PubMed

Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui

2014-01-01

Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003-2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003-2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May-June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation.

Effects of Climatic Factors and Ecosystem Responses on the Inter-Annual Variability of Evapotranspiration in a Coniferous Plantation in Subtropical China

PubMed Central

Xu, Mingjie; Wen, Xuefa; Wang, Huimin; Zhang, Wenjiang; Dai, Xiaoqin; Song, Jie; Wang, Yidong; Fu, Xiaoli; Liu, Yunfen; Sun, Xiaomin; Yu, Guirui

2014-01-01

Because evapotranspiration (ET) is the second largest component of the water cycle and a critical process in terrestrial ecosystems, understanding the inter-annual variability of ET is important in the context of global climate change. Eight years of continuous eddy covariance measurements (2003–2010) in a subtropical coniferous plantation were used to investigate the impacts of climatic factors and ecosystem responses on the inter-annual variability of ET. The mean and standard deviation of annual ET for 2003–2010 were 786.9 and 103.4 mm (with a coefficient of variation of 13.1%), respectively. The inter-annual variability of ET was largely created in three periods: March, May–June, and October, which are the transition periods between seasons. A set of look-up table approaches were used to separate the sources of inter-annual variability of ET. The annual ETs were calculated by assuming that (a) both the climate and ecosystem responses among years are variable (Vcli-eco), (b) the climate is variable but the ecosystem responses are constant (Vcli), and (c) the climate is constant but ecosystem responses are variable (Veco). The ETs that were calculated under the above assumptions suggested that the inter-annual variability of ET was dominated by ecosystem responses and that there was a negative interaction between the effects of climate and ecosystem responses. These results suggested that for long-term predictions of water and energy balance in global climate change projections, the ecosystem responses must be taken into account to better constrain the uncertainties associated with estimation. PMID:24465610

Ecology and the ratchet of events: climate variability, niche dimensions, and species distributions

USGS Publications Warehouse

Jackson, Stephen T.; Betancourt, Julio L.; Booth, Robert K.; Gray, Stephen T.

2009-01-01

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions

USGS Publications Warehouse

Jackson, S.T.; Betancourt, J.L.; Booth, R.K.; Gray, S.T.

2009-01-01

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and morefundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics.

Ecology and the ratchet of events: Climate variability, niche dimensions, and species distributions

PubMed Central

Jackson, Stephen T.; Betancourt, Julio L.; Booth, Robert K.; Gray, Stephen T.

2009-01-01

Climate change in the coming centuries will be characterized by interannual, decadal, and multidecadal fluctuations superimposed on anthropogenic trends. Predicting ecological and biogeographic responses to these changes constitutes an immense challenge for ecologists. Perspectives from climatic and ecological history indicate that responses will be laden with contingencies, resulting from episodic climatic events interacting with demographic and colonization events. This effect is compounded by the dependency of environmental sensitivity upon life-stage for many species. Climate variables often used in empirical niche models may become decoupled from the proximal variables that directly influence individuals and populations. Greater predictive capacity, and more-fundamental ecological and biogeographic understanding, will come from integration of correlational niche modeling with mechanistic niche modeling, dynamic ecological modeling, targeted experiments, and systematic observations of past and present patterns and dynamics. PMID:19805104

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

PubMed

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

2015-04-01

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

A Skilful Marine Sclerochronological Network Based Reconstruction of North Atlantic Subpolar Gyre Dynamics

NASA Astrophysics Data System (ADS)

Reynolds, D.; Hall, I. R.; Slater, S. M.; Scourse, J. D.; Wanamaker, A. D.; Halloran, P. R.; Garry, F. K.

2017-12-01

Spatial network analyses of precisely dated, and annually resolved, tree-ring proxy records have facilitated robust reconstructions of past atmospheric climate variability and the associated mechanisms and forcings that drive it. In contrast, a lack of similarly dated marine archives has constrained the use of such techniques in the marine realm, despite the potential for developing a more robust understanding of the role basin scale ocean dynamics play in the global climate system. Here we show that a spatial network of marine molluscan sclerochronological oxygen isotope (δ18Oshell) series spanning the North Atlantic region provides a skilful reconstruction of basin scale North Atlantic sea surface temperatures (SSTs). Our analyses demonstrate that the composite marine series (referred to as δ18Oproxy_PC1) is significantly sensitive to inter-annual variability in North Atlantic SSTs (R=-0.61 P<0.01) and surface air temperatures (SATs; R=-0.67, P<0.01) over the 20th century. Subpolar gyre (SPG) SSTs dominates variability in the δ18Oproxy_PC1 series at sub-centennial frequencies (R=-0.51, P<0.01). Comparison of the δ18Oproxy_PC1 series against variability in the strength of the European Slope Current and maximum North Atlantic meridional overturning circulation derived from numeric climate models (CMIP5), indicates that variability in the SPG region, associated with the strength of the surface currents of the North Atlantic, are playing a significant role in shaping the multi-decadal scale SST variability over the industrial era. These analyses demonstrate that spatial networks developed from sclerochronological archives can provide powerful baseline archives of past ocean variability that can facilitate the development of a quantitative understanding for the role the oceans play in the global climate systems and constraining uncertainties in numeric climate models.

Nonlinear dynamics and predictability in the atmospheric sciences

NASA Technical Reports Server (NTRS)

Ghil, M.; Kimoto, M.; Neelin, J. D.

1991-01-01

Systematic applications of nonlinear dynamics to studies of the atmosphere and climate are reviewed for the period 1987-1990. Problems discussed include paleoclimatic applications, low-frequency atmospheric variability, and interannual variability of the ocean-atmosphere system. Emphasis is placed on applications of the successive bifurcation approach and the ergodic theory of dynamical systems to understanding and prediction of intraseasonal, interannual, and Quaternary climate changes.

Natural Variability and Anthropogenic Trends in the Ocean Carbon Sink

NASA Astrophysics Data System (ADS)

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

2017-01-01

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

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.

Revealing The Impact Of Climate Variability On The Wind Resource Using Data Mining Techniques

NASA Astrophysics Data System (ADS)

Clifton, A.; Lundquist, J. K.

2011-12-01

Wind turbines harvest energy from the wind. Winds at heights where industrial-scale turbines operate, up to 200 m above ground, experience a complex interaction between the atmosphere and the Earth's surface. Previous studies for a variety of locations have shown that the wind resource varies over time. In some locations, this variability can be related to large-scale climate oscillations as revealed in climate indices such as the El-Nino-Southern Oscillation (ENSO). These indices can be used to quantify climate change in the past, and can also be extracted from models of future climate. Understanding the correlation between climate indices and wind resources therefore allows us to understand how climate change may influence wind energy production. We present a new methodology for assessing relevant climate modes of oscillation at a given site in order to quantify future wind resource variability. We demonstrate the method on a 14-year record of 10-minute averaged wind speed and wind direction data from several levels of an 80m tower at the National Renewable Energy Laboratory (NREL) National Wind Technology Center near Boulder, Colorado. Data mining techniques (based on k-means clustering) identify 4 major groups of wind speed and direction. After removing annual means, each cluster was compared to a series of climate indices, including the Arctic Oscillation (AO) and Multivariate ENSO Index (MEI). Statistically significant relationships emerge between individual clusters and climate indices. At this location, this result is consistent with the MEI's relationship with other meteorological parameters, such as precipitation, in the Rocky Mountain Region. The presentation will illustrate these relationships between wind resource at this location and other relevant climate indices, and suggest how these relationships can provide a foundation for quantifying the potential future variability of wind energy production at this site and others.

Comparative Analysis of Upper Ocean Heat Content Variability from Ensemble Operational Ocean Analyses

NASA Technical Reports Server (NTRS)

Xue, Yan; Balmaseda, Magdalena A.; Boyer, Tim; Ferry, Nicolas; Good, Simon; Ishikawa, Ichiro; Rienecker, Michele; Rosati, Tony; Yin, Yonghong; Kumar, Arun

2012-01-01

Upper ocean heat content (HC) is one of the key indicators of climate variability on many time-scales extending from seasonal to interannual to long-term climate trends. For example, HC in the tropical Pacific provides information on thermocline anomalies that is critical for the longlead forecast skill of ENSO. Since HC variability is also associated with SST variability, a better understanding and monitoring of HC variability can help us understand and forecast SST variability associated with ENSO and other modes such as Indian Ocean Dipole (IOD), Pacific Decadal Oscillation (PDO), Tropical Atlantic Variability (TAV) and Atlantic Multidecadal Oscillation (AMO). An accurate ocean initialization of HC anomalies in coupled climate models could also contribute to skill in decadal climate prediction. Errors, and/or uncertainties, in the estimation of HC variability can be affected by many factors including uncertainties in surface forcings, ocean model biases, and deficiencies in data assimilation schemes. Changes in observing systems can also leave an imprint on the estimated variability. The availability of multiple operational ocean analyses (ORA) that are routinely produced by operational and research centers around the world provides an opportunity to assess uncertainties in HC analyses, to help identify gaps in observing systems as they impact the quality of ORAs and therefore climate model forecasts. A comparison of ORAs also gives an opportunity to identify deficiencies in data assimilation schemes, and can be used as a basis for development of real-time multi-model ensemble HC monitoring products. The OceanObs09 Conference called for an intercomparison of ORAs and use of ORAs for global ocean monitoring. As a follow up, we intercompared HC variations from ten ORAs -- two objective analyses based on in-situ data only and eight model analyses based on ocean data assimilation systems. The mean, annual cycle, interannual variability and longterm trend of HC have been analyzed

Modeling the Distribution and Type of High-Latitude Natural Wetlands for Methane Studies

NASA Astrophysics Data System (ADS)

Romanski, J.; Matthews, E.

2017-12-01

High latitude (>50N) natural wetlands emit a substantial amount of methane to the atmosphere, and are located in a region of amplified warming. Northern hemisphere high latitudes are characterized by cold climates, extensive permafrost, poor drainage, short growing seasons, and slow decay rates. Under these conditions, organic carbon accumulates in the soil, sequestering CO2 from the atmosphere. Methanogens produce methane from this carbon reservoir, converting stored carbon into a powerful greenhouse gas. Methane emission from wetland ecosystems depends on vegetation type, climate characteristics (e.g, precipitation amount and seasonality, temperature, snow cover, etc.), and geophysical variables (e.g., permafrost, soil type, and landscape slope). To understand how wetland methane dynamics in this critical region will respond to climate change, we have to first understand how wetlands themselves will change and therefore, what the primary controllers of wetland distribution and type are. Understanding these relationships permits data-anchored, physically-based modeling of wetland distribution and type in other climate scenarios, such as paleoclimates or future climates, a necessary first step toward modeling wetland methane emissions in these scenarios. We investigate techniques and datasets for predicting the distribution and type of high latitude (>50N) natural wetlands from a suite of geophysical and climate predictors. Hierarchical clustering is used to derive an empirical methane-centric wetland model. The model is applied in a multistep process - first to predict the distribution of wetlands from relevant geophysical parameters, and then, given the predicted wetland distribution, to classify the wetlands into methane-relevant types using an expanded suite of climate and biogeophysical variables. As the optimum set of predictor variables is not known a priori, the model is applied iteratively, and each simulation is evaluated with respect to observed high-latitude wetlands.

Climate Variability and Wildfires: Insights from Global Earth System Models

NASA Astrophysics Data System (ADS)

Ward, D. S.; Shevliakova, E.; Malyshev, S.; Lamarque, J. F.; Wittenberg, A. T.

2016-12-01

Better understanding of the relationship between variability in global climate and emissions from wildfires is needed for predictions of fire activity on interannual to multi-decadal timescales. Here we investigate this relationship using the long, preindustrial control simulations and historical ensembles of two Earth System models; CESM1 and the NOAA/GFDL ESM2Mb. There is smaller interannual variability of global fires in both models than in present day inventories, especially in boreal regions where observed fires vary substantially from year to year. Patterns of fire response to climate oscillation indices, including the El Niño / Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and Atlantic Meridional Oscillation (AMO) are explored with the model results and compared to the response derived from satellite measurements and proxy observations. Increases in fire emissions in southeast Asia and boreal North America are associated with positive ENSO and PDO, while United States fires and Sahel fires decrease for the same climate conditions. Boreal fire emissions decrease in CESM1 for the warm phase of the AMO, while ESM2Mb did not produce a reliable AMO. CESM1 produces a weak negative trend in global fire emissions for the period 1920 to 2005, while ESM2Mb produces a positive trend over the same period. Both trends are statistically significant at a confidence level of 95% or greater given the variability derived from the respective preindustrial controls. In addition to climate variability impacts on fires, we also explore the impacts of fire emissions on climate variability and atmospheric chemistry. We analyze three long, free-evolving ESM2Mb simulations; one without fire emissions, one with constant year-over-year fire emissions based on a present day inventory, and one with interannually varying fire emissions coupled between the terrestrial and atmospheric components of the model, to gain a better understanding of the role of fire emissions in climate over long timescales.

The role of environmental variables on Aedes albopictus biology and chikungunya epidemiology

PubMed Central

Waldock, Joanna; Chandra, Nastassya L; Lelieveld, Jos; Proestos, Yiannis; Michael, Edwin; Christophides, George; Parham, Paul E

2013-01-01

Aedes albopictus is a vector of dengue and chikungunya viruses in the field, along with around 24 additional arboviruses under laboratory conditions. As an invasive mosquito species, Ae. albopictus has been expanding in geographical range over the past 20 years, although the poleward extent of mosquito populations is limited by winter temperatures. Nonetheless, population densities depend on environmental conditions and since global climate change projections indicate increasing temperatures and altered patterns of rainfall, geographic distributions of previously tropical mosquito species may change. Although mathematical models can provide explanatory insight into observed patterns of disease prevalence in terms of epidemiological and entomological processes, understanding how environmental variables affect transmission is possible only with reliable model parameterisation, which, in turn, is obtained only through a thorough understanding of the relationship between mosquito biology and environmental variables. Thus, in order to assess the impact of climate change on mosquito population distribution and regions threatened by vector-borne disease, a detailed understanding (through a synthesis of current knowledge) of the relationship between climate, mosquito biology, and disease transmission is required, but this process has not yet been undertaken for Ae. albopictus. In this review, the impact of temperature, rainfall, and relative humidity on Ae. albopictus development and survival are considered. Existing Ae. albopictus populations across Europe are mapped with current climatic conditions, considering whether estimates of climatic cutoffs for Ae. albopictus are accurate, and suggesting that environmental thresholds must be calibrated according to the scale and resolution of climate model outputs and mosquito presence data. PMID:23916332

Water isotope systematics: Improving our palaeoclimate interpretations

USGS Publications Warehouse

Jones, M. D.; Dee, S.; Anderson, L.; Baker, A.; Bowen, G.; Noone, D.

2016-01-01

The stable isotopes of oxygen and hydrogen, measured in a variety of archives, are widely used proxies in Quaternary Science. Understanding the processes that control δ18O change have long been a focus of research (e.g. Shackleton and Opdyke, 1973; Talbot, 1990 ; Leng, 2006). Both the dynamics of water isotope cycling and the appropriate interpretation of geological water-isotope proxy time series remain subjects of active research and debate. It is clear that achieving a complete understanding of the isotope systematics for any given archive type, and ideally each individual archive, is vital if these palaeo-data are to be used to their full potential, including comparison with climate model experiments of the past. Combining information from modern monitoring and process studies, climate models, and proxy data is crucial for improving our statistical constraints on reconstructions of past climate variability.As climate models increasingly incorporate stable water isotope physics, this common language should aid quantitative comparisons between proxy data and climate model output. Water-isotope palaeoclimate data provide crucial metrics for validating GCMs, whereas GCMs provide a tool for exploring the climate variability dominating signals in the proxy data. Several of the studies in this set of papers highlight how collaborations between palaeoclimate experimentalists and modelers may serve to expand the usefulness of palaeoclimate data for climate prediction in future work.This collection of papers follows the session on Water Isotope Systematics held at the 2013 AGU Fall Meeting in San Francisco. Papers in that session, the breadth of which are represented here, discussed such issues as; understanding sub-GNIP scale (Global Network for Isotopes in Precipitation, (IAEA/WMO, 2006)) variability in isotopes in precipitation from different regions, detailed examination of the transfer of isotope signals from precipitation to geological archives, and the implications of advances in understanding in these areas for the interpretation of palaeo records and proxy data – climate model comparison.Here, we briefly review these areas of research, and discuss challenges for the water isotope community in improving our ability to partition climate vs. auxiliary signals in palaeoclimate data.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Long-term forest management and climate effects on streamflow

Treesearch

Shelby G. Laird; C.R. Ford; S.H. Laseter; J.M. Vose

2011-01-01

Long-term watershed studies are a powerful tool for examining interactions among management activities, streamflow, and climatic variability. Understanding these interactions is critical for exploring the potential of forest management to adapt to or mitigate against the effects of climate change. The Coweeta Hydrologic Laboratory, located in North Carolina, USA, is a...

Middle and High School Students' Conceptions of Climate Change Mitigation and Adaptation Strategies

ERIC Educational Resources Information Center

Bofferding, Laura; Kloser, Matthew

2015-01-01

Both scientists and policy-makers emphasize the importance of education for influencing pro-environmental behavior and minimizing the effects of climate change on biological and physical systems. Education has the potential to impact students' system knowledge--their understanding of the variables that affect the climate system--and action…

Wild apple growth and climate change in southeast Kazakhstan

Treesearch

Irina P. Panyushkina; Nurjan S. Mukhamadiev; Ann M. Lynch; Nursagim A. Ashikbaev; Alexis H. Arizpe; Christopher D. O' Connor; Danyar Abjanbaev; Gulnaz Z. Mengdbayeva; Abay O. Sagitov

2017-01-01

Wild populations of Malus sieversii [Ldb.] M. Roem are valued genetic and watershed resources in Inner Eurasia. These populations are located in a region that has experienced rapid and on-going climatic change over the past several decades. We assess relationships between climate variables and wild apple radial growth with dendroclimatological techniques to understand...

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.

Regionally heterogeneous paleoenvironmental responses in the West African and South American monsoon systems on glacial to millennial timescales

NASA Astrophysics Data System (ADS)

Shanahan, T. M.; Hughen, K. A.; van Mooy, B.; Overpeck, J. T.; Baker, P. A.; Fritz, S.; Peck, J. A.; Scholz, C. A.; King, J. W.

2008-12-01

Although millennial-scale paleoenvironmental changes have been well characterized for high latitude sites, short-term climate variability in the tropics is less well understood. While the Intertropical Convergence Zone may act as an integrator of tropical climate changes, regional factors also play an important role in controlling the tropical response to climate forcing. Understanding these influences, and how they modulate the response to global climate forcing under different mean climate states is thus important for assessing how the tropics may respond to future climate change. Here, we examine new centennial-resolution records of paleoenvironmental change from isotopic and relative abundance data from molecular biomarkers in sediment cores from Lake Bosumtwi and Lake Titicaca. We assess the relative response of the West African and South American monsoon systems to millennial and suborbital-scale climate variability over the last ca. 30,000 years. While there is evidence for synchronous climate variability in the two systems, the dominant paleoenvironmental changes appear largely decoupled, highlighting the importance of regional climatology in controlling the response to climate forcing in tropical regions.

Climate controls the distribution of a widespread invasive species: Implications for future range expansion

USGS Publications Warehouse

McDowell, W.G.; Benson, A.J.; Byers, J.E.

2014-01-01

1. Two dominant drivers of species distributions are climate and habitat, both of which are changing rapidly. Understanding the relative importance of variables that can control distributions is critical, especially for invasive species that may spread rapidly and have strong effects on ecosystems. 2. Here, we examine the relative importance of climate and habitat variables in controlling the distribution of the widespread invasive freshwater clam Corbicula fluminea, and we model its future distribution under a suite of climate scenarios using logistic regression and maximum entropy modelling (MaxEnt). 3. Logistic regression identified climate variables as more important than habitat variables in controlling Corbicula distribution. MaxEnt modelling predicted Corbicula's range expansion westward and northward to occupy half of the contiguous United States. By 2080, Corbicula's potential range will expand 25–32%, with more than half of the continental United States being climatically suitable. 4. Our combination of multiple approaches has revealed the importance of climate over habitat in controlling Corbicula's distribution and validates the climate-only MaxEnt model, which can readily examine the consequences of future climate projections. 5. Given the strong influence of climate variables on Corbicula's distribution, as well as Corbicula's ability to disperse quickly and over long distances, Corbicula is poised to expand into New England and the northern Midwest of the United States. Thus, the direct effects of climate change will probably be compounded by the addition of Corbicula and its own influences on ecosystem function.

Modeling responses of large-river fish populations to global climate change through downscaling and incorporation of predictive uncertainty

USGS Publications Warehouse

Wildhaber, Mark L.; Wikle, Christopher K.; Anderson, Christopher J.; Franz, Kristie J.; Moran, Edward H.; Dey, Rima; Mader, Helmut; Kraml, Julia

2012-01-01

Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

CMIP5 Scientific Gaps and Recommendations for CMIP6

DOE PAGES

Stouffer, R. J.; Eyring, V.; Meehl, G. A.; ...

2017-01-23

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP,more » that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less

CMIP5 Scientific Gaps and Recommendations for CMIP6

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

Stouffer, R. J.; Eyring, V.; Meehl, G. A.

The Coupled Model Intercomparison Project (CMIP) is an ongoing coordinated international activity of numerical experimentation of unprecedented scope and impact on climate science. Its most recent phase, the fifth phase (CMIP5), has created nearly 2 PB of output from dozens of experiments performed by dozens of comprehensive climate models available to the climate science research community. In so doing, it has greatly advanced climate science. While CMIP5 has given answers to important science questions, with the help of a community survey we identify and motivate three broad topics here that guided the scientific framework of the next phase of CMIP,more » that is, CMIP6: (1) How does the Earth system respond to changes in forcing? (2) What are the origins and consequences of systematic model biases? (3) How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? CMIP has demonstrated the power of idealized experiments to better understand how the climate system works. We expect that these idealized approaches will continue to contribute to CMIP6. The quantification of radiative forcings and responses was poor, and thus it requires new methods and experiments to address this gap. There are a number of systematic model biases that appear in all phases of CMIP that remain a major climate modeling challenge. In conclusion, these biases need increased attention to better understand their origins and consequences through targeted experiments. Improving understanding of the mechanisms’ underlying internal climate variability for more skillful decadal climate predictions and long-term projections remains another challenge for CMIP6.« less

Decadal climate predictability in the southern Indian Ocean captured by SINTEX-F using a simple SST-nudging scheme.

PubMed

Morioka, Yushi; Doi, Takeshi; Behera, Swadhin K

2018-01-26

Decadal climate variability in the southern Indian Ocean has great influences on southern African climate through modulation of atmospheric circulation. Although many efforts have been made to understanding physical mechanisms, predictability of the decadal climate variability, in particular, the internally generated variability independent from external atmospheric forcing, remains poorly understood. This study investigates predictability of the decadal climate variability in the southern Indian Ocean using a coupled general circulation model, called SINTEX-F. The ensemble members of the decadal reforecast experiments were initialized with a simple sea surface temperature (SST) nudging scheme. The observed positive and negative peaks during late 1990s and late 2000s are well reproduced in the reforecast experiments initiated from 1994 and 1999, respectively. The experiments initiated from 1994 successfully capture warm SST and high sea level pressure anomalies propagating from the South Atlantic to the southern Indian Ocean. Also, the other experiments initiated from 1999 skillfully predict phase change from a positive to negative peak. These results suggest that the SST-nudging initialization has the essence to capture the predictability of the internally generated decadal climate variability in the southern Indian Ocean.

North African dust emissions and transport

NASA Astrophysics Data System (ADS)

Engelstaedter, Sebastian; Tegen, Ina; Washington, Richard

2006-11-01

The need for a better understanding of the role of atmospheric dust in the climate system and its impact on the environment has led to research of the underlying causes of dust variability in space and time in recent decades. North Africa is one of the largest dust producing regions in the world with dust emissions being highly variable on time scales ranging from diurnal to multiannual. Changes in the dust loading are expected to have an impact on regional and global climate, the biogeochemical cycle, and human environments. The development of satellite derived products of global dust distributions has improved our understanding of dust source regions and transport pathways in the recent years. Dust models are now capable of reproducing more realistic patterns of dust distributions due to an improved parameterization of land surface conditions. A recent field campaign has improved our understanding of the natural environment and emission processes of the most intense and persistent dust sources in the world, the Bodélé Depression in Chad. In situ measurements of dust properties during air craft observations in and down wind of source regions have led to new estimates of the radiative forcing effects which are crucial in predicting future climate change. With a focus on the North African desert regions, this paper provides a review of the understanding of dust source regions, the variability of dust emissions, climatic controls of dust entrainment and transport, the role of human impact on dust emission, and recent developments of global and regional dust models.

An integrated, indicator framework for assessing large-scale variations and change in seasonal timing and phenology (Invited)

NASA Astrophysics Data System (ADS)

Betancourt, J. L.; Weltzin, J. F.

2013-12-01

As part of an effort to develop an Indicator System for the National Climate Assessment (NCA), the Seasonality and Phenology Indicators Technical Team (SPITT) proposed an integrated, continental-scale framework for understanding and tracking seasonal timing in physical and biological systems. The framework shares several metrics with the EPA's National Climate Change Indicators. The SPITT framework includes a comprehensive suite of national indicators to track conditions, anticipate vulnerabilities, and facilitate intervention or adaptation to the extent possible. Observed, modeled, and forecasted seasonal timing metrics can inform a wide spectrum of decisions on federal, state, and private lands in the U.S., and will be pivotal for international efforts to mitigation and adaptation. Humans use calendars both to understand the natural world and to plan their lives. Although the seasons are familiar concepts, we lack a comprehensive understanding of how variability arises in the timing of seasonal transitions in the atmosphere, and how variability and change translate and propagate through hydrological, ecological and human systems. For example, the contributions of greenhouse warming and natural variability to secular trends in seasonal timing are difficult to disentangle, including earlier spring transitions from winter (strong westerlies) to summer (weak easterlies) patterns of atmospheric circulation; shifts in annual phasing of daily temperature means and extremes; advanced timing of snow and ice melt and soil thaw at higher latitudes and elevations; and earlier start and longer duration of the growing and fire seasons. The SPITT framework aims to relate spatiotemporal variability in surface climate to (1) large-scale modes of natural climate variability and greenhouse gas-driven climatic change, and (2) spatiotemporal variability in hydrological, ecological and human responses and impacts. The hierarchical framework relies on ground and satellite observations, and includes metrics of surface climate seasonality, seasonality of snow and ice, land surface phenology, ecosystem disturbance seasonality, and organismal phenology. Recommended metrics met the following requirements: (a) easily measured by day-of-year, number of days, or in the case of species migrations, by the latitude of the observation on a given date; (b) are observed or can be calculated across a high density of locations in many different regions of the U.S.; and (c) unambiguously describe both spatial and temporal variability and trends in seasonal timing that are climatically driven. The SPITT framework is meant to provide climatic and strategic guidance for the growth and application of seasonal timing and phenological monitoring efforts. The hope is that additional national indicators based on observed phenology, or evidence-based algorithms calibrated with observational data, will evolve with sustained and broad-scale monitoring of climatically sensitive species and ecological processes.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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.

The role of climate variability in extreme floods in Europe

NASA Astrophysics Data System (ADS)

Guimarães Nobre, Gabriela; Aerts, Jeroen C. J. H.; Jongman, Brenden; Ward, Philip J.

2017-04-01

Between 1980 and 2015, Europe experienced 18% of worldwide weather-related loss events, which accounted for over US500 billion in damage. Consequently, it is urgent to further develop adaptation strategies to mitigate the consequences of weather-related disasters, such as floods. Europe's capability to prepare for such disasters is challenged by a large range of uncertainties and a limited understanding of the driving forces of hydrometeorological hazards. One of the major sources of uncertainty is the relationship between climate variability and weather-related losses. Previous studies show that climate variability drives temporal changes in hydrometereological variables in Europe. However, their influence on flood risk has received little attention. We investigated the influence of the positive and negative phases of El Niño Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Arctic Oscillation (AO), on the seasonal frequency and intensity of extreme rainfall, and anomalies in flood occurrence and damage compared to the neutral phases of the indices of climate variability. Using statistical methods to analyze relationships between the indices of climate variability and four indicators of flooding, we found that positive and negative phases of NAO and AO are associated with more (or less) frequent and intense seasonal extreme rainfall over large areas of Europe. The relationship between ENSO and both the occurrence of extreme rainfall and intensity of extreme rainfall in Europe is much smaller than the relationship with NAO or AO, but still significant in some regions. We observe that flood damage and flood occurrence have strong links with climate variability, especially in southern and eastern Europe. Therefore, when investigating flooding across Europe, all three indices of climate variability should be considered. Seasonal forecasting of flooding could be enhanced by the inclusion of climate variability indicators .

Meteorological Modes of Variability for Fine Particulate Matter (PM2.5) Air Quality in the United States: Implications for PM2.5 Sensitivity to Climate Change

EPA Science Inventory

We applied a multiple linear regression model to understand the relationships of PM_2.5 with meteorological variables in the contiguous US and from there to infer the sensitivity of PM_2.5 to climate change. We used 2004-2008 PM_2.5 observations fro...

Climate, weather, and hops

USDA-ARS?s Scientific Manuscript database

As climate and weather become more variable, hop growers face increased uncertainty in making decisions about their crop. Given the unprecedented nature of these changes, growers may no longer have enough information and intuitive understanding to adequately assess the situation and evaluate their m...

Linking the climatic and geochemical controls on global soil carbon cycling

NASA Astrophysics Data System (ADS)

Doetterl, Sebastian; Stevens, Antoine; Six, Johan; Merckx, Roel; Van Oost, Kristof; Casanova Pinto, Manuel; Casanova-Katny, Angélica; Muñoz, Cristina; Boudin, Mathieu; Zagal Venegas, Erick; Boeckx, Pascal

2015-04-01

Climatic and geochemical parameters are regarded as the primary controls for soil organic carbon (SOC) storage and turnover. However, due to the difference in scale between climate and geochemical-related soil research, the interaction of these key factors for SOC dynamics have rarely been assessed. Across a large geochemical and climatic transect in similar biomes in Chile and the Antarctic Peninsula we show how abiotic geochemical soil features describing soil mineralogy and weathering pose a direct control on SOC stocks, concentration and turnover and are central to explaining soil C dynamics at larger scales. Precipitation and temperature had an only indirect control by regulating geochemistry. Soils with high SOC content have low specific potential CO2 respiration rates, but a large fraction of SOC that is stabilized via organo-mineral interactions. The opposite was observed for soils with low SOC content. The observed differences for topsoil SOC stocks along this transect of similar biomes but differing geo-climatic site conditions are of the same magnitude as differences observed for topsoil SOC stocks across all major global biomes. Using precipitation and a set of abiotic geochemical parameters describing soil mineralogy and weathering status led to predictions of high accuracy (R2 0.53-0.94) for different C response variables. Partial correlation analyses revealed that the strength of the correlation between climatic predictors and SOC response variables decreased by 51 - 83% when controlling for geochemical predictors. In contrast, controlling for climatic variables did not result in a strong decrease in the strength of the correlations of between most geochemical variables and SOC response variables. In summary, geochemical parameters describing soil mineralogy and weathering were found to be essential for accurate predictions of SOC stocks and potential CO2 respiration, while climatic factors were of minor importance as a direct control, but are important through governing soil weathering and geochemistry. In conclusion, we pledge for a stronger implementation of geochemical soil properties to predict SOC stocks on a global scale. Understanding the effects of climate (temperature and precipitation) change on SOC dynamics also requires good understanding of the relationship between climate and soil geochemistry.

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

PubMed

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

2013-06-15

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

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

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

Leng, Guoyong

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

Accurately measuring sea level change from space: an ESA Climate Change Initiative for MSL closure budget studies

NASA Astrophysics Data System (ADS)

Legeais, JeanFrancois; Cazenave, Anny; Ablain, Michael; Larnicol, Gilles; Benveniste, Jerome; Johannessen, Johnny; Timms, Gary; Andersen, Ole; Cipollini, Paolo; Roca, Monica; Rudenko, Sergei; Fernandes, Joana; Balmaseda, Magdalena; Quartly, Graham; Fenoglio-Marc, Luciana; Meyssignac, Benoit; Scharffenberg, Martin

2016-04-01

Sea level is a very sensitive index of climate change and variability. Sea level integrates the ocean warming, mountain glaciers and ice sheet melting. Understanding the sea level variability and changes implies an accurate monitoring of the sea level variable at climate scales, in addition to understanding the ocean variability and the exchanges between ocean, land, cryosphere, and atmosphere. That is why Sea Level is one of the Essential Climate Variables (ECV) selected in the frame of the ESA Climate Change Initiative (CCI) program. It aims at providing long-term monitoring of the sea level ECV with regular updates, as required for climate studies. The program is now in its second phase of 3 year (following phase I during 2011-2013). The objectives are firstly to involve the climate research community, to refine their needs and collect their feedbacks on product quality. And secondly to develop, test and select the best algorithms and standards to generate an updated climate time series and to produce and validate the Sea Level ECV product. This will better answer the climate user needs by improving the quality of the Sea Level products and maintain a sustain service for an up-to-date production. This has led to the production of the Sea Level ECV which has benefited from yearly extensions and now covers the period 1993-2014. We will firstly present the main achievements of the ESA CCI Sea Level Project. On the one hand, the major steps required to produce the 22 years climate time series are briefly described: collect and refine the user requirements, development of adapted algorithms for climate applications and specification of the production system. On the other hand, the product characteristics are described as well as the results from product validation, performed by several groups of the ocean and climate modeling community. At last, new altimeter standards have been developed and the best one have been recently selected in order to produce a full reprocessing of the dataset (performed in 2016) adapted for climate studies. These new standards will be presented as well as other results regarding the improvement of the sea level estimation in the Arctic Ocean and in coastal areas for which preliminary results suggest that significant improvements can be achieved.

Accurately measuring sea level change from space: an ESA climate change initiative for MSL closure budget studies

NASA Astrophysics Data System (ADS)

Legeais, JeanFrancois; Benveniste, Jérôme

2016-07-01

Sea level is a very sensitive index of climate change and variability. Sea level integrates the ocean warming, mountain glaciers and ice sheet melting. Understanding the sea level variability and changes implies an accurate monitoring of the sea level variable at climate scales, in addition to understanding the ocean variability and the exchanges between ocean, land, cryosphere, and atmosphere. That is why Sea Level is one of the Essential Climate Variables (ECV) selected in the frame of the ESA Climate Change Initiative (CCI) program. It aims at providing long-term monitoring of the sea level ECV with regular updates, as required for climate studies. The program is now in its second phase of 3 year (following phase I during 2011-2013). The objectives are firstly to involve the climate research community, to refine their needs and collect their feedbacks on product quality. And secondly to develop, test and select the best algorithms and standards to generate an updated climate time series and to produce and validate the Sea Level ECV product. This will better answer the climate user needs by improving the quality of the Sea Level products and maintain a sustain service for an up-to-date production. This has led to the production of a first version of the Sea Level ECV which has benefited from yearly extensions and now covers the period 1993-2014. Within phase II, new altimeter standards have been developed and tested in order to reprocess the dataset with the best standards for climate studies. The reprocessed ECV will be released in summer 2016. We will present the main achievements of the ESA CCI Sea Level Project. On the one hand, the major steps required to produce the 22 years climate time series are briefly described: collect and refine the user requirements, development of adapted algorithms for climate applications and specification of the production system. On the other hand, the product characteristics are described as well as the results from product validation, performed by several groups of the ocean and climate modeling community. Efforts have also focused on the improvement of the sea level estimation in the Arctic Ocean and in coastal areas for which preliminary results suggest that significant improvements can be achieved.

US Climate Variability and Predictability Project

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

Patterson, Mike

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

US Climate Variability and Predictability (CLIVAR) Project- Final Report

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

Patterson, Mike

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

Analysis of Water Use Efficiency derived from MODIS satellite image in Northeast Asia

NASA Astrophysics Data System (ADS)

Park, J.; Jang, K.; Kang, S.

2014-12-01

Water Use Efficiency (WUE) is defined as ratio of evapotranspriation (ET) to gross primary productivity (GPP). It can detect the changes of ecosystem properties due to the variability of enviromental condition, and provide a chance to understand the linkage between carbon and water processes in terrestrial ecosystem. In a changing climate, the understanding of ecosystem functional responses to climate variability is crucial for evaluating effect. However, continental or sub-continental scale WUE analysis is were rare. In this study, WUE was estimated in the Northeast Asia using satellite data from 2003 to 2010. ET and GPP were estimated using various MODIS products. The estimated ET and GPP showed favorable agreements with flux tower observations. WUE in the study domain showed considerable variations according to the plant functional types and climatic and elevational gradients. The results produced in this study indicate that satellite remote sensing provides a useful tool for monitoring variability of terrestrial ecosystem functions.

Ocean-atmosphere forcing of centennial hydroclimatic variability in the Pacific Northwest

USGS Publications Warehouse

Steinman, Byron A.; Abbott, Mark B.; Mann, Michael E.; Ortiz, Joseph D.; Feng, Song; Pompeani, David P.; Stansell, Nathan D.; Anderson, Lesleigh; Finney, Bruce P.; Bird, Broxton W.

2014-01-01

Reconstructing centennial timescale hydroclimate variability during the late Holocene is critically important for understanding large-scale patterns of drought and their relationship with climate dynamics. We present sediment oxygen isotope records spanning the last two millennia from 10 lakes, as well as climate model simulations, indicating that the Little Ice Age was dry relative to the Medieval Climate Anomaly in much of the Pacific Northwest of North America. This pattern is consistent with observed associations between the El Niño Southern Oscillation (ENSO), the Northern Annular Mode and drought as well as with proxy-based reconstructions of Pacific ocean-atmosphere variations over the past 1000 years. The large amplitude of centennial variability indicated by the lake data suggests that regional hydroclimate is characterized by longer-term shifts in ENSO-like dynamics, and that an improved understanding of the centennial timescale relationship between external forcing and drought conditions is necessary for projecting future hydroclimatic conditions in western North America.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

The influence of climate variability and change on the science and practice of restoration ecology

Treesearch

Donald A. Falk; Connie Millar

2016-01-01

Variation in Earth’s climate system has always been a primary driver of ecosystem processes and biological evolution. In recent decades, however, the prospect of anthropogenically driven change to the climate system has become an increasingly dominant concern for scientists and conservation biologists. Understanding how ecosystems may...

Exploring the control of land-atmospheric oscillations over terrestrial vegetation productivity

NASA Astrophysics Data System (ADS)

Depoorter, Mathieu; Green, Julia; Gentine, Pierre; Liu, Yi; van Eck, Christel; Regnier, Pierre; Dorigo, Wouter; Verhoest, Niko; Miralles, Diego

2015-04-01

Vegetation dynamics play an important role in the climate system due to their control on the carbon, energy and water cycles. The spatiotemporal variability of vegetation is regulated by internal climate variability as well as natural and anthropogenic forcing mechanisms, including fires, land use, volcano eruptions or greenhouse gas emissions. Ocean-atmospheric oscillations, affect the fluxes of heat and water over continents, leading to anomalies in radiation, precipitation or temperature at widely separated locations (i.e. teleconnections); an effect of ocean-atmospheric oscillations on terrestrial primary productivity can therefore be expected. While different studies have shown the general importance of internal climate variability for global vegetation dynamics, the control by particular teleconnections over the regional growth and decay of vegetation is still poorly understood. At continental to global scales, satellite remote sensing offers a feasible approach to enhance our understanding of the main drivers of vegetation variability. Traditional studies of the multi-decadal variability of global vegetation have been usually based on the normalized difference vegetation index (NDVI) derived from the Advanced Very High Resolution Radiometer (AVHRR), which extends back to the early '80s. There are, however, some limitations to NDVI observations; arguably the most important of these limitations is that from the plant physiology perspective the index does not have a well-defined meaning, appearing poorly correlated to vegetation productivity. On the other hand, recently developed records from other remotely-sensed properties of vegetation, like fluorescence or microwave vegetation optical depth, have proven a significantly better correspondence to above-ground biomass. To enhance our understanding of the controls of ocean-atmosphere oscillations over vegetation, we propose to explore the link between climate oscillation extremes and net primary productivity over the last two decades. The co-variability of a range of climate oscillation indices and newly-derived records of fluorescence and vegetation optical depth is analyzed using a statistical framework based on correlations, bootstrapping and Empirical Orthogonal Functions (EOFs). Results will enable us to characterize regional hotspots where particular climatic oscillations control vegetation productivity, as well as allowing us to underpin the climatic variables behind this control.

Human Responses to Climate Variability: The Case of South Africa

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-07-05

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

Climatic and Landscape Influences on Fire Regimes from 1984 to 2010 in the Western United States

PubMed Central

Liu, Zhihua; Wimberly, Michael C.

2015-01-01

An improved understanding of the relative influences of climatic and landscape controls on multiple fire regime components is needed to enhance our understanding of modern fire regimes and how they will respond to future environmental change. To address this need, we analyzed the spatio-temporal patterns of fire occurrence, size, and severity of large fires (> 405 ha) in the western United States from 1984–2010. We assessed the associations of these fire regime components with environmental variables, including short-term climate anomalies, vegetation type, topography, and human influences, using boosted regression tree analysis. Results showed that large fire occurrence, size, and severity each exhibited distinctive spatial and spatio-temporal patterns, which were controlled by different sets of climate and landscape factors. Antecedent climate anomalies had the strongest influences on fire occurrence, resulting in the highest spatial synchrony. In contrast, climatic variability had weaker influences on fire size and severity and vegetation types were the most important environmental determinants of these fire regime components. Topography had moderately strong effects on both fire occurrence and severity, and human influence variables were most strongly associated with fire size. These results suggest a potential for the emergence of novel fire regimes due to the responses of fire regime components to multiple drivers at different spatial and temporal scales. Next-generation approaches for projecting future fire regimes should incorporate indirect climate effects on vegetation type changes as well as other landscape effects on multiple components of fire regimes. PMID:26465959

Slow science: the value of long ocean biogeochemistry records.

PubMed

Henson, Stephanie A

2014-09-28

Sustained observations (SOs) have provided invaluable information on the ocean's biology and biogeochemistry for over 50 years. They continue to play a vital role in elucidating the functioning of the marine ecosystem, particularly in the light of ongoing climate change. Repeated, consistent observations have provided the opportunity to resolve temporal and/or spatial variability in ocean biogeochemistry, which has driven exploration of the factors controlling biological parameters and processes. Here, I highlight some of the key breakthroughs in biological oceanography that have been enabled by SOs, which include areas such as trophic dynamics, understanding variability, improved biogeochemical models and the role of ocean biology in the global carbon cycle. In the near future, SOs are poised to make progress on several fronts, including detecting climate change effects on ocean biogeochemistry, high-resolution observations of physical-biological interactions and greater observational capability in both the mesopelagic zone and harsh environments, such as the Arctic. We are now entering a new era for biological SOs, one in which our motivations have evolved from the need to acquire basic understanding of the ocean's state and variability, to a need to understand ocean biogeochemistry in the context of increasing pressure in the form of climate change, overfishing and eutrophication.

Past climate variability and change in the Arctic and at high latitudes

USGS Publications Warehouse

Alley, Richard B.; Brigham-Grette, Julie; Miller, Gifford H.; Polyak, Leonid; ,; ,; ,

2009-01-01

Paleoclimate records play a key role in our understanding of Earth's past and present climate system and in our confidence in predicting future climate changes. Paleoclimate data help to elucidate past and present active mechanisms of climate change by placing the short instrumental record into a longer term context and by permitting models to be tested beyond the limited time that instrumental measurements have been available.

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling.

PubMed

Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun'ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu

2017-02-01

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO 2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets.

State dependence of climatic instability over the past 720,000 years from Antarctic ice cores and climate modeling

PubMed Central

Kawamura, Kenji; Abe-Ouchi, Ayako; Motoyama, Hideaki; Ageta, Yutaka; Aoki, Shuji; Azuma, Nobuhiko; Fujii, Yoshiyuki; Fujita, Koji; Fujita, Shuji; Fukui, Kotaro; Furukawa, Teruo; Furusaki, Atsushi; Goto-Azuma, Kumiko; Greve, Ralf; Hirabayashi, Motohiro; Hondoh, Takeo; Hori, Akira; Horikawa, Shinichiro; Horiuchi, Kazuho; Igarashi, Makoto; Iizuka, Yoshinori; Kameda, Takao; Kanda, Hiroshi; Kohno, Mika; Kuramoto, Takayuki; Matsushi, Yuki; Miyahara, Morihiro; Miyake, Takayuki; Miyamoto, Atsushi; Nagashima, Yasuo; Nakayama, Yoshiki; Nakazawa, Takakiyo; Nakazawa, Fumio; Nishio, Fumihiko; Obinata, Ichio; Ohgaito, Rumi; Oka, Akira; Okuno, Jun’ichi; Okuyama, Junichi; Oyabu, Ikumi; Parrenin, Frédéric; Pattyn, Frank; Saito, Fuyuki; Saito, Takashi; Saito, Takeshi; Sakurai, Toshimitsu; Sasa, Kimikazu; Seddik, Hakime; Shibata, Yasuyuki; Shinbori, Kunio; Suzuki, Keisuke; Suzuki, Toshitaka; Takahashi, Akiyoshi; Takahashi, Kunio; Takahashi, Shuhei; Takata, Morimasa; Tanaka, Yoichi; Uemura, Ryu; Watanabe, Genta; Watanabe, Okitsugu; Yamasaki, Tetsuhide; Yokoyama, Kotaro; Yoshimori, Masakazu; Yoshimoto, Takayasu

2017-01-01

Climatic variabilities on millennial and longer time scales with a bipolar seesaw pattern have been documented in paleoclimatic records, but their frequencies, relationships with mean climatic state, and mechanisms remain unclear. Understanding the processes and sensitivities that underlie these changes will underpin better understanding of the climate system and projections of its future change. We investigate the long-term characteristics of climatic variability using a new ice-core record from Dome Fuji, East Antarctica, combined with an existing long record from the Dome C ice core. Antarctic warming events over the past 720,000 years are most frequent when the Antarctic temperature is slightly below average on orbital time scales, equivalent to an intermediate climate during glacial periods, whereas interglacial and fully glaciated climates are unfavourable for a millennial-scale bipolar seesaw. Numerical experiments using a fully coupled atmosphere-ocean general circulation model with freshwater hosing in the northern North Atlantic showed that climate becomes most unstable in intermediate glacial conditions associated with large changes in sea ice and the Atlantic Meridional Overturning Circulation. Model sensitivity experiments suggest that the prerequisite for the most frequent climate instability with bipolar seesaw pattern during the late Pleistocene era is associated with reduced atmospheric CO2 concentration via global cooling and sea ice formation in the North Atlantic, in addition to extended Northern Hemisphere ice sheets. PMID:28246631

Coral bleaching pathways under the control of regional temperature variability

NASA Astrophysics Data System (ADS)

Langlais, C. E.; Lenton, A.; Heron, S. F.; Evenhuis, C.; Sen Gupta, A.; Brown, J. N.; Kuchinke, M.

2017-11-01

Increasing sea surface temperatures (SSTs) are predicted to adversely impact coral populations worldwide through increasing thermal bleaching events. Future bleaching is unlikely to be spatially uniform. Therefore, understanding what determines regional differences will be critical for adaptation management. Here, using a cumulative heat stress metric, we show that characteristics of regional SST determine the future bleaching risk patterns. Incorporating observed information on SST variability, in assessing future bleaching risk, provides novel options for management strategies. As a consequence, the known biases in climate model variability and the uncertainties in regional warming rate across climate models are less detrimental than previously thought. We also show that the thresholds used to indicate reef viability can strongly influence a decision on what constitutes a potential refugia. Observing and understanding the drivers of regional variability, and the viability limits of coral reefs, is therefore critical for making meaningful projections of coral bleaching risk.

Finding "Models" in Clouds

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

Leung, Ruby

2017-05-01

Internationally recognized Climate Scientist Ruby Leung is a cloud gazer. But rather than looking for shapes, Ruby’s life’s calling is to develop regional atmospheric models to better predict and understand the effects of global climate change at scales relevant to humans and the environment. Ruby’s accomplishments include developing novel methods for modeling mountain clouds and precipitation in climate models, and improving understanding of hydroclimate variability and change. She also has led efforts to develop regional climate modeling capabilities in the Weather Research and Forecasting model that is widely adopted by scientists worldwide. Ruby is part of a team of PNNLmore » researchers studying the impacts of global warming.« less

The Climate Variability & Predictability (CVP) Program at NOAA - DYNAMO Recent Project Advancements

NASA Astrophysics Data System (ADS)

Lucas, S. E.; Todd, J. F.; Higgins, W.

2013-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International Geosphere-Biosphere Programme (IGBP), and the U.S. Global Change Research Program (USGCRP). The CVP program sits within the Earth System Science (ESS) Division at NOAA's Climate Program Office. Dynamics of the Madden-Julian Oscillation (DYNAMO): The Indian Ocean is one of Earth's most sensitive regions because the interactions between ocean and atmosphere there have a discernable effect on global climate patterns. The tropical weather that brews in that region can move eastward along the equator and reverberate around the globe, shaping weather and climate in far-off places. The vehicle for this variability is a phenomenon called the Madden-Julian Oscillation, or MJO. The MJO, which originates over the Indian Ocean roughly every 30 to 90 days, is known to influence the Asian and Australian monsoons. It can also enhance hurricane activity in the northeast Pacific and Gulf of Mexico, trigger torrential rainfall along the west coast of North America, and affect the onset of El Niño. CVP-funded scientists participated in the DYNAMO field campaign in 2011-12. Results from this international campaign are expected to improve researcher's insights into this influential phenomenon. A better understanding of the processes governing MJO is an essential step toward improving their representations in numerical models and improving MJO simulation and prediction. Recent results from CVP-funded projects will be summarized in this poster.

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

PubMed

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

2017-10-01

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

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.

Moving beyond a knowledge deficit perspective to understand climate action by youth

NASA Astrophysics Data System (ADS)

Busch, K. C.

2016-12-01

This presentation reports on an experiment testing two framings of uncertainty on students' intent to take action to mitigate climate change. Additionally, to explore possible mechanisms involved in the choice of taking mitigating action, several factors highlighted within behavior theory literature were measured to create a theoretical model for youth's choice to take mitigating action. The factors explored were: knowledge, certainty, affect, efficacy, and social norms. The experiment was conducted with 453 middle and high school students within the Bay Area. Findings indicated that these students did hold a basic understanding of the causes and effects of climate change. They were worried and felt negatively about the topic. They felt somewhat efficacious about their personal ability to mitigate climate change. The students reported that they associated with people who were more likely to think climate change was real and caused by humans. Students also reported that they often take part in private pro-environmental behaviors such as using less electricity. When asked to respond freely to a question about what think about climate change, participants described the negative effects of human-caused climate change on Earth systems at the global scale and as a current phenomenon. The results of the experiment showed that while the text portraying climate change with high uncertainty did affect student's own certainty and their perception of scientists' certainty, it did not affect behavioral intention. This result can be explained through regression analysis. It was found that efficacy and social norms were direct determinants of pro-environmental behaviors. The cognitive variables - knowledge and certainty - and the psychological variable - affect - were not significant predictors of pro-environmental behavior. The implications for this study are that while students hold basic understanding of the causes and effects of climate change, this understanding lacks personal relevance. Another implication of this study is that if we wish to have action-taking as an outcome of climate change education efforts, then the learning activities should include components to address efficacy and social norms.

Using landscape typologies to model socioecological systems: Application to agriculture of the United States Gulf Coast

DOE PAGES

Preston, Benjamin L.; King, Anthony Wayne; Mei, Rui; ...

2016-02-11

Agricultural enterprises are vulnerable to the effects of climate variability and change. Improved understanding of the determinants of vulnerability and adaptive capacity in agricultural systems is important for projecting and managing future climate risk. At present, three analytical tools dominate methodological approaches to understanding agroecological vulnerability to climate: process-based crop models, empirical crop models, and integrated assessment models. A common weakness of these approaches is their limited treatment of socio-economic conditions and human agency in modeling agroecological processes and outcomes. This study proposes a framework that uses spatial cluster analysis to generate regional socioecological typologies that capture geographic variance inmore » regional agricultural production and enable attribution of that variance to climatic, topographic, edaphic, and socioeconomic components. This framework was applied to historical corn production (1986-2010) in the U.S. Gulf of Mexico region as a testbed. The results demonstrate that regional socioeconomic heterogeneity is an important driving force in human dominated ecosystems, which we hypothesize, is a function of the link between socioeconomic conditions and the adaptive capacity of agricultural systems. Meaningful representation of future agricultural responses to climate variability and change is contingent upon understanding interactions among biophysical conditions, socioeconomic conditions, and human agency their incorporation in predictive models.« less

Using landscape typologies to model socioecological systems: Application to agriculture of the United States Gulf Coast

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

Preston, Benjamin L.; King, Anthony Wayne; Mei, Rui

Agricultural enterprises are vulnerable to the effects of climate variability and change. Improved understanding of the determinants of vulnerability and adaptive capacity in agricultural systems is important for projecting and managing future climate risk. At present, three analytical tools dominate methodological approaches to understanding agroecological vulnerability to climate: process-based crop models, empirical crop models, and integrated assessment models. A common weakness of these approaches is their limited treatment of socio-economic conditions and human agency in modeling agroecological processes and outcomes. This study proposes a framework that uses spatial cluster analysis to generate regional socioecological typologies that capture geographic variance inmore » regional agricultural production and enable attribution of that variance to climatic, topographic, edaphic, and socioeconomic components. This framework was applied to historical corn production (1986-2010) in the U.S. Gulf of Mexico region as a testbed. The results demonstrate that regional socioeconomic heterogeneity is an important driving force in human dominated ecosystems, which we hypothesize, is a function of the link between socioeconomic conditions and the adaptive capacity of agricultural systems. Meaningful representation of future agricultural responses to climate variability and change is contingent upon understanding interactions among biophysical conditions, socioeconomic conditions, and human agency their incorporation in predictive models.« less

Understanding the past to interpret the future: Comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

USGS Publications Warehouse

Tillman, Fred D.; Gangopadhyay, Subhrendu; Pruitt, Tom

2017-01-01

In evaluating potential impacts of climate change on water resources, water managers seek to understand how future conditions may differ from the recent past. Studies of climate impacts on groundwater recharge often compare simulated recharge from future and historical time periods on an average monthly or overall average annual basis, or compare average recharge from future decades to that from a single recent decade. Baseline historical recharge estimates, which are compared with future conditions, are often from simulations using observed historical climate data. Comparison of average monthly results, average annual results, or even averaging over selected historical decades, may mask the true variability in historical results and lead to misinterpretation of future conditions. Comparison of future recharge results simulated using general circulation model (GCM) climate data to recharge results simulated using actual historical climate data may also result in an incomplete understanding of the likelihood of future changes. In this study, groundwater recharge is estimated in the upper Colorado River basin, USA, using a distributed-parameter soil-water balance groundwater recharge model for the period 1951–2010. Recharge simulations are performed using precipitation, maximum temperature, and minimum temperature data from observed climate data and from 97 CMIP5 (Coupled Model Intercomparison Project, phase 5) projections. Results indicate that average monthly and average annual simulated recharge are similar using observed and GCM climate data. However, 10-year moving-average recharge results show substantial differences between observed and simulated climate data, particularly during period 1970–2000, with much greater variability seen for results using observed climate data.

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.

Determining the effect of key climate drivers on global hydropower production

NASA Astrophysics Data System (ADS)

Galelli, S.; Ng, J. Y.; Lee, D.; Block, P. J.

2017-12-01

Accounting for about 17% of total global electrical power production, hydropower is arguably the world's main renewable energy source and a key asset to meet Paris climate agreements. A key component of hydropower production is water availability, which depends on both precipitation and multiple drivers of climate variability acting at different spatial and temporal scales. To understand how these drivers impact global hydropower production, we study the relation between four patterns of ocean-atmosphere climate variability (i.e., El Niño Southern Oscillation, Pacific Decadal Oscillation, North Atlantic Oscillation, and Atlantic Multidecadal Oscillation) and monthly time series of electrical power production for over 1,500 hydropower reservoirs—obtained via simulation with a high-fidelity dam model forced with 20th century climate conditions. Notably significant relationships between electrical power productions and climate variability are found in many climate sensitive regions globally, including North and South America, East Asia, West Africa, and Europe. Coupled interactions from multiple, simultaneous climate drivers are also evaluated. Finally, we highlight the importance of using these climate drivers as an additional source of information within reservoir operating rules where the skillful predictability of inflow exists.

Young students, satellites aid understanding of climate-biosphere link

NASA Astrophysics Data System (ADS)

White, Michael A.; Schwartz, Mark D.; Running, Steven W.

Data collected by young students from kindergarten through high school are being combined with satellite data to develop a more consistent understanding of the intimate connection between climate dynamics and the terrestrial biosphere. Comparison of the two sets of data involving the onset of budburst among trees and other vegetation has been extremely encouraging.Surface-atmosphere interactions involving exchanges of carbon, water, and energy are strongly affected by interannual variability in the timing and length of the vegetation growing season, and satellite remote sensing has the unique ability to consistently monitor global spatiotemporal variability in growing season dynamics. But without a clear picture of how satellite information (Figure 1) relates to ground conditions, the application of satellite growing season estimates for monitoring of climate-vegetation interactions, calculation of energy budgets, and large-scale ecological modeling is extremely limited.The integrated phenological analysis of field data, satellite observations, and climate advocated by Schwartz [1998], for example, has been primarily limited by the lack of geographically extensive and consistently measured phenology databases.

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

NASA Astrophysics Data System (ADS)

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

2010-04-01

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

Biomass and the Climatic Space from historical to future scenarios of a Seasonally Dry Tropical Forest - Caatinga

NASA Astrophysics Data System (ADS)

Castanho, A. D. D. A.; Coe, M. T.; Maia Andrade, E.; Walker, W.; Baccini, A.; Brando, P. M.; Farina, M.

2017-12-01

The Caatinga found in the semiarid region in northeastern Brazil is the largest continuous seasonally dry tropical forest in South America. The region has for centuries been subject to anthropogenic activities of land conversion, abandonment, and regrowth. The region also has a large spatial variability of edaphic-climatic properties. These effects together contribute to a wide variability of plant physiognomies and biomass concentration. In addition to land use change due to anthropogenic activities the region is exposed in the near and long term to dryer conditions. The main goal of this work was to validate a high spatial resolution (30 m) map of above ground biomass, understand the climatic role in the biomass spatial variability in the present, and the potential threat to vegetation for future climatic shifts. Satellite-derived biomass products are advanced tools that can address spatial changes in forest structure for an extended region. Here we combine a compilation of published field phytosociological observations across the region with a new 30-meter spatial resolution satellite biomass product. Climate data used for this analyses were based on the CRU (Climate Research Unit, UEA) for the historical time period and for the future a mean and 25-75% quantiles of the CMIP Global Climate model estimates for the RCP scenarios of 4.5 and 8.5 W/m2. The high heterogeneity in the biomass and physiognomy distribution across the Caatinga region is mostly explained by the climatic space defined by the precipitation and dryness index. The Caatinga region has historically already been exposed to shift in its climatic properties, driving all the physiognomies, to a dryer climatic space within the last decade. Future climate intensify the observed trends. This study provides a clearer understanding of the spatial distribution of Caatinga vegetation, its biomass, and relationships to climate, which are essential for strategic development planning, preservation of the biome functions, human services, and biodiversity, face future climate scenarios.

Climate Variability and Its Impact on Forest Hydrology on South Carolina Coastal Plain, USA

Treesearch

Zhaohua Dai; Devendra Amatya; Ge Sun; Carl Trettin; Changsheng Li; Harbin Li

2011-01-01

Understanding the changes in hydrology of coastal forested wetlands induced by climate change is fundamental for developing strategies to sustain their functions and services. This study examined 60 years of climatic observations and 30 years of hydrological data, collected at the Santee Experimental Forest (SEF) in coastal South Carolina. We also applied a physically-...

Climate variability and fire effects on quaking aspen in the central Rocky Mountains, USA

Treesearch

Vachel A. Carter; Andrea Brunelle; Thomas A. Minckley; John D. Shaw; R. Justin DeRose; Simon Brewer

2017-01-01

Our understanding of how climate and fire have impacted quaking aspen (Populus tremuloides Michx.) communities prior to the 20th century is fairly limited. This study analysed the period between 4500 and 2000 cal. yr BP to assess the pre-historic role of climate and fire on an aspen community during an aspen-dominated period.

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...

An analytical approach to separate climate and human contributions to basin streamflow variability

NASA Astrophysics Data System (ADS)

Li, Changbin; Wang, Liuming; Wanrui, Wang; Qi, Jiaguo; Linshan, Yang; Zhang, Yuan; Lei, Wu; Cui, Xia; Wang, Peng

2018-04-01

Climate variability and anthropogenic regulations are two interwoven factors in the ecohydrologic system across large basins. Understanding the roles that these two factors play under various hydrologic conditions is of great significance for basin hydrology and sustainable water utilization. In this study, we present an analytical approach based on coupling water balance method and Budyko hypothesis to derive effectiveness coefficients (ECs) of climate change, as a way to disentangle contributions of it and human activities to the variability of river discharges under different hydro-transitional situations. The climate dominated streamflow change (ΔQc) by EC approach was compared with those deduced by the elasticity method and sensitivity index. The results suggest that the EC approach is valid and applicable for hydrologic study at large basin scale. Analyses of various scenarios revealed that contributions of climate change and human activities to river discharge variation differed among the regions of the study area. Over the past several decades, climate change dominated hydro-transitions from dry to wet, while human activities played key roles in the reduction of streamflow during wet to dry periods. Remarkable decline of discharge in upstream was mainly due to human interventions, although climate contributed more to runoff increasing during dry periods in the semi-arid downstream. Induced effectiveness on streamflow changes indicated a contribution ratio of 49% for climate and 51% for human activities at the basin scale from 1956 to 2015. The mathematic derivation based simple approach, together with the case example of temporal segmentation and spatial zoning, could help people understand variation of river discharge with more details at a large basin scale under the background of climate change and human regulations.

The essential interactions between understanding climate variability and climate change

NASA Astrophysics Data System (ADS)

Neelin, J. D.

2017-12-01

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

'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.

Impacts of Climate Variability and Change on (Marine) Animals: Physiological Underpinnings and Evolutionary Consequences.

PubMed

Pörtner, Hans O; Gutt, Julian

2016-07-01

Understanding thermal ranges and limits of organisms becomes important in light of climate change and observed effects on ecosystems as reported by the IPCC (2014). Evolutionary adaptation to temperature is presently unable to keep animals and other organisms in place; if they can these rather follow the moving isotherms. These effects of climate change on aquatic and terrestrial ecosystems have brought into focus the mechanisms by which temperature and its oscillations shape the biogeography and survival of species. For animals, the integrative concept of oxygen and capacity limited thermal tolerance (OCLTT) has successfully characterized the sublethal limits to performance and the consequences of such limits for ecosystems. Recent models illustrate how routine energy demand defines the realized niche. Steady state temperature-dependent performance profiles thus trace the thermal window and indicate a key role for aerobic metabolism, and the resulting budget of available energy (power), in defining performance under routine conditions, from growth to exercise and reproduction. Differences in the performance and productivity of marine species across latitudes relate to changes in mitochondrial density, capacity, and other features of cellular design. Comparative studies indicate how and why such mechanisms underpinning OCLTT may have developed on evolutionary timescales in different climatic zones and contributed to shaping the functional characteristics and species richness of the respective fauna. A cause-and-effect understanding emerges from considering the relationships between fluctuations in body temperature, cellular design, and performance. Such principles may also have been involved in shaping the functional characteristics of survivors in mass extinction events during earth's history; furthermore, they may provide access to understanding the evolution of endothermy in mammals and birds. Accordingly, an understanding is emerging how climate changes and variability throughout earth's history have influenced animal evolution and co-defined their success or failure from a bio-energetic point of view. Deepening such understanding may further reduce uncertainty about projected impacts of anthropogenic climate variability and change on the distribution, productivity and last not least, survival of aquatic and terrestrial species. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Climatic variability leads to later seasonal flowering of Floridian plants.

PubMed

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

2010-07-21

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

The role of the oceans in changes of the Earth's climate system

NASA Astrophysics Data System (ADS)

von Schuckmann, K.

2016-12-01

Any changes to the Earth's climate system affect an imbalance of the Earth's energy budget due to natural or human made climate forcing. The current positive Earth's energy imbalance is mostly caused by human activity, and is driving global warming. Variations in the world's ocean heat storage and its associated volume changes are a key factor to gauge global warming, to assess changes in the Earth's energy budget and to estimate contributions to the global sea level budget. Present-day sea-level rise is one of the major symptoms of the current positive Earth Energy Imbalance. Sea level also responds to natural climate variability that is superimposing and altering the global warming signal. The most prominent signature in the global mean sea level interannual variability is caused by El Niño-Southern Oscillation. It has been also shown that sea level variability in other regions of the Indo-Pacific area significantly alters estimates of the rate of sea level rise, i.e. in the Indonesian archipelago. In summary, improving the accuracy of our estimates of global Earth's climate state and variability is critical for advancing the understanding and prediction of the evolution of our climate, and an overview on recent findings on the role of the global ocean in changes of the Earth's climate system with particular focus on sea level variability in the Indo-Pacific region will be given in this contribution.

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.

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

Climate Variability and Weather Extremes: Model-Simulated and Historical Data. Chapter 9

NASA Technical Reports Server (NTRS)

Schubert, Siegfried D.; Lim, Young-Kwon

2012-01-01

Extremes in weather and climate encompass a wide array of phenomena including tropical storms, mesoscale convective systems, snowstorms, floods, heat waves, and drought. Understanding how such extremes might change in the future requires an understanding of their past behavior including their connections to large-scale climate variability and trends. Previous studies suggest that the most robust findings concerning changes in short-term extremes are those that can be most directly (though not completely) tied to the increase in the global mean temperatures. These include the findings that (IPCC 2007): There has been a widespread reduction in the number of frost days in mid-latitude regions in recent decades, an increase in the number of warm extremes, particularly warm nights, and a reduction in the number of cold extremes, particularly cold nights. For North America in particular (CCSP SAP 3.3, 2008): There are fewer unusually cold days during the last few decades. The last 10 years have seen a lower number of severe cold waves than for any other 10-year period in the historical record that dates back to 1895. There has been a decrease in the number of frost days and a lengthening of the frost-free season, particularly in the western part of North America. Other aspects of extremes such as the changes in storminess have a less clear signature of long term change, with considerable interannual, and decadal variability that can obscure any climate change signal. Nevertheless, regarding extratropical storms (CCSP SAP 3.3, 2008): The balance of evidence suggests that there has been a northward shift in the tracks of strong low pressure systems (storms) in both the North Atlantic and North Pacific basins. For North America: Regional analyses suggest that there has been a decrease in snowstorms in the South and lower Midwest of the United States, and an increase in snowstorms in the upper Midwest and Northeast. Despite the progress already made, our understanding of the basic mechanisms by which extremes vary is incomplete. As noted in IPCC (2007), Incomplete global data sets and remaining model uncertainties still restrict understanding of changes in extremes and attribution of changes to causes, although understanding of changes in the intensity, frequency and risk of extremes has improved. Separating decadal and other shorter-term variability from climate change impacts on extremes requires a better understanding of the processes responsible for the changes. In particular, the physical processes linking sea surface temperature changes to regional climate changes, and a basic understanding of the inherent variability in weather extremes and how that is impacted by atmospheric circulation changes at subseasonal to decadal and longer time scales, are still inadequately understood. Given the fundamental limitations in the time span and quality of global observations, substantial progress on these issues will rely increasingly on improvements in models, with observations continuing to play a critical role, though less as a detection tool, and more as a tool for addressing physical processes, and to insure the quality of the climate models and the verisimilitude of the simulations (CCSP SAP 1.3, 2008).

Understanding extreme rainfall events in Australia through historical data

NASA Astrophysics Data System (ADS)

Ashcroft, Linden; Karoly, David John

2016-04-01

Historical climate data recovery is still an emerging field in the Australian region. The majority of Australia's instrumental climate analyses begin in 1900 for rainfall and 1910 for temperature, particularly those focussed on extreme event analysis. This data sparsity for the past in turn limits our understanding of long-term climate variability, constraining efforts to predict the impact of future climate change. To address this need for improved historical data in Australia, a new network of recovered climate observations has recently been developed, centred on the highly populated southeastern Australian region (Ashcroft et al., 2014a, 2014b). The dataset includes observations from more than 39 published and unpublished sources and extends from British settlement in 1788 to the formation of the Australian Bureau of Meteorology in 1908. Many of these historical sources provide daily temperature and rainfall information, providing an opportunity to improve understanding of the multidecadal variability of Australia's extreme events. In this study we combine the historical data for three major Australian cities - Melbourne, Sydney and Adelaide - with modern observations to examine extreme rainfall variability over the past 174 years (1839-2013). We first explore two case studies, combining instrumental and documentary evidence to support the occurrence of severe storms in Sydney in 1841 and 1844. These events appear to be at least as extreme as Sydney's modern 24-hour rainfall record. Next we use a suite of rainfall indices to assess the long-term variability of rainfall in southeastern Australia. In particular, we focus on the stationarity of the teleconnection between the El Niño-Southern Oscillation (ENSO) phenomenon and extreme rainfall events. Using ENSO reconstructions derived from both palaeoclimatic and documentary sources, we determine the historical relationship between extreme rainfall in southeastern Australia and ENSO, and examine whether or not this relationship has remained stable since the early to mid-19th century. Ashcroft, L., Gergis, J., Karoly, D.J., 2014a. A historical climate dataset for southeastern Australia, 1788-1859. Geosci. Data J. 1, 158-178. doi:10.1002/gdj3.19 Ashcroft, L., Karoly, D.J., Gergis, J., 2014b. Southeastern Australian climate variability 1860-2009: A multivariate analysis. Int. J. Climatol. 34, 1928-1944. doi:10.1002/joc.3812

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.

Phylogenetic assemblage structure of North American trees is more strongly shaped by glacial-interglacial climate variability in gymnosperms than in angiosperms.

PubMed

Ma, Ziyu; Sandel, Brody; Svenning, Jens-Christian

2016-05-01

How fast does biodiversity respond to climate change? The relationship of past and current climate with phylogenetic assemblage structure helps us to understand this question. Studies of angiosperm tree diversity in North America have already suggested effects of current water-energy balance and tropical niche conservatism. However, the role of glacial-interglacial climate variability remains to be determined, and little is known about any of these relationships for gymnosperms. Moreover, phylogenetic endemism, the concentration of unique lineages in restricted ranges, may also be related to glacial-interglacial climate variability and needs more attention. We used a refined phylogeny of both angiosperms and gymnosperms to map phylogenetic diversity, clustering and endemism of North American trees in 100-km grid cells, and climate change velocity since Last Glacial Maximum together with postglacial accessibility to recolonization to quantify glacial-interglacial climate variability. We found: (1) Current climate is the dominant factor explaining the overall patterns, with more clustered angiosperm assemblages toward lower temperature, consistent with tropical niche conservatism. (2) Long-term climate stability is associated with higher angiosperm endemism, while higher postglacial accessibility is linked to to more phylogenetic clustering and endemism in gymnosperms. (3) Factors linked to glacial-interglacial climate change have stronger effects on gymnosperms than on angiosperms. These results suggest that paleoclimate legacies supplement current climate in shaping phylogenetic patterns in North American trees, and especially so for gymnosperms.

Coral Records of 20th Century Central Tropical Pacific SST and Salinity: Signatures of Natural and Anthropogenic Climate Change

NASA Astrophysics Data System (ADS)

Nurhati, I. S.; Cobb, K.; Di Lorenzo, E.

2011-12-01

Accurate forecasts of regional climate changes in many regions of the world largely depend on quantifying anthropogenic trends in tropical Pacific climate against its rich background of interannual to decadal-scale climate variability. However, the strong natural climate variability combined with limited instrumental climate datasets have obscured potential anthropogenic climate signals in the region. Here, we present coral-based sea-surface temperature (SST) and salinity proxy records over the 20th century (1898-1998) from the central tropical Pacific - a region sensitive to El Niño-Southern Oscillation (ENSO) whose variability strongly impacts the global climate. The SST and salinity proxy records are reconstructed via coral Sr/Ca and the oxygen isotopic composition of seawater (δ18Osw), respectively. On interannual (2-7yr) timescales, the SST proxy record tracks both eastern- and central-Pacific flavors of ENSO variability (R=0.65 and R=0.67, respectively). Interannual-scale salinity variability in our coral record highlights profound differences in precipitation and ocean advections during the two flavors of ENSO. On decadal (8yr-lowpassed) timescales, the central tropical Pacific SST and salinity proxy records are controlled by different sets of dynamics linked to the leading climate modes of North Pacific climate variability. Decadal-scale central tropical Pacific SST is highly correlated to the recently discovered North Pacific Gyre Oscillation (NPGO; R=-0.85), reflecting strong dynamical links between the central Pacific warming mode and extratropical decadal climate variability. Whereas decadal-scale salinity variations in the central tropical Pacific are significantly correlated with the Pacific Decadal Oscillation (PDO; R=0.54), providing a better understanding on low-frequency salinity variability in the region. Having characterized natural climate variability in this region, the coral record shows a +0.5°C warming trend throughout the last century. However, the most prominent feature of the new coral records is an unprecedented freshening trend since the mid-20th century, in line with global climate models (GCMs) projections of enhanced hydrological patterns (wet areas are getting wetter and vice versa) under greenhouse forcing. Taken together, the coral records provide key constraints on tropical Pacific climate trends that may improve regional climate projections in areas affected by tropical Pacific climate variability.
Central Tropical Pacific SST and Salinity Proxy Records

Understanding scale dependency of climatic processes with diarrheal disease

NASA Astrophysics Data System (ADS)

Nasr Azadani, F.; Jutla, A.; Akanda, A. S. S.; Colwell, R. R.

2015-12-01

The issue of scales in linking climatic processes with diarrheal diseases is perhaps one of the most challenging aspect to develop any predictive algorithm for outbreaks and to understand impacts of changing climate. Majority of diarrheal diseases have shown to be strongly associated with climate modulated environmental processes where pathogens survive. Using cholera as an example of characteristic diarrheal diseases, this study will provide methodological insights on dominant scale variability in climatic processes that are linked with trigger and transmission of disease. Cholera based epidemiological models use human to human interaction as a main transmission mechanism, however, environmental conditions for creating seasonality in outbreaks is not explicitly modeled. For example, existing models cannot create seasonality, unless some of the model parameters are a-priori chosen to vary seasonally. A systems based feedback approach will be presented to understand role of climatic processes on trigger and transmission disease. In order to investigate effect of changing climate on cholera, a downscaling approach using support vector machine will be used. Our preliminary results using three climate models, ECHAM5, GFDL, and HADCM show that varying modalities in future cholera outbreaks.

MODIS EVI as a Surrogate for Net Primary Production across Precipitation Regimes

USDA-ARS?s Scientific Manuscript database

According to Global Climate Models (GCMs) the occurrence of extreme events of precipitation will be more frequent in the future. Therefore, important challenges arise regarding climate variability, which are mainly related to the understanding of ecosystem responses to changes in precipitation patte...

Objective spatiotemporal proxy-model comparisons of the Asian monsoon for the last millennium

NASA Astrophysics Data System (ADS)

Anchukaitis, K. J.; Cook, E. R.; Ammann, C. M.; Buckley, B. M.; D'Arrigo, R. D.; Jacoby, G.; Wright, W. E.; Davi, N.; Li, J.

2008-12-01

The Asian monsoon system can be studied using a complementary proxy/simulation approach which evaluates climate models using estimates of past precipitation and temperature, and which subsequently applies the best understanding of the physics of the climate system as captured in general circulation models to evaluate the broad-scale dynamics behind regional paleoclimate reconstructions. Here, we use a millennial-length climate field reconstruction of monsoon season summer (JJA) drought, developed from tree- ring proxies, with coupled climate simulations from NCAR CSM1.4 and CCSM3 to evaluate the cause of large- scale persistent droughts over the last one thousand years. Direct comparisons are made between the external forced response within the climate model and the spatiotemporal field reconstruction. In order to identify patterns of drought associated with internal variability in the climate system, we use a model/proxy analog technique which objectively selects epochs in the model that most closely reproduce those observed in the reconstructions. The concomitant ocean-atmosphere dynamics are then interpreted in order to identify and understand the internal climate system forcing of low frequency monsoon variability. We examine specific periods of extensive or intensive regional drought in the 15th, 17th, and 18th centuries, many of which are coincident with major cultural changes in the region.

Framework for a hydrologic climate-response network in New England

USGS Publications Warehouse

Lent, Robert M.; Hodgkins, Glenn A.; Dudley, Robert W.; Schalk, Luther F.

2015-01-01

Many climate-related hydrologic variables in New England have changed in the past century, and many are expected to change during the next century. It is important to understand and monitor these changes because they can affect human water supply, hydroelectric power generation, transportation infrastructure, and stream and riparian ecology. This report describes a framework for hydrologic monitoring in New England by means of a climate-response network. The framework identifies specific inland hydrologic variables that are sensitive to climate variation; identifies geographic regions with similar hydrologic responses; proposes a fixed-station monitoring network composed of existing streamflow, groundwater, lake ice, snowpack, and meteorological data-collection stations for evaluation of hydrologic response to climate variation; and identifies streamflow basins for intensive, process-based studies and for estimates of future hydrologic conditions.

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

PubMed

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

2016-01-01

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

Exploring the Climate Change, Migration and Conflict Nexus.

PubMed

Burrows, Kate; Kinney, Patrick L

2016-04-22

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

Exploring the Climate Change, Migration and Conflict Nexus

PubMed Central

Burrows, Kate; Kinney, Patrick L.

2016-01-01

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

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.

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

PubMed Central

Monahan, William B.; Fisichelli, Nicholas A.

2014-01-01

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

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

PubMed

Monahan, William B; Fisichelli, Nicholas A

2014-01-01

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

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

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

Maslowski, Wieslaw

This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate throughmore » polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.« less

The Role of Global Hydrologic Processes in Interannual and Long-Term Climate Variability

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.

1997-01-01

The earth's climate and its variability is linked inextricably with the presence of water on our planet. El Nino / Southern Oscillation-- the major mode of interannual variability-- is characterized by strong perturbations in oceanic evaporation, tropical rainfall, and radiation. On longer time scales, the major feedback mechanism in CO2-induced global warming is actually that due to increased water vapor holding capacity of the atmosphere. The global hydrologic cycle effects on climate are manifested through influence of cloud and water vapor on energy fluxes at the top of atmosphere and at the surface. Surface moisture anomalies retain the "memory" of past precipitation anomalies and subsequently alter the partitioning of latent and sensible heat fluxes at the surface. At the top of atmosphere, water vapor and cloud perturbations alter the net amount of radiation that the earth's climate system receives. These pervasive linkages between water, radiation, and surface processes present major complexities for observing and modeling climate variations. Major uncertainties in the observations include vertical structure of clouds and water vapor, surface energy balance, and transport of water and heat by wind fields. Modeling climate variability and change on a physical basis requires accurate by simplified submodels of radiation, cloud formation, radiative exchange, surface biophysics, and oceanic energy flux. In the past, we m safely say that being "data poor' has limited our depth of understanding and impeded model validation and improvement. Beginning with pre-EOS data sets, many of these barriers are being removed. EOS platforms with the suite of measurements dedicated to specific science questions are part of our most cost effective path to improved understanding and predictive capability. This talk will highlight some of the major questions confronting global hydrology and the prospects for significant progress afforded by EOS-era measurements.

GC23G-1310: Investigation Into the Effects of Climate Variability and Land Cover Change on the Hydrologic System of the Lower Mekong Basin

NASA Technical Reports Server (NTRS)

Markert, Kel N.; Griffin, Robert; Limaye, Ashutosh S.; McNider, Richard T.; Anderson, Eric R.

2016-01-01

The Lower Mekong Basin (LMB) is an economically and ecologically important region that experiences hydrologic hazards such as floods and droughts, which can directly affect human well-being and limit economic growth and development. To effectively develop long-term plans for addressing hydrologic hazards, the regional hydrological response to climate variability and land cover change needs to be evaluated. This research aims to investigate how climate variability, specifically variations in the precipitation regime, and land cover change will affect hydrologic parameters both spatially and temporally within the LMB. The research goal is achieved by (1) modeling land cover change for a baseline land cover change scenario as well as changes in land cover with increases in forest or agriculture and (2) using projected climate variables and modeled land cover data as inputs into the Variable Infiltration Capacity (VIC) hydrologic model to simulate the changes to the hydrologic system. The VIC model outputs were analyzed against historic values to understand the relative contribution of climate variability and land cover to change, where these changes occur, and to what degree these changes affect the hydrology. This study found that the LMB hydrologic system is more sensitive to climate variability than land cover change. On average, climate variability was found to increase discharge and evapotranspiration (ET) while decreasing water storage. The change in land cover show that increasing forest area will slightly decrease discharge and increase ET while increasing agriculture area increases discharge and decreases ET. These findings will help the LMB by supporting individual country policy to plan for future hydrologic changes as well as policy for the basin as a whole.

Managing living marine resources in a dynamic environment: The role of seasonal to decadal climate forecasts

NASA Astrophysics Data System (ADS)

Tommasi, Desiree; Stock, Charles A.; Hobday, Alistair J.; Methot, Rick; Kaplan, Isaac C.; Eveson, J. Paige; Holsman, Kirstin; Miller, Timothy J.; Gaichas, Sarah; Gehlen, Marion; Pershing, Andrew; Vecchi, Gabriel A.; Msadek, Rym; Delworth, Tom; Eakin, C. Mark; Haltuch, Melissa A.; Séférian, Roland; Spillman, Claire M.; Hartog, Jason R.; Siedlecki, Samantha; Samhouri, Jameal F.; Muhling, Barbara; Asch, Rebecca G.; Pinsky, Malin L.; Saba, Vincent S.; Kapnick, Sarah B.; Gaitan, Carlos F.; Rykaczewski, Ryan R.; Alexander, Michael A.; Xue, Yan; Pegion, Kathleen V.; Lynch, Patrick; Payne, Mark R.; Kristiansen, Trond; Lehodey, Patrick; Werner, Francisco E.

2017-03-01

Recent developments in global dynamical climate prediction systems have allowed for skillful predictions of climate variables relevant to living marine resources (LMRs) at a scale useful to understanding and managing LMRs. Such predictions present opportunities for improved LMR management and industry operations, as well as new research avenues in fisheries science. LMRs respond to climate variability via changes in physiology and behavior. For species and systems where climate-fisheries links are well established, forecasted LMR responses can lead to anticipatory and more effective decisions, benefitting both managers and stakeholders. Here, we provide an overview of climate prediction systems and advances in seasonal to decadal prediction of marine-resource relevant environmental variables. We then describe a range of climate-sensitive LMR decisions that can be taken at lead-times of months to decades, before highlighting a range of pioneering case studies using climate predictions to inform LMR decisions. The success of these case studies suggests that many additional applications are possible. Progress, however, is limited by observational and modeling challenges. Priority developments include strengthening of the mechanistic linkages between climate and marine resource responses, development of LMR models able to explicitly represent such responses, integration of climate driven LMR dynamics in the multi-driver context within which marine resources exist, and improved prediction of ecosystem-relevant variables at the fine regional scales at which most marine resource decisions are made. While there are fundamental limits to predictability, continued advances in these areas have considerable potential to make LMR managers and industry decision more resilient to climate variability and help sustain valuable resources. Concerted dialog between scientists, LMR managers and industry is essential to realizing this potential.

Phenology at the crossroads?

NASA Astrophysics Data System (ADS)

Menzel, Annette

2014-05-01

Phenology is the study of the timing of natural events such as plant growth or animal migration. Currently nearly 500 papers are published annually that include 'phenolog*' in their title; many are related to anthropogenic change. Since seasonal events are triggered predominantly by climate, phenology has emerged as a key asset in identifying fingerprints of climate change in natural systems, especially since recent warming has been mirrored by significantly advancing spring events. Phenological changes have been reported across continents, habitats and taxa, predominantly as mean temporal changes ('trends') or as relationships to temperature and other drivers ('responses'), and have been summarised in various meta-analyses. However, a considerable variability in observed trends and responses is reported along with mixed messages of the footprint of climate change in nature. Phenology has made considerable advances but is a crossroads of understanding this variability. At the same time a change of emphasis in explanation, prediction and adaptation is emerging, which needs a full acknowledgement of this variability; likely yielding to more plasticity and resilience. In this review, I summarize current knowledge and recent insights into the role of • different observation methods, their accuracy and their target phenophases • observed events, species, traits, ontogenetic effects • species-specific safeguarding strategies, e.g. chilling, photoperiod • additional drivers other than climate, e.g. nutrients, GHG, biotic effects, anthropogenic / agricultural management • seasonal as well as spatio-temporal variation, effects of regional climate changes and analogous climates. This review clearly demonstrated that, comparable to weather and climate ensembles, only a full consideration of variation in responses allows a complete understanding of ecological, cultural and socioeconomic consequences of these phenological changes.

The climatic implications of the Holocene floods in the north-western Himalaya, India

NASA Astrophysics Data System (ADS)

Sharma, S.; Shukla, A. D.; Bartarya, S.; Marh, B.; Juyal, N.

2016-12-01

Understanding the growing trend of extreme hydrological events in response to climate variabilities is a major area of interest in the climate change science. More important so as the predictions suggest increased frequency and/or magnitude of floods in the Himalayan region due to more intense/frequent coupling between the Indian Summer Monsoon (ISM) and the mid-latitude westerlies. In view of this, studies pertaining to the geological evidence of extreme hydrological events (paleofloods) become important as these not only extend beyond the instrumental records but ensures better understanding of the pattern of river response to the extreme climate variability.The Satluj River in the north-western Himalaya is infamous for its history of recurrent and devastating floods for which there is no data beyond the historical record. The present study in the middle Satluj valley is a contribution towards expanding the cognizance of the climate and geomorphic processes responsible for the Holocene extreme events. Based on sedimentology and grain size variability a total of 24 flood events of increasing magnitude are identified. The geochemical data indicate that the flood sediments were mostly generated and transported from the Higher Himalayan Crystalline with some contribution from the Trans-Himalaya. The optical chronology allow us to identify four major flood clusters which are dated between 13-11 ka; 8-4 ka; 4-2 ka and < 2 ka respectively. Climatically, these correspond to the cooler/relatively drier climatic condition (weak monsoon) and broadly correlate with the phases of negative Arctic Oscillation (‒AO) and negative North Atlantic Oscillation (-NAO).

Quantifying climate-growth relationships at the stand level in a mature mixed-species conifer forest.

PubMed

Teets, Aaron; Fraver, Shawn; Weiskittel, Aaron R; Hollinger, David Y

2018-03-11

A range of environmental factors regulate tree growth; however, climate is generally thought to most strongly influence year-to-year variability in growth. Numerous dendrochronological (tree-ring) studies have identified climate factors that influence year-to-year variability in growth for given tree species and location. However, traditional dendrochronology methods have limitations that prevent them from adequately assessing stand-level (as opposed to species-level) growth. We argue that stand-level growth analyses provide a more meaningful assessment of forest response to climate fluctuations, as well as the management options that may be employed to sustain forest productivity. Working in a mature, mixed-species stand at the Howland Research Forest of central Maine, USA, we used two alternatives to traditional dendrochronological analyses by (1) selecting trees for coring using a stratified (by size and species), random sampling method that ensures a representative sample of the stand, and (2) converting ring widths to biomass increments, which once summed, produced a representation of stand-level growth, while maintaining species identities or canopy position if needed. We then tested the relative influence of seasonal climate variables on year-to-year variability in the biomass increment using generalized least squares regression, while accounting for temporal autocorrelation. Our results indicate that stand-level growth responded most strongly to previous summer and current spring climate variables, resulting from a combination of individualistic climate responses occurring at the species- and canopy-position level. Our climate models were better fit to stand-level biomass increment than to species-level or canopy-position summaries. The relative growth responses (i.e., percent change) predicted from the most influential climate variables indicate stand-level growth varies less from to year-to-year than species-level or canopy-position growth responses. By assessing stand-level growth response to climate, we provide an alternative perspective on climate-growth relationships of forests, improving our understanding of forest growth dynamics under a fluctuating climate. © 2018 John Wiley & Sons Ltd.

Climate change patterns in Amazonia and biodiversity.

PubMed

Cheng, Hai; Sinha, Ashish; Cruz, Francisco W; Wang, Xianfeng; Edwards, R Lawrence; d'Horta, Fernando M; Ribas, Camila C; Vuille, Mathias; Stott, Lowell D; Auler, Augusto S

2013-01-01

Precise characterization of hydroclimate variability in Amazonia on various timescales is critical to understanding the link between climate change and biodiversity. Here we present absolute-dated speleothem oxygen isotope records that characterize hydroclimate variation in western and eastern Amazonia over the past 250 and 20 ka, respectively. Although our records demonstrate the coherent millennial-scale precipitation variability across tropical-subtropical South America, the orbital-scale precipitation variability between western and eastern Amazonia exhibits a quasi-dipole pattern. During the last glacial period, our records imply a modest increase in precipitation amount in western Amazonia but a significant drying in eastern Amazonia, suggesting that higher biodiversity in western Amazonia, contrary to 'Refugia Hypothesis', is maintained under relatively stable climatic conditions. In contrast, the glacial-interglacial climatic perturbations might have been instances of loss rather than gain in biodiversity in eastern Amazonia, where forests may have been more susceptible to fragmentation in response to larger swings in hydroclimate.

Climate-driven changes in forest succession and the influence of management on forest carbon dynamics in the Puget Lowlands of Washington State, USA

Treesearch

Danelle M. Laflower; Matthew D. Hurteau; George W. Koch; Malcolm P. North; Bruce A. Hungate

2016-01-01

Projecting the response of forests to changing climate requires understanding how biotic and abiotic controls on tree growth will change over time. As temperature and interannual precipitation variability increase, the overall forest response is likely to be influenced by species-specific responses to changing climate. Management actions that alter composition...

Fire-climate interactions in the American west since 1400 CE

Treesearch

Valerie Trouet; Alan H. Taylor; Eugene R. Wahl; Carl N. Skinner

2010-01-01

Despite a strong anthropogenic fingerprint on 20th Century wildland fire activity in the American West, climate remains a main driver. A better understanding of the spatiotemporal variability in fire‐climate interactions is therefore crucial for fire management. Here, we present annually resolved, tree‐ring based fire records for four regions in the American West that...

Water yield responses to climate change and variability across the North–South Transect of Eastern China (NSTEC)

Treesearch

Nan Lu; Ge Sun; Xiaoming Feng; Bojie Fu

2013-01-01

China is facing a growing water crisis due to climate and land use change, and rise in human water demand across this rapidly developing country. Understanding the spatial and temporal ecohydrologic responses to climate change is critical to sustainable water resource management. We investigated water yield (WY) responses to historical (1981–2000) and projected...

Earth Observations in Support of Offshore Wind Energy Management in the Euro-Atlantic Region

NASA Astrophysics Data System (ADS)

Liberato, M. L. R.

2017-12-01

Climate change is one of the most important challenges in the 21st century and the energy sector is a major contributor to GHG emissions. Therefore greater attention has been given to the evaluation of offshore wind energy potentials along coastal areas, as it is expected offshore wind energy to be more efficient and cost-effective in the near future. Europe is developing offshore sites for over two decades and has been growing at gigawatt levels in annual capacity. Portugal is among these countries, with the development of a 25MW WindFloat Atlantic wind farm project. The international scientific community has developed robust ability on the research of the climate system components and their interactions. Climate scientists have gained expertise in the observation and analysis of the climate system as well as on the improvement of model and predictive capabilities. Developments on climate science allow advancing our understanding and prediction of the variability and change of Earth's climate on all space and time scales, while improving skilful climate assessments and tools for dealing with future challenges of a warming planet. However the availability of greater datasets amplifies the complexity on manipulation, representation and consequent analysis and interpretation of such datasets. Today the challenge is to translate scientific understanding of the climate system into climate information for society and decision makers. Here we discuss the development of an integration tool for multidisciplinary research, which allows access, management, tailored pre-processing and visualization of datasets, crucial to foster research as a service to society. One application is the assessment and monitoring of renewable energy variability, such as wind or solar energy, at several time and space scales. We demonstrate the ability of the e-science platform for planning, monitoring and management of renewable energy, particularly offshore wind energy in the Euro-Atlantic region. Further we explore the automatization of processes using different domains and datasets, which facilitate further research in evaluating and understanding renewable energy variability. AcknowledgementsThis work is supported by Foundation for Science and Technology (FCT), Portugal, project UID/GEO/50019/2013 - Instituto Dom Luiz.

Quantitative Assessment of Antarctic Climate Variability and Change

NASA Astrophysics Data System (ADS)

Ordonez, A.; Schneider, D. P.

2013-12-01

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

Global Warming: Discussion for EOS Science Writers Workshop

NASA Technical Reports Server (NTRS)

Hansen, James E

1999-01-01

The existence of global warming this century is no longer an issue of scientific debate. But there are many important questions about the nature and causes of long-term climate change, th roles of nature and human-made climate forcings and unforced (chaotic) climate variability, the practical impacts of climate change, and what, if anything, should be done to reduce global warming, Global warming is not a uniform increase of temperature, but rather involves at complex geographically varying climate change. Understanding of global warming will require improved observations of climate change itself and the forcing factors that can lead to climate change. The NASA Terra mission and other NASA Earth Science missions will provide key measurement of climate change and climate forcings. The strategy to develop an understanding of the causes and predictability of long-term climate change must be based on combination of observations with models and analysis. The upcoming NASA missions will make important contributions to the required observations.

EFFECTS OF CLIMATE VARIABILITY ON NITROGEN FLUXES FROM SELECTED WATERSHEDS ALONG THE US EAST COAST

EPA Science Inventory

To anticipate vulnerabilities of coastal ecosystems to global climate change, a better understanding is needed of factors affecting current and past nitrogen fluxes from watersheds to coastal systems. This study undertook a statistical examination of long-term data sets of nutrie...

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.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

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

2013-01-01

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

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

PubMed Central

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

2013-01-01

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

Climate Observations from Space

NASA Astrophysics Data System (ADS)

Briggs, Stephen

2016-07-01

The latest Global Climate Observing System (GCOS) Status Report on global climate observations, delivered to the UNFCCC COP21 in November 2016, showed how satellite data are critical for observations relating to climate. Of the 50 Essential Climate Variables (ECVs) identified by GCOS as necessary for understanding climate change, about half are derived only from satellite data while half of the remainder have a significant input from satellites. Hence data from Earth observing satellite systems are now a fundamental requirement for understanding the climate system and for managing the consequences of climate change. Following the Paris Agreement of COP21 this need is only greater. Not only will satellites have to continue to provide data for modelling and predicting climate change but also for a much wider range of actions relating to climate. These include better information on loss and damage, resilience, improved adaptation to change, and on mitigation including information on greenhouse gas emissions. In addition there is an emerging need for indicators of the risks associated with future climate change which need to be better quantified, allowing policy makers both to understand what decisions need to be taken, and to see the consequences of their actions. The presentation will set out some of the ways in which satellite data are important in all aspects of understanding, managing and predicting climate change and how they may be used to support future decisions by those responsible for policy related to managing climate change and its consequences.

The Dynamics of Vulnerability and Implications for Climate Change Adaptation: Lessons from Urban Water Management

NASA Astrophysics Data System (ADS)

Dilling, L.; Daly, M.; Travis, W.; Wilhelmi, O.; Klein, R.; Kenney, D.; Ray, A. J.; Miller, K.

2013-12-01

Recent reports and scholarship have suggested that adapting to current climate variability may represent a "no regrets" strategy for adapting to climate change. Filling "adaptation deficits" and other approaches that rely on addressing current vulnerabilities are of course helpful for responding to current climate variability, but we find here that they are not sufficient for adapting to climate change. First, following a comprehensive review and unique synthesis of the natural hazards and climate adaptation literatures, we advance six reasons why adapting to climate variability is not sufficient for adapting to climate change: 1) Vulnerability is different at different levels of exposure; 2) Coping with climate variability is not equivalent to adaptation to longer term change; 3) The socioeconomic context for vulnerability is constantly changing; 4) The perception of risk associated with climate variability does not necessarily promote adaptive behavior in the face of climate change; 5) Adaptations made to short term climate variability may reduce the flexibility of the system in the long term; and 6) Adaptive actions may shift vulnerabilities to other parts of the system or to other people. Instead we suggest that decision makers faced with choices to adapt to climate change must consider the dynamics of vulnerability in a connected system-- how choices made in one part of the system might impact other valued outcomes or even create new vulnerabilities. Furthermore we suggest that rather than expressing climate change adaptation as an extension of adaptation to climate variability, the research and practice communities would do well to articulate adaptation as an imperfect policy, with tradeoffs and consequences and that decisions be prioritized to preserve flexibility be revisited often as climate change unfolds. We then present the results of a number of empirical studies of decision making for drought in urban water systems in the United States to understand: a) the variety of actions taken; b) the limitations of actions available to water managers; and c) the effectiveness of actions taken to date. Time permitting, we briefly present the results of 3 in-depth case studies of drought response and current perception of preparedness with respect to future drought and climate change among urban water system managers. We examine the role of governance, system connectivity, public perceptions and other factors in driving decision making and outcomes.

Slow science: the value of long ocean biogeochemistry records

PubMed Central

Henson, Stephanie A.

2014-01-01

Sustained observations (SOs) have provided invaluable information on the ocean's biology and biogeochemistry for over 50 years. They continue to play a vital role in elucidating the functioning of the marine ecosystem, particularly in the light of ongoing climate change. Repeated, consistent observations have provided the opportunity to resolve temporal and/or spatial variability in ocean biogeochemistry, which has driven exploration of the factors controlling biological parameters and processes. Here, I highlight some of the key breakthroughs in biological oceanography that have been enabled by SOs, which include areas such as trophic dynamics, understanding variability, improved biogeochemical models and the role of ocean biology in the global carbon cycle. In the near future, SOs are poised to make progress on several fronts, including detecting climate change effects on ocean biogeochemistry, high-resolution observations of physical–biological interactions and greater observational capability in both the mesopelagic zone and harsh environments, such as the Arctic. We are now entering a new era for biological SOs, one in which our motivations have evolved from the need to acquire basic understanding of the ocean's state and variability, to a need to understand ocean biogeochemistry in the context of increasing pressure in the form of climate change, overfishing and eutrophication. PMID:25157192

Variability in understory evapotranspiration with overstory density in Siberian larch forests

NASA Astrophysics Data System (ADS)

Tobio, A.; Loranty, M. M.; Kropp, H.; Pena, H., III; Alexander, H. D.; Natali, S.; Kholodov, A. L.

2016-12-01

Arctic ecosystems are changing rapidly in response to amplified rates of climate change. Increased vegetation productivity, altered ecosystem carbon and hydrologic cycling, and increased wildfire severity are among the key responses to changing permafrost and climate conditions. Boreal larch forests in northeastern Siberia are a critical but understudied ecosystem affected by these modifications. Understory vegetation in these ecosystems, which typically have low canopy cover, may account for half of all water fluxes. Despite the potential importance of the understory for ecosystem water exchange, there has been relatively little research examining variability in understory evapotranspiration in boreal larch forests. In particular, the water balance of understory shrubs and mosses is largely undefined and could provide insight on how understory vegetation and our changing climate interact. This is especially important because both observed increases in vegetation productivity and wildfire severity could lead to increases in forests density, altering the proportional contributions of over- and understory vegetation to whole ecosystem evapotranspiration. In order to better understand variability in understory evapotranspiration we measured in larch forests with differing overstory density and permafrost conditions that likely vary as a consequence of fire severity. We used the static chamber technique to measure fluxes across a range of understory vegetation types and environmental conditions. In general, we found that the understory vegetation in low density stands transpires more than that in high density stands. This tends to be correlated with a larger amount of aboveground biomass in the low density stands, and an increase in solar radiation, due to less shading by overstory trees. These results will help us to better understand water balances, evapotranspiration variability, and productivity changes associated with climate on understory vegetation. Additionally, our results will help understand how fire regime shifts may alter understory contributions to ecosystem evapotranspiration in Siberian larch forests.

Response of western mountain ecosystems to climatic variability and change: The Western Mountain Initiative

USGS Publications Warehouse

Stephenson, Nathan L.; Peterson, Dave; Fagre, Daniel B.; Allen, Craig D.; McKenzie, Donald; Baron, Jill S.; O'Brian, Kelly

2007-01-01

Mountain ecosystems within our national parks and other protected areas provide valuable goods and services such as clean water, biodiversity conservation, and recreational opportunities, but their potential responses to expected climatic changes are inadequately understood. The Western Mountain Initiative (WMI) is a collaboration of scientists whose research focuses on understanding and predicting responses of western mountain ecosystems to climatic variability and change. It is a legacy of the Global Change Research Program initiated by the National Park Service (NPS) in 1991 and continued by the U.S. Geological Survey (USGS) to this day as part of the U.S. Climate Change Science Program (http://www.climatescience.gov/). All WMI scientists are active participants in CIRMOUNT, and seek to further its goals.

From the Last Interglacial to the Anthropocene: Modelling a Complete Glacial Cycle (PalMod)

NASA Astrophysics Data System (ADS)

Brücher, Tim; Latif, Mojib

2017-04-01

We will give a short overview and update on the current status of the national climate modelling initiative PalMod (Paleo Modelling, www.palmod.de). PalMod focuses on the understanding of the climate system dynamics and its variability during the last glacial cycle. The initiative is funded by the German Federal Ministry of Education and Research (BMBF) and its specific topics are: (i) to identify and quantify the relative contributions of the fundamental processes which determined the Earth's climate trajectory and variability during the last glacial cycle, (ii) to simulate with comprehensive Earth System Models (ESMs) the climate from the peak of the last interglacial - the Eemian warm period - up to the present, including the changes in the spectrum of variability, and (iii) to assess possible future climate trajectories beyond this century during the next millennia with sophisticated ESMs tested in such a way. The research is intended to be conducted over a period of 10 years, but with shorter funding cycles. PalMod kicked off in February 2016. The first phase focuses on the last deglaciation (app. the last 23.000 years). From the ESM perspective PalMod pushes forward model development by coupling ESM with dynamical ice sheet models. Computer scientists work on speeding up climate models using different concepts (like parallelisation in time) and one working group is dedicated to perform a comprehensive data synthesis to validate model performance. The envisioned approach is innovative in three respects. First, the consortium aims at simulating a full glacial cycle in transient mode and with comprehensive ESMs which allow full interactions between the physical and biogeochemical components of the Earth system, including ice sheets. Second, we shall address climate variability during the last glacial cycle on a large range of time scales, from interannual to multi-millennial, and attempt to quantify the relative contributions of external forcing and processes internal to the Earth system to climate variability at different time scales. Third, in order to achieve a higher level of understanding of natural climate variability at time scales of millennia, its governing processes and implications for the future climate, we bring together three different research communities: the Earth system modeling community, the proxy data community and the computational science community. The consortium consists of 18 partners including all major modelling centers within Germany. The funding comprises approximately 65 PostDoc positions and more than 120 scientists are involved. PalMod is coordinated at the Helmholtz Centre for Ocean Research Kiel (GEOMAR).

Deploying temporary networks for upscaling of sparse network stations

USDA-ARS?s Scientific Manuscript database

Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, busin...

Climate change in the Brazilian northeast

NASA Astrophysics Data System (ADS)

Rodrigues, Regina R.; Haarsma, Reindert J.; Hoelzemann, Judith J.

2012-10-01

Climate Change, Impacts and Vulnerabilities in Brazil: Preparing the Brazilian Northeast for the Future; Natal, Brazil, 27 May to 01 June 2012 The variability of the semiarid climate of the Brazilian northeast has enormous environmental and social implications. Because most of the population in this area depends on subsistence agriculture, periods of severe drought in the past have caused extreme poverty and subsequent migration to urban centers. From the ecological point of view, frequent and prolonged droughts can lead to the desertification of large areas. Understanding the causes of rainfall variability, in particular periods of severe drought, is crucial for accurate forecasting, mitigation, and adaptation in this important region of Brazil.

An Integrated Hydro-Economic Model for Economy-Wide Climate Change Impact Assessment for Zambia

NASA Astrophysics Data System (ADS)

Zhu, T.; Thurlow, J.; Diao, X.

2008-12-01

Zambia is a landlocked country in Southern Africa, with a total population of about 11 million and a total area of about 752 thousand square kilometers. Agriculture in the country depends heavily on rainfall as the majority of cultivated land is rain-fed. Significant rainfall variability has been a huge challenge for the country to keep a sustainable agricultural growth, which is an important condition for the country to meet the United Nations Millennium Development Goals. The situation is expected to become even more complex as climate change would impose additional impacts on rainwater availability and crop water requirements, among other changes. To understand the impacts of climate variability and change on agricultural production and national economy, a soil hydrology model and a crop water production model are developed to simulate actual crop water uses and yield losses under water stress which provide annual shocks for a recursive dynamic computational general equilibrium (CGE) model developed for Zambia. Observed meteorological data of the past three decades are used in the integrated hydro-economic model for climate variability impact analysis, and as baseline climatology for climate change impact assessment together with several GCM-based climate change scenarios that cover a broad range of climate projections. We found that climate variability can explain a significant portion of the annual variations of agricultural production and GDP of Zambia in the past. Hidden beneath climate variability, climate change is found to have modest impacts on agriculture and national economy of Zambia around 2025 but the impacts would be pronounced in the far future if appropriate adaptations are not implemented. Policy recommendations are provided based on scenario analysis.

Paleoclimates: Understanding climate change past and present

USGS Publications Warehouse

Cronin, Thomas M.

2010-01-01

The field of paleoclimatology relies on physical, chemical, and biological proxies of past climate changes that have been preserved in natural archives such as glacial ice, tree rings, sediments, corals, and speleothems. Paleoclimate archives obtained through field investigations, ocean sediment coring expeditions, ice sheet coring programs, and other projects allow scientists to reconstruct climate change over much of earth's history. When combined with computer model simulations, paleoclimatic reconstructions are used to test hypotheses about the causes of climatic change, such as greenhouse gases, solar variability, earth's orbital variations, and hydrological, oceanic, and tectonic processes. This book is a comprehensive, state-of-the art synthesis of paleoclimate research covering all geological timescales, emphasizing topics that shed light on modern trends in the earth's climate. Thomas M. Cronin discusses recent discoveries about past periods of global warmth, changes in atmospheric greenhouse gas concentrations, abrupt climate and sea-level change, natural temperature variability, and other topics directly relevant to controversies over the causes and impacts of climate change. This text is geared toward advanced undergraduate and graduate students and researchers in geology, geography, biology, glaciology, oceanography, atmospheric sciences, and climate modeling, fields that contribute to paleoclimatology. This volume can also serve as a reference for those requiring a general background on natural climate variability.

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.

Collaborative Research: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic

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

Gutowski, William J.

This project developed and applied a regional Arctic System model for enhanced decadal predictions. It built on successful research by four of the current PIs with support from the DOE Climate Change Prediction Program, which has resulted in the development of a fully coupled Regional Arctic Climate Model (RACM) consisting of atmosphere, land-hydrology, ocean and sea ice components. An expanded RACM, a Regional Arctic System Model (RASM), has been set up to include ice sheets, ice caps, mountain glaciers, and dynamic vegetation to allow investigation of coupled physical processes responsible for decadal-scale climate change and variability in the Arctic. RASMmore » can have high spatial resolution (~4-20 times higher than currently practical in global models) to advance modeling of critical processes and determine the need for their explicit representation in Global Earth System Models (GESMs). The pan-Arctic region is a key indicator of the state of global climate through polar amplification. However, a system-level understanding of critical arctic processes and feedbacks needs further development. Rapid climate change has occurred in a number of Arctic System components during the past few decades, including retreat of the perennial sea ice cover, increased surface melting of the Greenland ice sheet, acceleration and thinning of outlet glaciers, reduced snow cover, thawing permafrost, and shifts in vegetation. Such changes could have significant ramifications for global sea level, the ocean thermohaline circulation and heat budget, ecosystems, native communities, natural resource exploration, and commercial transportation. The overarching goal of the RASM project has been to advance understanding of past and present states of arctic climate and to improve seasonal to decadal predictions. To do this the project has focused on variability and long-term change of energy and freshwater flows through the arctic climate system. The three foci of this research are: - Changes in the freshwater flux between arctic climate system components resulting from decadal changes in land and sea ice, seasonal snow, vegetation, and ocean circulation. - Changing energetics due to decadal changes in ice mass, vegetation, and air-sea interactions. - The role of small-scale atmospheric and oceanic processes that influence decadal variability. This research has been addressing modes of natural climate variability as well as extreme and rapid climate change. RASM can facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts.« less

Improving preparedness of farmers to Climate Variability: A case study of Vidarbha region of Maharashtra, India

NASA Astrophysics Data System (ADS)

Swami, D.; Parthasarathy, D.; Dave, P.

2016-12-01

A key objective of the ongoing research is to understand the risk and vulnerability of agriculture and farming communities with respect to multiple climate change attributes, particularly monsoon variability and hydrology such as ground water availability. Climate Variability has always been a feature affecting Indian agriculture but the nature and characteristics of this variability is not well understood. Indian monsoon patterns are highly variable and most of the studies focus on larger domain such as Central India or Western coast (Ghosh et al., 2009) but district level analysis is missing i.e. the linkage between agriculture and climate variables at finer scale has not been investigated comprehensively. For example, Eastern Vidarbha region in Maharashtra is considered as one of the most agriculturally sensitive region in India, where every year a large number of farmers commit suicide. The main reasons for large number of suicides are climate related stressors such as droughts, hail storms, and monsoon variability aggravated with poor socio-economic conditions. Present study has tried to explore the areas in Vidarbha region of Maharashtra where famers and crop productivity, specifically cotton, sorghum, is highly vulnerable to monsoon variability, hydrological and socio-economic variables which are further modelled to determine the maximal contributing factor towards crops and farmers' vulnerability. After analysis using primary and secondary data, it will aid in decision making regarding field operations such as time of sowing, harvesting and irrigation requirements by optimizing the cropping pattern with climatic, hydrological and socio-economic variables. It also suggests the adaptation strategies to farmers regarding different types of cropping and water harvesting practices, optimized dates and timings for harvesting, sowing, water and nutrient requirements of particular crops according to the specific region. Primarily along with secondary analysis captured here can be highly beneficial for the farmers and policy makers while formulating agricultural policies related to climate change.

Assessing the role of internal climate variability in Antarctica's contribution to future sea-level rise

NASA Astrophysics Data System (ADS)

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

2017-12-01

The Antarctic ice sheet (AIS) has the potential to be a major contributor to future sea-level rise (SLR). Current projections of SLR due to AIS mass loss remain highly uncertain. Better understanding of how ice sheets respond to future climate forcing and variability is essential for assessing the long-term risk of SLR. However, the predictability of future climate is limited by uncertainties from emission scenarios, model structural differences, and the internal variability that is inherently generated within the fully coupled climate system. Among those uncertainties, the impact of internal variability on the AIS changes has not been explicitly assessed. In this study, we quantify the effect of internal variability on the AIS evolutions by using climate fields from two large-ensemble experiments using the Community Earth System Model to force a three-dimensional ice sheet model. We find that internal variability of climate fields, particularly atmospheric fields, among ensemble members leads to significantly different AIS responses. Our results show that the internal variability can cause about 80 mm differences of AIS contribution to SLR by 2100 compared to the ensemble-mean contribution of 380-450 mm. Moreover, using ensemble-mean climate fields as the forcing in the ice sheet model does not produce realistic simulations of the ice loss. Instead, it significantly delays the onset of retreat of the West Antarctic Ice Sheet for up to 20 years and significantly underestimates the AIS contribution to SLR by 0.07-0.11 m in 2100 and up to 0.34 m in the 2250's. Therefore, because the uncertainty caused by internal variability is irreducible, we seek to highlight a critical need to assess the role of internal variability in projecting the AIS loss over the next few centuries. By quantifying the impact of internal variability on AIS contribution to SLR, policy makers can obtain more robust estimates of SLR and implement suitable adaptation strategies.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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

PubMed

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

2015-01-15

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Climate 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.

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

PubMed

Bonebrake, Timothy C; Mastrandrea, Michael D

2010-07-13

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

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.

Atmospheric River Characteristics under Decadal Climate Variability

NASA Astrophysics Data System (ADS)

Done, J.; Ge, M.

2017-12-01

How does decadal climate variability change the nature and predictability of atmospheric river events? Decadal swings in atmospheric river frequency, or shifts in the proportion of precipitation falling as rain, could challenge current water resource and flood risk management practice. Physical multi-scale processes operating between Pacific sea surface temperatures (SSTs) and atmospheric rivers over the Western U.S. are explored using the global Model for Prediction Across Scales (MPAS). A 45km global mesh is refined over the Western U.S. to 12km to capture the major terrain effects on precipitation. The performance of the MPAS is first evaluated for a case study atmospheric river event over California. Atmospheric river characteristics are then compared in a pair of idealized simulations, each driven by Pacific SST patterns characteristic of opposite phases of the Interdecadal Pacific Oscillation (IPO). Given recent evidence that we have entered a positive phase of the IPO, implications for current reservoir management practice over the next decade will be discussed. This work contributes to the NSF-funded project UDECIDE (Understanding Decision-Climate Interactions on Decadal Scales). UDECIDE brings together practitioners, engineers, statisticians, and climate scientists to understand the role of decadal climate information for water management and decisions.

It's a Sooty Problem: Black Carbon and Aerosols from Space

NASA Technical Reports Server (NTRS)

Kaufman, Yoram J.

2005-01-01

Our knowledge of atmospheric aerosols (smoke, pollution, dust or sea salt particles, small enough to be suspended in the air), their evolution, composition, variability in space and time and interaction with solar radiation, clouds and precipitation is lacking despite decades of research. Just recently we recognized that understanding the global aerosol system is fundamental for progress in climate change and hydrological cycle research. While a single instrument was used to demonstrate 50 yrs ago that the global CO2 levels are rising, posing thread to our climate, we need an may of satellites, surface networks of radiometers, elaborated laboratory and field experiments coupled with chemical transport models to understand the global aerosol system. This complexity of the aerosol problem results from their short lifetime (1 week), variability of the chemical composition and complex chemical and physical processes in the atmosphere. The result is a heterogeneous distribution of aerosol and their properties. The new generation of satellites and surface networks of radiometers provides exciting opportunities to measure the aerosol properties and their interaction with clouds and climate. However farther development in the satellite capability, aerosol chemical models and climate models is needed to fully decipher the aerosol secrets with accuracy required to predict future climates.

Climatic Variability Leads to Later Seasonal Flowering of Floridian Plants

PubMed Central

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

2010-01-01

Understanding species responses to global change will help predict shifts in species distributions as well as aid in conservation. Changes in the timing of seasonal activities of organisms over time may be the most responsive and easily observable indicator of environmental changes associated with global climate change. It is unknown how global climate change will affect species distributions and developmental events in subtropical ecosystems or if climate change will differentially favor nonnative species. Contrary to previously observed trends for earlier flowering onset of plant species with increasing spring temperatures from mid and higher latitudes, we document a trend for delayed seasonal flowering among plants in Florida. Additionally, there were few differences in reproductive responses by native and nonnative species to climatic changes. We argue that plants in Florida have different reproductive cues than those from more northern climates. With global change, minimum temperatures have become more variable within the temperate-subtropical zone that occurs across the peninsula and this variation is strongly associated with delayed flowering among Florida plants. Our data suggest that climate change varies by region and season and is not a simple case of species responding to consistently increasing temperatures across the region. Research on climate change impacts need to be extended outside of the heavily studied higher latitudes to include subtropical and tropical systems in order to properly understand the complexity of regional and seasonal differences of climate change on species responses. PMID:20657765

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

Demographic consequences of climate change and land cover help explain a history of extirpations and range contraction in a declining snake species.

PubMed

Pomara, Lars Y; LeDee, Olivia E; Martin, Karl J; Zuckerberg, Benjamin

2014-07-01

Developing conservation strategies for threatened species increasingly requires understanding vulnerabilities to climate change, in terms of both demographic sensitivities to climatic and other environmental factors, and exposure to variability in those factors over time and space. We conducted a range-wide, spatially explicit climate change vulnerability assessment for Eastern Massasauga (Sistrurus catenatus), a declining endemic species in a region showing strong environmental change. Using active season and winter adult survival estimates derived from 17 data sets throughout the species' range, we identified demographic sensitivities to winter drought, maximum precipitation during the summer, and the proportion of the surrounding landscape dominated by agricultural and urban land cover. Each of these factors was negatively associated with active season adult survival rates in binomial generalized linear models. We then used these relationships to back-cast adult survival with dynamic climate variables from 1950 to 2008 using spatially explicit demographic models. Demographic models for 189 population locations predicted known extant and extirpated populations well (AUC = 0.75), and models based on climate and land cover variables were superior to models incorporating either of those effects independently. These results suggest that increasing frequencies and severities of extreme events, including drought and flooding, have been important drivers of the long-term spatiotemporal variation in a demographic rate. We provide evidence that this variation reflects nonadaptive sensitivity to climatic stressors, which are contributing to long-term demographic decline and range contraction for a species of high-conservation concern. Range-wide demographic modeling facilitated an understanding of spatial shifts in climatic suitability and exposure, allowing the identification of important climate refugia for a dispersal-limited species. Climate change vulnerability assessment provides a framework for linking demographic and distributional dynamics to environmental change, and can thereby provide unique information for conservation planning and management. © 2013 John Wiley & Sons Ltd.

Using Time Series of Landsat Data to Improve Understanding of Short- and Long-Term Changes to Vegetation Phenology in Response to Climate Change

NASA Astrophysics Data System (ADS)

Friedl, M. A.; Melaas, E. K.; Sulla-menashe, D. J.; Gray, J. M.

2014-12-01

Phenology, the seasonal progression of organisms through stages of dormancy, active growth, and senescence is a key regulator of ecosystem processes and is widely used as an indicator of vegetation responses to climate change. This is especially true in temperate forests, where seasonal dynamics in canopy development and senescence are tightly coupled to the climate system. Despite this, understanding of climate-phenology interactions is incomplete. A key impediment to improving this understanding is that available datasets are geographically sparse, and in most cases include relatively short time series. Remote sensing has been widely promoted as a useful tool for studies of large-scale phenology, but long-term studies from remote sensing have been limited to AVHRR data, which suffers from limitations related to its coarse spatial resolution and uncertainties in atmospheric corrections and radiometric adjustments that are used to create AVHRR time series. In this study, we used 30 years of Landsat data to quantify the nature and magnitude of long-term trends and short-term variability in the timing of spring leaf emergence and fall senescence. Our analysis focuses on temperate forest locations in the Northeastern United States that are co-located with surface meteorological observations, where we have estimated the timing of leaf emergence and leaf senescence at annual time steps using atmospherically corrected surface reflectances from Landsat TM and ETM+ imagery. Comparison of results from Landsat against ground observations demonstrates that phenological events can be reliably estimated from Landsat time series. More importantly, results from this analysis suggest two main conclusions related to the nature of climate change impacts on temperate forest phenology. First, there is clear evidence of trends towards longer growing seasons in the Landsat record. Second, interannual variability is large, with average year-to-year variability exceeding the magnitude of total changes to the growing season that have occurred over the last three decades. Based on these results we suggest that year-to-year variability in phenology, rather than long-term trends, provides the best basis for predicting future changes in temperate forest phenology in response to climate change.

How does complex terrain influence responses of carbon and water cycle processes to climate variability and climate change? (Invited)

NASA Astrophysics Data System (ADS)

Bond, B. J.; Peterson, K.; McKane, R.; Lajtha, K.; Quandt, D. J.; Allen, S. T.; Sell, S.; Daly, C.; Harmon, M. E.; Johnson, S. L.; Spies, T.; Sollins, P.; Abdelnour, A. G.; Stieglitz, M.

2010-12-01

We are pursuing the ambitious goal of understanding how complex terrain influences the responses of carbon and water cycle processes to climate variability and climate change. Our studies take place in H.J. Andrews Experimental Forest, an LTER (Long Term Ecological Research) site situated in Oregon’s central-western Cascade Range. Decades of long-term measurements and intensive research have revealed influences of topography on vegetation patterns, disturbance history, and hydrology. More recent research has shown surprising interactions between microclimates and synoptic weather patterns due to cold air drainage and pooling in mountain valleys. Using these data and insights, in addition to a recent LiDAR (Light Detection and Ranging) reconnaissance and a small sensor network, we are employing process-based models, including “SPA” (Soil-Plant-Atmosphere, developed by Mathew Williams of the University of Edinburgh), and “VELMA” (Visualizing Ecosystems for Land Management Alternatives, developed by Marc Stieglitz and colleagues of the Georgia Institute of Technology) to focus on two important features of mountainous landscapes: heterogeneity (both spatial and temporal) and connectivity (atmosphere-canopy-hillslope-stream). Our research questions include: 1) Do fine-scale spatial and temporal heterogeneity result in emergent properties at the basin scale, and if so, what are they? 2) How does connectivity across ecosystem components affect system responses to climate variability and change? Initial results show that for environmental drivers that elicit non-linear ecosystem responses on the plot scale, such as solar radiation, soil depth and soil water content, fine-scale spatial heterogeneity may produce unexpected emergent properties at larger scales. The results from such modeling experiments are necessarily a function of the supporting algorithms. However, comparisons based on models such as SPA and VELMA that operate at much different spatial scales (plots vs. hillslopes) and levels of biophysical organization (individual plants vs. aggregate plant biomass) can help us to understand how and why mountainous ecosystems may have distinctive responses to climate variability and climate change.

Climate variability controls on unsaturated water and chemical movement, High Plains aquifer, USA

USGS Publications Warehouse

Gurdak, J.J.; Hanson, R.T.; McMahon, P.B.; Bruce, B.W.; McCray, J.E.; Thyne, G.D.; Reedy, R.C.

2007-01-01

Responses in the vadose zone and groundwater to interannual, interdecadal, and multidecadal climate variability have important implications for groundwater resource sustainability, yet they are poorly documented and not well understood in most aquifers of the USA. This investigation systematically examines the role of interannual to multidecadal climate variability on groundwater levels, deep infiltration (3-23 m) events, and downward displacement (>1 m) of chloride and nitrate reservoirs in thick (15-50 m) vadose zones across the regionally extensive High Plains aquifer. Such vadose zone responses are unexpected across much of the aquifer given a priori that unsaturated total-potential profiles indicate upward water movement from the water table toward the root zone, mean annual potential evapotranspiration exceeds mean annual precipitation, and millennia-scale evapoconcentration results in substantial vadose zone chloride and nitrate reservoirs. Using singular spectrum analysis (SSA) to reconstruct precipitation and groundwater level time-series components, variability was identified in all time series as partially coincident with known climate cycles, such as the Pacific Decadal Oscillation (PDO) (10-25 yr) and the El Nin??o/Southern Oscillation (ENSO) (2-6 yr). Using these lag-correlated hydrologic time series, a new method is demonstrated to estimate climate-varying unsaturated water flux. The results suggest the importance of interannual to interdecadal climate variability on water-flux estimation in thick vadose zones and provide better understanding of the climate-induced transients responsible for the observed deep infiltration and chemical-mobilization events. Based on these results, we discuss implications for climate-related sustainability of the High Plains aquifer. ?? Soil Science Society of America.

Analysis of shifts in the spatial distribution of vegetation due to climate change

NASA Astrophysics Data System (ADS)

del Jesus, Manuel; Díez-Sierra, Javier; Rinaldo, Andrea; Rodríguez-Iturbe, Ignacio

2017-04-01

Climate change will modify the statistical regime of most climatological variables, inducing changes on average values and in the natural variability of environmental variables. These environmental variables may be used to explain the spatial distribution of functional types of vegetation in arid and semiarid watersheds through the use of plant optimization theories. Therefore, plant optimization theories may be used to approximate the response of the spatial distribution of vegetation to a changing climate. Predicting changes in these spatial distributions is important to understand how climate change may affect vegetated ecosystems, but it is also important for hydrological engineering applications where climate change effects on water availability are assessed. In this work, Maximum Entropy Production (MEP) is used as the plant optimization theory that describes the spatial distribution of functional types of vegetation. Current climatological conditions are obtained from direct observations from meteorological stations. Climate change effects are evaluated for different temporal horizons and different climate change scenarios using numerical model outputs from the CMIP5. Rainfall estimates are downscaled by means of a stochastic point process used to model rainfall. The study is carried out for the Rio Salado watershed, located within the Sevilleta LTER site, in New Mexico (USA). Results show the expected changes in the spatial distribution of vegetation and allow to evaluate the expected variability of the changes. The updated spatial distributions allow to evaluate the vegetated ecosystem health and its updated resilience. These results can then be used to inform the hydrological modeling part of climate change assessments analyzing water availability in arid and semiarid watersheds.

Forest cover change, climate variability, and hydrological responses

Treesearch

Xiaohua Wei; Rita Winkler; Ge Sun

2017-01-01

Understanding ecohydrological response to environmental change is critical for protecting watershed functions, sustaining clean water supply, and other ecosystem services, safeguarding public safety, floods mitigation, and drought response. Understanding ecohyhdrological processes and their implications to forest and water management has become increasingly important...

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.

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

Does an understanding of ecosystems responses to rainfall pulses improve predictions of responses of drylands to climate change?

USDA-ARS?s Scientific Manuscript database

Drylands will experience more intense and frequent droughts and floods. Ten-year field experiments manipulating the amount and variability of precipitation suggest that we cannot predict responses of drylands to climate change based on pulse experimentation. Long-term drought experiments showed no e...

Differential responses of carbon and water vapor fluxes to climate among evergreen needleleaf forests in the USA

USDA-ARS?s Scientific Manuscript database

Understanding of differences in carbon and water vapor fluxes of spatially distributed evergreen needle leaf forests (ENFs) is crucial to accurately estimating regional carbon and water budgets and when predicting the responses of ENFs to future climate. We investigated cross-site variability in car...

The PAGES 2k Network, Phase 3: Themes and Call for Participation

NASA Astrophysics Data System (ADS)

von Gunten, L.; Mcgregor, H. V.; Martrat, B.; St George, S.; Neukom, R.; Bothe, O.; Linderholm, H. W.; Phipps, S. J.; Abram, N.

2017-12-01

The past 2000 years (the "2k" interval) provides critical context for understanding recent anthropogenic forcing of the climate and provides baseline information about the characteristics of natural climate variability. It also presents opportunities to improve the interpretation of proxy observations and to evaluate the climate models used to make future projections. Phases 1 and 2 of the PAGES 2k Network focussed on building regional and global surface temperature reconstructions for terrestrial regions and the oceans, and comparing these with model simulations to identify mechanisms of climate variation on interannual to bicentennial time scales. Phase 3 was launched in May 2017 and aims to address major questions around past hydroclimate, climate processes and proxy uncertainties. Its scientific themes are: Theme 1: "Climate Variability, Modes and Mechanisms"Further understand the mechanisms driving regional climate variability and change on interannual to centennial time scales; Theme 2: "Methods and Uncertainties"Reduce uncertainties in the interpretation of observations imprinted in paleoclimatic archives by environmental sensors; Theme 3: "Proxy and Model Understanding"Identify and analyse the extent of agreement between reconstructions and climate model simulations. Research is organized as a linked network of well-defined projects, identified and led by 2k community members. The 2k projects focus on specific scientific questions aligned with Phase 3 themes, rather than being defined along regional boundaries. New 2k projects can be proposed at any time at http://www.pastglobalchanges.org/ini/wg/2k-network/projects An enduring element of PAGES 2k is a culture of collegiality, transparency, and reciprocity. Phase 3 seeks to stimulate community based projects and facilitate collaboration between researchers from different regions and career stages, drawing on the breadth and depth of the global PAGES 2k community. All PAGES 2k projects also promote best practises in data stewardship for the research community. The network is open to anyone who is interested. If you would like to participate in PAGES 2k or receive updates, please join our mailing list or speak to a coordinating committee member.

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.

Characteristics, processes, and causes of the spatio-temporal variabilities of the East Asian monsoon system

NASA Astrophysics Data System (ADS)

Huang, Ronghui; Chen, Jilong; Wang, Lin; Lin, Zhongda

2012-09-01

Recent advances in the study of the characteristics, processes, and causes of spatio-temporal variabilities of the East Asian monsoon (EAM) system are reviewed in this paper. The understanding of the EAM system has improved in many aspects: the basic characteristics of horizontal and vertical structures, the annual cycle of the East Asian summer monsoon (EASM) system and the East Asian winter monsoon (EAWM) system, the characteristics of the spatio-temporal variabilities of the EASM system and the EAWM system, and especially the multiple modes of the EAM system and their spatio-temporal variabilities. Some new results have also been achieved in understanding the atmosphere-ocean interaction and atmosphere-land interaction processes that affect the variability of the EAM system. Based on recent studies, the EAM system can be seen as more than a circulation system, it can be viewed as an atmosphere-ocean-land coupled system, namely, the EAM climate system. In addition, further progress has been made in diagnosing the internal physical mechanisms of EAM climate system variability, especially regarding the characteristics and properties of the East Asia-Pacific (EAP) teleconnection over East Asia and the North Pacific, the "Silk Road" teleconnection along the westerly jet stream in the upper troposphere over the Asian continent, and the dynamical effects of quasi-stationary planetary wave activity on EAM system variability. At the end of the paper, some scientific problems regarding understanding the EAM system variability are proposed for further study.

Hydro-climatic control of stream water dissolved organic carbon (DOC) across northern catchments within the North-Watch program

NASA Astrophysics Data System (ADS)

Laudon, Hjalmar; Tetzlaff, Doerthe; Seibert, Jan; Soulsby, Chris; Carey, Sean; Buttle, Jim; McDonnell, Jeff; McGuire, Kevin; Caissie, Daniel; Shanley, Jamie

2010-05-01

There has been an increasing interest in understanding the regulating mechanisms of surface water dissolved organic carbon (DOC) the last decade. A majority of this recent work has been based on individual well characterized research catchments or on regional synoptic datasets combined with readily available landscape and climatic variables. However, as the production and transport of DOC primarily is a function of hydro-climatic conditions a better description of catchment hydrological functioning across large geographic regions would be favorable for moving the mechanistic understanding forward. To do this we report from a first assessment of catchment DOC within the international inter-catchment comparison program North-Watch (http://www.abdn.ac.uk/northwatch/). North-Watch includes long-term research catchments ranging from northern temperate regions to the boreal and sub-arctic biomes with the aim to better understand the variable hydrological and biogeochemical responses in Northern catchments to climate change. The North-Watch catchments are located in Sweden (Krycklan), Scotland (Mharcaidh, Girnock and Strontian), the US (Sleepers River and HJ Andrews) and Canada (Catamaran, Dorset and Wolf Creek). The annual average DOC concentration in the nine catchments investigated were directly linked to hydro-climatic influences (e.g. temperature, water storage) and landscape configuration. In general, the DOC concentration followed a parabolic shape with temperature, where the highest concentrations were found in the boreal and near boreal sites and with the lowest concentrations in the temperate and sub-arctic catchments. The between catchment variability in DOC concentration could also be explained by catchment water storage and amount of wetlands in the catchment. Whereas there is a mechanistic link between long-term climatic conditions and the areal coverage of wetlands, the total catchment storage of water is more strongly linked to topography, parent material and soil depth. The result from this analysis will serve as a conceptual framework for understanding biogeochemical response to environmental change across northern catchments. The next step in this work will be to include more detailed comparisons of the role catchment hydrological functioning for explaining the patterns and dynamics of catchment DOC of these northern watersheds.

Rapid climate fluctuations over the past millennium: evidence from a lacustrine record of Basomtso Lake, southeastern Tibetan Plateau

PubMed Central

Li, Kai; Liu, Xingqi; Herzschuh, Ulrike; Wang, Yongbo

2016-01-01

Abrupt climate changes and fluctuations over short time scales are superimposed on long-term climate changes. Understanding rapid climate fluctuations at the decadal time scale over the past millennium will enhance our understanding of patterns of climate variability and aid in forecasting climate changes in the future. In this study, climate changes on the southeastern Tibetan Plateau over the past millennium were determined from a 4.82-m-long sediment core from Basomtso Lake. At the centennial time scale, the Medieval Climate Anomaly (MCA), Little Ice Age (LIA) and Current Warm Period (CWP) are distinct in the Basomtso region. Rapid climate fluctuations inferred from five episodes with higher sediment input and likely warmer conditions, as well as seven episodes with lower sediment input and likely colder conditions, were well preserved in our record. These episodes with higher and lower sediment input are characterized by abrupt climate changes and short time durations. Spectral analysis indicates that the climate variations at the centennial scale on the southeastern Tibetan Plateau are influenced by solar activity during the past millennium. PMID:27091591

Contrasting scaling properties of interglacial and glacial climates

PubMed Central

Shao, Zhi-Gang; Ditlevsen, Peter D.

2016-01-01

Understanding natural climate variability is essential for assessments of climate change. This is reflected in the scaling properties of climate records. The scaling exponents of the interglacial and the glacial climates are fundamentally different. The Holocene record is monofractal, with a scaling exponent H∼0.7. On the contrary, the glacial record is multifractal, with a significantly higher scaling exponent H∼1.2, indicating a longer persistence time and stronger nonlinearities in the glacial climate. The glacial climate is dominated by the strong multi-millennial Dansgaard–Oeschger (DO) events influencing the long-time correlation. However, by separately analysing the last glacial maximum lacking DO events, here we find the same scaling for that period as for the full glacial period. The unbroken scaling thus indicates that the DO events are part of the natural variability and not externally triggered. At glacial time scales, there is a scale break to a trivial scaling, contrasting the DO events from the similarly saw-tooth-shaped glacial cycles. PMID:26980084

Stable oxygen and carbon isotope characteristics in speleothems from Southern Africa - how good are they?

NASA Astrophysics Data System (ADS)

Holmgren, K.

2009-04-01

Much remains to be understood about the interaction between the African climate system, its surrounding ocean-atmosphere climate variability and the global climate system. A better understanding of the regional climate evolution is crucial for understanding global climate dynamics and issues surrounding environmental change throughout Africa and a prerequisite for increasing climate forecasting capabilities for the region. As part of developing this understanding, a longer term perspective that reaches beyond the information available from instrumental records is required. Speleothems are frequently abundant in southern Africa. Quite a few records are now available, reporting significant changes in climate and environmental conditions over longer and shorter time scales. Conclusions are mainly based on the stable isotopic composition of the speleothems. The interpretation of the stable isotope data is, however, not always straight-forward, since many processes contribute to the observed signal in the speleothem and these processes may influence the signal differently at different spatial and temporal scales. For example was the Makapansgat speleothem oxygen isotope record, originally interpreted as being generally determined by shifts in atmospheric circulation pattern (Lee-Thorp et al. 2001, Holmgren et al. 2003), recently challenged and re-interpreted by Partin et al. (2008) to reflect annual rainfall amounts. Historically, less attention has been paid to the stable carbon isotope composition in speleothems. Today, an increasing number of studies demonstrate the potential of stable carbon variations as providing additional information on climate and environment. Measured variations can be a function of the amount of C3 versus C4 vegetation, vegetation cover and soil biological activity, bedrock proportion, rainfall amount and the drip rate. Clearly the multitudes of plausible processes behind the isotopic composition of speleothems in southern Africa (as well as elsewhere) are a challenge to firm conclusions. However, the need for more globally well dispersed terrestrial palaeoclimatic records; the strong advantages of speleothems to provide precise ages and the empirical experience of successful solutions in previous speleothem research, encourage us to continue research on speleothems from southern Africa. If the understanding of the forcing mechanisms behind measured variables in speleothems can be increased, then there is a great potential for retrieving good climate records from the sub-continent, since the availability of caves containing speleothems is fairly frequent. Available speleothem research from southern Africa will be summarised and potentials and constraints will be discussed. References: Holmgren, K., Lee-Thorp, J.A., Cooper, G.J., Lundblad, K., Partridge, T.C., Scott, L., Sithaldeen, R., Talma, A.S. and Tyson, P.D. 2003: Persistent Millennial-Scale Climatic Variability over the Past 25 thousand Years in Southern Africa. Quaternary Science Reviews, 22, 2311-2326. Lee-Thorp, J.A., Holmgren, K., S.E. Lauritzen, Linge, H., Moberg, A., Partridge, T.C., Stevenson, C. and Tyson P., 2001: Rapid climate shifts in the southern African interior throughout the mid to late Holocene. Geophysical Research Letters 28, 4507-4510. Partin, J.W., Cobb, K.M. and Banner, J.L. 2008: Climate variability recorded in tropical and sub-tropical speleothems. PAGES news, 16, 3, p. 9-10.

Groundwater level responses to precipitation variability in Mediterranean insular aquifers

NASA Astrophysics Data System (ADS)

Lorenzo-Lacruz, Jorge; Garcia, Celso; Morán-Tejeda, Enrique

2017-09-01

Groundwater is one of the largest and most important sources of fresh water on many regions under Mediterranean climate conditions, which are exposed to large precipitation variability that includes frequent meteorological drought episodes, and present high evapotranspiration rates and water demand during the dry season. The dependence on groundwater increases in those areas with predominant permeable lithologies, contributing to aquifer recharge and the abundance of ephemeral streams. The increasing pressure of tourism on water resources in many Mediterranean coastal areas, and uncertainty related to future precipitation and water availability, make it urgent to understand the spatio-temporal response of groundwater bodies to precipitation variability, if sustainable use of the resource is to be achieved. We present an assessment of the response of aquifers to precipitation variability based on correlations between the Standardized Precipitation Index (SPI) at various time scales and the Standardized Groundwater Index (SGI) across a Mediterranean island. We detected three main responses of aquifers to accumulated precipitation anomalies: (i) at short time scales of the SPI (<6 months); (ii) at medium time scales (6-24 months); and at long time scales (>24 months). The differing responses were mainly explained by differences in lithology and the percentage of highly permeable rock strata in the aquifer recharge areas. We also identified differences in the months and seasons when aquifer storages are more dependent on precipitation; these were related to climate seasonality and the degree of aquifer exploitation or underground water extraction. The recharge of some aquifers, especially in mountainous areas, is related to precipitation variability within a limited spatial extent, whereas for aquifers located in the plains, precipitation variability influence much larger areas; the topography and geological structure of the island explain these differences. Results indicate large spatial variability in the response of aquifers to precipitation in a very small area, highlighting the importance of having high spatial resolution hydro-climatic databases available to enable full understanding of the effects of climate variability on scarce water resources.

The influence of lithology on surface water sources

EPA Science Inventory

Understanding the temporal and spatial variability of surface water sources within a basin is vital to our ability to manage the impacts of climate variability and land cover change. Water stable isotopes can be used as a tool to determine geographic and seasonal sources of water...

Impacts of temperature and its variability on mortality in New England

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

Building Training Curricula for Accelerating the Use of NOAA Climate Products and Tools

NASA Astrophysics Data System (ADS)

Timofeyeva-Livezey, M. M.; Meyers, J. C.; Stevermer, A.; Abshire, W. E.; Beller-Simms, N.; Herring, D.

2016-12-01

The National Oceanic and Atmospheric Administration (NOAA) plays a leading role in U.S. intergovernmental efforts on the Climate Data Initiative and the Climate Resilience Toolkit (CRT). CRT (http://toolkit.climate.gov/) is a valuable resource that provides tools, information, and subject matter expertise to decision makers in various sectors, such as agriculture, water resources and transportation, to help them build resilience to our changing climate. In order to make best use of the toolkit and all the resources within it, a training component is critical. The training section helps building users' understanding of the data, science, and impacts of climate variability and change. CRT identifies five steps in building resilience that includes use of appropriate tools to support decision makers depending on their needs. One tool that can be potentially integrated into CRT is NOAA's Local Climate Analysis Tool (LCAT), which provides access to trusted NOAA data and scientifically-sound analysis techniques for doing regional and local climate studies on climate variability and climate change. However, in order for LCAT to be used effectively, we have found an iterative learning approach using specific examples to train users. For example, for LCAT application in analysis of water resources, we use existing CRT case studies for Arizona and Florida water supply users. The Florida example demonstrates primary sensitivity to climate variability impacts, whereas the Arizona example takes into account longer- term climate change. The types of analyses included in LCAT are time series analysis of local climate and the estimated rate of change in the local climate. It also provides a composite analysis to evaluate the relationship between local climate and climate variability events such as El Niño Southern Oscillation, the Pacific North American Index, and other modes of climate variability. This paper will describe the development of a training module for use of LCAT and its integration into CRT. An iterative approach was used that incorporates specific examples of decision making while working with subject matter experts within the water supply community. The recommended strategy is to use a "stepping stone" learning structure to build users knowledge of best practices for use of LCAT.

Uncertainties in Past and Future Global Water Availability

NASA Astrophysics Data System (ADS)

Sheffield, J.; Kam, J.

2014-12-01

Understanding how water availability changes on inter-annual to decadal time scales and how it may change in the future under climate change are a key part of understanding future stresses on water and food security. Historic evaluations of water availability on regional to global scales are generally based on large-scale model simulations with their associated uncertainties, in particular for long-term changes. Uncertainties are due to model errors and missing processes, parameter uncertainty, and errors in meteorological forcing data. Recent multi-model inter-comparisons and impact studies have highlighted large differences for past reconstructions, due to different simplifying assumptions in the models or the inclusion of physical processes such as CO2 fertilization. Modeling of direct anthropogenic factors such as water and land management also carry large uncertainties in their physical representation and from lack of socio-economic data. Furthermore, there is little understanding of the impact of uncertainties in the meteorological forcings that underpin these historic simulations. Similarly, future changes in water availability are highly uncertain due to climate model diversity, natural variability and scenario uncertainty, each of which dominates at different time scales. In particular, natural climate variability is expected to dominate any externally forced signal over the next several decades. We present results from multi-land surface model simulations of the historic global availability of water in the context of natural variability (droughts) and long-term changes (drying). The simulations take into account the impact of uncertainties in the meteorological forcings and the incorporation of water management in the form of reservoirs and irrigation. The results indicate that model uncertainty is important for short-term drought events, and forcing uncertainty is particularly important for long-term changes, especially uncertainty in precipitation due to reduced gauge density in recent years. We also discuss uncertainties in future projections from these models as driven by bias-corrected and downscaled CMIP5 climate projections, in the context of the balance between climate model robustness and climate model diversity.

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

PubMed

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

2013-01-01

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

The ARGO Project: Global Ocean Observations for Understanding and Prediction of Climate Variability. Report for Calendar Year 2004

DTIC Science & Technology

2004-01-01

international Argo practices. Data appropriate for research applications and for comparison with climate change models are not available for several...global ocean heat and fresh water storage and the detection and attribution of climate change . These presentations can be accessed at http...stresses on ocean ecosystems have serious consequences, and sometimes dramatic ones, such as coral reef bleaching . In the future, the impacts of a

Past crops yield dynamics reconstruction from tree-ring chronologies in the forest-steppe zone based on low- and high-frequency components

NASA Astrophysics Data System (ADS)

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

2018-05-01

Interrelations of the yield variability of the main crops (wheat, barley, and oats) with hydrothermal regime and growth of conifer trees ( Pinus sylvestris and Larix sibirica) in forest-steppes were investigated in Khakassia, South Siberia. An attempt has been made to understand the role and mechanisms of climatic impact on plants productivity. It was found that amongst variables describing moisture supply, wetness index had maximum impact. Strength of climatic response and correlations with tree growth are different for rain-fed and irrigated crops yield. Separated high-frequency variability components of yield and tree-ring width have more pronounced relationships between each other and with climatic variables than their chronologies per se. Corresponding low-frequency variability components are strongly correlated with maxima observed after 1- to 5-year time shift of tree-ring width. Results of analysis allowed us to develop original approach of crops yield dynamics reconstruction on the base of high-frequency variability component of the growth of pine and low-frequency one of larch.

Regional changes in extreme monsoon rainfall deficit and excess in India

NASA Astrophysics Data System (ADS)

Pal, Indrani; Al-Tabbaa, Abir

2010-04-01

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

Where the Rubber Hits the Road: The Politics and Science of Climate Change in Congress

NASA Astrophysics Data System (ADS)

Koppes, M.

2004-12-01

Scientific understanding of the magnitude and rate of global and regional climate change is being actively communicated to Capitol Hill, however this information is being framed within the political debate that has brought climate change policy in the U.S. to a practical standstill. Efforts by scientists to communicate to Congress advances in the understanding of climate change have been obscured by policy-makers, lobbyists and some scientists themselves, into two polarized camps: those that who claim that current climate change is insignificant and/or of non-anthropogenic origin, and those who predict irreversible climate change in the near future and advocate a precautionary approach to anthropogenic contributions. As a science policy advisor to a Member of Congress active in the climate policy debate over the past year, I have observed firsthand most of the scientific information on climate change presented to Congress being partitioned into these camps. The political debate surrounding climate change policy has centered on the policymakers' understanding of scientific uncertainty. Communication by researchers of the definition of risk and uncertainty in climate science, in the language and framework of the legislative debate, is of utmost importance in order for policymakers to effectively understand and utilize science in the decision-making process. A comparison with the recent white paper on climate change policy developed by the UK Science and Technology council and currently adopted by UK policymakers demonstrates the importance of a general public understanding of the existing magnitude of climate change, uncertainties in the rate of future climate variability and its associated economic and social costs. Communication of research results on climate change has been most effective in the policy debate when framed within the context of economic or security risks in the short term. Other effective methods include communicating local and regional climate scenarios and associated probabilities to individual policy-makers, as is currently being utilized to promote sponsorship of the Climate Stewardship Act in Congress.

Evaluating climate variability and management impacts on carbon dynamics of a temperate forest using a variety of techniques

NASA Astrophysics Data System (ADS)

Arain, M. A.

2015-12-01

Climate variability, extreme weather events, forest age and management history impacts carbon sequestration in forest ecosystems. A variety of measurement techniques such as eddy covariance, dendrochronology, automatic soil CO2 chambers and remote sensing are employed fully understand forest carbon dynamics. Here, we present carbon flux measurements from 2003-2014 in a 76-year old managed temperate pine ((-Pinus strobus L.) forest, near Lake Erie in southern Ontario, Canada. Forest was partially thinned (30% tree harvested) in 1983 and 2012. The thinning in 2012 did not significantly impact carbon fluxes as post-thinning fluxes were within the range of inter-annual variability. Mean annual post-thinning (2012-2104) gross ecosystem productivity (GEP) measure by the eddy covariance technique was 1518 ± 78 g C m-2 year-1 as compared to pre-thinning (2003-2011) GEP of 1384 ± 121 g C m-2·year-1. Over the same period, mean post-thinning net ecosystem productivity (NEP) was 185 ± 75 g C m-2 year-1 as compared to post-thinning NEP of 180 ± 70 g C m-2 year-1, indicating that pre-thinning NEP was not significantly different than post-thinning NEP. Only post-thinning mean annual ecosystem respiration (Re; 1322 ± 54 g C m-2 year-1) was higher than pre-thinning Re (1195 ± 101 g C m-2 year-1). Soil CO2 efflux measurements showed similar trends. We also evaluated the impacts of climate variability and management regime on the full life cycle of the forest using annual radial tree-ring growths from 15 trees and compared them with historical climate (temperature and precipitation) data. While the annual growth rates displayed weak correlation with long-term climatic records, the growth was generally reduced during years with extreme drought (-36% of mean annual precipitation) and extreme temperature variability (±0.6 - 1.0°C). Overall, forest was more sensitive to management regime than climate variability. It showed higher growth stress during low light condition after crown closure. When partial thinning was introduced in 1983, it responded slowly and took about 5 to 7 years to show measureable increase in its growth, despite favorable climatic conditions. This study will help to advance our understanding of carbon dynamic of forest ecosystems.

Extreme weather and climate events with ecological relevance: a review

PubMed Central

Meehl, Gerald A.

2017-01-01

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation. This article is part of the themed issue ‘Behavioural, ecological and evolutionary responses to extreme climatic events’. PMID:28483866

Extreme weather and climate events with ecological relevance: a review.

PubMed

Ummenhofer, Caroline C; Meehl, Gerald A

2017-06-19

Robust evidence exists that certain extreme weather and climate events, especially daily temperature and precipitation extremes, have changed in regard to intensity and frequency over recent decades. These changes have been linked to human-induced climate change, while the degree to which climate change impacts an individual extreme climate event (ECE) is more difficult to quantify. Rapid progress in event attribution has recently been made through improved understanding of observed and simulated climate variability, methods for event attribution and advances in numerical modelling. Attribution for extreme temperature events is stronger compared with other event types, notably those related to the hydrological cycle. Recent advances in the understanding of ECEs, both in observations and their representation in state-of-the-art climate models, open new opportunities for assessing their effect on human and natural systems. Improved spatial resolution in global climate models and advances in statistical and dynamical downscaling now provide climatic information at appropriate spatial and temporal scales. Together with the continued development of Earth System Models that simulate biogeochemical cycles and interactions with the biosphere at increasing complexity, these make it possible to develop a mechanistic understanding of how ECEs affect biological processes, ecosystem functioning and adaptation capabilities. Limitations in the observational network, both for physical climate system parameters and even more so for long-term ecological monitoring, have hampered progress in understanding bio-physical interactions across a range of scales. New opportunities for assessing how ECEs modulate ecosystem structure and functioning arise from better scientific understanding of ECEs coupled with technological advances in observing systems and instrumentation.This article is part of the themed issue 'Behavioural, ecological and evolutionary responses to extreme climatic events'. © 2017 The Author(s).

Final Technical Report for DOE Award SC0006616

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

Robertson, Andrew

2015-08-01

This report summarizes research carried out by the project "Collaborative Research, Type 1: Decadal Prediction and Stochastic Simulation of Hydroclimate Over Monsoonal Asia. This collaborative project brought together climate dynamicists (UCLA, IRI), dendroclimatologists (LDEO Tree Ring Laboratory), computer scientists (UCI), and hydrologists (Columbia Water Center, CWC), together with applied scientists in climate risk management (IRI) to create new scientific approaches to quantify and exploit the role of climate variability and change in the growing water crisis across southern and eastern Asia. This project developed new tree-ring based streamflow reconstructions for rivers in monsoonal Asia; improved understanding of hydrologic spatio-temporal modesmore » of variability over monsoonal Asia on interannual-to-centennial time scales; assessed decadal predictability of hydrologic spatio-temporal modes; developed stochastic simulation tools for creating downscaled future climate scenarios based on historical/proxy data and GCM climate change; and developed stochastic reservoir simulation and optimization for scheduling hydropower, irrigation and navigation releases.« less

Large-scale climatic anomalies affect marine predator foraging behaviour and demography.

PubMed

Bost, Charles A; Cotté, Cedric; Terray, Pascal; Barbraud, Christophe; Bon, Cécile; Delord, Karine; Gimenez, Olivier; Handrich, Yves; Naito, Yasuhiko; Guinet, Christophe; Weimerskirch, Henri

2015-10-27

Determining the links between the behavioural and population responses of wild species to environmental variations is critical for understanding the impact of climate variability on ecosystems. Using long-term data sets, we show how large-scale climatic anomalies in the Southern Hemisphere affect the foraging behaviour and population dynamics of a key marine predator, the king penguin. When large-scale subtropical dipole events occur simultaneously in both subtropical Southern Indian and Atlantic Oceans, they generate tropical anomalies that shift the foraging zone southward. Consequently the distances that penguins foraged from the colony and their feeding depths increased and the population size decreased. This represents an example of a robust and fast impact of large-scale climatic anomalies affecting a marine predator through changes in its at-sea behaviour and demography, despite lack of information on prey availability. Our results highlight a possible behavioural mechanism through which climate variability may affect population processes.

Large-scale climatic anomalies affect marine predator foraging behaviour and demography

NASA Astrophysics Data System (ADS)

Bost, Charles A.; Cotté, Cedric; Terray, Pascal; Barbraud, Christophe; Bon, Cécile; Delord, Karine; Gimenez, Olivier; Handrich, Yves; Naito, Yasuhiko; Guinet, Christophe; Weimerskirch, Henri

2015-10-01

Determining the links between the behavioural and population responses of wild species to environmental variations is critical for understanding the impact of climate variability on ecosystems. Using long-term data sets, we show how large-scale climatic anomalies in the Southern Hemisphere affect the foraging behaviour and population dynamics of a key marine predator, the king penguin. When large-scale subtropical dipole events occur simultaneously in both subtropical Southern Indian and Atlantic Oceans, they generate tropical anomalies that shift the foraging zone southward. Consequently the distances that penguins foraged from the colony and their feeding depths increased and the population size decreased. This represents an example of a robust and fast impact of large-scale climatic anomalies affecting a marine predator through changes in its at-sea behaviour and demography, despite lack of information on prey availability. Our results highlight a possible behavioural mechanism through which climate variability may affect population processes.

Climate Change Impacts at Department of Defense

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

Kotamarthi, Rao; Wang, Jiali; Zoebel, Zach

This project is aimed at providing the U.S. Department of Defense (DoD) with a comprehensive analysis of the uncertainty associated with generating climate projections at the regional scale that can be used by stakeholders and decision makers to quantify and plan for the impacts of future climate change at specific locations. The merits and limitations of commonly used downscaling models, ranging from simple to complex, are compared, and their appropriateness for application at installation scales is evaluated. Downscaled climate projections are generated at selected DoD installations using dynamic and statistical methods with an emphasis on generating probability distributions of climatemore » variables and their associated uncertainties. The sites selection and selection of variables and parameters for downscaling was based on a comprehensive understanding of the current and projected roles that weather and climate play in operating, maintaining, and planning DoD facilities and installations.« less

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

NASA Astrophysics Data System (ADS)

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

2003-12-01

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

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

PubMed

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

2016-10-06

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

Detection and Attribution of Simulated Climatic Extreme Events and Impacts: High Sensitivity to Bias Correction

NASA Astrophysics Data System (ADS)

Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Kirsten, T.; Mahecha, M. D.

2015-12-01

Understanding, quantifying and attributing the impacts of climatic extreme events and variability is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit pronounced biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. We assess how biases and their correction affect the quantification and attribution of simulated extremes and variability in i) climatological variables and ii) impacts on ecosystem functioning as simulated by a terrestrial biosphere model. Our study demonstrates that assessments of simulated climatic extreme events and impacts in the terrestrial biosphere are highly sensitive to bias correction schemes with major implications for the detection and attribution of these events. We introduce a novel ensemble-based resampling scheme based on a large regional climate model ensemble generated by the distributed weather@home setup[1], which fully preserves the physical consistency and multivariate correlation structure of the model output. We use extreme value statistics to show that this procedure considerably improves the representation of climatic extremes and variability. Subsequently, biosphere-atmosphere carbon fluxes are simulated using a terrestrial ecosystem model (LPJ-GSI) to further demonstrate the sensitivity of ecosystem impacts to the methodology of bias correcting climate model output. We find that uncertainties arising from bias correction schemes are comparable in magnitude to model structural and parameter uncertainties. The present study consists of a first attempt to alleviate climate model biases in a physically consistent way and demonstrates that this yields improved simulations of climate extremes and associated impacts. [1] http://www.climateprediction.net/weatherathome/

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

NASA Astrophysics Data System (ADS)

Venema, Victor; Auchmann, Renate; Aguilar, Enric; Auer, Ingeborg; Azorin-Molina, Cesar; Brandsma, Theo; Brunetti, Michele; Dienst, Manuel; Domonkos, Peter; Gilabert, Alba; Lindén, Jenny; Milewska, Ewa; Nordli, Øyvind; Prohom, Marc; Rennie, Jared; Stepanek, Petr; Trewin, Blair; Vincent, Lucie; Willett, Kate; Wolff, Mareile

2016-04-01

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 relocations, (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. Metadata that describe the parallel measurements is as important as the data itself and will be collected as well. For example, the types of the instruments, their siting, height, maintenance, etc. Because they are widely used to study moderate extremes, we will compute the indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). In case the daily data cannot be shared, we would appreciate contributions containing these indices from parallel measurements. For more information: http://tinyurl.com/ISTI-Parallel

Influence of School-Level Variables on Aggression and Associated Attitudes of Middle School Students

ERIC Educational Resources Information Center

Henry, David B.; Farrell, Albert D.; Schoeny, Michael E.; Tolan, Patrick H.; Dymnicki, Allison B.

2011-01-01

This study sought to understand school-level influences on aggressive behavior and related social cognitive variables. Participants were 5106 middle school students participating in a violence prevention project. Predictors were school-level norms opposing aggression and favoring nonviolence, interpersonal climate (positive student-teacher…

Variability and change of sea level and its components in the Indo-Pacific region during the altimetry era

NASA Astrophysics Data System (ADS)

Wu, Quran; Zhang, Xuebin; Church, John A.; Hu, Jianyu

2017-03-01

Previous studies have shown that regional sea level exhibits interannual and decadal variations associated with the modes of climate variability. A better understanding of those low-frequency sea level variations benefits the detection and attribution of climate change signals. Nonetheless, the contributions of thermosteric, halosteric, and mass sea level components to sea level variability and trend patterns remain unclear. By focusing on signals associated with dominant climate modes in the Indo-Pacific region, we estimate the interannual and decadal fingerprints and trend of each sea level component utilizing a multivariate linear regression of two adjoint-based ocean reanalyses. Sea level interannual, decadal, and trend patterns primarily come from thermosteric sea level (TSSL). Halosteric sea level (HSSL) is of regional importance in the Pacific Ocean on decadal time scale and dominates sea level trends in the northeast subtropical Pacific. The compensation between TSSL and HSSL is identified in their decadal variability and trends. The interannual and decadal variability of temperature generally peak at subsurface around 100 m but that of salinity tend to be surface-intensified. Decadal temperature and salinity signals extend deeper into the ocean in some regions than their interannual equivalents. Mass sea level (MassSL) is critical for the interannual and decadal variability of sea level over shelf seas. Inconsistencies exist in MassSL trend patterns among various estimates. This study highlights regions where multiple processes work together to control sea level variability and change. Further work is required to better understand the interaction of different processes in those regions.

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

NASA Astrophysics Data System (ADS)

Hamdy, A.; Trisorio-Liuzzi, G.

2009-04-01

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

Changing Conditions in the Arctic: An Analysis of 45 years of Tropospheric Ozone Measurements at Barrow Observatory

NASA Astrophysics Data System (ADS)

McClure-Begley, A.; Petropavlovskikh, I. V.; Crepinsek, S.; Jefferson, A.; Emmons, L. K.; Oltmans, S. J.

2017-12-01

In order to understand the impact of climate on local bio-systems, understanding the changes to the atmospheric composition and processes in the Arctic boundary layer and free troposphere is imperative. In the Arctic, many conditions influence tropospheric ozone variability such as: seasonal halogen caused depletion events, long range transport of pollutants from mid-northern latitudes, compounds released from wildfires, and different meteorological conditions. The Barrow station in Utqiagvik, Alaska has collected continuous measurements of ground-level ozone since 1973. This unique long-term time series allows for analysis of the influence of a rapidly changing climate on ozone conditions in this region. Specifically, this study analyzes the frequency of enhanced ozone episodes over time and provides in depth analysis of periods of positive deviations from the expected conditions. To discern the contribution of different pollutant sources to observed ozone variability, co-located measurements of aerosols, carbon monoxide, and meteorological conditions are used. In addition, the NCAR Mozart-4/MOPITT Chemical Forecast model and NOAA Hysplit back-trajectory analysis provide information on transport patterns to the Arctic and confirmation of the emission sources that influenced the observed conditions. These anthropogenic influences on ozone variability in and below the boundary layer are essential for developing an understanding of the interaction of climate change and the bio-systems in the Arctic.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

PubMed Central

Ramírez, Alonso; Pringle, Catherine M.

2018-01-01

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

The role of updraft velocity in temporal variability of cloud hydrometeor number

NASA Astrophysics Data System (ADS)

Sullivan, Sylvia; Nenes, Athanasios; Lee, Dong Min; Oreopoulos, Lazaros

2016-04-01

Significant effort has been dedicated to incorporating direct aerosol-cloud links, through parameterization of liquid droplet activation and ice crystal nucleation, within climate models. This significant accomplishment has generated the need for understanding which parameters affecting hydrometer formation drives its variability in coupled climate simulations, as it provides the basis for optimal parameter estimation as well as robust comparison with data, and other models. Sensitivity analysis alone does not address this issue, given that the importance of each parameter for hydrometer formation depends on its variance and sensitivity. To address the above issue, we develop and use a series of attribution metrics defined with adjoint sensitivities to attribute the temporal variability in droplet and crystal number to important aerosol and dynamical parameters. This attribution analysis is done both for the NASA Global Modeling and Assimilation Office Goddard Earth Observing System Model, Version 5 and the National Center for Atmospheric Research Community Atmosphere Model Version 5.1. Within the GEOS simulation, up to 48% of temporal variability in output ice crystal number and 61% in droplet number can be attributed to input updraft velocity fluctuations, while for the CAM simulation, they explain as much as 89% of the ice crystal number variability. This above results suggest that vertical velocity in both model frameworks is seen to be a very important (or dominant) driver of hydrometer variability. Yet, observations of vertical velocity are seldomly available (or used) to evaluate the vertical velocities in simulations; this strikingly contrasts the amount and quality of data available for aerosol-related parameters. Consequentially, there is a strong need for retrievals or measurements of vertical velocity for addressing this important knowledge gap that requires a significant investment and effort by the atmospheric community. The attribution metrics as a tool of understanding for hydrometer variability can be instrumental for understanding the source of differences between models used for aerosol-cloud-climate interaction studies.

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

PubMed Central

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

2014-01-01

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

Climate Modeling in the Calculus and Differential Equations Classroom

ERIC Educational Resources Information Center

Kose, Emek; Kunze, Jennifer

2013-01-01

Students in college-level mathematics classes can build the differential equations of an energy balance model of the Earth's climate themselves, from a basic understanding of the background science. Here we use variable albedo and qualitative analysis to find stable and unstable equilibria of such a model, providing a problem or perhaps a…

A variable-instar climate-driven individual beetle-based phenology model for the invasive Asian longhorned beetle (Coleoptera: Cerambycidae)

Treesearch

R. Talbot Trotter, III; Melody A. Keena

2016-01-01

Efforts to manage and eradicate invasive species can benefit from an improved understanding of the physiology, biology, and behavior of the target species, and ongoing efforts to eradicate the Asian longhorned beetle (Anoplophora glabripennis Motschulsky) highlight the roles this information may play. Here, we present a climate-driven phenology...

National climate assessment technical report on the impacts of climate and land use and land cover change

USGS Publications Warehouse

Loveland, Thomas; Mahmood, Rezaul; Patel-Weynand, Toral; Karstensen, Krista; Beckendorf, Kari; Bliss, Norman; Carleton, Andrew

2012-01-01

This technical report responds to the recognition by the U.S. Global Change Research Program (USGCRP) and the National Climate Assessment (NCA) of the importance of understanding how land use and land cover (LULC) affects weather and climate variability and change and how that variability and change affects LULC. Current published, peer-reviewed, scientific literature and supporting data from both existing and original sources forms the basis for this report's assessment of the current state of knowledge regarding land change and climate interactions. The synthesis presented herein documents how current and future land change may alter environment processes and in turn, how those conditions may affect both land cover and land use by specifically investigating, * The primary contemporary trends in land use and land cover, * The land-use and land-cover sectors and regions which are most affected by weather and climate variability,* How land-use practices are adapting to climate change, * How land-use and land-cover patterns and conditions are affecting weather and climate, and * The key elements of an ongoing Land Resources assessment. These findings present information that can be used to better assess land change and climate interactions in order to better assess land management and adaptation strategies for future environmental change and to assist in the development of a framework for an ongoing national assessment.

A preliminary study on teak tree ring cellulose δ18O from northwestern Thailand: the potential for developing multiproxy records of Thailand summer monsoon variability

NASA Astrophysics Data System (ADS)

Muangsong, Chotika; Cai, Binggui; Pumijumnong, Nathsuda; Lei, Guoliang; Wang, Fang

2018-05-01

Thailand monsoon is located in the transition zone between the Indian and western North Pacific monsoons. Assuredly, proxy climate data from this area could improve our understanding of the nature of Asian monsoon. Tree rings and stalagmites from this area are two potential materials for high-resolution paleoclimate reconstructions. However, a comprehensive understanding of these multiproxy records is still a challenge. In this study, a 76-year tree ring cellulose oxygen isotope value (δ18O) of a teak tree from northwestern Thailand was developed to test its climatic significance and potential for multiproxy climate reconstruction. The results indicate that the interannual variability of cellulose δ18O can be interpreted as a proxy of rainfall in the early monsoon season (May to July rainfall) as well as a proxy of relative humidity. Comparisons with speleothem proxies from the same locality and tree ring records from wider geographical areas provide a basis for developing a multiproxy approach. The results from a teleconnection analysis reveal that the El Niño-Southern Oscillation (ENSO) is an important climate mode that impacts monsoon rainfall in Thailand. High-quality proxy records covering recent decades are critically important not only to improve proxy data calibrations but also to provide a better understanding of teleconnections within the modern atmosphere. Preliminary findings demonstrated the potential of tree ring stable isotopes from Thai teak to develop multiproxy climate reconstruction.

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

NASA Astrophysics Data System (ADS)

Horton, Radley M.

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

Effects of temporal variation in temperature and density dependence on insect population dynamics

USDA-ARS?s Scientific Manuscript database

Understanding effects of environmental variation on insect populations is important in light of predictions about increasing future climatic variability. In order to understand the effects of changing environmental variation on population dynamics and life history evolution in insects one would need...

Role of the North Atlantic Ocean in Low Frequency Climate Variability

NASA Astrophysics Data System (ADS)

Danabasoglu, G.; Yeager, S. G.; Kim, W. M.; Castruccio, F. S.

2017-12-01

The Atlantic Ocean is a unique basin with its extensive, North - South overturning circulation, referred to as the Atlantic meridional overturning circulation (AMOC). AMOC is thought to represent the dynamical memory of the climate system, playing an important role in decadal and longer time scale climate variability as well as prediction of the earth's future climate on these time scales via its large heat and salt transports. This oceanic memory is communicated to the atmosphere primarily through the influence of persistent sea surface temperature (SST) variations. Indeed, many modeling studies suggest that ocean circulation, i.e., AMOC, is largely responsible for the creation of coherent SST variability in the North Atlantic, referred to as Atlantic Multidecadal Variability (AMV). AMV has been linked to many (multi)decadal climate variations in, e.g., Sahel and Brazilian rainfall, Atlantic hurricane activity, and Arctic sea-ice extent. In the absence of long, continuous observations, much of the evidence for the ocean's role in (multi)decadal variability comes from model simulations. Although models tend to agree on the role of the North Atlantic Oscillation in creating the density anomalies that proceed the changes in ocean circulation, model fidelity in representing variability characteristics, mechanisms, and air-sea interactions remains a serious concern. In particular, there is increasing evidence that models significantly underestimate low frequency variability in the North Atlantic compared to available observations. Such model deficiencies can amplify the relative influence of external or stochastic atmospheric forcing in generating (multi)decadal variability, i.e., AMV, at the expense of ocean dynamics. Here, a succinct overview of the current understanding of the (North) Atlantic Ocean's role on the regional and global climate, including some outstanding questions, will be presented. In addition, a few examples of the climate impacts of the AMV via atmospheric teleconnections from a set of coupled simulations, also considering the relative roles of its tropical and extratropical components, will be highlighted.

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

PubMed Central

Vincenzi, Simone

2014-01-01

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

Climate Variability and Sugarcane Yield in Louisiana.

NASA Astrophysics Data System (ADS)

Greenland, David

2005-11-01

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

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.

Response of lake chemistry to atmospheric deposition and climate in selected Class I wilderness areas in the western United States, 1993-2009

USGS Publications Warehouse

Mast, M. Alisa

2011-01-01

The U.S. Geological Survey, in cooperation with the U.S. Department of Agriculture Forest Service, Air Resource Management, conducted a study to evaluate long-term trends in lake-water chemistry for 64 high-elevation lakes in selected Class I wilderness areas in Colorado, Idaho, Utah, and Wyoming during 1993 to 2009. Understanding how and why lake chemistry is changing in mountain areas is essential for effectively managing and protecting high-elevation aquatic ecosystems. Trends in emissions, atmospheric deposition, and climate variables (air temperature and precipitation amount) were evaluated over a similar period of record. A main objective of the study was to determine if changes in atmospheric deposition of contaminants in the Rocky Mountain region have resulted in measurable changes in the chemistry of high-elevation lakes. A second objective was to investigate linkages between lake chemistry and air temperature and precipitation to improve understanding of the sensitivity of mountain lakes to climate variability.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

PubMed

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

2013-01-01

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

The Climate Resilience Toolkit: Central gateway for risk assessment and resilience planning at all governance scales

NASA Astrophysics Data System (ADS)

Herring, D.; Lipschultz, F.

2016-12-01

As people and organizations grapple with a changing climate amid a range of other factors simultaneously shifting, there is a need for credible, legitimate & salient scientific information in useful formats. In addition, an assessment framework is needed to guide the process of planning and implementing projects that allow communities and businesses to adapt to specific changing conditions, while also building overall resilience to future change. We will discuss how the U.S. Climate Resilience Toolkit (CRT) can improve people's ability to understand and manage their climate-related risks and opportunities, and help them make their communities and businesses more resilient. In close coordination with the U.S. Climate Data Initiative, the CRT is continually evolving to offer actionable authoritative information, relevant tools, and subject matter expertise from across the U.S. federal government in one easy-to-use location. The Toolkit's "Climate Explorer" is designed to help people understand potential climate conditions over the course of this century. It offers easy access to downloadable maps, graphs, and data tables of observed and projected temperature, precipitation and other decision-relevant climate variables dating back to 1950 and out to 2100. Since climate is only one of many changing factors affecting decisions about the future, it also ties climate information to a wide range of relevant variables to help users explore vulnerabilities and impacts. New topic areas have been added, such as "Fisheries," "Regions," and "Built Environment" sections that feature case studies and personal experiences in making adaptation decisions. A curated "Reports" section is integrated with semantic web capabilities to help users locate the most relevant information sources. As part of the USGCRP's sustained assessment process, the CRT is aligning with other federal activities, such as the upcoming 4th National Climate Assessment.

Predicting Plant Diversity Patterns in Madagascar: Understanding the Effects of Climate and Land Cover Change in a Biodiversity Hotspot

PubMed Central

Brown, Kerry A.; Parks, Katherine E.; Bethell, Colin A.; Johnson, Steig E.; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar’s plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future. PMID:25856241

Predicting plant diversity patterns in Madagascar: understanding the effects of climate and land cover change in a biodiversity hotspot.

PubMed

Brown, Kerry A; Parks, Katherine E; Bethell, Colin A; Johnson, Steig E; Mulligan, Mark

2015-01-01

Climate and land cover change are driving a major reorganization of terrestrial biotic communities in tropical ecosystems. In an effort to understand how biodiversity patterns in the tropics will respond to individual and combined effects of these two drivers of environmental change, we use species distribution models (SDMs) calibrated for recent climate and land cover variables and projected to future scenarios to predict changes in diversity patterns in Madagascar. We collected occurrence records for 828 plant genera and 2186 plant species. We developed three scenarios, (i.e., climate only, land cover only and combined climate-land cover) based on recent and future climate and land cover variables. We used this modelling framework to investigate how the impacts of changes to climate and land cover influenced biodiversity across ecoregions and elevation bands. There were large-scale climate- and land cover-driven changes in plant biodiversity across Madagascar, including both losses and gains in diversity. The sharpest declines in biodiversity were projected for the eastern escarpment and high elevation ecosystems. Sharp declines in diversity were driven by the combined climate-land cover scenarios; however, there were subtle, region-specific differences in model outputs for each scenario, where certain regions experienced relatively higher species loss under climate or land cover only models. We strongly caution that predicted future gains in plant diversity will depend on the development and maintenance of dispersal pathways that connect current and future suitable habitats. The forecast for Madagascar's plant diversity in the face of future environmental change is worrying: regional diversity will continue to decrease in response to the combined effects of climate and land cover change, with habitats such as ericoid thickets and eastern lowland and sub-humid forests particularly vulnerable into the future.

A collaborative characterization of North American grasslands and rangelands: climate, ecohydrology and carbon sink-source dynamics

NASA Astrophysics Data System (ADS)

Petrie, M. D.; Brunsell, N. A.; Vargas, R.; Collins, S. L.

2013-12-01

Grassland and rangeland ecoregions extend across the North American continent and exhibit diversity in climate, ecosystem services, and biophysical processes. In many grasslands and rangelands, the potential for reductions in ecosystem services and for large-scale ecosystem state change may increase under future climate scenarios. Climate change projections for North America vary, however, and the way changing climate will influence specific ecoregions is largely unknown. To better understand the regional effects of climate change on grasslands and rangelands, it is important to better understand the biophysical characteristics of these systems locally, and to identify the sensitivity of these characteristics to observed climate variation. In our study, we propose to use eddy covariance, soil moisture and precipitation data to identify how the grasslands and rangelands of North America differ in their responses to climate variability through time, with specific focus on the active growing season. Our primary goal is to determine the sensitivity of ecosystem Net Primary Productivity [NPP] to variation in temperature and precipitation patterns, and classify North American grasslands and rangelands by these sensitivities in addition to more standard climate and productivity variables. Our preliminary analyses in mesic, semiarid and arid grasslands in Kansas, Colorado and New Mexico show significant (P < 0.05) differences in climate, carbon sink strength and growing season length, and suggest that patterns of seasonal productivity and precipitation sensitivity may elucidate important grassland and rangeland responses to changing climate. Using change in Gross Primary Productivity (GPP) as an indicator of the onset of photosynthesis in spring and of senescense in the fall, grassland and rangeland ecosystems in Kansas (top and bottom left panels) and New Mexico (bottom right panel) display differing patterns of activity throughout the year.

Observed Temporal and Spatial Variability in the Marine Environment at the Sub-Antarctic Prince Edward Islands - Evidence of a Changing Climate?

NASA Astrophysics Data System (ADS)

Asdar, S.; Deshayes, J.; Ansorge, I. J.

2016-02-01

The sub-Antarctic Prince Edward Islands (PEI) (47°S,38°E) are classified as isolated, hostile, impoverished regions, in which the terrestrial and marine ecosystems are relatively simple and extremely sensitive to perturbations. Their location between the Sub-Antarctic Front (SAF) and the Antarctic Polar Front (APF), bordering the Antarctic Circumpolar Current (ACC) provides an ideal natural laboratory for studying how organisms, ecological processes and ecosystems respond to a changing ocean climate in the Southern Ocean. Recent studies have proposed that climate changes reported at the PEI may correspond in time to a southward shift of the ACC and in particular of the SAF. This southward migration in the geographic position is likely to coincide with dramatic changes in the distribution of species and total productivity of this region. This study focuses on the inter-comparison of observations available at these islands. Using spectral analysis which is a study of the frequency domain characteristics of a process, we first determine the dominant characteristics of both the temporal and spatial variability of physical and biogeochemical properties. In doing so the authors are able to determine whether and how these indices of variability interact with one another in order to understand better the mechanisms underpinning this variability, i.e. the seasonal zonal migrations associated with the SAF. Additionally, we include in our analysis recent data from 2 ADCP moorings deployed between the islands from 2014 to 2015. These in-situ observations of circulation and hydrography in the vicinity of the islands provide a unique opportunity to establish a better understanding of how large scale climatic variability may impact local conditions, and more importantly its influence on the fragile ecosystem surrounding the PEI.

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

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

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

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

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

DOE PAGES

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

2015-06-01

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

Understanding changes of stomatal conductance under different atmospheric humidity levels for different tropical rainforest species in Biosphere 2

NASA Astrophysics Data System (ADS)

Tornito, A. J. G.

2016-12-01

Understanding the dynamics of climate change is one of the biggest questions that scientists across the globe ask today. With understanding climate change comes the need to understand the ecological systems and how their biological and chemical processes contribute to climate change. As ocean ecosystems, rainforests are very productive systems and are responsible for most of the world's carbon budget. To maintain cooler conditions, tropical forests mitigate warming through evapotranspiration. The purpose of this project was to measure short-term plasticity by looking at stomatal conductance levels of different tropical rainforest species of plants in the rainforest, savannah, and desert habitats in the Biosphere 2 facility in Oracle, Arizona. It is known that stomatal conductance is affected by CO2, H2O, and light availability. It has been observed that temperature levels may not affect stomatal conductance because of the variability associated with it. Results indicated that there is a potential trend amongst these rainforest species when placed in different humidity percentage areas. By understanding stomatal conductance in response to humidity, we can better understand how productive rainforest systems are when humidity levels decrease, which may potentially occur as Earth undergoes global climate change.

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

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

2015-09-01

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

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

NASA Astrophysics Data System (ADS)

Venema, Victor; Auchmann, Renate; Aguilar, Enric

2015-04-01

n this work we introduce the rationale behind the ongoing compilation of a parallel measurements database, under the umbrella 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., relocations and changes in instrumentation, instrument height or data collection and manipulation procedures. These so-called inhomogeneities distort the climate signal and can hamper the assessment of trends and variability. 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). 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 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, 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. In the ISTI Parallel Observations Science Team (POST), we will gather parallel data in their native format (to avoid undetectable conversion errors we will convert it to a standard format ourselves). 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 temperature measurements, the influencing factors are expected to be insolation, wind and clouds cover; in case of parallel precipitation measurements, wind and temperature are potentially important. Metadata that describe the parallel measurements is as important as the data itself and will be collected as well. For example, the types of the instruments, their siting, height, maintenance, etc. Because they are widely used to study moderate extremes, we will compute the indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). In case the daily data cannot be shared, we would appreciate these indices from parallel measurements. For more information: http://tinyurl.com/ISTI-Parallel

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.

Carbon-water Cycling in the Critical Zone: Understanding Ecosystem Process Variability Across Complex Terrain

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

Barnard, Holly; Brooks, Paul

2016-06-16

One of the largest knowledge gaps in environmental science is the ability to understand and predict how ecosystems will respond to future climate variability. The links between vegetation, hydrology, and climate that control carbon sequestration in plant biomass and soils remain poorly understood. Soil respiration is the second largest carbon flux of terrestrial ecosystems, yet there is no consensus on how respiration will change as water availability and temperature co-vary. To address this knowledge gap, we use the variation in soil development and topography across an elevation and climate gradient on the Front Range of Colorado to conduct a naturalmore » experiment that enables us to examine the co-evolution of soil carbon, vegetation, hydrology, and climate in an accessible field laboratory. The goal of this project is to further our ability to combine plant water availability, carbon flux and storage, and topographically driven hydrometrics into a watershed scale predictive model of carbon balance. We hypothesize: (i) landscape structure and hydrology are important controls on soil respiration as a result of spatial variability in both physical and biological drivers: (ii) variation in rates of soil respiration during the growing season is due to corresponding shifts in belowground carbon inputs from vegetation; and (iii) aboveground carbon storage (biomass) and species composition are directly correlated with soil moisture and therefore, can be directly related to subsurface drainage patterns.« less

Understanding hydro-climatic drivers of infectious diarrheal diseases in South Asia and their projected risks from regional climate models

NASA Astrophysics Data System (ADS)

Hasan, M. A.; Akanda, A. S.; Jutla, A.; Huq, A.; Colwell, R. R.

2017-12-01

Diarrheal diseases remain a major threat to global public health and are the second largest cause of death for children under the age of five. Cholera and Rotavirus diarrhea together comprise more than two-thirds of the diarrheal morbidity in South Asia. Recent studies have shown strong influences of hydrologic processes and climatic variabilities on the onset, intensity, and seasonality of the outbreaks of these diseases. However, our understanding of the propagation and manifestation of these diseases in a changing climate in vulnerable regions of the world are still limited. In this study, we build on our understanding of the role of the hydro-climatic drivers of diarrheal diseases in South Asia in recent decades to project the probable risks of the diseases in this century using the climate projection scenarios from dynamically downscaled climate models. To build the current model, we conducted a multivariate logistic regression assessment using 34 climate indices to examine the role of temperature and rainfall extremes over the seasonality of rotavirus and cholera over a South Asian country, Bangladesh. We utilize the availability of long and reliable time-series of cholera and rotavirus from Bangladesh and conducted a temporal and spatial analysis derived from both ground and satellite observations. For projecting the future risks of the diseases, we used five bias-corrected Regional Climate Model (RCM) results of the CMIP5 series under the RCP 4.5 scenario. Cholera risk shows a significantly higher rate of increase compared to Rotavirus in Bangladesh in the 21st century. As the disease is significantly influenced by extreme rainfall, majority projections showed a significant increase in flood-driven cholera risk. Most RCMs suggest a warmer winter in future years, suggesting reduced risk for Rotavirus. However, as the dryness of the climate is also highly correlated with rotavirus epidemics, the incremental risk of the disease due to drier winters would likely undermine the reduced risk due to temperature increase. Probabilistic risk assessments of these diarrheal diseases with respect to hydro-climatic variability will, not only improve the local policymaking processes, but also allow us to pinpoint the climate-health hotspots around the globe.

Patterns and variability of projected bioclimatic habitat for Pinus albicaulis in the Greater Yellowstone Area.

PubMed

Chang, Tony; Hansen, Andrew J; Piekielek, Nathan

2014-01-01

Projected climate change at a regional level is expected to shift vegetation habitat distributions over the next century. For the sub-alpine species whitebark pine (Pinus albicaulis), warming temperatures may indirectly result in loss of suitable bioclimatic habitat, reducing its distribution within its historic range. This research focuses on understanding the patterns of spatiotemporal variability for future projected P.albicaulis suitable habitat in the Greater Yellowstone Area (GYA) through a bioclimatic envelope approach. Since intermodel variability from General Circulation Models (GCMs) lead to differing predictions regarding the magnitude and direction of modeled suitable habitat area, nine bias-corrected statistically down-scaled GCMs were utilized to understand the uncertainty associated with modeled projections. P.albicaulis was modeled using a Random Forests algorithm for the 1980-2010 climate period and showed strong presence/absence separations by summer maximum temperatures and springtime snowpack. Patterns of projected habitat change by the end of the century suggested a constant decrease in suitable climate area from the 2010 baseline for both Representative Concentration Pathways (RCPs) 8.5 and 4.5 climate forcing scenarios. Percent suitable climate area estimates ranged from 2-29% and 0.04-10% by 2099 for RCP 8.5 and 4.5 respectively. Habitat projections between GCMs displayed a decrease of variability over the 2010-2099 time period related to consistent warming above the 1910-2010 temperature normal after 2070 for all GCMs. A decreasing pattern of projected P.albicaulis suitable habitat area change was consistent across GCMs, despite strong differences in magnitude. Future ecological research in species distribution modeling should consider a full suite of GCM projections in the analysis to reduce extreme range contractions/expansions predictions. The results suggest that restoration strageties such as planting of seedlings and controlling competing vegetation may be necessary to maintain P.albicaulis in the GYA under the more extreme future climate scenarios.

Patterns and Variability of Projected Bioclimatic Habitat for Pinus albicaulis in the Greater Yellowstone Area

PubMed Central

Chang, Tony; Hansen, Andrew J.; Piekielek, Nathan

2014-01-01

Projected climate change at a regional level is expected to shift vegetation habitat distributions over the next century. For the sub-alpine species whitebark pine (Pinus albicaulis), warming temperatures may indirectly result in loss of suitable bioclimatic habitat, reducing its distribution within its historic range. This research focuses on understanding the patterns of spatiotemporal variability for future projected P.albicaulis suitable habitat in the Greater Yellowstone Area (GYA) through a bioclimatic envelope approach. Since intermodel variability from General Circulation Models (GCMs) lead to differing predictions regarding the magnitude and direction of modeled suitable habitat area, nine bias-corrected statistically down-scaled GCMs were utilized to understand the uncertainty associated with modeled projections. P.albicaulis was modeled using a Random Forests algorithm for the 1980–2010 climate period and showed strong presence/absence separations by summer maximum temperatures and springtime snowpack. Patterns of projected habitat change by the end of the century suggested a constant decrease in suitable climate area from the 2010 baseline for both Representative Concentration Pathways (RCPs) 8.5 and 4.5 climate forcing scenarios. Percent suitable climate area estimates ranged from 2–29% and 0.04–10% by 2099 for RCP 8.5 and 4.5 respectively. Habitat projections between GCMs displayed a decrease of variability over the 2010–2099 time period related to consistent warming above the 1910–2010 temperature normal after 2070 for all GCMs. A decreasing pattern of projected P.albicaulis suitable habitat area change was consistent across GCMs, despite strong differences in magnitude. Future ecological research in species distribution modeling should consider a full suite of GCM projections in the analysis to reduce extreme range contractions/expansions predictions. The results suggest that restoration strageties such as planting of seedlings and controlling competing vegetation may be necessary to maintain P.albicaulis in the GYA under the more extreme future climate scenarios. PMID:25372719

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

NASA Astrophysics Data System (ADS)

Beltrame, L.; Dunne, T.; Rose, H.; Walker, J.; Morgan, E.; Vickerman, P.; Wagener, T.

2016-12-01

Liver fluke is a flatworm parasite infecting grazing animals worldwide. In the UK, it causes considerable production losses to cattle and sheep industries and costs farmers millions of pounds each year due to reduced growth rates and lower milk yields. Large part of the parasite life-cycle takes place outside of the host, with its survival and development strongly controlled by climatic and hydrologic conditions. Evidence of climate-driven changes in the distribution and seasonality of fluke disease already exists, as the infection is increasingly expanding to new areas and becoming a year-round problem. Therefore, it is crucial to assess current and potential future impacts of climate variability on the disease to guide interventions at the farm scale and mitigate risk. Climate-based fluke risk models have been available since the 1950s, however, they are based on empirical relationships derived between historical climate and incidence data, and thus are unlikely to be robust for simulating risk under changing conditions. Moreover, they are not dynamic, but estimate risk over large regions in the UK based on monthly average climate conditions, so they do not allow investigating the effects of climate variability for supporting farmers' decisions. In this study, we introduce a mechanistic model for fluke, which represents habitat suitability for disease development at 25m resolution with a daily time step, explicitly linking the parasite life-cycle to key hydro-climate conditions. The model is used on a case study in the UK and sensitivity analysis is performed to better understand the role of climate variability on the space-time dynamics of the disease, while explicitly accounting for uncertainties. Comparisons are presented with experts' knowledge and a widely used empirical model.

Predicting the geographic distribution of Lutzomyia longipalpis (Diptera: Psychodidae) and visceral leishmaniasis in the state of Mato Grosso do Sul, Brazil

PubMed Central

de Almeida, Paulo Silva; Sciamarelli, Alan; Batista, Paulo Mira; Ferreira, Ademar Dimas; Nascimento, João; Raizer, Josué; Andrade, José Dilermando; Gurgel-Gonçalves, Rodrigo

2013-01-01

To understand the geographic distribution of visceral leishmaniasis (VL) in the state of Mato Grosso do Sul (MS), Brazil, both the climatic niches of Lutzomyia longipalpis and VL cases were analysed. Distributional data were obtained from 55 of the 79 counties of MS between 2003-2012. Ecological niche models (ENM) of Lu. longipalpis and VL cases were produced using the maximum entropy algorithm based on eight climatic variables. Lu. longipalpis showed a wide distribution in MS. The highest climatic suitability for Lu. longipalpis was observed in southern MS. Temperature seasonality and annual mean precipitation were the variables that most influenced these models. Two areas of high climatic suitability for the occurrence of VL cases were predicted: one near Aquidauana and another encompassing several municipalities in the southeast region of MS. As expected, a large overlap between the models for Lu. longipalpis and VL cases was detected. Northern and northwestern areas of MS were suitable for the occurrence of cases, but did not show high climatic suitability for Lu. longipalpis . ENM of vectors and human cases provided a greater understanding of the geographic distribution of VL in MS, which can be applied to the development of future surveillance strategies. PMID:24402151

Predicting the geographic distribution of Lutzomyia longipalpis (Diptera: Psychodidae) and visceral leishmaniasis in the state of Mato Grosso do Sul, Brazil.

PubMed

Almeida, Paulo Silva de; Sciamarelli, Alan; Batista, Paulo Mira; Ferreira, Ademar Dimas; Nascimento, João; Raizer, Josué; Andrade Filho, José Dilermando; Gurgel-Gonçalves, Rodrigo

2013-12-01

To understand the geographic distribution of visceral leishmaniasis (VL) in the state of Mato Grosso do Sul (MS), Brazil, both the climatic niches of Lutzomyia longipalpis and VL cases were analysed. Distributional data were obtained from 55 of the 79 counties of MS between 2003-2012. Ecological niche models (ENM) of Lu. longipalpis and VL cases were produced using the maximum entropy algorithm based on eight climatic variables. Lu. longipalpis showed a wide distribution in MS. The highest climatic suitability for Lu. longipalpis was observed in southern MS. Temperature seasonality and annual mean precipitation were the variables that most influenced these models. Two areas of high climatic suitability for the occurrence of VL cases were predicted: one near Aquidauana and another encompassing several municipalities in the southeast region of MS. As expected, a large overlap between the models for Lu. longipalpis and VL cases was detected. Northern and northwestern areas of MS were suitable for the occurrence of cases, but did not show high climatic suitability for Lu. longipalpis. ENM of vectors and human cases provided a greater understanding of the geographic distribution of VL in MS, which can be applied to the development of future surveillance strategies.

Characterizing drought for forested landscapes and streams

Treesearch

Charlie Luce; Neil Pederson; John Campbell; Connie Millar; Patrick Kormos; James M. Vose; Ross Woods

2016-01-01

The purpose of this chapter is to explore drought as a hydrometeorological phenomenon and reflect broadly on the characteristics of drought that influence forests, rangelands, and streams. It is a synthesis of understanding about drought processes, hydrology, paleoclimatology, and historical climate variability, and how this understanding can help predict potential...

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

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.

2016-01-01

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

Revealing Relationships among Relevant Climate Variables with Information Theory

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

Impact on Hydrological Flows and Water Quality Using the Swat Model - the Case of Piracicaba Watershed

NASA Astrophysics Data System (ADS)

Queiroz, M. R.; Rocha, H.

2013-05-01

Understanding the functionality of water cycle in Brazilian ecosystems is one of the factors that generate the power to formulate smart strategies for biodiversity conservation and sustainable productivity in agro-ecosystems, promoting the generation of information that support the demands of occupation. Good policy formulation of land use depends on the expected climate change in the coming decades, as well as, surface cover and management must adapt to the socio-economic regional vocations so as to cause minimal impact. The changes in the land use influence the quantity and quality of water, contributing to floods and environmental changes. Additionally, climate change and variability, either natural or manmade cause, directly affect the human life. One of the main effects of weather occurs in the runoff generated in the basins, which in turn affects the water supply and demand in various sectors such as supply, irrigation and energy. The results Will show the impacts of climate variability on water resources (quantity and quality) to the Piracicaba watershed, through numerical modeling SWAT (Soil and Water Assessment Tool), developed with the objective to analyze the impacts of changes in land use on runoff and underground production of sediment and water quality. The results of this proposal will provide information to answer better understanding of the ecological functionality and freshwater ecosystems in Brazil, and particularly in the study region in the state of São Paulo, increase the predictability of the Earth's climate system, from knowledge of the response of terrestrial biota to different forms of climate variability and increased knowledge of alternative socio-economic adaptation of terrestrial biota and climate change.

Relating farmer's perceptions of climate change risk to adaptation behaviour in Hungary.

PubMed

Li, Sen; Juhász-Horváth, Linda; Harrison, Paula A; Pintér, László; Rounsevell, Mark D A

2017-01-01

Understanding how farmers perceive climate change risks and how this affects their willingness to adopt adaptation practices is critical for developing effective climate change response strategies for the agricultural sector. This study examines (i) the perceptual relationships between farmers' awareness of climate change phenomena, beliefs in climate change risks and actual adaptation behaviour, and (ii) how these relationships may be modified by farm-level antecedents related to human, social, financial capitals and farm characteristics. An extensive household survey was designed to investigate the current pattern of adaptation strategies and collect data on these perceptual variables and their potential antecedents from private landowners in Veszprém and Tolna counties, Hungary. Path analysis was used to explore the causal connections between variables. We found that belief in the risk of climate change was heightened by an increased awareness of directly observable climate change phenomena (i.e. water shortages and extreme weather events). The awareness of extreme weather events was a significant driver of adaptation behaviour. Farmers' actual adaptation behaviour was primarily driven by financial motives and managerial considerations (i.e. the aim of improving profit and product sales; gaining farm ownership and the amount of land managed; and, the existence of a successor), and stimulated by an innovative personality and the availability of information from socio-agricultural networks. These results enrich the empirical evidence in support of improving understanding of farmer decision-making processes, which is critical in developing well-targeted adaptation policies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Temporal and spatial variability in North Carolina piedmont stream temperature

Treesearch

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

2009-01-01

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

Climate Modeling and Causal Identification for Sea Ice Predictability

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

Hunke, Elizabeth Clare; Urrego Blanco, Jorge Rolando; Urban, Nathan Mark

This project aims to better understand causes of ongoing changes in the Arctic climate system, particularly as decreasing sea ice trends have been observed in recent decades and are expected to continue in the future. As part of the Sea Ice Prediction Network, a multi-agency effort to improve sea ice prediction products on seasonal-to-interannual time scales, our team is studying sensitivity of sea ice to a collection of physical process and feedback mechanism in the coupled climate system. During 2017 we completed a set of climate model simulations using the fully coupled ACME-HiLAT model. The simulations consisted of experiments inmore » which cloud, sea ice, and air-ocean turbulent exchange parameters previously identified as important for driving output uncertainty in climate models were perturbed to account for parameter uncertainty in simulated climate variables. We conducted a sensitivity study to these parameters, which built upon a previous study we made for standalone simulations (Urrego-Blanco et al., 2016, 2017). Using the results from the ensemble of coupled simulations, we are examining robust relationships between climate variables that emerge across the experiments. We are also using causal discovery techniques to identify interaction pathways among climate variables which can help identify physical mechanisms and provide guidance in predictability studies. This work further builds on and leverages the large ensemble of standalone sea ice simulations produced in our previous w14_seaice project.« less

Modeling mountain pine beetle habitat suitability within Sequoia National Park

NASA Astrophysics Data System (ADS)

Nguyen, Andrew

Understanding significant changes in climate and their effects on timber resources can help forest managers make better decisions regarding the preservation of natural resources and land management. These changes may to alter natural ecosystems dependent on historical and current climate conditions. Increasing mountain pine beetle (MBP) outbreaks within the southern Sierra Nevada are the result of these alterations. This study better understands MPB behavior within Sequoia National Park (SNP) and model its current and future habitat distribution. Variables contributing to MPB spread are vegetation stress, soil moisture, temperature, precipitation, disturbance, and presence of Ponderosa (Pinus ponderosa) and Lodgepole (Pinus contorta) pine trees. These variables were obtained using various modeled, insitu, and remotely sensed sources. The generalized additive model (GAM) was used to calculate the statistical significance of each variable contributing to MPB spread and also created maps identifying habitat suitability. Results indicate vegetation stress and forest disturbance to be variables most indicative of MPB spread. Additionally, the model was able to detect habitat suitability of MPB with a 45% accuracy concluding that a geospatial driven modeling approach can be used to delineate potential MPB spread within SNP.

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

PubMed

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

2014-11-01

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

Differential Impacts of Climate Change on Crops and Agricultural Regions in India

NASA Astrophysics Data System (ADS)

Sharma, A. N.

2015-12-01

As India's farmers and policymakers consider potential adaptation strategies to climate change, some questions loom large: - Which climate variables best explain the variability of crop yields? - How does the vulnerability of crop yields to climate vary regionally? - How are these risks likely to change in the future? While process-based crop modelling has started to answer many of these questions, we believe statistical approaches can complement these in improving our understanding of climate vulnerabilities and appropriate responses. We use yield data collected over three decades for more than ten food crops grown in India along with a variety of statistical approaches to answer the above questions. The ability of climate variables to explain yield variation varies greatly by crop and season, which is expected. Equally important, the ability of models to predict crop yields as well as their coefficients varies greatly by district even for districts which are relatively close to each other and similar in their agricultural practices. We believe these results encourage caution and nuance when making projections about climate impacts on crop yields in the future. Most studies about climate impacts on crop yields focus on a handful of major food crops. By extending our analysis to all the crops with long-term district level data in India as well as two growing seasons we gain a more comprehensive picture. Our results indicate that there is a great deal of variability even at relatively small scales, and that this must be taken into account if projections are to be made useful to policymakers.

Computational data sciences for assessment and prediction of climate extremes

NASA Astrophysics Data System (ADS)

Ganguly, A. R.

2011-12-01

Climate extremes may be defined inclusively as severe weather events or large shifts in global or regional weather patterns which may be caused or exacerbated by natural climate variability or climate change. This area of research arguably represents one of the largest knowledge-gaps in climate science which is relevant for informing resource managers and policy makers. While physics-based climate models are essential in view of non-stationary and nonlinear dynamical processes, their current pace of uncertainty reduction may not be adequate for urgent stakeholder needs. The structure of the models may in some cases preclude reduction of uncertainty for critical processes at scales or for the extremes of interest. On the other hand, methods based on complex networks, extreme value statistics, machine learning, and space-time data mining, have demonstrated significant promise to improve scientific understanding and generate enhanced predictions. When combined with conceptual process understanding at multiple spatiotemporal scales and designed to handle massive data, interdisciplinary data science methods and algorithms may complement or supplement physics-based models. Specific examples from the prior literature and our ongoing work suggests how data-guided improvements may be possible, for example, in the context of ocean meteorology, climate oscillators, teleconnections, and atmospheric process understanding, which in turn can improve projections of regional climate, precipitation extremes and tropical cyclones in an useful and interpretable fashion. A community-wide effort is motivated to develop and adapt computational data science tools for translating climate model simulations to information relevant for adaptation and policy, as well as for improving our scientific understanding of climate extremes from both observed and model-simulated data.

Functions of Parental Involvement and Effects of School Climate on Bullying Behaviors among South Korean Middle School Students

ERIC Educational Resources Information Center

Lee, Chang-Hun; Song, Juyoung

2012-01-01

This study uses an ecological systems theory to understand bullying behavior. Emphasis is given to overcome limitations found in the literature, such as very little empirical research on functions of parental involvement and the impacts of school climate on bullying as an outcome variable. Two functions of parental involvement investigated are (a)…

Sustained Satellite Missions for Climate Data Records

NASA Technical Reports Server (NTRS)

Halpern, David

2012-01-01

Satellite CDRs possess the accuracy, longevity, and stability for sustained moni toring of critical variables to enhance understanding of the global integrated Earth system and predict future conditions. center dot Satellite CDRs are a critical element of a global climate observing system. center dot Satellite CDRs are a difficult challenge and require high - level managerial commitment, extensive intellectual capital, and adequate funding.

Using fire regimes to delineate zones in a high-resolution lake sediment record from the western United States

Treesearch

Jesse L. Morris; Andrea Brunelle; R. Justin DeRose; Heikki Seppa; Mitchell J. Power; Vachel Carter; Ryan Bares

2013-01-01

Paleoenvironmental reconstructions are important for understanding the influence of long-term climate variability on ecosystems and landscape disturbance dynamics. In this paper we explore the linkages among past climate, vegetation, and fire regimes using a high-resolution pollen and charcoal reconstruction from Morris Pond located on the Markagunt Plateau in...

Climate Variability and Ponderosa Pine Colonizations in Central Wyoming: Integrating Dendroecology and Dendroclimatology

NASA Astrophysics Data System (ADS)

Lesser, M.; Wentzel, C.; Gray, S.; Jackson, S.

2007-12-01

Many tree species are predicted to expand into new territory over the coming decades in response to changing climate. By studying tree expansions over the last several centuries we can begin to understand the mechanisms underlying these changes and anticipate their consequences for forest management. Woody-plant demographics and decadal to multidecadal climate variability are often closely linked in semi-arid regions. Integrated tree-ring analysis, combining dendroecology and dendroclimatology to document, respectively, the demographic history of the population and the climatic history of the region, can reveal ecological dynamics in response to climate variability. We studied four small, disjunct populations of Pinus ponderosa in the Bighorn Basin of north-central Wyoming. These populations are located 30 to 100 kilometers from the nearest core populations of ponderosa pine in the western Bighorn Mountains. Packrat midden studies have shown that ponderosa pine colonized the western slopes of the Bighorn Range 1500 years ago, so the disjunct populations in the basin must be younger. All trees (living and dead) at each of the four disjunct populations were mapped, cored, and then aged using tree-ring based techniques. We obtained records of hydroclimatic variability from the Bighorn Basin using four tree-ring series from Pinus flexilis (3 sites) and Pseudotsuga menziesii (1 site). The four disjunct populations were all established within the past 500 years. Initially, the populations grew slowly with low recruitment rates until the early 19th century, when they experienced one or more large recruitment pulses. These pulses coincided with extended wet periods in the climate reconstruction. However, similar wet periods before the 19th Century were not accompanied by recruitment pulses, indicating that other factors (e.g., population density, genetic variability) are also important in colonization and expansion. We are currently obtaining genetic data and carrying out population modeling to differentiate the effects of population dynamics, genetic variability, and climate variability on recruitment and expansion of these populations.

Knowledge discovery and nonlinear modeling can complement climate model simulations for predictive insights about climate extremes and their impacts

NASA Astrophysics Data System (ADS)

Ganguly, A. R.; Steinbach, M.; Kumar, V.

2009-12-01

The IPCC AR4 not only provided conclusive evidence about anticipated global warming at century scales, but also indicated with a high level of certainty that the warming is caused by anthropogenic emissions. However, an outstanding knowledge-gap is to develop credible projections of climate extremes and their impacts. Climate extremes are defined in this context as extreme weather and hydrological events, as well as changes in regional hydro-meteorological patterns, especially at decadal scales. While temperature extremes from climate models have relatively better skills, hydrological variables and their extremes have significant shortcomings. Credible projections about tropical storms, sea level rise, coastal storm surge, land glacier melts, and landslides remain elusive. The next generation of climate models is expected to have higher precision. However, their ability to provide more accurate projections of climate extremes remains to be tested. Projections of observed trends into the future may not be reliable in non-stationary environments like climate change, even though functional relationships derived from physics may hold. On the other hand, assessments of climate change impacts which are useful for stakeholders and policy makers depend critically on regional and decadal scale projections of climate extremes. Thus, climate impacts scientists often need to develop qualitative inferences about the not so-well predicted climate extremes based on insights from observations (e.g., increased hurricane intensity) or conceptual understanding (e.g., relation of wildfires to regional warming or drying and hurricanes to SST). However, neither conceptual understanding nor observed trends may be reliable when extrapolating in a non-stationary environment. These urgent societal priorities offer fertile grounds for nonlinear modeling and knowledge discovery approaches. Thus, qualitative inferences on climate extremes and impacts may be transformed into quantitative predictive insights based on a combination of hypothesis-guided data analysis and relatively hypothesis-free but data-guided discovery processes. The analysis and discovery approaches need to be cognizant of climate data characteristics like nonlinear processes, low-frequency variability, long-range spatial dependence and long-memory temporal processes; the value of physically-motivated conceptual understanding and functional associations; as well as possible thresholds and tipping points in the impacted natural, engineered or human systems. Case studies focusing on new methodologies as well as novel climate insights are discussed with a focus on stakeholder requirements.

Drought change in the middle reach of the Yellow River since the late Ming Dynasty and their correlation with runoff

NASA Astrophysics Data System (ADS)

Chen, F.

2017-12-01

Because of the reported decreasing trends in precipitation and streamflow in north-central China (Starting point of Ancient Silk Road), it is essential to understand long-term in water resource availability in this area. Thus, this research presents a new February-August PDSI reconstruction spanning CE 1615-2013 for the southern edge of the Gobi Desert under a highly variable arid and semi-arid climate in northern China. In addition to this new PDSI reconstruction, some previously published annual precipitation/PDSI reconstructions from the neighbouring regions were also used to infer the large-scale hydro-climatic signal of the middle reach of the Yellow River. Spatial correlation analyses with gridded precipitation data showed that the tree-ring records were indeed able to capture much of the regional interannual hydro-climatic signal variability. Using principal component analyses on the reconstructions and documentary records, many large-scale dry and flood events were found during the period AD 1615-2006. Many of these dry events have had profound impacts on the people of the study area over the past several centuries. Temporal correlations among the reconstruction and climatic indices, such as the El Niño-Southern Oscillation, demonstrate that water availability is influenced by tropical and high-latitude forcings in the Pacific rim. Continued work in this direction should enable us to understand better the hydrological change under global warming and the past climate variability of the silk road over long temporal and large spatial scales.

Detrending phenological time series improves climate-phenology analyses and reveals evidence of plasticity.

PubMed

Iler, Amy M; Inouye, David W; Schmidt, Niels M; Høye, Toke T

2017-03-01

Time series have played a critical role in documenting how phenology responds to climate change. However, regressing phenological responses against climatic predictors involves the risk of finding potentially spurious climate-phenology relationships simply because both variables also change across years. Detrending by year is a way to address this issue. Additionally, detrending isolates interannual variation in phenology and climate, so that detrended climate-phenology relationships can represent statistical evidence of phenotypic plasticity. Using two flowering phenology time series from Colorado, USA and Greenland, we detrend flowering date and two climate predictors known to be important in these ecosystems: temperature and snowmelt date. In Colorado, all climate-phenology relationships persist after detrending. In Greenland, 75% of the temperature-phenology relationships disappear after detrending (three of four species). At both sites, the relationships that persist after detrending suggest that plasticity is a major component of sensitivity of flowering phenology to climate. Finally, simulations that created different strengths of correlations among year, climate, and phenology provide broader support for our two empirical case studies. This study highlights the utility of detrending to determine whether phenology is related to a climate variable in observational data sets. Applying this as a best practice will increase our understanding of phenological responses to climatic variation and change. © 2016 by the Ecological Society of America.

Predicting climate effects on Pacific sardine

PubMed Central

Deyle, Ethan R.; Fogarty, Michael; Hsieh, Chih-hao; Kaufman, Les; MacCall, Alec D.; Munch, Stephan B.; Perretti, Charles T.; Ye, Hao; Sugihara, George

2013-01-01

For many marine species and habitats, climate change and overfishing present a double threat. To manage marine resources effectively, it is necessary to adapt management to changes in the physical environment. Simple relationships between environmental conditions and fish abundance have long been used in both fisheries and fishery management. In many cases, however, physical, biological, and human variables feed back on each other. For these systems, associations between variables can change as the system evolves in time. This can obscure relationships between population dynamics and environmental variability, undermining our ability to forecast changes in populations tied to physical processes. Here we present a methodology for identifying physical forcing variables based on nonlinear forecasting and show how the method provides a predictive understanding of the influence of physical forcing on Pacific sardine. PMID:23536299

Contrasting scaling properties of interglacial and glacial climates

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter; Shao, Zhi-Gang

2017-04-01

Understanding natural climate variability is essential for assessments of climate change. This is reflected in the scaling properties of climate records. The scaling exponents of the interglacial and the glacial climates are fundamentally different. The Holocene record is monofractal, with a scaling exponent H˜0.7. On the contrary, the glacial record is multifractal, with a significantly higher scaling exponent H˜1.2, indicating a longer persistence time and stronger nonlinearities in the glacial climate. The glacial climate is dominated by the strong multi-millennial Dansgaard-Oeschger (DO) events influencing the long-time correlation. However, by separately analysing the last glacial maximum lacking DO events, here we find the same scaling for that period as for the full glacial period. The unbroken scaling thus indicates that the DO events are part of the natural variability and not externally triggered. At glacial time scales, there is a scale break to a trivial scaling, contrasting the DO events from the similarly saw-tooth-shaped glacial cycles. Ref: Zhi-Gang Shao and Peter Ditlevsen, Nature Comm. 7, 10951, 2016

The amplitude of decadal to multidecadal variability in precipitation simulated by state-of-the-art climate models

NASA Astrophysics Data System (ADS)

Ault, T. R.; Cole, J. E.; St. George, S.

2012-11-01

We assess the magnitude of decadal to multidecadal (D2M) variability in Climate Model Intercomparison Project 5 (CMIP5) simulations that will be used to understand, and plan for, climate change as part of the Intergovernmental Panel on Climate Change's 5th Assessment Report. Model performance on D2M timescales is evaluated using metrics designed to characterize the relative and absolute magnitude of variability at these frequencies. In observational data, we find that between 10% and 35% of the total variance occurs on D2M timescales. Regions characterized by the high end of this range include Africa, Australia, western North America, and the Amazon region of South America. In these areas D2M fluctuations are especially prominent and linked to prolonged drought. D2M fluctuations account for considerably less of the total variance (between 5% and 15%) in the CMIP5 archive of historical (1850-2005) simulations. The discrepancy between observation and model based estimates of D2M prominence reflects two features of the CMIP5 archive. First, interannual components of variability are generally too energetic. Second, decadal components are too weak in several key regions. Our findings imply that projections of the future lack sufficient decadal variability, presenting a limited view of prolonged drought and pluvial risk.

Global Meteorological Drought: A Synthesis of Current Understanding with a Focus on SST Drivers of Precipitation Deficits

NASA Technical Reports Server (NTRS)

Schubert, S.; Stewart, R.; Wang, H.; Barlow, M.; Berbery, H.; Cai, W.; Hoerling, M.; Kanikicharla, K.; Koster, R.; Lyon, B.;

Soil carbon cycling proxies: Understanding their critical role in predicting climate change feedbacks

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

Bailey, Vanessa L.; Bond-Lamberty, Ben; DeAngelis, Kristen

The complexity of processes and interactions that drive soil C dynamics necessitate the use of proxy variables to represent soil characteristics that cannot be directly measured (correlative proxies), or that aggregate information about multiple soil characteristics into one variable (integrative proxies). These proxies have proven useful for understanding the soil C cycle, which is highly variable in both space and time, and are now being used to make predictions of the C fate and persistence under future climate scenarios. As these proxies are used at increasingly larger scales, the C pools and processes that proxies represent must be thoughtfully consideredmore » in order to minimize uncertainties in empirical understanding, as well as in model parameters and in model outcomes. The importance of these uncertainties is further amplified by the current need to make predictions of the C cycle for the non steady state environmental conditions resulting from global climate change. To clarify the appropriate uses of proxy variables, we provide specific examples of proxy variables that could improve decision making, adaptation choices, and modeling skill, while not foreclosing on – and also encouraging – continued work on their mechanistic underpinnings. We explore the use of three common soil proxies used to study soil organic matter: metabolic quotient, clay content, and physical fractionation. We also consider emerging data types, specifically genome-sequence data, and how these serve as proxies for microbial community activities. We opine that the demand for increasing mechanistic detail, and the flood of data from new imaging and genetic techniques, does not replace the value of correlative and integrative proxies--variables that are simpler, easier, or cheaper to measure. By closely examining the current knowledge gaps and broad assumptions in soil C cycling with the proxies already in use, we can develop new hypotheses and specify criteria for new and needed proxies.« less

Quantitative predictions of streamflow variability in the Susquehanna River Basin

NASA Astrophysics Data System (ADS)

Alexander, R.; Boyer, E. W.; Leonard, L. N.; Duffy, C.; Schwarz, G. E.; Smith, R. A.

2012-12-01

Hydrologic researchers and water managers have increasingly sought an improved understanding of the major processes that control fluxes of water and solutes across diverse environmental settings and large spatial scales. Regional analyses of observed streamflow data have led to advances in our knowledge of relations among land use, climate, and streamflow, with methodologies ranging from statistical assessments of multiple monitoring sites to the regionalization of the parameters of catchment-scale mechanistic simulation models. However, gaps remain in our understanding of the best ways to transfer the knowledge of hydrologic response and governing processes among locations, including methods for regionalizing streamflow measurements and model predictions. We developed an approach to predict variations in streamflow using the SPARROW (SPAtially Referenced Regression On Watershed attributes) modeling infrastructure, with mechanistic functions, mass conservation constraints, and statistical estimation of regional and sub-regional parameters. We used the model to predict discharge in the Susquehanna River Basin (SRB) under varying hydrological regimes that are representative of contemporary flow conditions. The resulting basin-scale water balance describes mean monthly flows in stream reaches throughout the entire SRB (represented at a 1:100,000 scale using the National Hydrologic Data network), with water supply and demand components that are inclusive of a range of hydrologic, climatic, and cultural properties (e.g., precipitation, evapotranspiration, soil and groundwater storage, runoff, baseflow, water use). We compare alternative models of varying complexity that reflect differences in the number and types of explanatory variables and functional expressions as well as spatial and temporal variability in the model parameters. Statistical estimation of the models reveals the levels of complexity that can be uniquely identified, subject to the information content and uncertainties of the hydrologic and climate measurements. Assessment of spatial variations in the model parameters and predictions provides an improved understanding of how much of the hydrologic response to land use, climate, and other properties is unique to specific locations versus more universally observed across catchments of the SRB. This approach advances understanding of water cycle variability at any location throughout the stream network, as a function of both landscape characteristics (e.g., soils, vegetation, land use) and external forcings (e.g., precipitation quantity and frequency). These improvements in predictions of streamflow dynamics will advance the ability to predict spatial and temporal variability in key solutes, such as nutrients, and their delivery to the Chesapeake Bay.

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.

Global patterns in the poleward expansion of mangrove forests

NASA Astrophysics Data System (ADS)

Cavanaugh, K. C.; Feller, I. C.

2016-12-01

Understanding the processes that limit the geographic ranges of species is one of the central goals of ecology and biogeography. This issue is particularly relevant for coastal wetlands given that climate change is expected to lead to a `tropicalization' of temperate coastal and marine ecosystems. In coastal wetlands around the world, there have already been observations of mangroves expanding into salt marshes near the current poleward range limits of mangroves. However, there is still uncertainty regarding regional variability in the factors that control mangrove range limits. Here we used time series of Landsat satellite imagery to characterize patterns of mangrove abundance near their poleward range limits around the world. We tested the commonly held assumption that temporal variation in abundance should increase towards the edge of the range. We also compared variability in mangrove abundance to climate factors thought to set mangrove range limits (air temperature, water temperature, and aridity). In general, variability in mangrove abundance at range edges was high relative to range centers and this variability was correlated to one or more climate factors. However, the strength of these relationships varied among poleward range limits, suggesting that some mangrove range limits are control by processes other than climate, such as dispersal limitation.

Reconstructing Past Seasonal to Multicentennial-Scale Variability in the NE Atlantic Ocean Using the Long-Lived Marine Bivalve Mollusk Glycymeris glycymeris

NASA Astrophysics Data System (ADS)

Reynolds, D. J.; Hall, I. R.; Slater, S. M.; Scourse, J. D.; Halloran, P. R.; Sayer, M. D. J.

2017-11-01

The lack of long-term, highly resolved (annual to subannual) and absolutely dated baseline records of marine variability extending beyond the instrumental period (last 50-100 years) hinders our ability to develop a comprehensive understanding of the role the ocean plays in the climate system. Specifically, without such records, it remains difficult to fully quantify the range of natural climate variability mediated by the ocean and to robustly attribute recent changes to anthropogenic or natural drivers. Here we present a 211 year (1799-2010 C.E.; all dates hereafter are Common Era) seawater temperature (SWT) reconstruction from the northeast Atlantic Ocean derived from absolutely dated, annually resolved, oxygen isotope ratios recorded in the shell carbonate (δ18Oshell) of the long-lived marine bivalve mollusk Glycymeris glycymeris. The annual record was calibrated using subannually resolved δ18Oshell values drilled from multiple shells covering the instrumental period. Calibration verification statistics and spatial correlation analyses indicate that the δ18Oshell record contains significant skill at reconstructing Northeast Atlantic Ocean mean summer SWT variability associated with changes in subpolar gyre dynamics and the North Atlantic Current. Reconciling differences between the δ18Oshell data and corresponding growth increment width chronology demonstrates that 68% of the variability in G. glycymeris shell growth can be explained by the combined influence of biological productivity and SWT variability. These data suggest that G. glycymeris can provide seasonal to multicentennial absolutely dated baseline records of past marine variability that will lead to the development of a quantitative understanding of the role the marine environment plays in the global climate system.

Visualization and Analysis of Climate Simulation Performance Data

NASA Astrophysics Data System (ADS)

Röber, Niklas; Adamidis, Panagiotis; Behrens, Jörg

2015-04-01

Visualization is the key process of transforming abstract (scientific) data into a graphical representation, to aid in the understanding of the information hidden within the data. Climate simulation data sets are typically quite large, time varying, and consist of many different variables sampled on an underlying grid. A large variety of climate models - and sub models - exist to simulate various aspects of the climate system. Generally, one is mainly interested in the physical variables produced by the simulation runs, but model developers are also interested in performance data measured along with these simulations. Climate simulation models are carefully developed complex software systems, designed to run in parallel on large HPC systems. An important goal thereby is to utilize the entire hardware as efficiently as possible, that is, to distribute the workload as even as possible among the individual components. This is a very challenging task, and detailed performance data, such as timings, cache misses etc. have to be used to locate and understand performance problems in order to optimize the model implementation. Furthermore, the correlation of performance data to the processes of the application and the sub-domains of the decomposed underlying grid is vital when addressing communication and load imbalance issues. High resolution climate simulations are carried out on tens to hundreds of thousands of cores, thus yielding a vast amount of profiling data, which cannot be analyzed without appropriate visualization techniques. This PICO presentation displays and discusses the ICON simulation model, which is jointly developed by the Max Planck Institute for Meteorology and the German Weather Service and in partnership with DKRZ. The visualization and analysis of the models performance data allows us to optimize and fine tune the model, as well as to understand its execution on the HPC system. We show and discuss our workflow, as well as present new ideas and solutions that greatly aided our understanding. The software employed is based on Avizo Green, ParaView and SimVis, as well as own developed software extensions.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

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

PubMed

Vincenzi, Simone

2014-08-06

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

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Geo(spatial) Health Investigation of Rotavirus in an Endemic Region: Hydroclimatic Influences and Epidemiology of Rotavirus in Bangladesh

NASA Astrophysics Data System (ADS)

Hasan, M. A.; Akanda, A. S.; Jutla, A.; Colwell, R. R.

2016-12-01

Rotavirus is the leading cause of severe dehydrating diarrhea among children under 5. Over 80% of the approximate half a million child deaths every year occur in South Asia and sub-Saharan Africa alone. Although less explored than cholera as a climate driven and influenced global health problem, recent studies have showed that the disease shown strong seasonality and spatio-temporal variability depending on regional hydroclimatic and local environmental conditions. Understanding the epidemiology of this disease, especially the spatio-temporal incidence patterns with respect to environmental factors is vitally important to allow for identification of "hotspots", preventative preparations, and vaccination strategies to improve wellbeing of the vulnerable populations. With climate change, spatio-temporal signatures and footprints of the disease are changing along with increasing burden. However, a robust understanding of the relationships between rotavirus epidemiology and hydroclimatic drivers is yet to be developed. In this study, we evaluate the seasonality and epidemiologic characteristics of rotavirous infection and its spatio-temporal incidence patterns with respect to regional hydroclimatic variables and their extremes in an endemic region in South Asia. Hospital-based surveillance data from different geographic locations allowed us to explore the detailed spatial and temporal characteristics of rotavirus propagation under the influence of climate variables in both coastal and inland areas. The rotavirus transmission patterns show two peaks in a year in the capital city of Dhaka, where winter season (highest in January) shows a high peak and the July-August monsoon season shows a smaller peak. Correlation with climate variables revealed that minimum temperature has strong influence on the winter season outbreak, while rainfall extremes show a strong positive association with the secondary monsoon peak. Spatial analysis also revealed that humidity and soil wetness may influence the timing as drier areas experience earlier outbreaks than wetter areas. Accurate understanding of rotavirus propagation with respect to hydroclimatic and environmental variability can be utilized to establish global surveillance and forecast imminent risk of diarrheal outbreaks in vulnerable regions.

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

PubMed

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

2016-09-01

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

Unified Synthesis Product (USP) Recommendations

NASA Astrophysics Data System (ADS)

Peterson, T. C.

2009-05-01

The USP identifies a number of areas in which inadequate information or understanding hampers our ability to estimate likely future climate change and its impacts. For example, our knowledge of changes in tornadoes, hail, and ice storms is quite limited, making it difficult to know if and how such events have changed as climate has warmed, and how they might change in the future. Research on ecological responses to climate change also is limited, as is our understanding of social responses. The Report identifies the five most important gaps in knowledge and offers some thoughts on how to address those gaps: 1. Expand our understanding of climate change impacts. There is a clear need to increase understanding of how ecosystems, social and economic systems, human health, and the built environment will be affected by climate change in the context of other stresses. This includes ecosystems as well as economic systems, human health, and the built environment. 2. Refine ability to project climate change at local scales. One of the main messages to emerge from the past decade of synthesis and assessments is that while climate change is a global issue, it has a great deal of regional variability. There is an indisputable need to improve understanding of climate system effects at these smaller scales, because these are often the scales of decision-making in society. 3. Expand capacity to provide decision makers and the public with relevant information on climate change and its impacts. The United States has tremendous potential to create more comprehensive measurement, archive, and data-access systems that could provide great benefit to society. 4. Improve understanding of and ability to identify thresholds likely to lead to abrupt changes in the climate system. Paleoclimatic data shows that climate can and has changed quite abruptly when certain thresholds are crossed. Similarly, there is evidence that ecological and human systems can undergo abrupt change when tipping points are reached. 5. Enhance understanding of how society can adapt to climate change in the context of multiple stresses. There is currently limited knowledge about the ability of communities, regions, and sectors to adapt to future climate change. It is essential to improve understanding of how the capacity to adapt to a changing climate might be exercised, and the vulnerabilities to climate change and other environmental stresses that might remain. Results from these efforts would inform future assessments that continue building our understanding of humanity's impacts on climate, and climate's impacts on us. Such assessments will continue to play a role in helping the U.S. respond to changing conditions. A vision for future climate change assessments includes both sustained extensive practitioner and stakeholder involvement, and periodic, targeted, scientifically rigorous reports similar to the CCSP Synthesis and Assessment Products.

Population, Environment, and Climate in the Albertine Rift: Understanding Local Impacts of Regional Change

NASA Astrophysics Data System (ADS)

Hartter, J.; Ryan, S. J.; Diem, J.; Palace, M. W.

2012-12-01

Climate change is of critical concern for conservation and to develop appropriate policies and responses, it is important not only to anticipate the nature of changes, but also how they are perceived, interpreted and adapted to by local people. The Albertine Rift in East Africa is one of the most threatened biodiversity hotspots due to dense settlement, extreme poverty, and land conversion. We synthesize ongoing NSF-CNH research, where Ugandan park landscapes are examined to understand the impacts of climate change on livelihoods. Kibale National Park, the main study site, exemplifies the challenges facing many parks because of its isolation within a densely populated agricultural landscape. Three separate household surveys (n=251, 130, 100) reveal that the most perceived benefits provided by Kibale were ecosystem services and farmers cite rainfall as one of the park's most important benefits, but are also concerned with variable precipitation. Analysis of 30+ years of daily rainfall station data shows total rainfall has not changed significantly, but timing and transitions of seasons and intra-seasonal distribution are highly variable, which may contribute to changes in farming schedules and threaten food security. Further, the contrast between land use/cover change over 25 years around the park and the stability of forest within the park underscores the need to understand this landscape for future sustainability planning and the inevitable population growth outside its boundaries. Understanding climate change impacts and feedbacks to and from socio-ecological systems are important to address the dual challenge of biodiversity conservation and poverty alleviation.

Modeling the role of environmental variables on the population dynamics of the malaria vector Anopheles gambiae sensu stricto

PubMed Central

2012-01-01

Background The impact of weather and climate on malaria transmission has attracted considerable attention in recent years, yet uncertainties around future disease trends under climate change remain. Mathematical models provide powerful tools for addressing such questions and understanding the implications for interventions and eradication strategies, but these require realistic modeling of the vector population dynamics and its response to environmental variables. Methods Published and unpublished field and experimental data are used to develop new formulations for modeling the relationships between key aspects of vector ecology and environmental variables. These relationships are integrated within a validated deterministic model of Anopheles gambiae s.s. population dynamics to provide a valuable tool for understanding vector response to biotic and abiotic variables. Results A novel, parsimonious framework for assessing the effects of rainfall, cloudiness, wind speed, desiccation, temperature, relative humidity and density-dependence on vector abundance is developed, allowing ease of construction, analysis, and integration into malaria transmission models. Model validation shows good agreement with longitudinal vector abundance data from Tanzania, suggesting that recent malaria reductions in certain areas of Africa could be due to changing environmental conditions affecting vector populations. Conclusions Mathematical models provide a powerful, explanatory means of understanding the role of environmental variables on mosquito populations and hence for predicting future malaria transmission under global change. The framework developed provides a valuable advance in this respect, but also highlights key research gaps that need to be resolved if we are to better understand future malaria risk in vulnerable communities. PMID:22877154

The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors

NASA Astrophysics Data System (ADS)

Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.

2016-12-01

Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection capabilities of existing sensors.

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

NASA Astrophysics Data System (ADS)

Vallam, P.; Qin, X. S.

2017-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Effects of climate and fire on short-term vegetation recovery in the boreal larch forests of Northeastern China.

PubMed

Liu, Zhihua

2016-11-18

Understanding the influence of climate variability and fire characteristics in shaping postfire vegetation recovery will help to predict future ecosystem trajectories in boreal forests. In this study, I asked: (1) which remotely-sensed vegetation index (VI) is a good proxy for vegetation recovery? and (2) what are the relative influences of climate and fire in controlling postfire vegetation recovery in a Siberian larch forest, a globally important but poorly understood ecosystem type? Analysis showed that the shortwave infrared (SWIR) VI is a good indicator of postfire vegetation recovery in boreal larch forests. A boosted regression tree analysis showed that postfire recovery was collectively controlled by processes that controlled seed availability, as well as by site conditions and climate variability. Fire severity and its spatial variability played a dominant role in determining vegetation recovery, indicating seed availability as the primary mechanism affecting postfire forest resilience. Environmental and immediate postfire climatic conditions appear to be less important, but interact strongly with fire severity to influence postfire recovery. If future warming and fire regimes manifest as expected in this region, seed limitation and climate-induced regeneration failure will become more prevalent and severe, which may cause forests to shift to alternative stable states.

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

PubMed Central

Allainé, Dominique; Sauzet, Sandrine; Cohas, Aurélie

2016-01-01

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

Effects of climate and fire on short-term vegetation recovery in the boreal larch forests of Northeastern China

PubMed Central

Liu, Zhihua

2016-01-01

Understanding the influence of climate variability and fire characteristics in shaping postfire vegetation recovery will help to predict future ecosystem trajectories in boreal forests. In this study, I asked: (1) which remotely-sensed vegetation index (VI) is a good proxy for vegetation recovery? and (2) what are the relative influences of climate and fire in controlling postfire vegetation recovery in a Siberian larch forest, a globally important but poorly understood ecosystem type? Analysis showed that the shortwave infrared (SWIR) VI is a good indicator of postfire vegetation recovery in boreal larch forests. A boosted regression tree analysis showed that postfire recovery was collectively controlled by processes that controlled seed availability, as well as by site conditions and climate variability. Fire severity and its spatial variability played a dominant role in determining vegetation recovery, indicating seed availability as the primary mechanism affecting postfire forest resilience. Environmental and immediate postfire climatic conditions appear to be less important, but interact strongly with fire severity to influence postfire recovery. If future warming and fire regimes manifest as expected in this region, seed limitation and climate-induced regeneration failure will become more prevalent and severe, which may cause forests to shift to alternative stable states. PMID:27857204

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

PubMed

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

2016-12-28

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

Crossing Scales and Disciplines to Understand Challenges for Climate Change Adaptation and Water Resources Management in Chile and Californi

NASA Astrophysics Data System (ADS)

Vicuna, S.; Melo, O.; Meza, F. J.; Medellin-Azuara, J.; Herman, J. D.; Sandoval Solis, S.

2017-12-01

California and Chile share similarities in terms of climate, ecosystems, topography and water use. In both regions, the hydro-climatologic system is characterized by a typical Mediterranean climate, rainy winters and dry summers, highly variable annual precipitation, and snowmelt-dependent water supply systems. Water use in both regions has also key similarities, with the highest share devoted to high-value irrigated crops, followed by urban water use and a significant hydropower-driven power supply system. Snowmelt-driven basins in semiarid regions are highly sensitive to climate change for two reasons, temperature effects on snowmelt timing and water resources scarcity in these regions subject to ever-increasing demands. Research in both regions also coincide in terms of the potential climate change impacts. Expected impacts on California and Chile water resources have been well-documented in terms of changes in water supply and water demand, though significant uncertainties remain. Both regions have recently experienced prolonged droughts, providing an opportunity to understand the future challenges and potential adaptive responses under climate change. This study connects researchers from Chile and California with the goal of understanding the problem of how to adapt to climate change impacts on water resources and agriculture at the various spatial and temporal scales. The project takes advantage of the complementary contexts between Chile and California in terms of similar climate and hydrologic conditions, water management institutions, patterns of water consumption and, importantly, a similar challenge facing recent drought scenarios to understand the challenges faced by a changing climate.

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.

The combination of work organizational climate and individual work commitment predicts return to work in women but not in men.

PubMed

Holmgren, Kristina; Ekbladh, Elin; Hensing, Gunnel; Dellve, Lotta

2013-02-01

To analyze if the combination of organizational climate and work commitment can predict return to work (RTW). This prospective Swedish study was based on 2285 participants, 19 to 64 years old, consecutively selected from the employed population, newly sick-listed for more than 14 days. Data were collected in 2008 through postal questionnaire and from register data. Among women, the combination of good organizational climate and fair work commitment predicted an early RTW with an adjusted relative risk of 2.05 (1.32 to 3.18). Among men, none of the adjusted variables or combinations of variables was found significantly to predict RTW. This study demonstrated the importance of integrative effects of organizational climate and individual work commitment on RTW among women. These factors did not predict RTW in men. More research is needed to understand the RTW process among men.

Advanced spectral methods for climatic time series

USGS Publications Warehouse

Ghil, M.; Allen, M.R.; Dettinger, M.D.; Ide, K.; Kondrashov, D.; Mann, M.E.; Robertson, A.W.; Saunders, A.; Tian, Y.; Varadi, F.; Yiou, P.

2002-01-01

The analysis of univariate or multivariate time series provides crucial information to describe, understand, and predict climatic variability. The discovery and implementation of a number of novel methods for extracting useful information from time series has recently revitalized this classical field of study. Considerable progress has also been made in interpreting the information so obtained in terms of dynamical systems theory. In this review we describe the connections between time series analysis and nonlinear dynamics, discuss signal- to-noise enhancement, and present some of the novel methods for spectral analysis. The various steps, as well as the advantages and disadvantages of these methods, are illustrated by their application to an important climatic time series, the Southern Oscillation Index. This index captures major features of interannual climate variability and is used extensively in its prediction. Regional and global sea surface temperature data sets are used to illustrate multivariate spectral methods. Open questions and further prospects conclude the review.

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

PubMed

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

2018-05-01

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

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

PubMed

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

2017-09-20

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

The PAGES 2k Network, Phase 3: Introduction, Goals and Call for Participation

NASA Astrophysics Data System (ADS)

McGregor, Helen; Phipps, Steven; von Gunten, Lucien; Martrat, Belen; Linderholm, Lars; Abram, Nerilie; Bothe, Oliver; Neukom, Raphael; St. George, Scott; Evans, Michael; Kaufman, Darrell; Goosse, Hugues; Turney, Chris

2017-04-01

The past 2000 years (the "2k" interval) provides critical context for recent anthropogenic forcing of the climate, baseline information about Earth's natural climate variability, opportunities to improve the interpretation of proxy observations, and evaluation of climate models. The PAGES 2k Network (2008-2013 Phase 1; 2014-2016 Phase 2) built regional and global surface temperature reconstructions for terrestrial regions and the oceans, and used comparison with realistically forced simulations to identify mechanisms of climate variation on interannual to bicentennial time scales. The goals of Phase 3 (2017-2019), which launches in May 2017 at the PAGES Open Science Meeting, are to: 1) Further understand the mechanisms driving regional climate variability and change on interannual to centennial time scales (Theme: "Climate Variability, Modes and Mechanisms"); 2) Reduce uncertainties in the interpretation of observations imprinted in paleoclimatic archives by environmental sensors (Theme: "Methods and Uncertainties"); and 3) Identify and analyse the extent of agreement between reconstructions and climate model simulations (Theme: "Proxy and Model Understanding") Research will be organized as a linked network of well-defined projects and targeted manuscripts, identified and led by 2k members. The 2k projects will focus on specific scientific questions aligned with Phase 3 goals, rather than being defined along regional boundaries. An enduring element from earlier phases of PAGES 2k will be a culture of collegiality, transparency, and reciprocity. Phase 3 seeks to stimulate community based projects and facilitate collaboration of researchers from different regions and career stages, drawing on breadth and depth of the global PAGES 2k community; support end-to-end workflow transparency and open data and knowledge access; and develop collaborations with other research communities and engage with stakeholders. If you would like to participate in PAGES 2k Phase 3 or receive updates, please join our mailing list, or speak to a coordinating committee member.

The influence of soil-site factors on sugar maple (Acer saccharum Marsh.) growth response to climatic change in central Ontario

NASA Astrophysics Data System (ADS)

Schutten, K.; Gedalof, Z.

2010-12-01

Over the past several decades, concerns about climatic change and its potential impacts on Canada’s various geographical regions and associated ecological processes have grown steadily, especially among land and resource managers. As these risks transition into tangible outcomes in the field, it will be important for resource managers to understand historical climatic variability and natural ecological trends in order to effectively respond to a changing climate. Sugar maple (Acer saccharum Marsh.) is considered a stable endpoint for mature forests in the northern hardwood community of central Ontario, and it tends to be the dominant species, in a beech-ironwood-yellow birch matrix. In North America, this species is used for both hardwood lumber and for maple sugar (syrup) products; where it dominates, large recreational opportunities also exist. There are many biotic and abiotic factors that play a large role in the growth and productivity of sugar maple stands, such as soil pH, moisture regime, and site slope and aspect. This research undertaking aims to add to the body of literature addressing the following question: how do site factors influence the sensitivity of sugar maple growth to climatic change? The overall objective of the research is to evaluate how biotic and abiotic factors influence the sensitivity of sugar maple annual radial growth to climatic variability. This research will focus on sugar maple growth and productivity in Algonquin Provincial Park, and the impact that climatic variability has had in the past on these stands based on site-specific characteristics. In order to complete this goal, 20 sites were identified in Algonquin Provincial Park based on variability of known soil and site properties. These sites were visited in order to collect biotic and abiotic site data, and to measure annual radial growth increment of trees. Using regional climate records and standard dendrochronological methods, the collected increment growth data will be used to build site-specific chronologies in order to determine the differences in tree growth response to climatic variability due to differences in soil and site quality. Preliminary results suggest that variability in site-specific abiotic and biotic conditions may strongly influence individual stand growth responses to climatic variability.

The influence of ENSO, PDO and PNA on secular rainfall variations in Hawai‘i

Treesearch

Abby G. Frazier; Oliver Elison Timm; Thomas W. Giambelluca; Henry F. Diaz

2017-01-01

Over the last century, significant declines in rainfall across the state of Hawai‘i have been observed, and it is unknown whether these declines are due to natural variations in climate, or manifestations of human-induced climate change. Here, a statistical analysis of the observed rainfall variability was applied as first step towards better understanding causes for...

Drought impacts on ecosystem functions of the U.S. National Forests and Grasslands: Part I evaluation of a water and carbon balance model

Treesearch

Shanlei Sun; Ge Sun; Peter Caldwell; Steven G. McNulty; Erika Cohen; Jingfeng Xiao; Yang Zhang

2015-01-01

Understanding and quantitatively evaluating the regional impacts of climate change and variability (e.g., droughts) on forest ecosystem functions (i.e., water yield, evapotranspiration, and productivity) and services (e.g., fresh water supply and carbon sequestration) is of great importance for developing climate change adaptation strategies for National Forests and...

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.

Old World megadroughts and pluvials during the Common Era.

PubMed

Cook, Edward R; Seager, Richard; Kushnir, Yochanan; Briffa, Keith R; Büntgen, Ulf; Frank, David; Krusic, Paul J; Tegel, Willy; van der Schrier, Gerard; Andreu-Hayles, Laia; Baillie, Mike; Baittinger, Claudia; Bleicher, Niels; Bonde, Niels; Brown, David; Carrer, Marco; Cooper, Richard; Čufar, Katarina; Dittmar, Christoph; Esper, Jan; Griggs, Carol; Gunnarson, Björn; Günther, Björn; Gutierrez, Emilia; Haneca, Kristof; Helama, Samuli; Herzig, Franz; Heussner, Karl-Uwe; Hofmann, Jutta; Janda, Pavel; Kontic, Raymond; Köse, Nesibe; Kyncl, Tomáš; Levanič, Tom; Linderholm, Hans; Manning, Sturt; Melvin, Thomas M; Miles, Daniel; Neuwirth, Burkhard; Nicolussi, Kurt; Nola, Paola; Panayotov, Momchil; Popa, Ionel; Rothe, Andreas; Seftigen, Kristina; Seim, Andrea; Svarva, Helene; Svoboda, Miroslav; Thun, Terje; Timonen, Mauri; Touchan, Ramzi; Trotsiuk, Volodymyr; Trouet, Valerie; Walder, Felix; Ważny, Tomasz; Wilson, Rob; Zang, Christian

2015-11-01

Climate model projections suggest widespread drying in the Mediterranean Basin and wetting in Fennoscandia in the coming decades largely as a consequence of greenhouse gas forcing of climate. To place these and other "Old World" climate projections into historical perspective based on more complete estimates of natural hydroclimatic variability, we have developed the "Old World Drought Atlas" (OWDA), a set of year-to-year maps of tree-ring reconstructed summer wetness and dryness over Europe and the Mediterranean Basin during the Common Era. The OWDA matches historical accounts of severe drought and wetness with a spatial completeness not previously available. In addition, megadroughts reconstructed over north-central Europe in the 11th and mid-15th centuries reinforce other evidence from North America and Asia that droughts were more severe, extensive, and prolonged over Northern Hemisphere land areas before the 20th century, with an inadequate understanding of their causes. The OWDA provides new data to determine the causes of Old World drought and wetness and attribute past climate variability to forced and/or internal variability.

Characterizing Climate Controls on Vegetation Seasonality in the North American Southwest

NASA Astrophysics Data System (ADS)

Fish, M. A.; Cook, B.; Smerdon, J. E.; Seager, R.; Williams, P.

2014-12-01

The North American Southwest, which extends from Colorado to southern Mexico and California to eastern Texas, encompasses a diversity of climates, elevations, and ecosystems. This region is expected to experience significant climatic change, and associated impacts, in the coming decades. To better understand the spatiotemporal variability of vegetation in the Southwest and the expected climatic controls on timing and spatial extend of vegetation growth, we compared GIMMS normalized difference vegetation index (NDVI, 1981-2011) against temperature and precipitation data. Spatial variations in vegetation seasonality and the timing of peak NDVI are linked to spatial variability in the precipitation regimes across the Southwest. Regions with spring NDVI peaks are dominated by winter precipitation, while late summer and fall peaks are in regions with significant summer precipitation driven by the North American Monsoon. Inter-annual variability in peak NDVI is positively correlated with precipitation and negatively correlated with temperature, with the largest correlation coefficients at one-month lags. The only significant long-term trends in NDVI are for northern Mexico, where agricultural productivity has been increasing over the last 30 years.

Old World megadroughts and pluvials during the Common Era

PubMed Central

Cook, Edward R.; Seager, Richard; Kushnir, Yochanan; Briffa, Keith R.; Büntgen, Ulf; Frank, David; Krusic, Paul J.; Tegel, Willy; van der Schrier, Gerard; Andreu-Hayles, Laia; Baillie, Mike; Baittinger, Claudia; Bleicher, Niels; Bonde, Niels; Brown, David; Carrer, Marco; Cooper, Richard; Čufar, Katarina; Dittmar, Christoph; Esper, Jan; Griggs, Carol; Gunnarson, Björn; Günther, Björn; Gutierrez, Emilia; Haneca, Kristof; Helama, Samuli; Herzig, Franz; Heussner, Karl-Uwe; Hofmann, Jutta; Janda, Pavel; Kontic, Raymond; Köse, Nesibe; Kyncl, Tomáš; Levanič, Tom; Linderholm, Hans; Manning, Sturt; Melvin, Thomas M.; Miles, Daniel; Neuwirth, Burkhard; Nicolussi, Kurt; Nola, Paola; Panayotov, Momchil; Popa, Ionel; Rothe, Andreas; Seftigen, Kristina; Seim, Andrea; Svarva, Helene; Svoboda, Miroslav; Thun, Terje; Timonen, Mauri; Touchan, Ramzi; Trotsiuk, Volodymyr; Trouet, Valerie; Walder, Felix; Ważny, Tomasz; Wilson, Rob; Zang, Christian

2015-01-01

Climate model projections suggest widespread drying in the Mediterranean Basin and wetting in Fennoscandia in the coming decades largely as a consequence of greenhouse gas forcing of climate. To place these and other “Old World” climate projections into historical perspective based on more complete estimates of natural hydroclimatic variability, we have developed the “Old World Drought Atlas” (OWDA), a set of year-to-year maps of tree-ring reconstructed summer wetness and dryness over Europe and the Mediterranean Basin during the Common Era. The OWDA matches historical accounts of severe drought and wetness with a spatial completeness not previously available. In addition, megadroughts reconstructed over north-central Europe in the 11th and mid-15th centuries reinforce other evidence from North America and Asia that droughts were more severe, extensive, and prolonged over Northern Hemisphere land areas before the 20th century, with an inadequate understanding of their causes. The OWDA provides new data to determine the causes of Old World drought and wetness and attribute past climate variability to forced and/or internal variability. PMID:26601136

Process connectivity reveals ecohydrologic sensitivity to drought and rainfall pulses

NASA Astrophysics Data System (ADS)

Goodwell, A. E.; Kumar, P.

2017-12-01

Ecohydrologic fluxes within atmosphere, canopy and soil systems exhibit complex and joint variability. This complexity arises from direct and indirect forcing and feedback interactions that can cause fluctuations to propagate between water, energy, and nutrient fluxes at various time scales. When an ecosystem is perturbed in the form of a single storm event, an accumulating drought, or changes in climate and land cover, this aspect of joint variability may dictate responsiveness and resilience of the entire system. A characterization of the time-dependent and multivariate connectivity between processes, fluxes, and states is necessary to identify and understand these aspects of ecohydrologic systems. We construct Temporal Information Partitioning Networks (TIPNets), based on information theory measures, to identify time-dependencies between variables measured at flux towers along elevation and climate gradients in relation to their responses to moisture-related perturbations. Along a flux tower transect in the Reynolds Creek Critical Zone Observatory (CZO) in Idaho, we detect a significant network response to a large 2015 dry season rainfall event that enhances microbial respiration and latent heat fluxes. At a transect in the Southern Sierra CZO in California, we explore network properties in relation to drought responses from 2011 to 2015. We find that both high and low elevation sites exhibit decreased connectivity between atmospheric and soil variables and latent heat fluxes, but the higher elevation site is less sensitive to this altered connectivity in terms of average monthly heat fluxes. Through a novel approach to gage the responsiveness of ecosystem fluxes to shifts in connectivity, this study aids our understanding of ecohydrologic sensitivity to short-term rainfall events and longer term droughts. This study is relevant to ecosystem resilience under a changing climate, and can lead to a greater understanding of shifting behaviors in many types of complex systems.

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.

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

NASA Technical Reports Server (NTRS)

Roberts, Yolanda; Pilewskie, Peter; Kindel, Bruce; Feldman, Daniel; Collins, William D.

2012-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Use of NARCCAP data to characterize regional climate uncertainty in the impact of global climate change on large river fish population: Missouri River sturgeon example

NASA Astrophysics Data System (ADS)

Anderson, C. J.; Wildhaber, M. L.; Wikle, C. K.; Moran, E. H.; Franz, K. J.; Dey, R.

2012-12-01

Climate change operates over a broad range of spatial and temporal scales. Understanding the effects of change on ecosystems requires accounting for the propagation of information and uncertainty across these scales. For example, to understand potential climate change effects on fish populations in riverine ecosystems, climate conditions predicted by course-resolution atmosphere-ocean global climate models must first be translated to the regional climate scale. In turn, this regional information is used to force watershed models, which are used to force river condition models, which impact the population response. A critical challenge in such a multiscale modeling environment is to quantify sources of uncertainty given the highly nonlinear nature of interactions between climate variables and the individual organism. We use a hierarchical modeling approach for accommodating uncertainty in multiscale ecological impact studies. This framework allows for uncertainty due to system models, model parameter settings, and stochastic parameterizations. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. We use NARCCAP data to determine confidence the capability of climate models to simulate relevant processes and to quantify regional climate variability within the context of the hierarchical model of uncertainty quantification. By confidence, we mean the ability of the regional climate model to replicate observed mechanisms. We use the NCEP-driven simulations for this analysis. This provides a base from which regional change can be categorized as either a modification of previously observed mechanisms or emergence of new processes. The management implications for these categories of change are significantly different in that procedures to address impacts from existing processes may already be known and need adjustment; whereas, an emergent processes may require new management strategies. The results from hierarchical analysis of uncertainty are used to study the relative change in weights of the endangered Missouri River pallid sturgeon (Scaphirhynchus albus) under a 21st century climate scenario.

Understanding north-western Mediterranean climate variability: a multi-proxy and multi-sequence approach based on wavelet analysis.

NASA Astrophysics Data System (ADS)

Azuara, Julien; Lebreton, Vincent; Jalali, Bassem; Sicre, Marie-Alexandrine; Sabatier, Pierre; Dezileau, Laurent; Peyron, Odile; Frigola, Jaime; Combourieu-Nebout, Nathalie

2017-04-01

Forcings and physical mechanisms underlying Holocene climate variability still remain poorly understood. Comparison of different paleoclimatic reconstructions using spectral analysis allows to investigate their common periodicities and helps to understand the causes of past climate changes. Wavelet analysis applied on several proxy time series from the Atlantic domain already revealed the first key-issues on the origin of Holocene climate variability. However the differences in duration, resolution and variance between the time-series are important issues for comparing paleoclimatic sequences in the frequency domain. This work compiles 7 paleoclimatic proxy records from 4 time-series from the north-western Mediterranean all ranging from 7000 to 1000 yrs cal BP: -pollen and clay mineral contents from the lagoonal sediment core PB06 recovered in southern France, -Sea Surface Temperatures (SST) derived from alkenones, concentration of terrestrial alkanes and their average chain length (ACL) from core KSGC-31_GolHo-1B recovered in the Gulf of Lion inner-shelf, - δ18O record from speleothems recovered in the Asiul Cave in north-western Spain, -grain size record from the deep basin sediment drift core MD99-2343 north of Minorca island. A comparison of their frequency content is proposed using wavelet analysis and cluster analysis of wavelet power spectra. Common cyclicities are assessed using cross-wavelet analysis. In addition, a new algorithm is used in order to propagate the age model errors within wavelet power spectra. Results are consistents with a non-stationnary Holocene climate variability. The Halstatt cycles (2000-2500 years) depicted in many proxies (ACL, errestrial alkanes and SSTs) demonstrate solar activity influence in the north-western Mediterranean climate. Cluster analysis shows that pollen and ACL proxies, both indicating changes in aridity, are clearly distinct from other proxies and share significant common periodicities around 1000 and 600 years, since the mid-Holocene. The 1000 years period is also evidenced in terrestrial alkanes and Minorca sediment drift grain size, which respectively indicate changes in the Rhône hydrology and changes in the north-western Mediterranean deep water formation. These findings suggests that an original climate driver influences the Gulf of Lion area. Finally, both clay mineral content from PB06, indicative of past storminess and δ18O record from the north western Iberia, related to precipitations, record the well known 1500 years period since the middle Holocene. The presence of this period, widely encountered in the Atlantic, highlights the link between the north-western Mediterranean and the Atlantic climate variability.

A synthesis of the theories and concepts of early human evolution.

PubMed

Maslin, Mark A; Shultz, Susanne; Trauth, Martin H

2015-03-05

Current evidence suggests that many of the major events in hominin evolution occurred in East Africa. Hence, over the past two decades, there has been intensive work undertaken to understand African palaeoclimate and tectonics in order to put together a coherent picture of how the environment of Africa has varied over the past 10 Myr. A new consensus is emerging that suggests the unusual geology and climate of East Africa created a complex, environmentally very variable setting. This new understanding of East African climate has led to the pulsed climate variability hypothesis that suggests the long-term drying trend in East Africa was punctuated by episodes of short alternating periods of extreme humidity and aridity which may have driven hominin speciation, encephalization and dispersals out of Africa. This hypothesis is unique as it provides a conceptual framework within which other evolutionary theories can be examined: first, at macro-scale comparing phylogenetic gradualism and punctuated equilibrium; second, at a more focused level of human evolution comparing allopatric speciation, aridity hypothesis, turnover pulse hypothesis, variability selection hypothesis, Red Queen hypothesis and sympatric speciation based on sexual selection. It is proposed that each one of these mechanisms may have been acting on hominins during these short periods of climate variability, which then produce a range of different traits that led to the emergence of new species. In the case of Homo erectus (sensu lato), it is not just brain size that changes but life history (shortened inter-birth intervals, delayed development), body size and dimorphism, shoulder morphology to allow thrown projectiles, adaptation to long-distance running, ecological flexibility and social behaviour. The future of evolutionary research should be to create evidence-based meta-narratives, which encompass multiple mechanisms that select for different traits leading ultimately to speciation.

A synthesis of the theories and concepts of early human evolution

PubMed Central

Maslin, Mark A.; Shultz, Susanne; Trauth, Martin H.

2015-01-01

Current evidence suggests that many of the major events in hominin evolution occurred in East Africa. Hence, over the past two decades, there has been intensive work undertaken to understand African palaeoclimate and tectonics in order to put together a coherent picture of how the environment of Africa has varied over the past 10 Myr. A new consensus is emerging that suggests the unusual geology and climate of East Africa created a complex, environmentally very variable setting. This new understanding of East African climate has led to the pulsed climate variability hypothesis that suggests the long-term drying trend in East Africa was punctuated by episodes of short alternating periods of extreme humidity and aridity which may have driven hominin speciation, encephalization and dispersals out of Africa. This hypothesis is unique as it provides a conceptual framework within which other evolutionary theories can be examined: first, at macro-scale comparing phylogenetic gradualism and punctuated equilibrium; second, at a more focused level of human evolution comparing allopatric speciation, aridity hypothesis, turnover pulse hypothesis, variability selection hypothesis, Red Queen hypothesis and sympatric speciation based on sexual selection. It is proposed that each one of these mechanisms may have been acting on hominins during these short periods of climate variability, which then produce a range of different traits that led to the emergence of new species. In the case of Homo erectus (sensu lato), it is not just brain size that changes but life history (shortened inter-birth intervals, delayed development), body size and dimorphism, shoulder morphology to allow thrown projectiles, adaptation to long-distance running, ecological flexibility and social behaviour. The future of evolutionary research should be to create evidence-based meta-narratives, which encompass multiple mechanisms that select for different traits leading ultimately to speciation. PMID:25602068

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.

Spatio-temporal Variability of Stratified Snowpack Cold Content Observed in the Rocky Mountains

NASA Astrophysics Data System (ADS)

Schmidt, J. S.; Sexstone, G. A.; Serreze, M. C.

2017-12-01

Snowpack cold content (CCsnow) is the energy required to bring a snowpack to an isothermal temperature of 0.0°C. The spatio-temporal variability of CCsnow is complex as it is a measure that integrates the response of a snowpack to each component of the snow-cover energy balance. Snow and ice at high elevation is climate sensitive water storage for the Western U.S. Therefore, an improved understanding of the spatio-temporal variability of CCsnow may provide insight into snowpack dynamics and sensitivity to climate change. In this study, stratified snowpit observations of snow water equivalent (SWE) and snow temperature (Tsnow) from the USGS Rocky Mountain Snowpack network (USGS RMS) were used to evaluate vertical CCsnow profiles over a 16-year period in Montana, Idaho, Wyoming, Colorado and New Mexico. Since 1993, USGS RMS has collected snow chemistry, snow temperature, and SWE data throughout the Rocky Mountain region, making it well positioned for Anthropocene cryosphere benchmarking and climate change interpretation. Spatial grouping of locations based on similar CCsnow characteristics was evaluated and trend analyses were performed. Additionally, we evaluated the regional relation of CCsnow to snowmelt timing. CCsnow was more precisely calculated and more representative using vertically stratified field observed values than bulk values, which highlights the utility of the snowpack dataset presented here. Location specific annual and 16 year mean stratified snowpit profiles of SWE, Tsnow, and CCsnow well represent the physical geography and past weather patterns acting on the snowpack. Observed trends and spatial variability of CCsnow profiles explored by this study provides an improved understanding of changing snowpack behavior in the western U.S., and will be useful for assessing the regional sensitivity of snowpacks to future climate change.

Dynamical variability in the modelling of chemistry-climate interactions.

PubMed

Pyle, J A; Braesicke, P; Zeng, G

2005-01-01

We have used a version of the Met Office's climate model, into which we have introduced schemes for atmospheric chemistry, to study chemistry-dynamics-climate interactions. We have considered the variability of the stratospheric polar vortex, whose behaviour influences stratospheric ozone loss and will affect ozone recovery. In particular, we analyse the dynamical control of high latitude ozone in a model version which includes an assimilation of the equatorial quasi-biennial oscillation (QBO), demonstrating the stability of the linear relation between vortex strength and high latitude ozone. We discuss the effect of interactive model ozone on polar stratospheric cloud (PSC) area/volume and winter-spring stratospheric ozone loss in the northern hemisphere. In general we find larger polar ozone losses calculated in those model integrations in which modelled ozone is used interactively in the radiation scheme, even though we underestimate the slope of the ozone loss per PSC volume relation derived from observations. We have also looked at the influence of changing stratosphere-to-troposphere exchange on the tropospheric oxidizing capacity and, in particular, have considered the variability of tropospheric composition under different climate regimes (El Niño/La Niña, etc.). Focusing on the UT/LS, we show the response of ozone to El Niño in two different model set-ups (tropospheric/ stratospheric). In the stratospheric model set-up we find a distinct signal in the lower tropical stratosphere, which shows an anti-correlation between the Niño 3 index and the ozone column amount. In contrast ozone generally increases in the upper troposphere of the tropospheric model set-up after an El Niño. Understanding future trends in stratospheric ozone and tropospheric oxidizing capacity requires an understanding of natural variability, which we explore here.

Human activities and climate variability drive fast-paced change across the world's estuarine-coastal ecosystems

USGS Publications Warehouse

Cloern, James E.; Abreu, Paulo C.; Carstensen, Jacob; Chauvaud, Laurent; Elmgren, Ragnar; Grall, Jacques; Greening, Holly; Johansson, John O.R.; Kahru, Mati; Sherwood, Edward T.; Xu, Jie; Yin, Kedong

2016-01-01

Time series of environmental measurements are essential for detecting, measuring and understanding changes in the Earth system and its biological communities. Observational series have accumulated over the past 2–5 decades from measurements across the world's estuaries, bays, lagoons, inland seas and shelf waters influenced by runoff. We synthesize information contained in these time series to develop a global view of changes occurring in marine systems influenced by connectivity to land. Our review is organized around four themes: (i) human activities as drivers of change; (ii) variability of the climate system as a driver of change; (iii) successes, disappointments and challenges of managing change at the sea-land interface; and (iv) discoveries made from observations over time. Multidecadal time series reveal that many of the world's estuarine–coastal ecosystems are in a continuing state of change, and the pace of change is faster than we could have imagined a decade ago. Some have been transformed into novel ecosystems with habitats, biogeochemistry and biological communities outside the natural range of variability. Change takes many forms including linear and nonlinear trends, abrupt state changes and oscillations. The challenge of managing change is daunting in the coastal zone where diverse human pressures are concentrated and intersect with different responses to climate variability over land and over ocean basins. The pace of change in estuarine–coastal ecosystems will likely accelerate as the human population and economies continue to grow and as global climate change accelerates. Wise stewardship of the resources upon which we depend is critically dependent upon a continuing flow of information from observations to measure, understand and anticipate future changes along the world's coastlines.

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

On the Reprocessing and Reanalysis of Observations for Climate

NASA Technical Reports Server (NTRS)

Bosilovich, Michael G.; Kennedy, John; Dee, Dick; Allan, R.; O'Neill, Alan

2013-01-01

The long observational record is critical to our understanding of the Earths climate, but most observing systems were not developed with a climate objective in mind. As a result, tremendous efforts have gone into assessing and reprocessing the data records to improve their usefulness in climate studies. The purpose of this paper is to both review recent progress in reprocessing and reanalyzing observations, and to summarize the challenges that must be overcome in order to improve our understanding of climate and variability. Reprocessing improves data quality through more scrutiny and improved retrieval techniques for individual observing systems, while reanalysis merges many disparate observations with models through data assimilation, yet both aim to provide an climatology of Earth processes. Many challenges remain, such as tracking the improvement of processing algorithms and limited spatial coverage. Reanalyses have fostered significant research, yet reliable global trends in many physical fields are not yet attainable, despite significant advances in data assimilation and numerical modeling. Oceanic reanalyses have made significant advances in recent years, but will only be discussed here in terms of progress toward integrated Earth system analyses. Climate data sets are generally adequate for process studies and large-scale climate variability. Communication of the strengths, limitations and uncertainties of reprocessed observations and reanalysis data, not only among the community of developers, but also with the extended research community, including the new generations of researchers and the decision makers is crucial for further advancement of the observational data records. It must be emphasized that careful investigation of the data and processing methods are required to use the observations appropriately.

Glacial-Interglacial Variability of Nd isotopes in the South Atlantic and Southern Ocean

NASA Astrophysics Data System (ADS)

Knudson, K. P.; Goldstein, S. L.; Pena, L.; Seguí, M. J.; Kim, J.; Yehudai, M.; Fahey, T.

2017-12-01

Understanding the relationship between meridional overturning circulation and climate is key to understanding the processes and feedbacks underlying future climate changes. North Atlantic Deep Water (NADW) represents a major water mass that participates in global oceanic circulation and undergoes substantial reorganization with climate changes on millennial and orbital timescales. Nd isotopes are semi-quantitative water mass tracers that reflect the mixing of end-member water masses, and their values in the Southern Ocean offer the ability to characterize NADW variability over time. Here, we present paleo-circulation records of Nd isotopes measured on fish debris and Fe-Mn encrusted foraminifera from ODP Sites 1090 (42° 54.82'S, 3702 m), and 1094 (53° 10.81'S, 2807 m). Site 1090 is located in the Cape Basin, SE Atlantic, near the lower boundary between NADW and Circumpolar Deep Water (CDW), while 1094 is in the Circumpolar Current. They are ideal locations to monitor changes in the export of NADW to the Southern Ocean. These new results build on previous work (Pena and Goldstein, 2014) to document meridional overturning changes in the Southern Ocean.

Can pictures speak a thousand words in understanding climate change?

NASA Astrophysics Data System (ADS)

Walton, P.

2017-12-01

Pictures are able to engage, inspire and educate people in a way that the spoken or written word cannot, and with 21st Century technology we now have even more ways to present images. Researchers and campaigners working in climate change have used the power of images to great effect, bringing the issue of a warming planet into stark relief through iconic scenes such as the forlorn polar bear adrift on an iceberg. Whilst undeniably successful, this image has now become passé and invisible necessitating the scientific community to identify new ways to engage and educate the general public. This paper reports on a new high resolution visualisation app that has been developed by the European Space Agency to illustrate the change over time of a number of climate variables. Data, collected via satellite Earth observations, have been rendered into visually stunning animations that can be interrogated in a number of ways to allow the user to understand the spatial and temporal changes of that variable. But is it enough? Can it ever be that all that glisters really is gold?

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

A monthly global paleo-reanalysis of the atmosphere from 1600 to 2005 for studying past climatic variations

PubMed Central

Franke, Jörg; Brönnimann, Stefan; Bhend, Jonas; Brugnara, Yuri

2017-01-01

Climatic variations at decadal scales such as phases of accelerated warming or weak monsoons have profound effects on society and economy. Studying these variations requires insights from the past. However, most current reconstructions provide either time series or fields of regional surface climate, which limit our understanding of the underlying dynamics. Here, we present the first monthly paleo-reanalysis covering the period 1600 to 2005. Over land, instrumental temperature and surface pressure observations, temperature indices derived from historical documents and climate sensitive tree-ring measurements were assimilated into an atmospheric general circulation model ensemble using a Kalman filtering technique. This data set combines the advantage of traditional reconstruction methods of being as close as possible to observations with the advantage of climate models of being physically consistent and having 3-dimensional information about the state of the atmosphere for various variables and at all points in time. In contrast to most statistical reconstructions, centennial variability stems from the climate model and its forcings, no stationarity assumptions are made and error estimates are provided. PMID:28585926

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

PubMed Central

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

2006-01-01

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

North Atlantic Jet Variability in PMIP3 LGM Simulations

NASA Astrophysics Data System (ADS)

Hezel, P.; Li, C.

2017-12-01

North Atlantic jet variability in glacial climates has been shown inmodelling studies to be strongly influenced by upstream ice sheettopography. We analyze the results of 8 models from the PMIP3simulations, forced with a hybrid Laurentide Ice Sheet topography, andcompare them to the PMIP2 simulations which were forced with theICE-5G topography, to develop a general understanding of the NorthAtlantic jet and jet variability. The strengthening of the jet andreduced spatial variability is a robust feature of the last glacialmaximum (LGM) simulations compared to the pre-industrial state.However, the canonical picture of the LGM North Atlantic jet as beingmore zonal and elongated compared to pre-industrial climate states isnot a robust result across models, and may have arisen in theliterature as a function of multiple studies performed with the samemodel.

Clouds and the Earth's Radiant Energy System (CERES) Data Products for Climate Research

NASA Technical Reports Server (NTRS)

Kato, Seiji; Loeb, Norman G.; Rutan, David A.; Rose, Fred G.

2015-01-01

NASA's Clouds and the Earth's Radiant Energy System (CERES) project integrates CERES, Moderate Resolution Imaging Spectroradiometer (MODIS), and geostationary satellite observations to provide top-of-atmosphere (TOA) irradiances derived from broadband radiance observations by CERES instruments. It also uses snow cover and sea ice extent retrieved from microwave instruments as well as thermodynamic variables from reanalysis. In addition, these variables are used for surface and atmospheric irradiance computations. The CERES project provides TOA, surface, and atmospheric irradiances in various spatial and temporal resolutions. These data sets are for climate research and evaluation of climate models. Long-term observations are required to understand how the Earth system responds to radiative forcing. A simple model is used to estimate the time to detect trends in TOA reflected shortwave and emitted longwave irradiances.

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.

Information transfer and synchronization among the scales of climate variability: clues for understanding anomalies and extreme events?

NASA Astrophysics Data System (ADS)

Palus, Milan

2017-04-01

Deeper understanding of complex dynamics of the Earth atmosphere and climate is inevitable for sustainable development, mitigation and adaptation strategies for global change and for prediction of and resilience against extreme events. Traditional (linear) approaches cannot explain or even detect nonlinear interactions of dynamical processes evolving on multiple spatial and temporal scales. Combination of nonlinear dynamics and information theory explains synchronization as a process of adjustment of information rates [1] and causal relations (à la Granger) as information transfer [2]. Information born in dynamical complexity or information transferred among systems on a way to synchronization might appear as an abstract quantity, however, information transfer is tied to a transfer of mass and energy, as demonstrated in a recent study using directed (causal) climate networks [2]. Recently, an information transfer across scales of atmospheric dynamics has been observed [3]. In particular, a climate oscillation with the period around 7-8 years has been identified as a factor influencing variability of surface air temperature (SAT) on shorter time scales. Its influence on the amplitude of the SAT annual cycle was estimated in the range 0.7-1.4 °C and the effect on the overall variability of the SAT anomalies (SATA) leads to the changes 1.5-1.7 °C in the annual SATA means. The strongest effect of the 7-8 year cycle was observed in the winter SATA means where it reaches 4-5 °C in central European station and reanalysis data [4]. In the dynamics of El Niño-Southern Oscillation, three principal time scales have been identified: the annual cycle (AC), the quasibiennial (QB) mode(s) and the low-frequency (LF) variability. An intricate causal network of information flows among these modes helps to understand the occurrence of extreme El Niño events, characterized by synchronization of the QB modes and AC, and modulation of the QB amplitude by the LF mode. The latter also influences the phase of the AC and QB modes. These examples provide an inspiration for a discussion how novel data analysis methods, based on topics from nonlinear dynamical systems, their synchronization, (Granger) causality and information transfer, in combination with dynamical and statistical models of different complexity, can help in understanding and prediction of climate variability on different scales and in estimating probability of occurrence of extreme climate events. [1] M. Palus, V. Komarek, Z. Hrncir, K. Sterbova, Phys. Rev. E, 63(4), 046211 (2001) http://www.cs.cas.cz/mp/epr/sir1-a.html [2] J. Hlinka, N. Jajcay, D. Hartman, M. Palus, Smooth Information Flow in Temperature Climate Network Reflects Mass Transport, submitted to Chaos. http://www.cs.cas.cz/mp/epr/vetry-a.html [3] M. Palus, Phys. Rev. Lett. 112 078702 (2014) http://www.cs.cas.cz/mp/epr/xf1-a.html [4] N. Jajcay, J. Hlinka, S. Kravtsov, A. A. Tsonis, M. Palus, Geophys. Res. Lett. 43(2), 902-909 (2016) http://www.cs.cas.cz/mp/epr/xfgrl1-a.html

Long-term variability and environmental control of the carbon cycle in an oak-dominated temperate forest

Treesearch

Jing Xie; Jiquan Chen; Ge Sun; Housen Chu; Asko Noormets; Zutao Ouyang; Ranjeet John; Shiqiang Wan; Wenbin Guan

2014-01-01

Our understanding of the long-term carbon (C) cycle of temperate deciduous forests and its sensitivity to climate variability is limited due to the large temporal dynamics of C fluxes. The goal of the study was to quantify the effects of environmental variables on the C balance in a 70-year-old mixed-oak woodland forest over a 7-year period in northwest Ohio, USA. The...

Can we use the ozone response in a CCM to say which solar spectral irradiance is most likely correct?

NASA Astrophysics Data System (ADS)

Ball, William; Rozanov, Eugene; Shapiro, Anna

2015-04-01

Ozone plays a key role in the temperature structure of the Earth's atmosphere and absorbs damaging ultraviolet (UV) solar radiation. Evidence suggests that variations in stratospheric ozone resulting from changes in solar UV output may have an important role to play in weather over the North Atlantic and Europe on decadal timescales through a "top-down" coupling with the troposphere. However, the magnitude of the stratospheric response to the Sun over the 11-year solar cycle (SC) depends primarily on how much the UV changes. SC UV changes differ significantly between different observational instruments and the observations and models. The substantial disagreements between existing SSI datasets lead to different atmospheric responses when they are used in climate models and, therefore, we still cannot fully understand and simulate the ozone variability. We use the SOCOL chemistry-climate model, in specified dynamics mode, to calculate the atmospheric response from using different spectral irradiance from the SATIRE-S and NRLSSI models and with SORCE observations and a constant Sun. We compare the ozone and hydroxl results from these runs with observations to try to determine which SSI dataset is most likely to be correct. This is important to get a better understanding of which SSI dataset should be used in climate modelling and what magnitude of UV variability the Sun has. This will lead to a better understanding of the Sun's influence upon our climate and weather.

The Effect of Vaccination Coverage and Climate on Japanese Encephalitis in Sarawak, Malaysia

PubMed Central

Impoinvil, Daniel E.; Ooi, Mong How; Diggle, Peter J.; Caminade, Cyril; Cardosa, Mary Jane; Morse, Andrew P.

2013-01-01

Background Japanese encephalitis (JE) is the leading cause of viral encephalitis across Asia with approximately 70,000 cases a year and 10,000 to 15,000 deaths. Because JE incidence varies widely over time, partly due to inter-annual climate variability effects on mosquito vector abundance, it becomes more complex to assess the effects of a vaccination programme since more or less climatically favourable years could also contribute to a change in incidence post-vaccination. Therefore, the objective of this study was to quantify vaccination effect on confirmed Japanese encephalitis (JE) cases in Sarawak, Malaysia after controlling for climate variability to better understand temporal dynamics of JE virus transmission and control. Methodology/principal findings Monthly data on serologically confirmed JE cases were acquired from Sibu Hospital in Sarawak from 1997 to 2006. JE vaccine coverage (non-vaccine years vs. vaccine years) and meteorological predictor variables, including temperature, rainfall and the Southern Oscillation index (SOI) were tested for their association with JE cases using Poisson time series analysis and controlling for seasonality and long-term trend. Over the 10-years surveillance period, 133 confirmed JE cases were identified. There was an estimated 61% reduction in JE risk after the introduction of vaccination, when no account is taken of the effects of climate. This reduction is only approximately 45% when the effects of inter-annual variability in climate are controlled for in the model. The Poisson model indicated that rainfall (lag 1-month), minimum temperature (lag 6-months) and SOI (lag 6-months) were positively associated with JE cases. Conclusions/significance This study provides the first improved estimate of JE reduction through vaccination by taking account of climate inter-annual variability. Our analysis confirms that vaccination has substantially reduced JE risk in Sarawak but this benefit may be overestimated if climate effects are ignored. PMID:23951373

A preindustrial to present record of SST from Darwin Island, Galápagos: constraining Eastern Pacific decadal variability

NASA Astrophysics Data System (ADS)

Jimenez, G.; Cole, J. E.; Vetter, L.; Thompson, D. M.; Tudhope, A. W.

2017-12-01

Climate reconstructions from sub-seasonally resolved corals have greatly enhanced our understanding of climate variability related to the El Niño-Southern Oscillation (ENSO). However, few such records exist from the Eastern Pacific, which experiences the greatest ENSO-related variance in sea surface temperature (SST). Therefore, climate patterns and mechanisms in the region remain unclear, particularly on decadal to multidecadal timescales. Here, we present a new, bimonthly-resolved δ18O-SST reconstruction from a Darwin Island coral, in the northern Galápagos archipelago. Comparison with Sr/Ca data from the same coral demonstrates that δ18O values in the core dominantly track SST, as is expected in areas with low-magnitude sea surface salinity changes such as the Galápagos. Spanning 2015 to approximately 1800 CE, our record thus represents the longest sub-seasonally resolved SST reconstruction bridging the pre-industrial era to the present day in the Eastern Pacific. This time span and resolution is ideal for identifying climatic processes on a range of timescales: the presence of modern data allows us to calibrate the record using satellite datasets, while several decades of data preceding the onset of greenhouse warming enables comparison between natural and anthropogenic climate forcings. Together with other reconstructions from the region, we use the record to establish a baseline of (ENSO-related) Eastern Pacific interannual and decadal variability and assess evidence for climate emergence and trends. Preliminary evidence suggests increased decadal variability during the latter half of the twentieth century, as well as a secular warming trend of approximately 0.1°C/decade, in agreement with other Eastern Pacific coral records. Finally, we explore the applications of coral δ13C values in reconstructing regional upwelling. Our record contributes to constraining the pre- to post-industrial climate history of the Eastern Pacific and provides insight into natural versus forced climate variability in the region.

The Inter-Annual Variability Analysis of Carbon Exchange in Low Artic Fen Uncovers The Climate Sensitivity And The Uncertainties Around Net Ecosystem Exchange Partitioning

NASA Astrophysics Data System (ADS)

Blanco, E. L.; Lund, M.; Williams, M. D.; Christensen, T. R.; Tamstorf, M. P.

2015-12-01

An improvement in our process-based understanding of CO2 exchanges in the Arctic, and their climate sensitivity, is critical for examining the role of tundra ecosystems in changing climates. Arctic organic carbon storage has seen increased attention in recent years due to large potential for carbon releases following thaw. Our knowledge about the exact scale and sensitivity for a phase-change of these C stocks are, however, limited. Minor variations in Gross Primary Production (GPP) and Ecosystem Respiration (Reco) driven by changes in the climate can lead to either C sink or C source states, which likely will impact the overall C cycle of the ecosystem. Eddy covariance data is usually used to partition Net Ecosystem Exchange (NEE) into GPP and Reco achieved by flux separation algorithms. However, different partitioning approaches lead to different estimates. as well as undefined uncertainties. The main objectives of this study are to use model-data fusion approaches to (1) determine the inter-annual variability in C source/sink strength for an Arctic fen, and attribute such variations to GPP vs Reco, (2) investigate the climate sensitivity of these processes and (3) explore the uncertainties in NEE partitioning. The intention is to elaborate on the information gathered in an existing catchment area under an extensive cross-disciplinary ecological monitoring program in low Arctic West Greenland, established under the auspices of the Greenland Ecosystem Monitoring (GEM) program. The use of such a thorough long-term (7 years) dataset applied to the exploration in inter-annual variability of carbon exchange, related driving factors and NEE partition uncertainties provides a novel input into our understanding about land-atmosphere CO2 exchange.

Understanding the Influence of Climate Forecasts on Farmer Decisions as Planned Behavior

NASA Astrophysics Data System (ADS)

Artikov, Ikrom; Hoffman, Stacey J.; Lynne, Gary D.; Pytlik Zillig, Lisa M.; Hu, Qi; Tomkins, Alan J.; Hubbard, Kenneth G.; Hayes, Michael J.; Waltman, William

2006-09-01

Results of a set of four regression models applied to recent survey data of farmers in eastern Nebraska suggest the causes that drive farmer intentions of using weather and climate information and forecasts in farming decisions. The model results quantify the relative importance of attitude, social norm, perceived behavioral control, and financial capability in explaining the influence of climate-conditions information and short-term and long-term forecasts on agronomic, crop insurance, and crop marketing decisions. Attitude, serving as a proxy for the utility gained from the use of such information, had the most profound positive influence on the outcome of all the decisions, followed by norms. The norms in the community, as a proxy for the utility gained from allowing oneself to be influenced by others, played a larger role in agronomic decisions than in insurance or marketing decisions. In addition, the interaction of controllability (accuracy, availability, reliability, timeliness of weather and climate information), self-efficacy (farmer ability and understanding), and general preference for control was shown to be a substantive cause. Yet control variables also have an economic side: The farm-sales variable as a measure of financial ability and motivation intensified and clarified the role of control while also enhancing the statistical robustness of the attitude and norms variables in better clarifying how they drive the influence. Overall, the integrated model of planned behavior from social psychology and derived demand from economics, that is, the “planned demand model,” is more powerful than models based on either of these approaches alone. Taken together, these results suggest that the “human dimension” needs to be better recognized so as to improve effective use of climate and weather forecasts and information for farming decision making.

The climate change-infectious disease nexus: is it time for climate change syndemics?

PubMed

Heffernan, Claire

2013-12-01

Conceptualizing climate as a distinct variable limits our understanding of the synergies and interactions between climate change and the range of abiotic and biotic factors, which influence animal health. Frameworks such as eco-epidemiology and the epi-systems approach, while more holistic, view climate and climate change as one of many discreet drivers of disease. Here, I argue for a new paradigmatic framework: climate-change syndemics. Climate-change syndemics begins from the assumption that climate change is one of many potential influences on infectious disease processes, but crucially is unlikely to act independently or in isolation; and as such, it is the inter-relationship between factors that take primacy in explorations of infectious disease and climate change. Equally importantly, as climate change will impact a wide range of diseases, the frame of analysis is at the collective rather than individual level (for both human and animal infectious disease) across populations.

An Integrative Model for Understanding Team Organizational Citizenship Behavior: Its Antecedents and Consequences for Educational Teams

ERIC Educational Resources Information Center

Somech, Anit; Khotaba, Soha

2017-01-01

Purpose: The purpose of this paper is to use a model to broaden the understanding of the organizational citizenship behavior (OCB) phenomenon in educational teams and examines team OCB's mediating role in the relation of the contextual variables of team justice climate (distributive justice, procedural justice, interpersonal justice) to team…

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

Climate change and health modeling: horses for courses.

PubMed

Ebi, Kristie L; Rocklöv, Joacim

2014-01-01

Mathematical and statistical models are needed to understand the extent to which weather, climate variability, and climate change are affecting current and may affect future health burdens in the context of other risk factors and a range of possible development pathways, and the temporal and spatial patterns of any changes. Such understanding is needed to guide the design and the implementation of adaptation and mitigation measures. Because each model projection captures only a narrow range of possible futures, and because models serve different purposes, multiple models are needed for each health outcome ('horses for courses'). Multiple modeling results can be used to bracket the ranges of when, where, and with what intensity negative health consequences could arise. This commentary explores some climate change and health modeling issues, particularly modeling exposure-response relationships, developing early warning systems, projecting health risks over coming decades, and modeling to inform decision-making. Research needs are also suggested.

Project Ukko - Design of a climate service visualisation interface for seasonal wind forecasts

NASA Astrophysics Data System (ADS)

Hemment, Drew; Stefaner, Moritz; Makri, Stephann; Buontempo, Carlo; Christel, Isadora; Torralba-Fernandez, Veronica; Gonzalez-Reviriego, Nube; Doblas-Reyes, Francisco; de Matos, Paula; Dykes, Jason

2016-04-01

Project Ukko is a prototype climate service to visually communicate probabilistic seasonal wind forecasts for the energy sector. In Project Ukko, an interactive visualisation enhances the accessibility and readability to the latests advances in seasonal wind speed predictions developed as part of the RESILIENCE prototype of the EUPORIAS (EC FP7) project. Climate services provide made-to-measure climate information, tailored to the specific requirements of different users and industries. In the wind energy sector, understanding of wind conditions in the next few months has high economic value, for instance, for the energy traders. Current energy practices use retrospective climatology, but access to reliable seasonal predictions based in the recent advances in global climate models has potential to improve their resilience to climate variability and change. Despite their potential benefits, a barrier to the development of commercially viable services is the complexity of the probabilistic forecast information, and the challenge of communicating complex and uncertain information to decision makers in industry. Project Ukko consists of an interactive climate service interface for wind energy users to explore probabilistic wind speed predictions for the coming season. This interface enables fast visual detection and exploration of interesting features and regions likely to experience unusual changes in wind speed in the coming months.The aim is not only to support users to better understand the future variability in wind power resources, but also to bridge the gap between practitioners' traditional approach and the advanced prediction systems developed by the climate science community. Project Ukko is presented as a case study of cross-disciplinary collaboration between climate science and design, for the development of climate services that are useful, usable and effective for industry users. The presentation will reflect on the challenge of developing a climate service for industry users in the wind energy sector, the background to this challenge, our approach, and the evaluation of the visualisation interface.

Ecophysiological modeling of photosynthesis and carbon allocation to the tree stem in the boreal forest

NASA Astrophysics Data System (ADS)

Gennaretti, Fabio; Gea-Izquierdo, Guillermo; Boucher, Etienne; Berninger, Frank; Arseneault, Dominique; Guiot, Joel

2017-11-01

A better understanding of the coupling between photosynthesis and carbon allocation in the boreal forest, together with its associated environmental factors and mechanistic rules, is crucial to accurately predict boreal forest carbon stocks and fluxes, which are significant components of the global carbon budget. Here, we adapted the MAIDEN ecophysiological forest model to consider important processes for boreal tree species, such as nonlinear acclimation of photosynthesis to temperature changes, canopy development as a function of previous-year climate variables influencing bud formation and the temperature dependence of carbon partition in summer. We tested these modifications in the eastern Canadian taiga using black spruce (Picea mariana (Mill.) B.S.P.) gross primary production and ring width data. MAIDEN explains 90 % of the observed daily gross primary production variability, 73 % of the annual ring width variability and 20-30 % of its high-frequency component (i.e., when decadal trends are removed). The positive effect on stem growth due to climate warming over the last several decades is well captured by the model. In addition, we illustrate how we improve the model with each introduced model adaptation and compare the model results with those of linear response functions. Our results demonstrate that MAIDEN simulates robust relationships with the most important climate variables (those detected by classical response-function analysis) and is a powerful tool for understanding how environmental factors interact with black spruce ecophysiology to influence present-day and future boreal forest carbon fluxes.

Reconstructing pre-instrumental streamflow in Eastern Australia using a water balance approach

NASA Astrophysics Data System (ADS)

Tozer, C. R.; Kiem, A. S.; Vance, T. R.; Roberts, J. L.; Curran, M. A. J.; Moy, A. D.

2018-03-01

Streamflow reconstructions based on paleoclimate proxies provide much longer records than the short instrumental period records on which water resource management plans are currently based. In Australia there is a lack of in-situ high resolution paleoclimate proxy records, but remote proxies with teleconnections to Australian climate have utility in producing streamflow reconstructions. Here we investigate, via a case study for a catchment in eastern Australia, the novel use of an Antarctic ice-core based rainfall reconstruction within a Budyko-framework to reconstruct ∼1000 years of annual streamflow. The resulting streamflow reconstruction captures interannual to decadal variability in the instrumental streamflow, validating both the use of the ice core rainfall proxy record and the Budyko-framework method. In the preinstrumental era the streamflow reconstruction shows longer wet and dry epochs and periods of streamflow variability that are higher than observed in the instrumental era. Importantly, for both the instrumental record and preinstrumental reconstructions, the wet (dry) epochs in the rainfall record are shorter (longer) in the streamflow record and this non-linearity must be considered when inferring hydroclimatic risk or historical water availability directly from rainfall proxy records alone. These insights provide a better understanding of present infrastructure vulnerability in the context of past climate variability for eastern Australia. The streamflow reconstruction presented here also provides a better understanding of the range of hydroclimatic variability possible, and therefore represents a more realistic baseline on which to quantify the potential impacts of anthropogenic climate change on water security.

An Agenda for Climate Impacts Science

NASA Astrophysics Data System (ADS)

Kaye, J. A.

2009-12-01

The report Global Change Impacts in the United States released by the US Global Change Research Program in June 2009 identifies a number of areas in which inadequate information or understanding hampers our ability to estimate likely future climate change and its impacts. In this section of the report, the focus is on those areas of climate science that could contribute most towards advancing our knowledge of climate change impacts and those aspects of climate change responsible for these impacts in order to continue to guide decision making. The Report identifies the six most important gaps in knowledge and offers some thoughts on how to address those gaps: 1. Expand our understanding of climate change impacts. There is a clear need to increase understanding of how ecosystems, social and economic systems, human health, and the built environment will be affected by climate change in the context of other stresses. 2. Refine ability to project climate change, including extreme events, at local scales. While climate change is a global issue, it has a great deal of regional variability. There is an indisputable need to improve understanding of climate system effects at these smaller scales, because these are often the scales of decision-making in society. This includes advances in modeling capability and observations needed to address local scales and high-impact extreme events. 3. Expand capacity to provide decision makers and the public with relevant information on climate change and its impacts. Significant potential exists in the US to create more comprehensive measurement, archive, and data-access systems that could provide great benefit to society, which requires defining needed information, gathering it, expanding capacity to deliver it, and improving tools by which decision makers use it to best advantage. 4. Improve understanding of thresholds likely to lead to abrupt changes in climate or ecosystems. Potential areas of research include thresholds that could lead to rapid changes in ice-sheet dynamics that could impact future sea-level rise and tipping points in biological systems (including those that may be associated with ocean acidification). 5. Improve understanding of the most effective ways to reduce the rate and magnitude of climate change, as well as unintended consequences of such actions. Research will help to identify the desired mix of mitigation options necessary to control the rate and magnitude of climate change, and to examine possible unintended consequences of mitigation options. 6. Enhance understanding of how society can adapt to climate change. There is currently limited knowledge about the ability of communities, regions, and sectors to adapt to future climate change. It is important to improve understanding of how to enhance society’s capacity to adapt to a changing climate in the context of other environmental stresses.

Climate variability and vadose zone controls on damping of transient recharge

USGS Publications Warehouse

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

2018-01-01

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

Groundwater Variability in a Sandstone Catchment and Linkages with Large-scale Climatic Circulatio

NASA Astrophysics Data System (ADS)

Hannah, D. M.; Lavers, D. A.; Bradley, C.

2015-12-01

Groundwater is a crucial water resource that sustains river ecosystems and provides public water supply. Furthermore, during periods of prolonged high rainfall, groundwater-dominated catchments can be subject to protracted flooding. Climate change and associated projected increases in the frequency and intensity of hydrological extremes have implications for groundwater levels. This study builds on previous research undertaken on a Chalk catchment by investigating groundwater variability in a UK sandstone catchment: the Tern in Shropshire. In contrast to the Chalk, sandstone is characterised by a more lagged response to precipitation inputs; and, as such, it is important to determine the groundwater behaviour and its links with the large-scale climatic circulation to improve process understanding of recharge, groundwater level and river flow responses to hydroclimatological drivers. Precipitation, river discharge and groundwater levels for borehole sites in the Tern basin over 1974-2010 are analysed as the target variables; and we use monthly gridded reanalysis data from the Twentieth Century Reanalysis Project (20CR). First, groundwater variability is evaluated and associations with precipitation / discharge are explored using monthly concurrent and lagged correlation analyses. Second, gridded 20CR reanalysis data are used in composite and correlation analyses to identify the regions of strongest climate-groundwater association. Results show that reasonably strong climate-groundwater connections exist in the Tern basin, with a several months lag. These lags are associated primarily with the time taken for recharge waters to percolate through to the groundwater table. The uncovered patterns improve knowledge of large-scale climate forcing of groundwater variability and may provide a basis to inform seasonal prediction of groundwater levels, which would be useful for strategic water resource planning.

Relative roles of weather variables and change in human population in malaria: comparison over different states of India.

PubMed

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria.

Relative Roles of Weather Variables and Change in Human Population in Malaria: Comparison over Different States of India

PubMed Central

Goswami, Prashant; Murty, Upadhayula Suryanarayana; Mutheneni, Srinivasa Rao; Krishnan, Swathi Trithala

2014-01-01

Background Pro-active and effective control as well as quantitative assessment of impact of climate change on malaria requires identification of the major drivers of the epidemic. Malaria depends on vector abundance which, in turn, depends on a combination of weather variables. However, there remain several gaps in our understanding and assessment of malaria in a changing climate. Most of the studies have considered weekly or even monthly mean values of weather variables, while the malaria vector is sensitive to daily variations. Secondly, rarely all the relevant meteorological variables have been considered together. An important question is the relative roles of weather variables (vector abundance) and change in host (human) population, in the change in disease load. Method We consider the 28 states of India, characterized by diverse climatic zones and changing population as well as complex variability in malaria, as a natural test bed. An annual vector load for each of the 28 states is defined based on the number of vector genesis days computed using daily values of temperature, rainfall and humidity from NCEP daily Reanalysis; a prediction of potential malaria load is defined by taking into consideration changes in the human population and compared with the reported number of malaria cases. Results For most states, the number of malaria cases is very well correlated with the vector load calculated with the combined conditions of daily values of temperature, rainfall and humidity; no single weather variable has any significant association with the observed disease prevalence. Conclusion The association between vector-load and daily values of weather variables is robust and holds for different climatic regions (states of India). Thus use of all the three weather variables provides a reliable means of pro-active and efficient vector sanitation and control as well as assessment of impact of climate change on malaria. PMID:24971510

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

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

NASA Astrophysics Data System (ADS)

Switanek, M.; Troch, P. A.

2007-12-01

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

Challenges of coordinating global climate observations - Role of satellites in climate monitoring

NASA Astrophysics Data System (ADS)

Richter, C.

2017-12-01

Global observation of the Earth's atmosphere, ocean and land is essential for identifying climate variability and change, and for understanding their causes. Observation also provides data that are fundamental for evaluating, refining and initializing the models that predict how the climate system will vary over the months and seasons ahead, and that project how climate will change in the longer term under different assumptions concerning greenhouse gas emissions and other human influences. Long-term observational records have enabled the Intergovernmental Panel on Climate Change to deliver the message that warming of the global climate system is unequivocal. As the Earth's climate enters a new era, in which it is forced by human activities, as well as natural processes, it is critically important to sustain an observing system capable of detecting and documenting global climate variability and change over long periods of time. High-quality climate observations are required to assess the present state of the ocean, cryosphere, atmosphere and land and place them in context with the past. The global observing system for climate is not a single, centrally managed observing system. Rather, it is a composite "system of systems" comprising a set of climate-relevant observing, data-management, product-generation and data-distribution systems. Data from satellites underpin many of the Essential Climate Variables(ECVs), and their historic and contemporary archives are a key part of the global climate observing system. In general, the ECVs will be provided in the form of climate data records that are created by processing and archiving time series of satellite and in situ measurements. Early satellite data records are very valuable because they provide unique observations in many regions which were not otherwise observed during the 1970s and which can be assimilated in atmospheric reanalyses and so extend the satellite climate data records back in time.

Influences of climate, fire, and topography on contemporary age structure patterns of Douglas-fir at 205 old forest sites in western Oregon

Treesearch

Nathan J. Poage; Peter J. Weisberg; Peter C. Impara; John C. Tappeiner; Thomas S. Sensenig

2009-01-01

Knowledge of forest development is basic to understanding the ecology, dynamics, and management of forest ecosystems. We hypothesized that the age structure patterns of Douglas-fir at 205 old forest sites in western Oregon are extremely variable with long and (or) multiple establishment periods common, and that these patterns reflect variation in regional-scale climate...

The Effects of Solar Variability on Earth's Climate: A Workshop Report

NASA Technical Reports Server (NTRS)

2012-01-01

Solar irradiance, the flux of the Sun s output directed toward Earth, is Earth s main energy source.1 The Sun itself varies on several timescales over billions of years its luminosity increases as it evolves on the main sequence toward becoming a red giant; about every 11 years its sunspot activity cycles; and within just minutes flares can erupt and release massive amounts of energy. Most of the fluctuations from tens to thousands of years are associated with changes in the solar magnetic field. The focus of the National Research Council's September 2011 workshop on solar variability and Earth's climate, and of this summary report, is mainly magnetically driven variability and its possible connection with Earth's climate variations in the past 10,000 years. Even small variations in the amount or distribution of energy received at Earth can have a major influence on Earth's climate when they persist for decades. However, no satellite measurements have indicated that solar output and variability have contributed in a significant way to the increase in global mean temperature in the last 50 years. Locally, however, correlations between solar activity and variations in average weather may stand out beyond the global trend; such has been argued to be the case for the El Nino-Southern Oscillation, even in the present day. A key area of inquiry deals with establishing a unified record of the solar output and solar-modified particles that extends from the present to the prescientific past. The workshop focused attention on the need for a better understanding of the links between indices of solar activity such as cosmogenic isotopes and solar irradiance. A number of presentations focused on the timescale of the solar cycle and of the satellite record, and on the problem of extending this record back in time. Highlights included a report of progress on pyroheliometer calibration, leading to greater confidence in the time history and future stability of total solar irradiance (TSI), and surprising results on changes in spectral irradiance over the last solar cycle, which elicited spirited discussion. New perspectives on connections between features of the quiet and active areas of the photosphere and variations in TSI were also presented, emphasizing the importance of developing better understanding in order to extrapolate back in time using activity indices. Workshop participants reviews highlighted difficulties as well as causes for optimism in current understanding of the cosmogenic isotope record and the use of observed variability in Sun-like stars in reconstructing variations in TSI occurring on lower frequencies than the sunspot cycle. The workshop succeeded in bringing together informed, focused presentations on major drivers of the Sun-climate connection. The importance of the solar cycle as a unique quasi-periodic probe of climate responses on a timescale between the seasonal and Milankovitch cycles was recognized in several presentations. The signal need only be detectable, not dominant, for it to play this role of a useful probe. Some workshop participants also found encouraging progress in the top-down perspective, according to which solar variability affects surface climate by first perturbing the stratosphere, which then forces the troposphere and surface. This work is now informing and being informed by research on tropospheric responses to the Antarctic ozone hole and volcanic aerosols. In contrast to the top-down perspective is the bottom-up view that the interaction of solar energy with the ocean and surface leads to changes in dynamics and temperature. During the discussion of how dynamical air-sea coupling in the tropical Pacific and solar variability interact from a bottom-up perspective, several participants remarked on the wealth of open research questions in the dynamics of the climatic response to TSI and spectral variability. The discussion of the paleoclimate record emphasized that the link between solar varbility and Earth s climate is multifaceted and that some components are understood better than others. According to two presenters on paleoclimate, there is a need to study the idiosyncrasies of each key proxy record. Yet they also emphasized that there may be an emerging pattern of paleoclimate change coincident with periods of solar activity and inactivity, but only on long timescales of multiple decades to millennia. Several speakers discussed the effects of particle events and cosmic-ray variability. These are all areas of exciting fundamental research; however, they have not yet led to conclusive evidence for significant related climate effects. The key problem of attribution of climate variability on the timescales of the Little Ice Age and the Maunder Minimum were directly addressed in several presentations. Several workshop participants remarked that the combination of solar, paleoclimatic, and climate modeling research has the potential to dramatically improve the credibility of these attribution studies.

Overview of Aerosol Distribution

NASA Technical Reports Server (NTRS)

Kaufman, Yoram

2005-01-01

Our knowledge of atmospheric aerosols (smoke, pollution, dust or sea salt particles, small enough to be suspended in the air), their evolution, composition, variability in space and time and interaction with clouds and precipitation is still lacking despite decades of research. Understanding the global aerosol system is fundamental for progress in climate change and hydrological cycle research. While a single instrument was used to demonstrate 50 years ago that the global CO2 levels are rising, posing threat of global warming, we need an array of satellites and field measurements coupled with chemical transport models to understand the global aerosol system. This complexity of the aerosol problem results from their short lifetime (1 week) and variable chemical composition. A new generation of satellites provides exciting opportunities to measure the global distribution of aerosols, distinguishing natural from anthropogenic aerosol and measuring their interaction with clouds and climate. I shall discuss these topics and application of the data to air quality monitoring.

Improving Decision-Making Activities for Meningitis and Malaria

NASA Astrophysics Data System (ADS)

Ceccato, P.; Trzaska, S.; Perez, C.; Kalashnikova, O. V.; del Corral, J.; Cousin, R.; Blumenthal, M. B.; Connor, S.; Thomson, M. C.

2012-12-01

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community's capacity to understand, use, and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular Meningitis and Malaria. In this paper we present the new and improved products that have been developed for monitoring dust, temperature, rainfall and vectorial capacity model for monitoring and forecasting risks of Meningitis and Malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Factors Influencing Smallholder Farmers' Climate Change Perceptions: A Study from Farmers in Ethiopia

NASA Astrophysics Data System (ADS)

Habtemariam, Lemlem Teklegiorgis; Gandorfer, Markus; Kassa, Getachew Abate; Heissenhuber, Alois

2016-08-01

Factors influencing climate change perceptions have vital roles in designing strategies to enrich climate change understanding. Despite this, factors that influence smallholder farmers' climate change perceptions have not yet been adequately studied. As many of the smallholder farmers live in regions where climate change is predicted to have the most negative impact, their climate change perception is of particular interest. In this study, based on data collected from Ethiopian smallholder farmers, we assessed farmers' perceptions and anticipations of past and future climate change. Furthermore, the factors influencing farmers' climate change perceptions and the relation between farmers' perceptions and available public climate information were assessed. Our findings revealed that a majority of respondents perceive warming temperatures and decreasing rainfall trends that correspond with the local meteorological record. Farmers' perceptions about the past climate did not always reflect their anticipations about the future. A substantial number of farmers' anticipations of future climate were less consistent with climate model projections. The recursive bivariate probit models employed to explore factors affecting different categories of climate change perceptions illustrate statistical significance for explanatory variables including location, gender, age, education, soil fertility status, climate change information, and access to credit services. The findings contribute to the literature by providing evidence not just on farmers' past climate perceptions but also on future climate anticipations. The identified factors help policy makers to provide targeted extension and advisory services to enrich climate change understanding and support appropriate farm-level climate change adaptations.

Factors Influencing Smallholder Farmers' Climate Change Perceptions: A Study from Farmers in Ethiopia.

PubMed

Habtemariam, Lemlem Teklegiorgis; Gandorfer, Markus; Kassa, Getachew Abate; Heissenhuber, Alois

2016-08-01

Factors influencing climate change perceptions have vital roles in designing strategies to enrich climate change understanding. Despite this, factors that influence smallholder farmers' climate change perceptions have not yet been adequately studied. As many of the smallholder farmers live in regions where climate change is predicted to have the most negative impact, their climate change perception is of particular interest. In this study, based on data collected from Ethiopian smallholder farmers, we assessed farmers' perceptions and anticipations of past and future climate change. Furthermore, the factors influencing farmers' climate change perceptions and the relation between farmers' perceptions and available public climate information were assessed. Our findings revealed that a majority of respondents perceive warming temperatures and decreasing rainfall trends that correspond with the local meteorological record. Farmers' perceptions about the past climate did not always reflect their anticipations about the future. A substantial number of farmers' anticipations of future climate were less consistent with climate model projections. The recursive bivariate probit models employed to explore factors affecting different categories of climate change perceptions illustrate statistical significance for explanatory variables including location, gender, age, education, soil fertility status, climate change information, and access to credit services. The findings contribute to the literature by providing evidence not just on farmers' past climate perceptions but also on future climate anticipations. The identified factors help policy makers to provide targeted extension and advisory services to enrich climate change understanding and support appropriate farm-level climate change adaptations.

Impact of Hydrologic Variability on Ecosystem Dynamics and the Sustainable Use of Soil and Water Resources

NASA Astrophysics Data System (ADS)

Porporato, A. M.

2013-05-01

We discuss the key processes by which hydrologic variability affects the probabilistic structure of soil moisture dynamics in water-controlled ecosystems. These in turn impact biogeochemical cycling and ecosystem structure through plant productivity and biodiversity as well as nitrogen availability and soil conditions. Once the long-term probabilistic structure of these processes is quantified, the results become useful to understand the impact of climatic changes and human activities on ecosystem services, and can be used to find optimal strategies of water and soil resources management under unpredictable hydro-climatic fluctuations. Particular applications regard soil salinization, phytoremediation and optimal stochastic irrigation.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

Chiriboga, A.

2007-12-01

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

Climate Teleconnections and Recent Patterns of Human and Animal Disease Outbreaks

PubMed Central

Anyamba, Assaf; Linthicum, Kenneth J.; Small, Jennifer L.; Collins, Kathrine M.; Tucker, Compton J.; Pak, Edwin W.; Britch, Seth C.; Eastman, James Ronald; Pinzon, Jorge E.; Russell, Kevin L.

2012-01-01

Background Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya. Methods and Findings We derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST) anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004–2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3–4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found that chikungunya outbreaks occurred under conditions of anomalously high temperatures and drought over Eastern Africa. However, in Southeast Asia, chikungunya outbreaks were negatively correlated (p<0.05) with drought conditions, but positively correlated with warmer-than-normal temperatures and rainfall. Conclusions/Significance Extremes in climate conditions forced by the El Niño/Southern Oscillation (ENSO) lead to severe droughts or floods, ideal ecological conditions for disease vectors to emerge, and may result in epizootics and epidemics of Rift Valley fever and chikungunya. However, the immune status of livestock (Rift Valley fever) and human (chikungunya) populations is a factor that is largely unknown but very likely plays a role in the spatial-temporal patterns of these disease outbreaks. As the frequency and severity of extremes in climate increase, the potential for globalization of vectors and disease is likely to accelerate. Understanding the underlying patterns of global and regional climate variability and their impacts on ecological drivers of vector-borne diseases is critical in long-range planning of appropriate disease and disease-vector response, control, and mitigation strategies. PMID:22292093

Climate teleconnections and recent patterns of human and animal disease outbreaks.

PubMed

Anyamba, Assaf; Linthicum, Kenneth J; Small, Jennifer L; Collins, Kathrine M; Tucker, Compton J; Pak, Edwin W; Britch, Seth C; Eastman, James Ronald; Pinzon, Jorge E; Russell, Kevin L

2012-01-01

Recent clusters of outbreaks of mosquito-borne diseases (Rift Valley fever and chikungunya) in Africa and parts of the Indian Ocean islands illustrate how interannual climate variability influences the changing risk patterns of disease outbreaks. Although Rift Valley fever outbreaks have been known to follow periods of above-normal rainfall, the timing of the outbreak events has largely been unknown. Similarly, there is inadequate knowledge on climate drivers of chikungunya outbreaks. We analyze a variety of climate and satellite-derived vegetation measurements to explain the coupling between patterns of climate variability and disease outbreaks of Rift Valley fever and chikungunya. We derived a teleconnections map by correlating long-term monthly global precipitation data with the NINO3.4 sea surface temperature (SST) anomaly index. This map identifies regional hot-spots where rainfall variability may have an influence on the ecology of vector borne disease. Among the regions are Eastern and Southern Africa where outbreaks of chikungunya and Rift Valley fever occurred 2004-2009. Chikungunya and Rift Valley fever case locations were mapped to corresponding climate data anomalies to understand associations between specific anomaly patterns in ecological and climate variables and disease outbreak patterns through space and time. From these maps we explored associations among Rift Valley fever disease occurrence locations and cumulative rainfall and vegetation index anomalies. We illustrated the time lag between the driving climate conditions and the timing of the first case of Rift Valley fever. Results showed that reported outbreaks of Rift Valley fever occurred after ∼3-4 months of sustained above-normal rainfall and associated green-up in vegetation, conditions ideal for Rift Valley fever mosquito vectors. For chikungunya we explored associations among surface air temperature, precipitation anomalies, and chikungunya outbreak locations. We found that chikungunya outbreaks occurred under conditions of anomalously high temperatures and drought over Eastern Africa. However, in Southeast Asia, chikungunya outbreaks were negatively correlated (p<0.05) with drought conditions, but positively correlated with warmer-than-normal temperatures and rainfall. Extremes in climate conditions forced by the El Niño/Southern Oscillation (ENSO) lead to severe droughts or floods, ideal ecological conditions for disease vectors to emerge, and may result in epizootics and epidemics of Rift Valley fever and chikungunya. However, the immune status of livestock (Rift Valley fever) and human (chikungunya) populations is a factor that is largely unknown but very likely plays a role in the spatial-temporal patterns of these disease outbreaks. As the frequency and severity of extremes in climate increase, the potential for globalization of vectors and disease is likely to accelerate. Understanding the underlying patterns of global and regional climate variability and their impacts on ecological drivers of vector-borne diseases is critical in long-range planning of appropriate disease and disease-vector response, control, and mitigation strategies.

Climate Change Education for General Education Faculty

NASA Astrophysics Data System (ADS)

Ozbay, G.; Fox-Lykens, R.; Fuoco, M. J.; Phalen, L.; Harcourt, P.; Veron, D. E.; Rogers, M.; Merrill, J.

2016-12-01

As MADE-CLEAR scientists, our ultimate goal is to inform the public about climate change through education. Education will provide citizens with important tools for adapting and coping against climate change through the understanding of the cause and effects of climate change, and the role they play in counteracting these effects. MADE-CLEAR is connecting educators with resources such as lesson plans and hands-on activities so they can easily incorporate climate change into their curriculum. This past year Delaware State University held workshops for Chemistry and Math faculty to provide information and resources to help integrate climate change education into their classes. We presented them with information on climate change and demonstrated several laboratory activities that would be applicable to their classes. Such activities included a sea level rise graphing exercise, ocean acidification pH demonstration, ocean acidification's effect on organism's demonstration, carbon dioxide variability and heat trapping gas simulation. The goals of the workshops are to implement a multidisciplinary approach in climate change education. Workshops are prepared hands-on heavy followed by the lectures and video resources. Pre- and post-workshop assessment questions on the workshop contents are provided to monitor faculty understanding of the climate change content. In doing so, we aim to improve climate literacy in our higher education students.

1996-2007 Interannual Spatio-Temporal Variability in Snowmelt in Two Montane Watersheds

NASA Astrophysics Data System (ADS)

Jepsen, S. M.; Molotch, N. P.; Williams, M. W.; Rittger, K. E.; Sickman, J. O.

2010-12-01

Snowmelt is a primary water resource for urban/agricultural centers and ecosystems near mountain regions. Stream chemistry from montane catchments is controlled by the flowpaths of water from snowmelt and the timing and duration of snow coverage. A process level understanding of the variability in these processes requires an understanding of the effect of changing climate and anthropogenic loading on spatio-temporal snowmelt patterns. With this as our objective, we applied a snow reconstruction model (SRM) to two well-studied montane watersheds, Tokopah Basin (TOK), California and Green Lake 4 Valley (GLV), Colorado, to examine interannual variability in the timing and location of snowmelt in response to variable climate conditions during the period from 1996 to 2007. The reconstruction model back solves for snowmelt by combining surface energy fluxes, inferred from meteorological data, with sequences of melt season snow images derived from satellite data (i.e., snowmelt depletion curves). The SRM explained 84% of the observed interannual variability in maximum watershed SWE in TOK, with errors ranging from -23 to +27% for the different years. For GLV4, the SRM explained 61% of the interannual variability, with errors ranging from -37 to +34%. In GLV4, interannual variability in snowmelt timing is a factor of four greater than the variability in streamflow timing, unlike in TOK where the ratio is nearly 1:1. We attribute this difference primarily to differences in the magnitude of the turbulent fluxes and the hydrogeology of the two study areas.

Shifts in frog size and phenology: Testing predictions of climate change on a widespread anuran using data from prior to rapid climate warming.

PubMed

Sheridan, Jennifer A; Caruso, Nicholas M; Apodaca, Joseph J; Rissler, Leslie J

2018-01-01

Changes in body size and breeding phenology have been identified as two major ecological consequences of climate change, yet it remains unclear whether climate acts directly or indirectly on these variables. To better understand the relationship between climate and ecological changes, it is necessary to determine environmental predictors of both size and phenology using data from prior to the onset of rapid climate warming, and then to examine spatially explicit changes in climate, size, and phenology, not just general spatial and temporal trends. We used 100 years of natural history collection data for the wood frog, Lithobates sylvaticus with a range >9 million km 2 , and spatially explicit environmental data to determine the best predictors of size and phenology prior to rapid climate warming (1901-1960). We then tested how closely size and phenology changes predicted by those environmental variables reflected actual changes from 1961 to 2000. Size, phenology, and climate all changed as expected (smaller, earlier, and warmer, respectively) at broad spatial scales across the entire study range. However, while spatially explicit changes in climate variables accurately predicted changes in phenology, they did not accurately predict size changes during recent climate change (1961-2000), contrary to expectations from numerous recent studies. Our results suggest that changes in climate are directly linked to observed phenological shifts. However, the mechanisms driving observed body size changes are yet to be determined, given the less straightforward relationship between size and climate factors examined in this study. We recommend that caution be used in "space-for-time" studies where measures of a species' traits at lower latitudes or elevations are considered representative of those under future projected climate conditions. Future studies should aim to determine mechanisms driving trends in phenology and body size, as well as the impact of climate on population density, which may influence body size.

Regional agricultural susceptibility to climate variability: A district level analysis of Maharashtra, India

NASA Astrophysics Data System (ADS)

Swami, D.; Parthasarathy, D.; Dave, P.

2016-12-01

Climate variability (CV) has adverse impact on crop production and inadequate research carried out to assess the impact of CV on crop production has aggravated the ability of farmers to adapt (Jones et al., 2000). A better understanding of CV is required to reduce the vulnerability of farmers towards existing and future CV. Further, a wide variation in policies related to climate change exists at global level and considering the state/nation as a single unit for policy formulations may lead to under-representation of regional problems. Hence, the present work chooses to focus on CVassessment at the regional/district level of Maharashtra state in India. Here, interannual variability of wet and dry spells from year 1951-2013, are used as a measure of CV. Statistical declining trend of wet spells for (12/34) districts was observed across all the districts of Maharashtra. Districts showing highest change in wet spell pre and post 1976/77 are Beed, Latur and Osmanabad belong to Central Maharashtra Plateau zone and Western Maharashtra scarcity zone. Dry spells for (8/34) districts were found to statistically increase across all the districts of Maharashtra. Washim, Yavatmal of Vidarbha zone; and Latur, Parbhani of Amravati division belonging to Central Maharashtra Plateau zone and Central Vidarbha zone are found to reflect the large variation in their behavior pre and post 1976/77. Findings reveal that districts from the same agro-climate zones respond differently to CV, indicating significant spatial heterogeneity within the region. Trend in monsoon variability was found to be prominent after 1976/77, suggesting an enhanced role of climate change on climate variability after 1977. It necessitates separate policy formulation related to CV and agriculture for each district to bring out the solution for regional issues (socio-political, farmers, agriculturalists, economical) more clearly. Further we have attempted to link agriculture vulnerability and crop sensitivity to CV. Results signify spatial and temporal variability of different agro-ecological and climate parameters; suitable adaptation measures to famers and policy makers need to address this change. The findings can be utilized by farmers and policy makers while formulating agricultural policies and adaptation measures related to climate change.

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

USGS Publications Warehouse

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

2013-01-01

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

Hydrology, phenology and the USA National Phenology Network

USGS Publications Warehouse

Kish, George R.

2010-01-01

Phenology is the study of seasonally-recurring biological events (such as leaf-out, fruit production, and animal reproduction and migration) and how these events are influenced by environmental change. Phenological changes are some of the most sensitive biological indicators of climate change, and also affect nearly all aspects of ecosystem function. Spatially extensive patterns of phenological observations have been closely linked with climate variability. Phenology and hydrology are closely linked and affect one another across a variety of scales, from leaf intercellular spaces to the troposphere, and over periods of seconds to centuries. Ecosystem life cycles and diversity are also influenced by hydrologic processes such as floods and droughts. Therefore, understanding the relationships between hydrology and phenology is increasingly important in understanding how climate change affects biological and physical systems.

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

NASA Technical Reports Server (NTRS)

Walsh, Kevin; Camargo, Suzana J.; Vecchi, Gabriel A.; Daloz, Anne Sophie; Elsner, James; Emanuel, Kerry; Horn, Michael; Lim, Young-Kwon; Roberts, Malcolm; Patricola, Christina;

Dynamics of the Coupled Human-climate System Resulting from Closed-loop Control of Solar Geoengineering

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

MacMartin, Douglas; Kravitz, Benjamin S.; Keith, David

2014-07-08

If solar radiation management (SRM) were ever implemented, feedback of the observed climate state might be used to adjust the radiative forcing of SRM, in order to compensate for uncertainty in either the forcing or the climate response; this would also compensate for unexpected changes in the system, e.g. a nonlinear change in climate sensitivity. This feedback creates an emergent coupled human-climate system, with entirely new dynamics. In addition to the intended response to greenhouse-gas induced changes, the use of feedback would also result in a geoengineering response to natural climate variability. We use a simple box-diffusion dynamic model tomore » understand how changing feedback-control parameters and time delay affect the behavior of this coupled natural-human system, and verify these predictions using the HadCM3L general circulation model. In particular, some amplification of natural variability is unavoidable; any time delay (e.g., to average out natural variability, or due to decision-making) exacerbates this amplification, with oscillatory behavior possible if there is a desire for rapid correction (high feedback gain), but a delayed response needed for decision making. Conversely, the need for feedback to compensate for uncertainty, combined with a desire to avoid excessive amplification, results in a limit on how rapidly SRM could respond to uncertain changes.« less

Worthy of their name: how floods drive outbreaks of two major floodwater mosquitoes (Diptera: Culicidae).

PubMed

Berec, Ludĕk; Gelbic, Ivan; Sebesta, Oldrich

2014-01-01

An understanding of how climate variables drive seasonal dynamics of mosquito populations is critical to mitigating negative impacts of potential outbreaks, including both nuisance effects and risk of mosquito-borne infectious disease. Here, we identify climate variables most affecting seasonal dynamics of two major floodwater mosquitoes, Aedes vexans (Meigen, 1830) and Aedes sticticus (Meigen, 1838) (Diptera: Culicidae), along the lower courses of the Dyje River, at the border between the Czech Republic and Austria. Monthly trap counts of both floodwater mosquitoes varied both across sites and years. Despite this variability, both models used to fit the observed data at all sites (and especially that for Ae. sticticus) and site-specific models fitted the observed data quite well. The most important climate variables we identified-temperature and especially flooding-were driving seasonal dynamics of both Aedes species. We suggest that flooding determines seasonal peaks in the monthly mosquito trap counts while temperature modulates seasonality in these counts. Hence, floodwater mosquitoes indeed appear worthy of their name. Moreover, the climate variables we considered for modeling were able reasonably to predict mosquito trap counts in the month ahead. Our study can help in planning flood management; timely notification of people, given that these mosquitoes are a real nuisance in this region; public health policy management to mitigate risk from such mosquito-borne diseases as that caused in humans by the Tahyna virus; and anticipating negative consequences of climate change, which are expected only to worsen unless floods, or the mosquitoes themselves, are satisfactorily managed.

Deglacial variability of Antarctic Intermediate Water penetration into the North Atlantic from authigenic neodymium isotope ratios

NASA Astrophysics Data System (ADS)

Xie, Ruifang C.; Marcantonio, Franco; Schmidt, Matthew W.

2012-09-01

Understanding intermediate water circulation across the last deglacial is critical in assessing the role of oceanic heat transport associated with Atlantic Meridional Overturning Circulation variability across abrupt climate events. However, the links between intermediate water circulation and abrupt climate events such as the Younger Dryas (YD) and Heinrich Event 1 (H1) are still poorly constrained. Here, we reconstruct changes in Antarctic Intermediate Water (AAIW) circulation in the subtropical North Atlantic over the past 25 kyr by measuring authigenic neodymium isotope ratios in sediments from two sites in the Florida Straits. Our authigenic Nd isotope records suggest that there was little to no penetration of AAIW into the subtropical North Atlantic during the YD and H1. Variations in the northward penetration of AAIW into the Florida Straits documented in our authigenic Nd isotope record are synchronous with multiple climatic archives, including the Greenland ice core δ18O record, the Cariaco Basin atmosphere Δ14C reconstruction, the Bermuda Rise sedimentary Pa/Th record, and nutrient and stable isotope data from the tropical North Atlantic. The synchroneity of our Nd records with multiple climatic archives suggests a tight connection between AAIW variability and high-latitude North Atlantic climate change.

Assessing the Agricultural Vulnerability for India under Changing Climate

NASA Astrophysics Data System (ADS)

Sharma, Tarul; Vardhan Murari, Harsha; Karmakar, Subhankar; Ghosh, Subimal; Singh, Jitendra

2016-04-01

Global climate change has proven to show majorly negative impacts for the far future. These negative impacts adversely affect almost all the fields including agriculture, water resources, tourism, and marine ecosystem. Among these, the effects on agriculture are considered to be of prime importance since its regional impacts can directly affect the global food security. Under such lines, it becomes essential to understand how climate change directs agricultural production for a region along with its vulnerability. In India, rice and wheat are considered as major staple diet and hence understanding its production loss/gain due to regional vulnerability to climate change becomes necessary. Here, an attempt has been made to understand the agricultural vulnerability for rice and wheat, considering yield as a function of temperature and precipitation during growing period. In order to accomplish this objective, the ratio of actual to potential evapo-transpiration has been considered which serves as a reliable indicator; with more this ratio towards unity, less vulnerable will be the region. The current objective needs an integration of climatic, hydrological and agricultural parameters; that can be achieved by simulating a climate data driven hydrologic (Variable Infiltration Capacity, VIC) model and a crop (Decision Support System for Agrotechnology Transfer, DSSAT) model. The proposed framework is an attempt to derive a crop vulnerability map that can facilitate in strategizing adaption practices which can reduce the adverse impacts of climate change in future.

Wood Cellular Dendroclimatology: A Pilot Study on Bristlecone Pine in the Southwest US

NASA Astrophysics Data System (ADS)

Ziaco, E.; Biondi, F.; Heinrich, I.

2015-12-01

Tree-rings provide paleoclimatic records at annual to seasonal resolution for regions or periods with no instrumental climatic data. Relationships between climatic variability and wood cellular features allow for a more complete understanding of the physiological mechanisms that control the climatic response of trees. Given the increasing importance of wood anatomy as a source of dendroecological information, such studies are now starting in the US. We analyzed 10 cores of bristlecone pine (Pinus longaeva D.K. Bailey) from a high-elevation site included in the Nevada Climate-ecohydrological Assessment Network (NevCAN). Century-long chronologies (1870-2013) of wood anatomical parameters (lumen area, cell diameter, cell wall thickness) can be developed by capturing strongly contrasted microscopic images using a Confocal Laser Scanning Microscope, and then measuring cellular parameters with task-specific software. Measures of empirical signal strength were used to test the strength of the environmental information embedded in wood anatomy. Correlation functions between ring-width, cellular features, and PRISM climatic variables were produced for the period 1926-2013. Time series of anatomical features present lower autocorrelation compared to ring widths, highlighting the role of environmental conditions occurring at the time of cell formation. Mean chronologies of radial lumen length and cell diameter carry a stronger climatic signal compared to cell wall thickness, and are significantly correlated with climatic variables (maximum temperature and total precipitation) in spring (Mar-Apr) and during the growing season (Jun-Sep), whereas ring widths show weaker or no correlation. Wood anatomy holds great potential to refine dendroclimatic reconstructions at higher temporal resolution, providing better estimates of hydroclimatic variability and plant physiological adaptations in the southwest US.

Nonlinearities, scale-dependence, and individualism of boreal forest trees to climate forcing

NASA Astrophysics Data System (ADS)

Wolken, J. M.; Mann, D. H.; Grant, T. A., III; Lloyd, A. H.; Hollingsworth, T. N.

2013-12-01

Our understanding of the climate-growth relationships of trees are complicated by the nonlinearity and variability of these responses through space and time. Furthermore, trees growing at the same site may exhibit opposing growth responses to climate, a phenomenon termed growth divergence. To date the majority of dendrochronological studies in Interior Alaska have involved white spruce growing at treeline, even though black spruce is the most abundant tree species. Although changing climate-growth relationships have been observed in black spruce, there is little known about the multivariate responses of individual trees to temperature and precipitation and whether or not black spruce exhibits growth divergences similar to those documented for white spruce. To evaluate the occurrence of growth divergences in black spruce, we collected cores from trees growing on a steep, north-facing toposequence having a gradient in environmental parameters. Our overall goal was to assess how the climate-growth relationships of black spruce change over space and time. Specifically, we evaluated how topography influences the climate-growth relationships of black spruce and if the growth responses to climate are homogeneous. At the site-level most trees responded negatively to temperature and positively to precipitation, while at the tree-level black spruce exhibited heterogenous growth responses to climate that varied in both space (i.e., between sites) and time (i.e., seasonally and annually). There was a dominant response-type at each site, but there was also considerable variability in the proportion of trees exhibiting each response-type combination. Even in a climatically extreme setting like Alaska's boreal forest, tree responses to climate variability are spatially and temporally complex, as well as highly nonlinear.

Monitoring Climate Variability and Change in Northern Alaska: Updates to the U.S. Geological Survey (USGS) Climate and Permafrost Monitoring Network

NASA Astrophysics Data System (ADS)

Urban, F. E.; Clow, G. D.; Meares, D. C.

2004-12-01

Observations of long-term climate and surficial geological processes are sparse in most of the Arctic, despite the fact that this region is highly sensitive to climate change. Instrumental networks that monitor the interplay of climatic variability and geological/cryospheric processes are a necessity for documenting and understanding climate change. Improvements to the spatial coverage and temporal scale of Arctic climate data are in progress. The USGS, in collaboration with The Bureau of Land Management (BLM) and The Fish and Wildlife Service (FWS) currently maintains two types of monitoring networks in northern Alaska: (1) A 15 site network of continuously operating active-layer and climate monitoring stations, and (2) a 21 element array of deep bore-holes in which the thermal state of deep permafrost is monitored. Here, we focus on the USGS Alaska Active Layer and Climate Monitoring Network (AK-CLIM). These 15 stations are deployed in longitudinal transects that span Alaska north of the Brooks Range, (11 in The National Petroleum Reserve Alaska, (NPRA), and 4 in The Arctic National Wildlife Refuge (ANWR)). An informative overview and update of the USGS AK-CLIM network is presented, including insight to current data, processing and analysis software, and plans for data telemetry. Data collection began in 1998 and parameters currently measured include air temperature, soil temperatures (5-120 cm), snow depth, incoming and reflected short-wave radiation, soil moisture (15 cm), wind speed and direction. Custom processing and analysis software has been written that calculates additional parameters such as active layer thaw depth, thawing-degree-days, albedo, cloudiness, and duration of seasonal snow cover. Data from selected AK-CLIM stations are now temporally sufficient to begin identifying trends, anomalies, and inter-annual variability in the climate of northern Alaska.

Large deviation probabilities for correlated Gaussian stochastic processes and daily temperature anomalies

NASA Astrophysics Data System (ADS)

Massah, Mozhdeh; Kantz, Holger

2016-04-01

As we have one and only one earth and no replicas, climate characteristics are usually computed as time averages from a single time series. For understanding climate variability, it is essential to understand how close a single time average will typically be to an ensemble average. To answer this question, we study large deviation probabilities (LDP) of stochastic processes and characterize them by their dependence on the time window. In contrast to iid variables for which there exists an analytical expression for the rate function, the correlated variables such as auto-regressive (short memory) and auto-regressive fractionally integrated moving average (long memory) processes, have not an analytical LDP. We study LDP for these processes, in order to see how correlation affects this probability in comparison to iid data. Although short range correlations lead to a simple correction of sample size, long range correlations lead to a sub-exponential decay of LDP and hence to a very slow convergence of time averages. This effect is demonstrated for a 120 year long time series of daily temperature anomalies measured in Potsdam (Germany).

Decadal-Scale Forecasting of Climate Drivers for Marine Applications.

PubMed

Salinger, J; Hobday, A J; Matear, R J; O'Kane, T J; Risbey, J S; Dunstan, P; Eveson, J P; Fulton, E A; Feng, M; Plagányi, É E; Poloczanska, E S; Marshall, A G; Thompson, P A

Climate influences marine ecosystems on a range of time scales, from weather-scale (days) through to climate-scale (hundreds of years). Understanding of interannual to decadal climate variability and impacts on marine industries has received less attention. Predictability up to 10 years ahead may come from large-scale climate modes in the ocean that can persist over these time scales. In Australia the key drivers of climate variability affecting the marine environment are the Southern Annular Mode, the Indian Ocean Dipole, the El Niño/Southern Oscillation, and the Interdecadal Pacific Oscillation, each has phases that are associated with different ocean circulation patterns and regional environmental variables. The roles of these drivers are illustrated with three case studies of extreme events-a marine heatwave in Western Australia, a coral bleaching of the Great Barrier Reef, and flooding in Queensland. Statistical and dynamical approaches are described to generate forecasts of climate drivers that can subsequently be translated to useful information for marine end users making decisions at these time scales. Considerable investment is still needed to support decadal forecasting including improvement of ocean-atmosphere models, enhancement of observing systems on all scales to support initiation of forecasting models, collection of important biological data, and integration of forecasts into decision support tools. Collaboration between forecast developers and marine resource sectors-fisheries, aquaculture, tourism, biodiversity management, infrastructure-is needed to support forecast-based tactical and strategic decisions that reduce environmental risk over annual to decadal time scales. © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Moradkhani, Hamid; Rana, Arun

2018-01-01

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

Climate variability drives recent tree mortality in Europe.

PubMed

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

2017-11-01

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

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

PubMed

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

2014-12-01

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

Water-the Nation's Fundamental Climate Issue A White Paper on the U.S. Geological Survey Role and Capabilities

USGS Publications Warehouse

Lins, Harry F.; Hirsch, Robert M.; Kiang, Julie

2010-01-01

Of all the potential threats posed by climatic variability and change, those associated with water resources are arguably the most consequential for both society and the environment (Waggoner, 1990). Climatic effects on agriculture, aquatic ecosystems, energy, and industry are strongly influenced by climatic effects on water. Thus, understanding changes in the distribution, quantity and quality of, and demand for water in response to climate variability and change is essential to planning for and adapting to future climatic conditions. A central role of the U.S. Geological Survey (USGS) with respect to climate is to document environmental changes currently underway and to develop improved capabilities to predict future changes. Indeed, a centerpiece of the USGS role is a new Climate Effects Network of monitoring sites. Measuring the climatic effects on water is an essential component of such a network (along with corresponding effects on terrestrial ecosystems). The USGS needs to be unambiguous in communicating with its customers and stakeholders, and with officials at the Department of the Interior, that although modeling future impacts of climate change is important, there is no more critical role for the USGS in climate change science than that of measuring and describing the changes that are currently underway. One of the best statements of that mission comes from a short paper by Ralph Keeling (2008) that describes the inspiration and the challenges faced by David Keeling in operating the all-important Mauna Loa Observatory over a period of more than four decades. Ralph Keeling stated: 'The only way to figure out what is happening to our planet is to measure it, and this means tracking changes decade after decade and poring over the records.' There are three key ideas that are important to the USGS in the above-mentioned sentence. First, to understand what is happening requires measurement. While models are a tool for learning and testing our understanding, they are not a substitute for observations. The second key idea is that measurement needs to be done over a period of many decades. When viewing hydrologic records over time scales of a few years to a few decades, trends commonly appear. However, when viewed in the context of many decades to centuries, these short-term trends are recognized as being part of much longer term oscillations. Thus, while we might want to initiate monitoring of important aspects of our natural resources, the data that will prove to be most useful in the next few years are those records that already have long-term continuity. USGS streamflow and groundwater level data are excellent examples of such long-term records. These measured data span many decades, follow standard protocols for collection and quality assurance, and are stored in a database that provides access to the full period of record. The third point from the Keeling quote relates to the notion of ?poring over the records.? Important trends will not generally jump off the computer screen at us. Thoughtful analyses are required to get past a number of important but confounding influences in the record, such as the role of seasonal variation, changes in water management, or influences of quasi-periodic phenomena, such as El Ni?o-Southern Oscillation (ENSO) or the Pacific Decadal Oscillation (PDO). No organization is better situated to pore over the records than the USGS because USGS scientists know the data, quality-assure the data, understand the factors that influence the data, and have the ancillary information on the watersheds within which the data are collected. To fulfill the USGS role in understanding climatic variability and change, we need to continually improve and strengthen two of our key capabilities: (1) preserving continuity of long-term water data collection and (2) analyzing and interpreting water data to determine how the Nation's water resources are changing. Understanding change in water resources

Regional Arctic System Model (RASM): A Tool to Advance Understanding and Prediction of Arctic Climate Change at Process Scales

NASA Astrophysics Data System (ADS)

Maslowski, W.; Roberts, A.; Osinski, R.; Brunke, M.; Cassano, J. J.; Clement Kinney, J. L.; Craig, A.; Duvivier, A.; Fisel, B. J.; Gutowski, W. J., Jr.; Hamman, J.; Hughes, M.; Nijssen, B.; Zeng, X.

2014-12-01

The Arctic is undergoing rapid climatic changes, which are some of the most coordinated changes currently occurring anywhere on Earth. They are exemplified by the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Global Climate and Global Earth System Models (GC/ESMs) are in broad agreement with these changes, the rate of change in the GC/ESMs remains outpaced by observations. Reasons for that stem from a combination of coarse model resolution, inadequate parameterizations, unrepresented processes and a limited knowledge of physical and other real world interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the GC/ESM limitations in simulating observed seasonal to decadal variability and trends in the sea ice cover and climate. RASM is a high resolution, fully coupled, pan-Arctic climate model that uses the Community Earth System Model (CESM) framework. It uses the Los Alamos Sea Ice Model (CICE) and Parallel Ocean Program (POP) configured at an eddy-permitting resolution of 1/12° as well as the Weather Research and Forecasting (WRF) and Variable Infiltration Capacity (VIC) models at 50 km resolution. All RASM components are coupled via the CESM flux coupler (CPL7) at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled earth system model, which due to the additional constraints from lateral boundary conditions and nudging within a regional model domain facilitates detailed comparisons with observational statistics that are not possible with GC/ESMs. In this talk, we will emphasize the utility of RASM to understand sensitivity to variable parameter space, importance of critical processes, coupled feedbacks and ultimately to reduce uncertainty in arctic climate change projections.

Pedagogical approaches, contextual variables, and the development of student self-efficacy in undergraduate physics courses

NASA Astrophysics Data System (ADS)

Fencl, Heidi S.; Scheel, Karen R.

2004-09-01

Self-efficacy, or a person's situation-specific belief that s/he can succeed in a given task, has been successful in a variety of educational studies for predicting behaviors such as perseverance and success (grades), and for understanding which behaviors are attempted or avoided. The focus of this study was to examine if classroom factors such as teaching strategies and classroom climate contribute to students' physics self-efficacy. 121 undergraduates in first semester, calculus-based introductory physics courses completed surveys assessing course experiences, self-efficacy and other outcome variables, and demographic information. Students in sections including a mix of teaching strategies did significantly better than students in the traditional section on outcome variables including self-efficacy. When individual strategies were examined, the strongest relationships were found between cooperative learning strategies and all sources of self-efficacy, and between climate variables and all sources of efficacy.

Analysis on variability and trend in Antarctic sea ice albedo between 1983 and 2009

NASA Astrophysics Data System (ADS)

Seo, Minji; Kim, Hyun-cheol; Choi, Sungwon; Lee, Kyeong-sang; Han, Kyung-soo

2017-04-01

Sea ice is key parameter in order to understand the cryosphere climate change. Several studies indicate the different trend of sea ice between Antarctica and Arctic. Albedo is important factor for understanding the energy budget and factors for observing of environment changes of Cryosphere such as South Pole, due to it mainly covered by ice and snow with high albedo value. In this study, we analyzed variability and trend of long-term sea ice albedo data to understand the changes of sea ice over Antarctica. In addiction, sea ice albedo researched the relationship with Antarctic oscillation in order to determine the atmospheric influence. We used the sea ice albedo data at The Satellite Application Facility on Climate Monitoring and Antarctic Oscillation data at NOAA Climate Prediction Center (CPC). We analyzed the annual trend in albedo using linear regression to understand the spatial and temporal tendency. Antarctic sea ice albedo has two spatial trend. Weddle sea / Ross sea sections represent a positive trend (0.26% ˜ 0.04% yr-1) and Bellingshausen Amundsen sea represents a negative trend (- 0.14 ˜ -0.25%yr-1). Moreover, we performed the correlation analysis between albedo and Antarctic oscillation. As a results, negative area indicate correlation coefficient of - 0.3639 and positive area indicates correlation coefficient of - 0.0741. Theses results sea ice albedo has regional trend according to ocean. Decreasing sea ice trend has negative relationship with Antarctic oscillation, its represent a possibility that sea ice influence atmospheric factor.

Identifying alternate pathways for climate change to impact inland recreational fishers

USGS Publications Warehouse

Hunt, Len M.; Fenichel, Eli P.; Fulton, David C.; Mendelsohn, Robert; Smith, Jordan W.; Tunney, Tyler D.; Lynch, Abigail J.; Paukert, Craig P.; Whitney, James E.

2016-01-01

Fisheries and human dimensions literature suggests that climate change influences inland recreational fishers in North America through three major pathways. The most widely recognized pathway suggests that climate change impacts habitat and fish populations (e.g., water temperature impacting fish survival) and cascades to impact fishers. Climate change also impacts recreational fishers by influencing environmental conditions that directly affect fishers (e.g., increased temperatures in northern climates resulting in extended open water fishing seasons and increased fishing effort). The final pathway occurs from climate change mitigation and adaptation efforts (e.g., refined energy policies result in higher fuel costs, making distant trips more expensive). To address limitations of past research (e.g., assessing climate change impacts for only one pathway at a time and not accounting for climate variability, extreme weather events, or heterogeneity among fishers), we encourage researchers to refocus their efforts to understand and document climate change impacts to inland fishers.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Adapting the US Food System to Climate Change Goes Beyond the Farm Gate

NASA Astrophysics Data System (ADS)

Easterling, W. E.

2014-12-01

The literature on climate change effects on food and agriculture has concentrated primarily on how crops and livestock likely will be directly affected by climate variability and change and by elevated carbon dioxide. Integrated assessments have simulated large-scale economic response to shifting agricultural productivity caused by climate change, including possible changes in food costs and prices. A small but growing literature has shown how different facets of agricultural production inside the farm gate could be adapted to climate variability and change. Very little research has examined how the full food system (production, processing and storage, transportation and trade, and consumption) is likely to be affected by climate change and how different adaptation approaches will be required by different parts of the food system. This paper will share partial results of a major assessment sponsored by USDA to determine how climate change-induced changes in global food security could affect the US food system. Emphasis is given to understanding how adaptation strategies differ widely across the food system. A common thread, however, is risk management-based decision making. Technologies and management strategies may co-evolve with climate change but a risk management framework for implementing those technologies and strategies may provide a stable foundation.

Role of climate and invasive species in structuring trout distributions in the interior Columbia River Basin, USA

USGS Publications Warehouse

Wenger, Seth J.; Isaak, Daniel J.; Dunham, Jason B.; Fausch, Kurt D.; Luce, Charles H.; Neville, Helen M.; Rieman, Bruce E.; Young, Michael K.; Nagel, David E.; Horan, Dona L.; Chandler, Gwynne L.

2011-01-01

Recent and projected climate warming trends have prompted interest in impacts on coldwater fishes. We examined the role of climate (temperature and flow regime) relative to geomorphology and land use in determining the observed distributions of three trout species in the interior Columbia River Basin, USA. We considered two native species, cutthroat trout (Oncorhynchus clarkii) and bull trout (Salvelinus confluentus), as well as nonnative brook trout (Salvelinus fontinalis). We also examined the response of the native species to the presence of brook trout. Analyses were conducted using multilevel logistic regression applied to a geographically broad database of 4165 fish surveys. The results indicated that bull trout distributions were strongly related to climatic factors, and more weakly related to the presence of brook trout and geomorphic variables. Cutthroat trout distributions were weakly related to climate but strongly related to the presence of brook trout. Brook trout distributions were related to both climate and geomorphic variables, including proximity to unconfined valley bottoms. We conclude that brook trout and bull trout are likely to be adversely affected by climate warming, whereas cutthroat trout may be less sensitive. The results illustrate the importance of considering species interactions and flow regime alongside temperature in understanding climate effects on fish.

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

NASA Astrophysics Data System (ADS)

Davy, Richard; Esau, Igor

2015-04-01

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

Hydrologic sensitivity of headwater catchments to climate and landscape variability

NASA Astrophysics Data System (ADS)

Kelleher, Christa; Wagener, Thorsten; McGlynn, Brian; Nippgen, Fabian; Jencso, Kelsey

2013-04-01

Headwater streams cumulatively represent an extensive portion of the United States stream network, yet remain largely unmonitored and unmapped. As such, we have limited understanding of how these systems will respond to change, knowledge that is important for preserving these unique ecosystems, the services they provide, and the biodiversity they support. We compare responses across five adjacent headwater catchments located in Tenderfoot Creek Experimental Forest in Montana, USA, to understand how local differences may affect the sensitivity of headwaters to change. We utilize global, variance-based sensitivity analysis to understand which aspects of the physical system (e.g., vegetation, topography, geology) control the variability in hydrologic behavior across these basins, and how this varies as a function of time (and therefore climate). Basin fluxes and storages, including evapotranspiration, snow water equivalent and melt, soil moisture and streamflow, are simulated using the Distributed Hydrology-Vegetation-Soil Model (DHSVM). Sensitivity analysis is applied to quantify the importance of different physical parameters to the spatial and temporal variability of different water balance components, allowing us to map similarities and differences in these controls through space and time. Our results show how catchment influences on fluxes vary across seasons (thus providing insight into transferability of knowledge in time), and how they vary across catchments with different physical characteristics (providing insight into transferability in space).

The Upstream and Downstream impact of Milankovitch cycles in continental nonmarine sedimentary records

NASA Astrophysics Data System (ADS)

Valero, Luis; Garcés, Miguel; Huerta, Pedro; Cabrera, Lluís

2016-04-01

Discerning the effects of climate in the stratigraphic record is crucial for the comprehension of past climate changes. The signature of climate in sedimentary sequences is often assessed by the identification of Milankovitch cycles, as they can be recognized due to their (quasi) periodic behaviour. The integration of diverse stratigraphic disciplines is required in order to understand the different processes involved in the expression of the orbital cycles in the sedimentary records. New advances in Stratigraphy disclose the different variables that affect the sedimentation along the sediment routing systems. These variables can be summarized as the relationship between accommodation and sediment supply (AS/SS), because they account for the shifts of the total mass balance of a basin. Based in these indicators we propose a synthetic model for the understanding of the expression of climate in continental basins. Sedimentation in internally drained lake basins is particularly sensitive to net precipitation/evaporation variations. Rapid base level oscillations modify the AS/SS ratio sufficiently as to mask possible sediment flux variations associated to the changing discharge. On the other hand, basins lacking a central lacustrine system do not experience climatically-driven accommodation changes, and thus are more sensitive to archive sediment pulses. Small basins lacking carbonate facies are the ideal candidates to archive the impact of orbital forcing in the landscapes, as their small-scale sediment transfer systems are unable to buffer the upstream signal. Sedimentation models that include the relationship between accommodation and sediment supply, the effects of density and type of vegetation, and its coupled response with climate are needed to enhance their reliability.

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

NASA Astrophysics Data System (ADS)

Mehta, V. M.

2017-12-01

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

Mountain hydrology of the western United States

USGS Publications Warehouse

Bales, Roger C.; Molotch, Noah P.; Painter, Thomas H; Dettinger, Michael D.; Rice, Robert; Dozier, Jeff

2006-01-01

Climate change and climate variability, population growth, and land use change drive the need for new hydrologic knowledge and understanding. In the mountainous West and other similar areas worldwide, three pressing hydrologic needs stand out: first, to better understand the processes controlling the partitioning of energy and water fluxes within and out from these systems; second, to better understand feedbacks between hydrological fluxes and biogeochemical and ecological processes; and, third, to enhance our physical and empirical understanding with integrated measurement strategies and information systems. We envision an integrative approach to monitoring, modeling, and sensing the mountain environment that will improve understanding and prediction of hydrologic fluxes and processes. Here extensive monitoring of energy fluxes and hydrologic states are needed to supplement existing measurements, which are largely limited to streamflow and snow water equivalent. Ground‐based observing systems must be explicitly designed for integration with remotely sensed data and for scaling up to basins and whole ranges.

Characterizing and understanding the climatic determinism of high- to low-frequency variations in precipitation in northwestern France using a coupled wavelet multiresolution/statistical downscaling approach

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Dieppois, Bastien; Hannah, David; Lavers, David; Fossa, Manuel; Laignel, Benoit; Debret, Maxime

2017-04-01

Geophysical signals oscillate over several time-scales that explain different amount of their overall variability and may be related to different physical processes. Characterizing and understanding such variabilities in hydrological variations and investigating their determinism is one important issue in a context of climate change, as these variabilities can be occasionally superimposed to long-term trend possibly due to climate change. It is also important to refine our understanding of time-scale dependent linkages between large-scale climatic variations and hydrological responses on the regional or local-scale. Here we investigate such links by conducting a wavelet multiresolution statistical dowscaling approach of precipitation in northwestern France (Seine river catchment) over 1950-2016 using sea level pressure (SLP) and sea surface temperature (SST) as indicators of atmospheric and oceanic circulations, respectively. Previous results demonstrated that including multiresolution decomposition in a statistical downscaling model (within a so-called multiresolution ESD model) using SLP as large-scale predictor greatly improved simulation of low-frequency, i.e. interannual to interdecadal, fluctuations observed in precipitation. Building on these results, continuous wavelet transform of simulated precipiation using multiresolution ESD confirmed the good performance of the model to better explain variability at all time-scales. A sensitivity analysis of the model to the choice of the scale and wavelet function used was also tested. It appeared that whatever the wavelet used, the model performed similarly. The spatial patterns of SLP found as the best predictors for all time-scales, which resulted from the wavelet decomposition, revealed different structures according to time-scale, showing possible different determinisms. More particularly, some low-frequency components ( 3.2-yr and 19.3-yr) showed a much wide-spread spatial extentsion across the Atlantic. Moreover, in accordance with other previous studies, the wavelet components detected in SLP and precipitation on interannual to interdecadal time-scales could be interpreted in terms of influence of the Gulf-Stream oceanic front on atmospheric circulation. Current works are now conducted including SST over the Atlantic in order to get further insights into this mechanism.

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

PubMed

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

2018-01-01

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

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

PubMed Central

Paoli, Amélie; Holand, Øystein; Kumpula, Jouko

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Centennial-scale vegetation dynamics and climate variability in SE Europe during Marine Isotope Stage 11 based on a pollen record from Lake Ohrid

NASA Astrophysics Data System (ADS)

Kousis, Ilias; Koutsodendris, Andreas; Peyron, Odile; Leicher, Niklas; Francke, Alexander; Wagner, Bernd; Giaccio, Biagio; Knipping, Maria; Pross, Jörg

2018-06-01

To better understand climate variability during Marine Isotope Stage (MIS) 11, we here present a new, centennial-scale-resolution pollen record from Lake Ohrid (Balkan Peninsula) derived from sediment cores retrieved during an International Continental Scientific Drilling Program (ICDP) campaign. Our palynological data, augmented by quantitative pollen-based climate reconstructions, provide insight into the vegetation dynamics and thus also climate variability in SE Europe during one of the best orbital analogues for the Holocene. Comparison of our palynological results with other proxy data from Lake Ohrid as well as with regional and global climate records shows that the vegetation in SE Europe responded sensitively both to long- and short-term climate change during MIS 11. The chronology of our palynological record is based on orbital tuning, and is further supported by the detection of a new tephra from the Vico volcano, central Italy, dated to 410 ± 2 ka. Our study indicates that MIS 11c (∼424-398 ka) was the warmest interval of MIS 11. The younger part of the interglacial (i.e., MIS 11b-11a; ∼398-367 ka) exhibits a gradual cooling trend passing over into MIS 10. It is characterized by considerable millennial-scale variability as inferred by six abrupt forest-contraction events. Interestingly, the first forest contraction occurred during full interglacial conditions of MIS 11c; this event lasted for ∼1.7 kyrs (406.2-404.5 ka) and was characterized by substantial reductions in winter temperature and annual precipitation. Most notably, it occurred ∼7 ka before the end of MIS 11c and ∼15 ka before the first strong ice-rafted debris event in the North Atlantic. Our findings suggest that millennial-scale climate variability during MIS 11 was established in Southern Europe already during MIS 11c, which is earlier than in the North Atlantic where it is registered only from MIS 11b onwards.

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.

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

USGS Publications Warehouse

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

2016-01-01

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

Understanding the origin of the solar cyclic activity for an improved earth climate prediction

NASA Astrophysics Data System (ADS)

Turck-Chièze, Sylvaine; Lambert, Pascal

This review is dedicated to the processes which could explain the origin of the great extrema of the solar activity. We would like to reach a more suitable estimate and prediction of the temporal solar variability and its real impact on the Earth climatic models. The development of this new field is stimulated by the SoHO helioseismic measurements and by some recent solar modelling improvement which aims to describe the dynamical processes from the core to the surface. We first recall assumptions on the potential different solar variabilities. Then, we introduce stellar seismology and summarize the main SOHO results which are relevant for this field. Finally we mention the dynamical processes which are presently introduced in new solar models. We believe that the knowledge of two important elements: (1) the magnetic field interplay between the radiative zone and the convective zone and (2) the role of the gravity waves, would allow to understand the origin of the grand minima and maxima observed during the last millennium. Complementary observables like acoustic and gravity modes, radius and spectral irradiance from far UV to visible in parallel to the development of 1D-2D-3D simulations will improve this field. PICARD, SDO, DynaMICCS are key projects for a prediction of the next century variability. Some helioseismic indicators constitute the first necessary information to properly describe the Sun-Earth climatic connection.

Linking crop yield anomalies to large-scale atmospheric circulation in Europe.

PubMed

Ceglar, Andrej; Turco, Marco; Toreti, Andrea; Doblas-Reyes, Francisco J

2017-06-15

Understanding the effects of climate variability and extremes on crop growth and development represents a necessary step to assess the resilience of agricultural systems to changing climate conditions. This study investigates the links between the large-scale atmospheric circulation and crop yields in Europe, providing the basis to develop seasonal crop yield forecasting and thus enabling a more effective and dynamic adaptation to climate variability and change. Four dominant modes of large-scale atmospheric variability have been used: North Atlantic Oscillation, Eastern Atlantic, Scandinavian and Eastern Atlantic-Western Russia patterns. Large-scale atmospheric circulation explains on average 43% of inter-annual winter wheat yield variability, ranging between 20% and 70% across countries. As for grain maize, the average explained variability is 38%, ranging between 20% and 58%. Spatially, the skill of the developed statistical models strongly depends on the large-scale atmospheric variability impact on weather at the regional level, especially during the most sensitive growth stages of flowering and grain filling. Our results also suggest that preceding atmospheric conditions might provide an important source of predictability especially for maize yields in south-eastern Europe. Since the seasonal predictability of large-scale atmospheric patterns is generally higher than the one of surface weather variables (e.g. precipitation) in Europe, seasonal crop yield prediction could benefit from the integration of derived statistical models exploiting the dynamical seasonal forecast of large-scale atmospheric circulation.

Late Holocene sea level variability and Atlantic Meridional Overturning Circulation

USGS Publications Warehouse

Cronin, Thomas M.; Farmer, Jesse R.; Marzen, R. E.; Thomas, E.; Varekamp, J.C.

2014-01-01

Pre-twentieth century sea level (SL) variability remains poorly understood due to limits of tide gauge records, low temporal resolution of tidal marsh records, and regional anomalies caused by dynamic ocean processes, notably multidecadal changes in Atlantic Meridional Overturning Circulation (AMOC). We examined SL and AMOC variability along the eastern United States over the last 2000 years, using a SL curve constructed from proxy sea surface temperature (SST) records from Chesapeake Bay, and twentieth century SL-sea surface temperature (SST) relations derived from tide gauges and instrumental SST. The SL curve shows multidecadal-scale variability (20–30 years) during the Medieval Climate Anomaly (MCA) and Little Ice Age (LIA), as well as the twentieth century. During these SL oscillations, short-term rates ranged from 2 to 4 mm yr−1, roughly similar to those of the last few decades. These oscillations likely represent internal modes of climate variability related to AMOC variability and originating at high latitudes, although the exact mechanisms remain unclear. Results imply that dynamic ocean changes, in addition to thermosteric, glacio-eustatic, or glacio-isostatic processes are an inherent part of SL variability in coastal regions, even during millennial-scale climate oscillations such as the MCA and LIA and should be factored into efforts that use tide gauges and tidal marsh sediments to understand global sea level rise.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Forecasting seasonal hydrologic response in major river basins

NASA Astrophysics Data System (ADS)

Bhuiyan, A. M.

2014-05-01

Seasonal precipitation variation due to natural climate variation influences stream flow and the apparent frequency and severity of extreme hydrological conditions such as flood and drought. To study hydrologic response and understand the occurrence of extreme hydrological events, the relevant forcing variables must be identified. This study attempts to assess and quantify the historical occurrence and context of extreme hydrologic flow events and quantify the relation between relevant climate variables. Once identified, the flow data and climate variables are evaluated to identify the primary relationship indicators of hydrologic extreme event occurrence. Existing studies focus on developing basin-scale forecasting techniques based on climate anomalies in El Nino/La Nina episodes linked to global climate. Building on earlier work, the goal of this research is to quantify variations in historical river flows at seasonal temporal-scale, and regional to continental spatial-scale. The work identifies and quantifies runoff variability of major river basins and correlates flow with environmental forcing variables such as El Nino, La Nina, sunspot cycle. These variables are expected to be the primary external natural indicators of inter-annual and inter-seasonal patterns of regional precipitation and river flow. Relations between continental-scale hydrologic flows and external climate variables are evaluated through direct correlations in a seasonal context with environmental phenomenon such as sun spot numbers (SSN), Southern Oscillation Index (SOI), and Pacific Decadal Oscillation (PDO). Methods including stochastic time series analysis and artificial neural networks are developed to represent the seasonal variability evident in the historical records of river flows. River flows are categorized into low, average and high flow levels to evaluate and simulate flow variations under associated climate variable variations. Results demonstrated not any particular method is suited to represent scenarios leading to extreme flow conditions. For selected flow scenarios, the persistence model performance may be comparable to more complex multivariate approaches, and complex methods did not always improve flow estimation. Overall model performance indicates inclusion of river flows and forcing variables on average improve model extreme event forecasting skills. As a means to further refine the flow estimation, an ensemble forecast method is implemented to provide a likelihood-based indication of expected river flow magnitude and variability. Results indicate seasonal flow variations are well-captured in the ensemble range, therefore the ensemble approach can often prove efficient in estimating extreme river flow conditions. The discriminant prediction approach, a probabilistic measure to forecast streamflow, is also adopted to derive model performance. Results show the efficiency of the method in terms of representing uncertainties in the forecasts.

CEOS SEO and GISS Meeting

NASA Technical Reports Server (NTRS)

Killough, Brian; Stover, Shelley

2008-01-01

The Committee on Earth Observation Satellites (CEOS) provides a brief to the Goddard Institute for Space Studies (GISS) regarding the CEOS Systems Engineering Office (SEO) and current work on climate requirements and analysis. A "system framework" is provided for the Global Earth Observation System of Systems (GEOSS). SEO climate-related tasks are outlined including the assessment of essential climate variable (ECV) parameters, use of the "systems framework" to determine relevant informational products and science models and the performance of assessments and gap analyses of measurements and missions for each ECV. Climate requirements, including instruments and missions, measurements, knowledge and models, and decision makers, are also outlined. These requirements would establish traceability from instruments to products and services allowing for benefit evaluation of instruments and measurements. Additionally, traceable climate requirements would provide a better understanding of global climate models.

A network-based approach for semi-quantitative knowledge mining and its application to yield variability

NASA Astrophysics Data System (ADS)

Schauberger, Bernhard; Rolinski, Susanne; Müller, Christoph

2016-12-01

Variability of crop yields is detrimental for food security. Under climate change its amplitude is likely to increase, thus it is essential to understand the underlying causes and mechanisms. Crop models are the primary tool to project future changes in crop yields under climate change. A systematic overview of drivers and mechanisms of crop yield variability (YV) can thus inform crop model development and facilitate improved understanding of climate change impacts on crop yields. Yet there is a vast body of literature on crop physiology and YV, which makes a prioritization of mechanisms for implementation in models challenging. Therefore this paper takes on a novel approach to systematically mine and organize existing knowledge from the literature. The aim is to identify important mechanisms lacking in models, which can help to set priorities in model improvement. We structure knowledge from the literature in a semi-quantitative network. This network consists of complex interactions between growing conditions, plant physiology and crop yield. We utilize the resulting network structure to assign relative importance to causes of YV and related plant physiological processes. As expected, our findings confirm existing knowledge, in particular on the dominant role of temperature and precipitation, but also highlight other important drivers of YV. More importantly, our method allows for identifying the relevant physiological processes that transmit variability in growing conditions to variability in yield. We can identify explicit targets for the improvement of crop models. The network can additionally guide model development by outlining complex interactions between processes and by easily retrieving quantitative information for each of the 350 interactions. We show the validity of our network method as a structured, consistent and scalable dictionary of literature. The method can easily be applied to many other research fields.

A new reference frame for astronomically-tuned Plio-Pleistocene climate variability derived from a benthic oxygen isotope splice of the Mediterranean

NASA Astrophysics Data System (ADS)

Lourens, L. J.; Ziegler, M.; Konijnendijk, T. Y. M.; Hilgen, F. J.; Bos, R.; Beekvelt, B.; van Loevezijn, A.; Collin, S.

2017-12-01

The astronomical theory of climate has revolutionized our understanding of past climate change and the development of highly accurate geologic time scales for the entire Cenozoic. Most of this understanding has come from the construction of astronomically tuned global ocean benthic foraminiferal oxygen isotope (δ18O) stacked record, derived by the international drilling operations of DSDP, ODP and IODP. The tuning includes fixed phase relationships between the obliquity and precession cycles and the inferred high-latitude climate, i.e. glacial-interglacial, response, which hark back to SPECMAP, using simple ice sheet models and a limited number of radiometric dates. This approach was largely implemented in the widely applied LR04 stack, though LR04 assumed shorter response times for the smaller ice caps during the Pliocene. In the past decades, an astronomically calibrated time scale for the Pliocene and Pleistocene of the Mediterranean has been developed, which has become the reference for the standard Geologic Time Scale. Typical of the Mediterranean marine sediments are the cyclic lithological alternations, reflecting the interference between obliquity and precession-paced low latitude climate variability, such as the African monsoon. Here we present the first benthic foraminiferal based oxygen isotope record of the Mediterranean reference scale, which strikingly mirrors the LR04. We will use this record to discuss the assumed open ocean glacial-interglacial related phase relations over the past 5.3 million years.