Reflections on the nature of non-linear responses of the climate to forcing

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter

2017-04-01

On centennial to multi-millennial time scales the paleoclimatic record shows that climate responds in a very non-linear way to the external forcing. Perhaps most puzzling is the change in glacial period duration at the Middle Pleistocene Transition. From a dynamical systems perspective, this could be a change in frequency locking between the orbital forcing and the climatic response or it could be a non-linear resonance phenomenon. In both cases the climate system shows a non-trivial oscillatory behaviour. From the records it seems that this behaviour can be described by an effective dynamics on a low-dimensional slow manifold. These different possible dynamical behaviours will be discussed. References: Arianna Marchionne, Peter Ditlevsen, and Sebastian Wieczorek, "Three types of nonlinear resonances", arXiv:1605.00858 Peter Ashwin and Peter Ditlevsen, "The middle Pleistocene transition as a generic bifurcation on a slow manifold", Climate Dynamics, 45, 2683, 2015. Peter D. Ditlevsen, "The bifurcation structure and noise assisted transitions in the Pleistocene glacial cycles", Paleoceanography, 24, PA3204, 2009

The impact of future forest dynamics on climate: interactive effects of changing vegetation and disturbance regimes

PubMed Central

Thom, Dominik; Rammer, Werner; Seidl, Rupert

2018-01-01

Currently, the temperate forest biome cools the earth’s climate and dampens anthropogenic climate change. However, climate change will substantially alter forest dynamics in the future, affecting the climate regulation function of forests. Increasing natural disturbances can reduce carbon uptake and evaporative cooling, but at the same time increase the albedo of a landscape. Simultaneous changes in vegetation composition can mitigate disturbance impacts, but also influence climate regulation directly (e.g., via albedo changes). As a result of a number of interactive drivers (changes in climate, vegetation, and disturbance) and their simultaneous effects on climate-relevant processes (carbon exchange, albedo, latent heat flux) the future climate regulation function of forests remains highly uncertain. Here we address these complex interactions to assess the effect of future forest dynamics on the climate system. Our specific objectives were (1) to investigate the long-term interactions between changing vegetation composition and disturbance regimes under climate change, (2) to quantify the response of climate regulation to changes in forest dynamics, and (3) to identify the main drivers of the future influence of forests on the climate system. We investigated these issues using the individual-based forest landscape and disturbance model (iLand). Simulations were run over 200 yr for Kalkalpen National Park (Austria), assuming different future climate projections, and incorporating dynamically responding wind and bark beetle disturbances. To consistently assess the net effect on climate the simulated responses of carbon exchange, albedo, and latent heat flux were expressed as contributions to radiative forcing. We found that climate change increased disturbances (+27.7% over 200 yr) and specifically bark beetle activity during the 21st century. However, negative feedbacks from a simultaneously changing tree species composition (+28.0% broadleaved species) decreased disturbance activity in the long run (−10.1%), mainly by reducing the host trees available for bark beetles. Climate change and the resulting future forest dynamics significantly reduced the climate regulation function of the landscape, increasing radiative forcing by up to +10.2% on average over 200 yr. Overall, radiative forcing was most strongly driven by carbon exchange. We conclude that future changes in forest dynamics can cause amplifying climate feedbacks from temperate forest ecosystems. PMID:29628526

Nonlinear dynamics in ecosystem response to climatic change: Case studies and policy implications

USGS Publications Warehouse

Burkett, Virginia R.; Wilcox, Douglas A.; Stottlemyer, Robert; Barrow, Wylie; Fagre, Dan; Baron, Jill S.; Price, Jeff; Nielsen, Jennifer L.; Allen, Craig D.; Peterson, David L.; Ruggerone, Greg; Doyle, Thomas

2005-01-01

Many biological, hydrological, and geological processes are interactively linked in ecosystems. These ecological phenomena normally vary within bounded ranges, but rapid, nonlinear changes to markedly different conditions can be triggered by even small differences if threshold values are exceeded. Intrinsic and extrinsic ecological thresholds can lead to effects that cascade among systems, precluding accurate modeling and prediction of system response to climate change. Ten case studies from North America illustrate how changes in climate can lead to rapid, threshold-type responses within ecological communities; the case studies also highlight the role of human activities that alter the rate or direction of system response to climate change. Understanding and anticipating nonlinear dynamics are important aspects of adaptation planning since responses of biological resources to changes in the physical climate system are not necessarily proportional and sometimes, as in the case of complex ecological systems, inherently nonlinear.

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

NASA Astrophysics Data System (ADS)

Kolokolov, Yury; Monovskaya, Anna

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

Sensitivity of proxies on non-linear interactions in the climate system

PubMed Central

Schultz, Johannes A.; Beck, Christoph; Menz, Gunter; Neuwirth, Burkhard; Ohlwein, Christian; Philipp, Andreas

2015-01-01

Recent climate change is affecting the earth system to an unprecedented extent and intensity and has the potential to cause severe ecological and socioeconomic consequences. To understand natural and anthropogenic induced processes, feedbacks, trends, and dynamics in the climate system, it is also essential to consider longer timescales. In this context, annually resolved tree-ring data are often used to reconstruct past temperature or precipitation variability as well as atmospheric or oceanic indices such as the North Atlantic Oscillation (NAO) or the Atlantic Multidecadal Oscillation (AMO). The aim of this study is to assess weather-type sensitivity across the Northern Atlantic region based on two tree-ring width networks. Our results indicate that nonstationarities in superordinate space and time scales of the climate system (here synoptic- to global scale, NAO, AMO) can affect the climate sensitivity of tree-rings in subordinate levels of the system (here meso- to synoptic scale, weather-types). This scale bias effect has the capability to impact even large multiproxy networks and the ability of these networks to provide information about past climate conditions. To avoid scale biases in climate reconstructions, interdependencies between the different scales in the climate system must be considered, especially internal ocean/atmosphere dynamics. PMID:26686001

Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition

NASA Astrophysics Data System (ADS)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2017-04-01

An analysis of global climate response to external forcing, both anthropogenic (mainly, CO2 and aerosol) and natural (solar and volcanic), is needed for adequate predictions of global climate change. Being complex dynamical system, the climate reacts to external perturbations exciting feedbacks (both positive and negative) making the response non-trivial and poorly predictable. Thus an extraction of internal modes of climate system, investigation of their interaction with external forcings and further modeling and forecast of their dynamics, are all the problems providing the success of climate modeling. In the report the new method for principal mode extraction from climate data is presented. The method is based on the Nonlinear Dynamical Mode (NDM) expansion [1,2], but takes into account a number of external forcings applied to the system. Each NDM is represented by hidden time series governing the observed variability, which, together with external forcing time series, are mapped onto data space. While forcing time series are considered to be known, the hidden unknown signals underlying the internal climate dynamics are extracted from observed data by the suggested method. In particular, it gives us an opportunity to study the evolution of principal system's mode structure in changing external conditions and separate the internal climate variability from trends forced by external perturbations. Furthermore, the modes so obtained can be extrapolated beyond the observational time series, and long-term prognosis of modes' structure including characteristics of interconnections and responses to external perturbations, can be carried out. In this work the method is used for reconstructing and studying the principal modes of climate variability on inter-annual and decadal time scales accounting the external forcings such as anthropogenic emissions, variations of the solar activity and volcanic activity. The structure of the obtained modes as well as their response to external factors, e.g. forecast their change in 21 century under different CO2 emission scenarios, are discussed. [1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510 [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. http://doi.org/10.1063/1.4968852

Energy Balance Models and Planetary Dynamics

NASA Technical Reports Server (NTRS)

Domagal-Goldman, Shawn

2012-01-01

We know that planetary dynamics can have a significant affect on the climate of planets. Planetary dynamics dominate the glacial-interglacial periods on Earth, leaving a significant imprint on the geological record. They have also been demonstrated to have a driving influence on the climates of other planets in our solar system. We should therefore expect th.ere to be similar relationships on extrasolar planets. Here we describe a simple energy balance model that can predict the growth and thickness of glaciers, and their feedbacks on climate. We will also describe model changes that we have made to include planetary dynamics effects. This is the model we will use at the start of our collaboration to handle the influence of dynamics on climate.

Agent-based Model for the Coupled Human-Climate System

NASA Astrophysics Data System (ADS)

Zvoleff, A.; Werner, B.

2006-12-01

Integrated assessment models have been used to predict the outcome of coupled economic growth, resource use, greenhouse gas emissions and climate change, both for scientific and policy purposes. These models generally have employed significant simplifications that suppress nonlinearities and the possibility of multiple equilibria in both their economic (DeCanio, 2005) and climate (Schneider and Kuntz-Duriseti, 2002) components. As one step toward exploring general features of the nonlinear dynamics of the coupled system, we have developed a series of variations on the well studied RICE and DICE models, which employ different forms of agent-based market dynamics and "climate surprises." Markets are introduced through the replacement of the production function of the DICE/RICE models with an agent-based market modeling the interactions of producers, policymakers, and consumer agents. Technological change and population growth are treated endogenously. Climate surprises are representations of positive (for example, ice sheet collapse) or negative (for example, increased aerosols from desertification) feedbacks that are turned on with probability depending on warming. Initial results point toward the possibility of large amplitude instabilities in the coupled human-climate system owing to the mismatch between short outlook market dynamics and long term climate responses. Implications for predictability of future climate will be discussed. Supported by the Andrew W Mellon Foundation and the UC Academic Senate.

How can climate change and engineered water conveyance affect sediment dynamics in the San Francisco Bay-Delta system?

USGS Publications Warehouse

Achete, Fernanda; Van der Wegen, Mick; Roelvink, Jan Adriaan; Jaffe, Bruce E.

2017-01-01

Suspended sediment concentration is an important estuarine health indicator. Estuarine ecosystems rely on the maintenance of habitat conditions, which are changing due to direct human impact and climate change. This study aims to evaluate the impact of climate change relative to engineering measures on estuarine fine sediment dynamics and sediment budgets. We use the highly engineered San Francisco Bay-Delta system as a case study. We apply a process-based modeling approach (Delft3D-FM) to assess the changes in hydrodynamics and sediment dynamics resulting from climate change and engineering scenarios. The scenarios consider a direct human impact (shift in water pumping location), climate change (sea level rise and suspended sediment concentration decrease), and abrupt disasters (island flooding, possibly as the results of an earthquake). Levee failure has the largest impact on the hydrodynamics of the system. Reduction in sediment input from the watershed has the greatest impact on turbidity levels, which are key to primary production and define habitat conditions for endemic species. Sea level rise leads to more sediment suspension and a net sediment export if little room for accommodation is left in the system due to continuous engineering works. Mitigation measures like levee reinforcement are effective for addressing direct human impacts, but less effective for a persistent, widespread, and increasing threat like sea level rise. Progressive adaptive mitigation measures to the changes in sediment and flow dynamics resulting from sea level rise may be a more effective strategy. Our approach shows that a validated process-based model is a useful tool to address long-term (decades to centuries) changes in sediment dynamics in highly engineered estuarine systems. In addition, our modeling approach provides a useful basis for long-term, process-based studies addressing ecosystem dynamics and health.

Stochastic dynamics of melt ponds and sea ice-albedo climate feedback

NASA Astrophysics Data System (ADS)

Sudakov, Ivan

Evolution of melt ponds on the Arctic sea surface is a complicated stochastic process. We suggest a low-order model with ice-albedo feedback which describes stochastic dynamics of melt ponds geometrical characteristics. The model is a stochastic dynamical system model of energy balance in the climate system. We describe the equilibria in this model. We conclude the transition in fractal dimension of melt ponds affects the shape of the sea ice albedo curve.

Modeling Climate Dynamically

ERIC Educational Resources Information Center

Walsh, Jim; McGehee, Richard

2013-01-01

A dynamical systems approach to energy balance models of climate is presented, focusing on low order, or conceptual, models. Included are global average and latitude-dependent, surface temperature models. The development and analysis of the differential equations and corresponding bifurcation diagrams provides a host of appropriate material for…

A Statistical-Dynamical Approach to Intraseasonal Prediction of Tropical Cyclogenesis in the Western North Pacific

DTIC Science & Technology

2009-03-01

state of the climate system...information about the current or forecasted state of the climate system. Collocated with FNMOD, is the Air Force’s 14th Weather Squadron (14WS; formerly...relationships between the LSEFs and TC formations can be skillful regardless of the oscillatory state of the climate system. D.

A network-base analysis of CMIP5 "historical" experiments

NASA Astrophysics Data System (ADS)

Bracco, A.; Foudalis, I.; Dovrolis, C.

2012-12-01

In computer science, "complex network analysis" refers to a set of metrics, modeling tools and algorithms commonly used in the study of complex nonlinear dynamical systems. Its main premise is that the underlying topology or network structure of a system has a strong impact on its dynamics and evolution. By allowing to investigate local and non-local statistical interaction, network analysis provides a powerful, but only marginally explored, framework to validate climate models and investigate teleconnections, assessing their strength, range, and impacts on the climate system. In this work we propose a new, fast, robust and scalable methodology to examine, quantify, and visualize climate sensitivity, while constraining general circulation models (GCMs) outputs with observations. The goal of our novel approach is to uncover relations in the climate system that are not (or not fully) captured by more traditional methodologies used in climate science and often adopted from nonlinear dynamical systems analysis, and to explain known climate phenomena in terms of the network structure or its metrics. Our methodology is based on a solid theoretical framework and employs mathematical and statistical tools, exploited only tentatively in climate research so far. Suitably adapted to the climate problem, these tools can assist in visualizing the trade-offs in representing global links and teleconnections among different data sets. Here we present the methodology, and compare network properties for different reanalysis data sets and a suite of CMIP5 coupled GCM outputs. With an extensive model intercomparison in terms of the climate network that each model leads to, we quantify how each model reproduces major teleconnections, rank model performances, and identify common or specific errors in comparing model outputs and observations.

Putting the Weather Back Into Climate

NASA Astrophysics Data System (ADS)

Smith, Leonard A.; Stainforth, David A.

2014-05-01

The literature contains a variety of definitions of climate, and the emphasis in these definitions has changed over time. Defining climate as a mean value is, of course, both limiting and misleading; definitions of climate based on averages have been deprecated as far back as 1931 [1]. In the context of current efforts to produce climate predictions for use in climate adaptation, it is timely to consider how well various definitions of climate serve the research for applications community. From a nonlinear dynamical systems perspective it is common to associate climate with a system's natural measure (or "attractor" if such an object exists). Such a definition is not easily applied to physical systems where we have limited observations over a restricted period of time; the duration of 30 years is often mentioned today and the origin of this period is discussed. Given a dynamic system in which parameters are evolving in time, the view of climate as a natural measure becomes problematic as, by definition, there may be no attractor per se. Attractors defined for particular parameter values cannot be expected to have any association with the probability of states under transient changes in the values of that parameter. Alternatively, distributions may be determined which reflect the transient situation, based on (rather broad) additional assumptions regarding the state of the system at some point in the past (say, an ice age planet vs an interglacial planet). Such distributions reflect many of the properties one would hope to be represented in a generalised definition of the system's climate. Here we trace how definitions of climate have changed over time and highlight a number of properties of definitions of climate which would facilitate common use across researchers, from observers to theoreticians, from climate modellers to mathematicians. We show while periodic changes in parameter values (such as those found in an annual cycle or a diurnal cycle) are easily incorporated within the traditional nonlinear dynamical systems view, non-periodic or secular changes (such as those due to increasing atmospheric greenhouse gas concentrations) yield an open challenge. We argue the need both for clarifying and for clearly meeting the open challenges of defining climate in relation to the state of an evolving system, and suggest a path forward. [1] Miller, A.A., 1931: Climatology. First Ed. Methuen.

The added value of dynamical downscaling in a climate change scenario simulation:A case study for European Alps and East Asia

NASA Astrophysics Data System (ADS)

Im, Eun-Soon; Coppola, Erika; Giorgi, Filippo

2010-05-01

Since anthropogenic climate change is a rather important factor for the future human life all over the planet and its effects are not globally uniform, climate information at regional or local scales become more and more important for an accurate assessment of the potential impact of climate change on societies and ecosystems. High resolution information with suitably fine-scale for resolving complex geographical features could be a critical factor for successful linkage between climate models and impact assessment studies. However, scale mismatch between them still remains major problem. One method for overcoming the resolution limitations of global climate models and for adding regional details to coarse-grid global projections is to use dynamical downscaling by means of a regional climate model. In this study, the ECHAM5/MPI-OM (1.875 degree) A1B scenario simulation has been dynamically downscaled by using two different approaches within the framework of RegCM3 modeling system. First, a mosaic-type parameterization of subgrid-scale topography and land use (Sub-BATS) is applied over the European Alpine region. The Sub-BATS system is composed of 15 km coarse-grid cell and 3 km sub-grid cell. Second, we developed the RegCM3 one-way double-nested system, with the mother domain encompassing the eastern regions of Asia at 60 km grid spacing and the nested domain covering the Korean Peninsula at 20 km grid spacing. By comparing the regional climate model output and the driving global model ECHAM5/MPI-OM output, it is possible to estimate the added value of physically-based dynamical downscaling when for example impact studies at hydrological scale are performed.

Cloud and ice in the planetary scale circulation and in climate

NASA Technical Reports Server (NTRS)

Herman, G. F.; Houghton, D. D.; Kutzbach, J. E.; Suomi, V. E.

1984-01-01

The roles of the cryosphere, and of cloud-radiative interactions are investigated. The effects clouds and ice have in the climate system are examined. The cloud radiation research attempts explain the modes of interaction (feedback) between raditive transfer, cloud formation, and atmospheric dynamics. The role of sea ice in weather and climate is also discussed. Models are used to describe the ice and atmospheric dynamics under study.

Calibration and combination of monthly near-surface temperature and precipitation predictions over Europe

NASA Astrophysics Data System (ADS)

Rodrigues, Luis R. L.; Doblas-Reyes, Francisco J.; Coelho, Caio A. S.

2018-02-01

A Bayesian method known as the Forecast Assimilation (FA) was used to calibrate and combine monthly near-surface temperature and precipitation outputs from seasonal dynamical forecast systems. The simple multimodel (SMM), a method that combines predictions with equal weights, was used as a benchmark. This research focuses on Europe and adjacent regions for predictions initialized in May and November, covering the boreal summer and winter months. The forecast quality of the FA and SMM as well as the single seasonal dynamical forecast systems was assessed using deterministic and probabilistic measures. A non-parametric bootstrap method was used to account for the sampling uncertainty of the forecast quality measures. We show that the FA performs as well as or better than the SMM in regions where the dynamical forecast systems were able to represent the main modes of climate covariability. An illustration with the near-surface temperature over North Atlantic, the Mediterranean Sea and Middle-East in summer months associated with the well predicted first mode of climate covariability is offered. However, the main modes of climate covariability are not well represented in most situations discussed in this study as the seasonal dynamical forecast systems have limited skill when predicting the European climate. In these situations, the SMM performs better more often.

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

Climatic water balance and agricultural productivity dynamics in Dobrogea, southeastern Romania, against the background of climate change over the past decades

NASA Astrophysics Data System (ADS)

Bandoc, Georgeta; Pravalie, Remus

2015-04-01

Interdisciplinary analyses of the relationship between climate system dynamics and agricultural system variation are an essential component for increasing the efficiency of water resource management, and for adapting crops at local level. This paper analyzes the dynamics of the climate water balance (CWB) in the past five decades in Romania's most arid region, Dobrogea, against the background of climate change, as well as the statistical relationship between the variation of CWB values and that of regional agricultural systems. Thus, a first stage consisted in detailed climatic analyses of CWB value variation between 1961 and 2009, based on climatic data provided by 9 regional weather stations. The study mainly focused on CWB trends (mm) recorded annually and seasonally (winter, spring, summer and autumn), using statistical methods such as the Mann-Kendall test and the Sen's slope method, as well as GIS methods in order to visualize the results. The second main stage was directed towards the analysis of the statistical relationship between the aforementioned climate indicator's dynamics and agricultural yields (t / ha / year) in the administrative-territorial units overlapping Dobrogea (generally the plateau region), while corn was considered for the case study as it is one of the region's main crops. In this instance, the agro-climatic data were analyzed / statistically correlated in the 1990-2003 period (depending on data availability for corn production output at administrative unit level), based on Thiessen-Voronoi polygons which were considered to be compact spatial units in which both data categories can be grouped in order to establish interannual relationships. In terms of climate, the results indicated an annual increase of the climatic water deficit at the stations located in the northern region of the study area, with maximum rates of -3.2 mm / year. In contrast, CWB values decreased seasonally (the climatic water deficit increased) roughly throughout Dobrogea (winter, spring and summer, with maximum negative rates of -1.4 mm / year in the warmest season), except for autumn, characterized by general increasing rates, with maximum values in the southwest (2.3 mm / year). However, a general trend overview indicated an overall lack of statistical significance. Considering the 1990-2003 time interval, the data analysis in the Thiessen polygons showed an overall similarity of agro-climatic oscillations, a first assessment of which indicated a general correlation between climate and agricultural data. However, upon analysis of the data series normality criterion, it was found that, during the 14 years, the CWB index variation influenced the dynamics of corn yields especially in the south-central region, in certain cases by up to 50%, causing losses of up to 11 kg / ha / year when the deficit increased by 1 mm. Therefore, while climatic results indicated CWB summer decreases (the most important season in corn productivity dynamics) in the northern region as well, the asymmetries found in agro-climatic data distributions in the northern region did not allow a statistical assessment of the dependence of agriculture on climatic conditions. Hence, for the northern region of the study area, the results indicate the role of additional factors in the dynamics of agricultural systems, which can be both natural (soil and groundwater characteristics) and anthropogenic (management conditions).

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.

Assessing global climate-terrestrial vegetation feedbacks on carbon and nitrogen cycling in the earth system model EC-Earth

NASA Astrophysics Data System (ADS)

Wårlind, David; Miller, Paul; Nieradzik, Lars; Söderberg, Fredrik; Anthoni, Peter; Arneth, Almut; Smith, Ben

2017-04-01

There has been great progress in developing an improved European Consortium Earth System Model (EC-Earth) in preparation for the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the next Assessment Report of the IPCC. The new model version has been complemented with ocean biogeochemistry, atmospheric composition (aerosols and chemistry) and dynamic land vegetation components, and has been configured to use the recommended CMIP6 forcing data sets. These new components will give us fresh insights into climate change. This study focuses on the terrestrial biosphere component Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) that simulates vegetation dynamics and compound exchange between the terrestrial biosphere and the atmosphere in EC-Earth. LPJ-GUESS allows for vegetation to dynamically evolve, depending on climate input, and in return provides the climate system and land surface scheme with vegetation-dependent fields such as vegetation types and leaf area index. We present the results of a study to examine the feedbacks between the dynamic terrestrial vegetation and the climate and their impact on the terrestrial ecosystem carbon and nitrogen cycles. Our results are based on a set of global, atmosphere-only historical simulations (1870 to 2014) with and without feedback between climate and vegetation and including or ignoring the effect of nitrogen limitation on plant productivity. These simulations show to what extent the addition degree of freedom in EC-Earth, introduced with the coupling of interactive dynamic vegetation to the atmosphere, has on terrestrial carbon and nitrogen cycling, and represent contributions to CMIP6 (C4MIP and LUMIP) and the EU Horizon 2020 project CRESCENDO.

The impacts of climate change in coastal marine systems.

PubMed

Harley, Christopher D G; Randall Hughes, A; Hultgren, Kristin M; Miner, Benjamin G; Sorte, Cascade J B; Thornber, Carol S; Rodriguez, Laura F; Tomanek, Lars; Williams, Susan L

2006-02-01

Anthropogenically induced global climate change has profound implications for marine ecosystems and the economic and social systems that depend upon them. The relationship between temperature and individual performance is reasonably well understood, and much climate-related research has focused on potential shifts in distribution and abundance driven directly by temperature. However, recent work has revealed that both abiotic changes and biological responses in the ocean will be substantially more complex. For example, changes in ocean chemistry may be more important than changes in temperature for the performance and survival of many organisms. Ocean circulation, which drives larval transport, will also change, with important consequences for population dynamics. Furthermore, climatic impacts on one or a few 'leverage species' may result in sweeping community-level changes. Finally, synergistic effects between climate and other anthropogenic variables, particularly fishing pressure, will likely exacerbate climate-induced changes. Efforts to manage and conserve living marine systems in the face of climate change will require improvements to the existing predictive framework. Key directions for future research include identifying key demographic transitions that influence population dynamics, predicting changes in the community-level impacts of ecologically dominant species, incorporating populations' ability to evolve (adapt), and understanding the scales over which climate will change and living systems will respond.

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

USGS Publications Warehouse

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

2015-01-01

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

Spatio-Temporal Dynamics of Maize Yield Water Constraints under Climate Change in Spain

PubMed Central

Ferrero, Rosana; Lima, Mauricio; Gonzalez-Andujar, Jose Luis

2014-01-01

Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent “hot-spots” in future climate change projections. Our new approach allowed us to: (1) evaluate new structural properties such as the stability of crop yield dynamics, (2) detect nonlinear responses to climate change (thresholds and discontinuities), challenging the usual linear way of thinking, and (3) examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity. PMID:24878747

Spatio-temporal dynamics of maize yield water constraints under climate change in Spain.

PubMed

Ferrero, Rosana; Lima, Mauricio; Gonzalez-Andujar, Jose Luis

2014-01-01

Many studies have analyzed the impact of climate change on crop productivity, but comparing the performance of water management systems has rarely been explored. Because water supply and crop demand in agro-systems may be affected by global climate change in shaping the spatial patterns of agricultural production, we should evaluate how and where irrigation practices are effective in mitigating climate change effects. Here we have constructed simple, general models, based on biological mechanisms and a theoretical framework, which could be useful in explaining and predicting crop productivity dynamics. We have studied maize in irrigated and rain-fed systems at a provincial scale, from 1996 to 2009 in Spain, one of the most prominent "hot-spots" in future climate change projections. Our new approach allowed us to: (1) evaluate new structural properties such as the stability of crop yield dynamics, (2) detect nonlinear responses to climate change (thresholds and discontinuities), challenging the usual linear way of thinking, and (3) examine spatial patterns of yield losses due to water constraints and identify clusters of provinces that have been negatively affected by warming. We have reduced the uncertainty associated with climate change impacts on maize productivity by improving the understanding of the relative contributions of individual factors and providing a better spatial comprehension of the key processes. We have identified water stress and water management systems as being key causes of the yield gap, and detected vulnerable regions where efforts in research and policy should be prioritized in order to increase maize productivity.

Climate effects and feedback structure determining weed population dynamics in a long-term experiment.

PubMed

Lima, Mauricio; Navarrete, Luis; González-Andujar, José Luis

2012-01-01

Pest control is one of the areas in which population dynamic theory has been successfully applied to solve practical problems. However, the links between population dynamic theory and model construction have been less emphasized in the management and control of weed populations. Most management models of weed population dynamics have emphasized the role of the endogenous process, but the role of exogenous variables such as climate have been ignored in the study of weed populations and their management. Here, we use long-term data (22 years) on two annual weed species from a locality in Central Spain to determine the importance of endogenous and exogenous processes (local and large-scale climate factors). Our modeling study determined two different feedback structures and climate effects in the two weed species analyzed. While Descurainia sophia exhibited a second-order feedback and low climate influence, Veronica hederifolia was characterized by a first-order feedback structure and important effects from temperature and rainfall. Our results strongly suggest the importance of theoretical population dynamics in understanding plant population systems. Moreover, the use of this approach, discerning between the effect of exogenous and endogenous factors, can be fundamental to applying weed management practices in agricultural systems and to controlling invasive weedy species. This is a radical change from most approaches currently used to guide weed and invasive weedy species managements.

Climate Effects and Feedback Structure Determining Weed Population Dynamics in a Long-Term Experiment

PubMed Central

Lima, Mauricio; Navarrete, Luis; González-Andujar, José Luis

2012-01-01

Pest control is one of the areas in which population dynamic theory has been successfully applied to solve practical problems. However, the links between population dynamic theory and model construction have been less emphasized in the management and control of weed populations. Most management models of weed population dynamics have emphasized the role of the endogenous process, but the role of exogenous variables such as climate have been ignored in the study of weed populations and their management. Here, we use long-term data (22 years) on two annual weed species from a locality in Central Spain to determine the importance of endogenous and exogenous processes (local and large-scale climate factors). Our modeling study determined two different feedback structures and climate effects in the two weed species analyzed. While Descurainia sophia exhibited a second-order feedback and low climate influence, Veronica hederifolia was characterized by a first-order feedback structure and important effects from temperature and rainfall. Our results strongly suggest the importance of theoretical population dynamics in understanding plant population systems. Moreover, the use of this approach, discerning between the effect of exogenous and endogenous factors, can be fundamental to applying weed management practices in agricultural systems and to controlling invasive weedy species. This is a radical change from most approaches currently used to guide weed and invasive weedy species managements. PMID:22272362

System dynamics approach for modeling of sugar beet yield considering the effects of climatic variables.

PubMed

Pervin, Lia; Islam, Md Saiful

2015-02-01

The aim of this study was to develop a system dynamics model for computation of yields and to investigate the dependency of yields on some major climatic parameters, i.e. temperature and rainfall, for Beta vulgaris subsp. (sugar beet crops) under future climate change scenarios. A system dynamics model was developed which takes account of the effects of rainfall and temperature on sugar beet yields under limited irrigation conditions. A relationship was also developed between the seasonal evapotranspiration and seasonal growing degree days for sugar beet crops. The proposed model was set to run for the present time period of 1993-2012 and for the future period 2013-2040 for Lethbridge region (Alberta, Canada). The model provides sugar beet yields on a yearly basis which are comparable to the present field data. It was found that the future average yield will be increased at about 14% with respect to the present average yield. The proposed model can help to improve the understanding of soil water conditions and irrigation water requirements of an area under certain climatic conditions and can be used for future prediction of yields for any crops in any region (with the required information to be provided). The developed system dynamics model can be used as a supporting tool for decision making, for improvement of agricultural management practice of any region. © 2014 Society of Chemical Industry.

Multistability and tipping: From mathematics and physics to climate and brain-Minireview and preface to the focus issue.

PubMed

Feudel, Ulrike; Pisarchik, Alexander N; Showalter, Kenneth

2018-03-01

Multistability refers to the coexistence of different stable states in nonlinear dynamical systems. This phenomenon has been observed in laboratory experiments and in nature. In this introduction, we briefly introduce the classes of dynamical systems in which this phenomenon has been found and discuss the extension to new system classes. Furthermore, we introduce the concept of critical transitions and discuss approaches to distinguish them according to their characteristics. Finally, we present some specific applications in physics, neuroscience, biology, ecology, and climate science.

Multistability and tipping: From mathematics and physics to climate and brain—Minireview and preface to the focus issue

NASA Astrophysics Data System (ADS)

Feudel, Ulrike; Pisarchik, Alexander N.; Showalter, Kenneth

2018-03-01

Multistability refers to the coexistence of different stable states in nonlinear dynamical systems. This phenomenon has been observed in laboratory experiments and in nature. In this introduction, we briefly introduce the classes of dynamical systems in which this phenomenon has been found and discuss the extension to new system classes. Furthermore, we introduce the concept of critical transitions and discuss approaches to distinguish them according to their characteristics. Finally, we present some specific applications in physics, neuroscience, biology, ecology, and climate science.

Enhancing seasonal climate prediction capacity for the Pacific countries

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Divergent carbon dynamics under climate change in forests with diverse soils, tree species, and land use histories

Treesearch

Robert M. Scheller; Alec M. Kretchun; Steve Van Tuyl; Kenneth L. Clark; Melissa S. Lucash; John Hom

2012-01-01

Accounting for both climate change and natural disturbances—which typically result in greenhouse gas emissions—is necessary to begin managing forest carbon sequestration. Gaining a complete understanding of forest carbon dynamics is, however, challenging in systems characterized by historic over-utilization, diverse soils and tree species, and...

Using simple chaotic models to interpret climate under climate change: Implications for probabilistic climate prediction

NASA Astrophysics Data System (ADS)

Daron, Joseph

2010-05-01

Exploring the reliability of model based projections is an important pre-cursor to evaluating their societal relevance. In order to better inform decisions concerning adaptation (and mitigation) to climate change, we must investigate whether or not our models are capable of replicating the dynamic nature of the climate system. Whilst uncertainty is inherent within climate prediction, establishing and communicating what is plausible as opposed to what is likely is the first step to ensuring that climate sensitive systems are robust to climate change. Climate prediction centers are moving towards probabilistic projections of climate change at regional and local scales (Murphy et al., 2009). It is therefore important to understand what a probabilistic forecast means for a chaotic nonlinear dynamic system that is subject to changing forcings. It is in this context that we present the results of experiments using simple models that can be considered analogous to the more complex climate system, namely the Lorenz 1963 and Lorenz 1984 models (Lorenz, 1963; Lorenz, 1984). Whilst the search for a low-dimensional climate attractor remains illusive (Fraedrich, 1986; Sahay and Sreenivasan, 1996) the characterization of the climate system in such terms can be useful for conceptual and computational simplicity. Recognising that a change in climate is manifest in a change in the distribution of a particular climate variable (Stainforth et al., 2007), we first establish the equilibrium distributions of the Lorenz systems for certain parameter settings. Allowing the parameters to vary in time, we investigate the dependency of such distributions to initial conditions and discuss the implications for climate prediction. We argue that the role of chaos and nonlinear dynamic behaviour ought to have more prominence in the discussion of the forecasting capabilities in climate prediction. References: Fraedrich, K. Estimating the dimensions of weather and climate attractors. J. Atmos. Sci, 43, 419-432, 1986. Lorenz, E. N. Deterministic nonperiodic flow. J. Atmos. Sci., 20, 130-141, 1963. Lorenz, E. N. Irregularity: a fundamental property of the atmosphere. Tellus, 36A, 98-110, 1984. Murphy, J. M., D. M. H. Sexton, G. J. Jenkins, B. B. B. Booth, C. C. Brown, R. T. Clark, M. Collins, G. R. Harris, E. J. Kendon, R. A. Betts, S. J. Brown, P. Boorman, T. P. Howard, K. A. Humphrey, M. P. McCarthy, R. E. McDonald, A. Stephens, C. Wallace, R. Warren, R. Wilby, and R. A. Wood. Uk climate projections science report: Climate change projections. 2009. Sahay, A. and K. R. Sreenivasan. The search for a low-dimensional characterization of a local climate system. Phil. Trans. R. Soc. A., 354, 1715-1750, 1996. Stainforth, D. A., M. R. Allen, E. R. Tredger, and L. A. Smith. Confidence, uncertainty and decision-support relevance in climate predictions. Phil. Trans. R. Soc. A, 365, 2145-2161, 2007.

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.

Management of complex dynamical systems

NASA Astrophysics Data System (ADS)

MacKay, R. S.

2018-02-01

Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.

Flow networks for Ocean currents

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Molkenthin, Nora; Marwan, Norbert; Kurths, Jürgen

2014-05-01

Complex networks have been successfully applied to various systems such as society, technology, and recently climate. Links in a climate network are defined between two geographical locations if the correlation between the time series of some climate variable is higher than a threshold. Therefore, network links are considered to imply heat exchange. However, the relationship between the oceanic and atmospheric flows and the climate network's structure is still unclear. Recently, a theoretical approach verifying the correlation between ocean currents and surface air temperature networks has been introduced, where the Pearson correlation networks were constructed from advection-diffusion dynamics on an underlying flow. Since the continuous approach has its limitations, i.e., by its high computational complexity, we here introduce a new, discrete construction of flow-networks, which is then applied to static and dynamic velocity fields. Analyzing the flow-networks of prototypical flows we find that our approach can highlight the zones of high velocity by degree and transition zones by betweenness, while the combination of these network measures can uncover how the flow propagates within time. We also apply the method to time series data of the Equatorial Pacific Ocean Current and the Gulf Stream ocean current for the changing velocity fields, which could not been done before, and analyse the properties of the dynamical system. Flow-networks can be powerful tools to theoretically understand the step from system's dynamics to network's topology that can be analyzed using network measures and is used for shading light on different climatic phenomena.

Exploring tropical forest vegetation dynamics using the FATES model

NASA Astrophysics Data System (ADS)

Koven, C. D.; Fisher, R.; Knox, R. G.; Chambers, J.; Kueppers, L. M.; Christoffersen, B. O.; Davies, S. J.; Dietze, M.; Holm, J.; Massoud, E. C.; Muller-Landau, H. C.; Powell, T.; Serbin, S.; Shuman, J. K.; Walker, A. P.; Wright, S. J.; Xu, C.

2017-12-01

Tropical forest vegetation dynamics represent a critical climate feedback in the Earth system, which is poorly represented in current global modeling approaches. We discuss recent progress on exploring these dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a demographic vegetation model for the CESM and ACME ESMs. We will discuss benchmarks of FATES predictions for forest structure against inventory sites, sensitivity of FATES predictions of size and age structure to model parameter uncertainty, and experiments using the FATES model to explore PFT competitive dynamics and the dynamics of size and age distributions in responses to changing climate and CO2.

Alternative future analysis for assessing the potential impact of climate change on urban landscape dynamics.

PubMed

He, Chunyang; Zhao, Yuanyuan; Huang, Qingxu; Zhang, Qiaofeng; Zhang, Da

2015-11-01

Assessing the impact of climate change on urban landscape dynamics (ULD) is the foundation for adapting to climate change and maintaining urban landscape sustainability. This paper demonstrates an alternative future analysis by coupling a system dynamics (SD) and a cellular automata (CA) model. The potential impact of different climate change scenarios on ULD from 2009 to 2030 was simulated and evaluated in the Beijing-Tianjin-Tangshan megalopolis cluster area (BTT-MCA). The results suggested that the integrated model, which combines the advantages of the SD and CA model, has the strengths of spatial quantification and flexibility. Meanwhile, the results showed that the influence of climate change would become more severe over time. In 2030, the potential urban area affected by climate change will be 343.60-1260.66 km(2) (5.55 -20.37 % of the total urban area, projected by the no-climate-change-effect scenario). Therefore, the effects of climate change should not be neglected when designing and managing urban landscape. Copyright © 2015 Elsevier B.V. All rights reserved.

Effects of dynamic agricultural decision making in an ecohydrological model

NASA Astrophysics Data System (ADS)

Reichenau, T. G.; Krimly, T.; Schneider, K.

2012-04-01

Due to various interdependencies between the cycles of water, carbon, nitrogen, and energy the impacts of climate change on ecohydrological systems can only be investigated in an integrative way. Furthermore, the human intervention in the environmental processes makes the system even more complex. On the one hand human impact affects natural systems. On the other hand the changing natural systems have a feedback on human decision making. One of the most important examples for this kind of interaction can be found in the agricultural sector. Management dates (planting, fertilization, harvesting) are chosen based on meteorological conditions and yield expectations. A faster development of crops under a warmer climate causes shorter cropping seasons. The choice of crops depends on their profitability, which is mainly determined by market prizes, the agro-political framework, and the (climate dependent) crop yield. This study investigates these relations for the district Günzburg located in the Upper Danube catchment in southern Germany. The modeling system DANUBIA was used to perform dynamically coupled simulations of plant growth, surface and soil hydrological processes, soil nitrogen transformations, and agricultural decision making. The agro-economic model simulates decisions on management dates (based on meteorological conditions and the crops' development state), on fertilization intensities (based on yield expectations), and on choice of crops (based on profitability). The environmental models included in DANUBIA are to a great extent process based to enable its use in a climate change scenario context. Scenario model runs until 2058 were performed using an IPCC A1B forcing. In consecutive runs, dynamic crop management, dynamic crop selection, and a changing agro-political framework were activated. Effects of these model features on hydrological and ecological variables were analyzed separately by comparing the results to a model run with constant crop distribution and constant management. Results show that the influence of the modeled dynamic management adaptation on variables like transpiration, carbon uptake, or nitrate leaching from the vadose zone is stronger than the influence of a dynamic choice of crops. Climate change was found to have a stronger impact on this modeled choice of crops than the agro-political framework. These results suggest that scenario studies in areas with a large share of arable land should take into account management adaptations to changing climate.

Effective control of complex turbulent dynamical systems through statistical functionals.

PubMed

Majda, Andrew J; Qi, Di

2017-05-30

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among complex systems in science and engineering, including climate, material, and neural science. Control of these complex systems is a grand challenge, for example, in mitigating the effects of climate change or safe design of technology with fully developed shear turbulence. Control of flows in the transition to turbulence, where there is a small dimension of instabilities about a basic mean state, is an important and successful discipline. In complex turbulent dynamical systems, it is impossible to track and control the large dimension of instabilities, which strongly interact and exchange energy, and new control strategies are needed. The goal of this paper is to propose an effective statistical control strategy for complex turbulent dynamical systems based on a recent statistical energy principle and statistical linear response theory. We illustrate the potential practical efficiency and verify this effective statistical control strategy on the 40D Lorenz 1996 model in forcing regimes with various types of fully turbulent dynamics with nearly one-half of the phase space unstable.

Quantifying nonergodicity in nonautonomous dissipative dynamical systems: An application to climate change

NASA Astrophysics Data System (ADS)

Drótos, Gábor; Bódai, Tamás; Tél, Tamás

2016-08-01

In nonautonomous dynamical systems, like in climate dynamics, an ensemble of trajectories initiated in the remote past defines a unique probability distribution, the natural measure of a snapshot attractor, for any instant of time, but this distribution typically changes in time. In cases with an aperiodic driving, temporal averages taken along a single trajectory would differ from the corresponding ensemble averages even in the infinite-time limit: ergodicity does not hold. It is worth considering this difference, which we call the nonergodic mismatch, by taking time windows of finite length for temporal averaging. We point out that the probability distribution of the nonergodic mismatch is qualitatively different in ergodic and nonergodic cases: its average is zero and typically nonzero, respectively. A main conclusion is that the difference of the average from zero, which we call the bias, is a useful measure of nonergodicity, for any window length. In contrast, the standard deviation of the nonergodic mismatch, which characterizes the spread between different realizations, exhibits a power-law decrease with increasing window length in both ergodic and nonergodic cases, and this implies that temporal and ensemble averages differ in dynamical systems with finite window lengths. It is the average modulus of the nonergodic mismatch, which we call the ergodicity deficit, that represents the expected deviation from fulfilling the equality of temporal and ensemble averages. As an important finding, we demonstrate that the ergodicity deficit cannot be reduced arbitrarily in nonergodic systems. We illustrate via a conceptual climate model that the nonergodic framework may be useful in Earth system dynamics, within which we propose the measure of nonergodicity, i.e., the bias, as an order-parameter-like quantifier of climate change.

Predictive models of forest dynamics.

PubMed

Purves, Drew; Pacala, Stephen

2008-06-13

Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.

Complexity of Tropical Pacific Ecosystem and Biogeochemistry: Diurnal to Decadal, Plankters to Penguins

NASA Astrophysics Data System (ADS)

Murtugudde, R. G.; Wang, X.; Valsala, V.; Karnauskas, K. B.

2016-12-01

Tropical Pacific spans nearly 50% of the global tropics allowing to have its own mind in terms of climate variability and physical-biogeochemical interactions. While the El Niño-Southern Oscillation (ENSO) and its flavors get much attention, it is fairly clear by now that any further improvements in ENSO prediction skills and reliability of global warming projections must begin to observe and represent bio-physical interactions in the climate and Earth System models. Coupled climate variability over the tropical Pacific has a global reach with its diurnal to decadal timescales being manifest in ecosystem and biogechemistry. Zonal and meridional contrasts in biogeochemistry across the tropical Pacific is closely related to seasonal variability, ENSO diversity and the PDO. Apparent dominance of ocean dynamic controls on biogeochemistry belies the potential biogeochemical feedbacks on ocean dynamics which may well explain some of the chronic biases in the state-of-the-art climate models. The east Pacific cold-tongue is the most productive open ocean region in the world and home to a unique physical-biogeochmical laboratory, viz., the Galapagos. The Galapagos islands not only control the coupled climate variability via their ability to terminate the equatorial undercurrent but also offer a clear example of a biological loophole in terms of their impact on local upwelling and an expanding penguin habitat in the face of global warming. The complex bio-physical interactions in the cold-tongue and their influence on climate predictions and projections require a holisti thinking on future observing systems. Tropical Pacific offers a natural laboratory for designing a robust and sustained physical-biogeochemical observation system that can effectively bridge climate predictions and projections into a unified framework for subseasonal to multidecadal timescales. Such a system will be a foundation for establishing similar systems over the rest of the World ocean to seemlessly merge climate predictions and projections with the need to constantly monitor climate impacts on marine resources. This talk will focus on the zonal contrasts of the ocean dynamics and biogechemistry across the tropical Pacific to make a case for integrated physical-biogeochemical observations for climate predictions and projections.

Oscillators and relaxation phenomena in Pleistocene climate theory

PubMed Central

Crucifix, Michel

2012-01-01

Ice sheets appeared in the northern hemisphere around 3 Ma (million years) ago and glacial–interglacial cycles have paced Earth's climate since then. Superimposed on these long glacial cycles comes an intricate pattern of millennial and sub-millennial variability, including Dansgaard–Oeschger and Heinrich events. There are numerous theories about these oscillations. Here, we review a number of them in order to draw a parallel between climatic concepts and dynamical system concepts, including, in particular, the relaxation oscillator, excitability, slow–fast dynamics and homoclinic orbits. Namely, almost all theories of ice ages reviewed here feature a phenomenon of synchronization between internal climate dynamics and astronomical forcing. However, these theories differ in their bifurcation structure and this has an effect on the way the ice age phenomenon could grow 3 Ma ago. All theories on rapid events reviewed here rely on the concept of a limit cycle excited by changes in the surface freshwater balance of the ocean. The article also reviews basic effects of stochastic fluctuations on these models, including the phenomenon of phase dispersion, shortening of the limit cycle and stochastic resonance. It concludes with a more personal statement about the potential for inference with simple stochastic dynamical systems in palaeoclimate science. PMID:22291227

Climate Dynamics and Hysteresis at Low and High Obliquity

NASA Astrophysics Data System (ADS)

Colose, C.; Del Genio, A. D.; Way, M.

2017-12-01

We explore the large-scale climate dynamics at low and high obliquity for an Earth-like planet using the ROCKE-3D (Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics) 3-D General Circulation model being developed at NASA GISS as part of the Nexus for Exoplanet System Science (NExSS) initiative. We highlight the role of ocean heat storage and transport in determining the seasonal cycle at high obliquity, and describe the large-scale circulation and resulting regional climate patterns using both aquaplanet and Earth topographical boundary conditions. Finally, we contrast the hysteresis structure to varying CO2 concentration for a low and high obliquity planet near the outer edge of the habitable zone. We discuss the prospects for habitability for a high obliquity planet susceptible to global glaciation.

The Emergence of Land Use as a Global Force in the Earth System

NASA Astrophysics Data System (ADS)

Ellis, E. C.

2015-12-01

Human societies have emerged as a global force capable of transforming the biosphere, hydrosphere, lithosphere, atmosphere and climate. As a result, the long-term dynamics of the Earth system can no longer be understood or predicted without understanding their coupling with human societal dynamics. Here, a general causal theory is presented to explain why behaviorally modern humans, unlike any prior multicellular species, gained this unprecedented capacity to reshape the Earth system and how this societal capacity has changed from the Pleistocene to the present and future. Sociocultural niche construction theory, building on existing theories of ecosystem engineering, niche construction, the extended evolutionary synthesis, cultural evolution, ultrasociality and social change, can explain both the long-term upscaling of human societies and their unprecedented capacity to transform the Earth system. Regime shifts in human sociocultural niche construction, from the clearing of land using fire, to shifting cultivation, to intensive agriculture, to global food systems dependent on fossil fuel combustion, have enabled human societies to scale up while gaining the capacity to reshape the global patterns and processes of biogeography, ecosystems, landscapes, biomes, the biosphere, and ultimately the functioning of the Earth system. Just as Earth's geophysical climate system shapes the long-term dynamics of energy and material flow across the "spheres" of the Earth system, human societies, interacting at global scale to form "human systems", are increasingly shaping the global dynamics of energy, material, biotic and information flow across the spheres of the Earth system, including a newly emerged anthroposphere comprised of human societies and their material cultures. Human systems and the anthroposphere are strongly coupled with climate and other Earth systems and are dynamic in response to evolutionary changes in human social organization, cooperative ecosystem engineering, non-kin exchange relationships, and energy systems. It is hoped that intentional societal efforts to alter the dynamics of human systems can ultimately move Earth systems towards more beneficial and less detrimental outcomes for both human societies and nonhuman species.

Simulations of Tornadoes, Tropical Cyclones, MJOs, and QBOs, using GFDL's multi-scale global climate modeling system

NASA Astrophysics Data System (ADS)

Lin, Shian-Jiann; Harris, Lucas; Chen, Jan-Huey; Zhao, Ming

2014-05-01

A multi-scale High-Resolution Atmosphere Model (HiRAM) is being developed at NOAA/Geophysical Fluid Dynamics Laboratory. The model's dynamical framework is the non-hydrostatic extension of the vertically Lagrangian finite-volume dynamical core (Lin 2004, Monthly Wea. Rev.) constructed on a stretchable (via Schmidt transformation) cubed-sphere grid. Physical parametrizations originally designed for IPCC-type climate predictions are in the process of being modified and made more "scale-aware", in an effort to make the model suitable for multi-scale weather-climate applications, with horizontal resolution ranging from 1 km (near the target high-resolution region) to as low as 400 km (near the antipodal point). One of the main goals of this development is to enable simulation of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously thought impossible. We will present preliminary results, covering a very wide spectrum of temporal-spatial scales, ranging from simulation of tornado genesis (hours), Madden-Julian Oscillations (intra-seasonal), topical cyclones (seasonal), to Quasi Biennial Oscillations (intra-decadal), using the same global multi-scale modeling system.

Seasonal Water Balance Forecasts for Drought Early Warning in Ethiopia

NASA Astrophysics Data System (ADS)

Spirig, Christoph; Bhend, Jonas; Liniger, Mark

2016-04-01

Droughts severely impact Ethiopian agricultural production. Successful early warning for drought conditions in the upcoming harvest season therefore contributes to better managing food shortages arising from adverse climatic conditions. So far, however, meteorological seasonal forecasts have not been used in Ethiopia's national food security early warning system (i.e. the LEAP platform). Here we analyse the forecast quality of seasonal forecasts of total rainfall and of the meteorological water balance as a proxy for plant available water. We analyse forecast skill of June to September rainfall and water balance from dynamical seasonal forecast systems, the ECMWF System4 and EC-EARTH global forecasting systems. Rainfall forecasts outperform forecasts assuming a stationary climate mainly in north-eastern Ethiopia - an area that is particularly vulnerable to droughts. Forecasts of the water balance index seem to be even more skilful and thus more useful than pure rainfall forecasts. The results vary though for different lead times and skill measures employed. We further explore the potential added value of dynamically downscaling the forecasts through several dynamical regional climate models made available through the EU FP7 project EUPORIAS. Preliminary results suggest that dynamically downscaled seasonal forecasts are not significantly better compared with seasonal forecasts from the global models. We conclude that seasonal forecasts of a simple climate index such as the water balance have the potential to benefit drought early warning in Ethiopia, both due to its positive predictive skill and higher usefulness than seasonal mean quantities.

Summer drought predictability over Europe: empirical versus dynamical forecasts

NASA Astrophysics Data System (ADS)

Turco, Marco; Ceglar, Andrej; Prodhomme, Chloé; Soret, Albert; Toreti, Andrea; Doblas-Reyes Francisco, J.

2017-08-01

Seasonal climate forecasts could be an important planning tool for farmers, government and insurance companies that can lead to better and timely management of seasonal climate risks. However, climate seasonal forecasts are often under-used, because potential users are not well aware of the capabilities and limitations of these products. This study aims at assessing the merits and caveats of a statistical empirical method, the ensemble streamflow prediction system (ESP, an ensemble based on reordering historical data) and an operational dynamical forecast system, the European Centre for Medium-Range Weather Forecasts—System 4 (S4) in predicting summer drought in Europe. Droughts are defined using the Standardized Precipitation Evapotranspiration Index for the month of August integrated over 6 months. Both systems show useful and mostly comparable deterministic skill. We argue that this source of predictability is mostly attributable to the observed initial conditions. S4 shows only higher skill in terms of ability to probabilistically identify drought occurrence. Thus, currently, both approaches provide useful information and ESP represents a computationally fast alternative to dynamical prediction applications for drought prediction.

An effective drift correction for dynamical downscaling of decadal global climate predictions

NASA Astrophysics Data System (ADS)

Paeth, Heiko; Li, Jingmin; Pollinger, Felix; Müller, Wolfgang A.; Pohlmann, Holger; Feldmann, Hendrik; Panitz, Hans-Jürgen

2018-04-01

Initialized decadal climate predictions with coupled climate models are often marked by substantial climate drifts that emanate from a mismatch between the climatology of the coupled model system and the data set used for initialization. While such drifts may be easily removed from the prediction system when analyzing individual variables, a major problem prevails for multivariate issues and, especially, when the output of the global prediction system shall be used for dynamical downscaling. In this study, we present a statistical approach to remove climate drifts in a multivariate context and demonstrate the effect of this drift correction on regional climate model simulations over the Euro-Atlantic sector. The statistical approach is based on an empirical orthogonal function (EOF) analysis adapted to a very large data matrix. The climate drift emerges as a dramatic cooling trend in North Atlantic sea surface temperatures (SSTs) and is captured by the leading EOF of the multivariate output from the global prediction system, accounting for 7.7% of total variability. The SST cooling pattern also imposes drifts in various atmospheric variables and levels. The removal of the first EOF effectuates the drift correction while retaining other components of intra-annual, inter-annual and decadal variability. In the regional climate model, the multivariate drift correction of the input data removes the cooling trends in most western European land regions and systematically reduces the discrepancy between the output of the regional climate model and observational data. In contrast, removing the drift only in the SST field from the global model has hardly any positive effect on the regional climate model.

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

NASA Astrophysics Data System (ADS)

Kolokolov, Yury; Monovskaya, Anna

2016-06-01

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

Quantifying Key Climate Parameter Uncertainties Using an Earth System Model with a Dynamic 3D Ocean

NASA Astrophysics Data System (ADS)

Olson, R.; Sriver, R. L.; Goes, M. P.; Urban, N.; Matthews, D.; Haran, M.; Keller, K.

2011-12-01

Climate projections hinge critically on uncertain climate model parameters such as climate sensitivity, vertical ocean diffusivity and anthropogenic sulfate aerosol forcings. Climate sensitivity is defined as the equilibrium global mean temperature response to a doubling of atmospheric CO2 concentrations. Vertical ocean diffusivity parameterizes sub-grid scale ocean vertical mixing processes. These parameters are typically estimated using Intermediate Complexity Earth System Models (EMICs) that lack a full 3D representation of the oceans, thereby neglecting the effects of mixing on ocean dynamics and meridional overturning. We improve on these studies by employing an EMIC with a dynamic 3D ocean model to estimate these parameters. We carry out historical climate simulations with the University of Victoria Earth System Climate Model (UVic ESCM) varying parameters that affect climate sensitivity, vertical ocean mixing, and effects of anthropogenic sulfate aerosols. We use a Bayesian approach whereby the likelihood of each parameter combination depends on how well the model simulates surface air temperature and upper ocean heat content. We use a Gaussian process emulator to interpolate the model output to an arbitrary parameter setting. We use Markov Chain Monte Carlo method to estimate the posterior probability distribution function (pdf) of these parameters. We explore the sensitivity of the results to prior assumptions about the parameters. In addition, we estimate the relative skill of different observations to constrain the parameters. We quantify the uncertainty in parameter estimates stemming from climate variability, model and observational errors. We explore the sensitivity of key decision-relevant climate projections to these parameters. We find that climate sensitivity and vertical ocean diffusivity estimates are consistent with previously published results. The climate sensitivity pdf is strongly affected by the prior assumptions, and by the scaling parameter for the aerosols. The estimation method is computationally fast and can be used with more complex models where climate sensitivity is diagnosed rather than prescribed. The parameter estimates can be used to create probabilistic climate projections using the UVic ESCM model in future studies.

Wasp waist or beer belly? Modeling food web structure and energetic control in Alaskan marine ecosystems, with implications for fishing and environmental forcing

NASA Astrophysics Data System (ADS)

Gaichas, Sarah; Aydin, Kerim; Francis, Robert C.

2015-11-01

The Eastern Bering Sea (EBS) and Gulf of Alaska (GOA) continental shelf ecosystems show some similar and some distinctive groundfish biomass dynamics. Given that similar species occupy these regions and fisheries management is also comparable, similarities might be expected, but to what can we attribute the differences? Different types of ecosystem structure and control (e.g. top-down, bottom-up, mixed) can imply different ecosystem dynamics and climate interactions. Further, the structural type identified for a given ecosystem may suggest optimal management for sustainable fishing. Here, we use information on the current system state derived from food web models of both the EBS and the GOA combined with dynamic ecosystem models incorporating uncertainty to classify each ecosystem by its structural type. We then suggest how this structure might be generally related to dynamics and predictability. We find that the EBS and GOA have fundamentally different food web structures both overall, and when viewed from the perspective of the same commercially and ecologically important species in each system, walleye pollock (Gadus chalcogrammus). EBS food web structure centers on a large mass of pollock, which appears to contribute to relative system stability and predictability. In contrast, GOA food web structure features high predator biomass, which contributes to a more dynamic, less predictable ecosystem. Mechanisms for climate influence on pollock production in the EBS are increasingly understood, while climate forcing mechanisms contributing to the potentially destabilizing high predator biomass in the GOA remain enigmatic. We present results of identical pollock fishing and climate-driven pollock recruitment simulations in the EBS and GOA which show different system responses, again with less predictable response in the GOA. Overall, our results suggest that identifying structural properties of fished food webs is as important for sustainable fisheries management as attempting to predict climate and fisheries effects within each ecosystem.

Nonlinear Dynamics of Complex Coevolutionary Systems in Historical Times

NASA Astrophysics Data System (ADS)

Perdigão, Rui A. P.

2016-04-01

A new theoretical paradigm for statistical-dynamical modeling of complex coevolutionary systems is introduced, with the aim to provide historical geoscientists with a practical tool to analyse historical data and its underlying phenomenology. Historical data is assumed to represent the history of dynamical processes of physical and socio-economic nature. If processes and their governing laws are well understood, they are often treated with traditional dynamical equations: deterministic approach. If the governing laws are unknown or impracticable, the process is often treated as if being random (even if it is not): statistical approach. Although single eventful details - such as the exact spatiotemporal structure of a particular hydro-meteorological incident - may often be elusive to a detailed analysis, the overall dynamics exhibit group properties summarized by a simple set of categories or dynamical regimes at multiple scales - from local short-lived convection patterns to large-scale hydro-climatic regimes. The overwhelming microscale complexity is thus conveniently wrapped into a manageable group entity, such as a statistical distribution. In a stationary setting whereby the distribution is assumed to be invariant, alternating regimes are approachable as dynamical intermittence. For instance, in the context of bimodal climatic oscillations such as NAO and ENSO, each mode corresponds to a dynamical regime or phase. However, given external forcings or longer-term internal variability and multiscale coevolution, the structural properties of the system may change. These changes in the dynamical structure bring about a new distribution and associated regimes. The modes of yesteryear may no longer exist as such in the new structural order of the system. In this context, aside from regime intermittence, the system exhibits structural regime change. New oscillations may emerge whilst others fade into the annals of history, e.g. particular climate fluctuations during the Little Ice Age. Traditional theories of stochastic processes and dynamical systems are grounded on the existence of so-called dynamical invariants; properties that remain unchanged as the dynamics unfold, assuming structural invariance and ergodicity of the underlying system. However, such theories are no longer optimal when trying to understand and model long-term historical records of coevolutionary systems. A new paradigm is thus needed. Therefore, we introduce a new class of dynamical systems that reinvent themselves as the dynamics unfold. Rather than only changing variables and parameters under a rigid framework, the governing laws are malleable themselves. The novel formulation captures and explains the coevolutionary dynamics of multiscale hydroclimatic systems, bringing along a physically sound understanding of their regimes, transitions and extremes over a long-term history.

Predicting response of fuel load to future changes in climate and atmospheric composition in the Southern United States.

Treesearch

Chi Zhang; Hanqin Tian; Yuhang Wang; Tao Zeng; Yongqiang Liu

2010-01-01

The model projected ecosystem carbon dynamics were incorporated into the default (contemporary) fuel load map developed by FCCS (Fuel Characteristic Classification System) to estimate the dynamics of fuel load in the Southern United States in response to projected changes in climate and atmosphere (CO2 and nitrogen deposition) from 2002 to 2050. The study results...

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.

a System Dynamics Approach for Looking at the Human and Environmental Interactions of Community-Based Irrigation Systems in New Mexico

NASA Astrophysics Data System (ADS)

Ochoa, C. G.; Tidwell, V. C.

2012-12-01

In the arid southwestern United States community water management systems have adapted to cope with climate variability and with socio-cultural and economic changes that have occurred since the establishment of these systems more than 300 years ago. In New Mexico, the community-based irrigation systems were established by Spanish settlers and have endured climate variability in the form of low levels of precipitation and have prevailed over important socio-political changes including the transfer of territory between Spain and Mexico, and between Mexico and the United States. Because of their inherent nature of integrating land and water use with society involvement these community-based systems have multiple and complex economic, ecological, and cultural interactions. Current urban population growth and more variable climate conditions are adding pressure to the survival of these systems. We are conducting a multi-disciplinary research project that focuses on characterizing these intrinsically complex human and natural interactions in three community-based irrigation systems in northern New Mexico. We are using a system dynamics approach to integrate different hydrological, ecological, socio-cultural and economic aspects of these three irrigation systems. Coupled with intensive field data collection, we are building a system dynamics model that will enable us to simulate important linkages and interactions between environmental and human elements occurring in each of these water management systems. We will test different climate variability and population growth scenarios and the expectation is that we will be able to identify critical tipping points of these systems. Results from this model can be used to inform policy recommendations relevant to the environment and to urban and agricultural land use planning in the arid southwestern United States.

Safety climate and culture: Integrating psychological and systems perspectives.

PubMed

Casey, Tristan; Griffin, Mark A; Flatau Harrison, Huw; Neal, Andrew

2017-07-01

Safety climate research has reached a mature stage of development, with a number of meta-analyses demonstrating the link between safety climate and safety outcomes. More recently, there has been interest from systems theorists in integrating the concept of safety culture and to a lesser extent, safety climate into systems-based models of organizational safety. Such models represent a theoretical and practical development of the safety climate concept by positioning climate as part of a dynamic work system in which perceptions of safety act to constrain and shape employee behavior. We propose safety climate and safety culture constitute part of the enabling capitals through which organizations build safety capability. We discuss how organizations can deploy different configurations of enabling capital to exert control over work systems and maintain safe and productive performance. We outline 4 key strategies through which organizations to reconcile the system control problems of promotion versus prevention, and stability versus flexibility. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Using Climate Regionalization to Understand Climate Forecast System Version 2 (CFSv2) Precipitation Performance for the Conterminous United States (CONUS)

NASA Technical Reports Server (NTRS)

Regonda, Satish K.; Zaitchik, Benjamin F.; Badr, Hamada S.; Rodell, Matthew

2016-01-01

Dynamically based seasonal forecasts are prone to systematic spatial biases due to imperfections in the underlying global climate model (GCM). This can result in low-forecast skill when the GCM misplaces teleconnections or fails to resolve geographic barriers, even if the prediction of large-scale dynamics is accurate. To characterize and address this issue, this study applies objective climate regionalization to identify discrepancies between the Climate Forecast SystemVersion 2 (CFSv2) and precipitation observations across the Contiguous United States (CONUS). Regionalization shows that CFSv2 1 month forecasts capture the general spatial character of warm season precipitation variability but that forecast regions systematically differ from observation in some transition zones. CFSv2 predictive skill for these misclassified areas is systematically reduced relative to correctly regionalized areas and CONUS as a whole. In these incorrectly regionalized areas, higher skill can be obtained by using a regional-scale forecast in place of the local grid cell prediction.

Project Zoom IN, Citizen Perspectives on Climate and Water Resources

NASA Astrophysics Data System (ADS)

Glaser, J. P.

2012-12-01

Perspective on climate and water resources can come from the top, scientists sharing invaluable data and findings about how climate dynamics function or quantifications of systems in flux. However, citizens are endowed with an equally as powerful tool for insight: ground zero experience. Project Zoom In is a nascent project undertaken by Global Media Forge to empower youth, educators and scientists with tools to reach the media with locale-specific imagery and perspective of climate dynamics and evidence of anecdotal resource management of liquid gold: fresh water. Zoom In is taking root in Colorado but is designed for national/international scaling. This effort has three limbs: (1) student, scientist and educator workshops teaching invaluable video production skills (2) engaging Colorado school systems to stimulate submission of clips to full video productions to our database, and (3) embedding the findings on a taxonomic GIS interface on-line. The website will be invaluable in classrooms and link network media to individuals with firsthand viewpoints on change.; Climate and Water Resources

Interactive Ice Sheet Flowline Model for High School and College Students

NASA Astrophysics Data System (ADS)

Stearns, L. A.; Rezvanbehbahani, S.; Shankar, S.

2017-12-01

Teaching about climate and climate change is conceptually challenging. While teaching tools and lesson plans are rapidly evolving to help teachers and students improve their understanding of climate processes, there are very few tools targeting ice sheet and glacier dynamics. We have built an interactive ice sheet model that allows students to explore how Antarctic glaciers respond to different climate perturbations. Interactive models offer advantages that are hard to obtain in traditional classroom settings; users can systematically investigate hypothetical situations, explore the effects of modifying systems, and repeatedly observe how systems interrelate. As a result, this project provides a much-needed bridge between the data and models used by the scientific community and students in high school and college. We target our instructional and assessment activities to three high school and college students with the overall aim of increasing understanding of ice sheet dynamics and the different ways that ice sheets are impacted by climate change, while also improving their fundamental math skills.

Emergent dynamics of the climate-economy system in the Anthropocene.

PubMed

Kellie-Smith, Owen; Cox, Peter M

2011-03-13

Global CO(2) emissions are understood to be the largest contributor to anthropogenic climate change, and have, to date, been highly correlated with economic output. However, there is likely to be a negative feedback between climate change and human wealth: economic growth is typically associated with an increase in CO(2) emissions and global warming, but the resulting climate change may lead to damages that suppress economic growth. This climate-economy feedback is assumed to be weak in standard climate change assessments. When the feedback is incorporated in a transparently simple model it reveals possible emergent behaviour in the coupled climate-economy system. Formulae are derived for the critical rates of growth of global CO(2) emissions that cause damped or long-term boom-bust oscillations in human wealth, thereby preventing a soft landing of the climate-economy system. On the basis of this model, historical rates of economic growth and decarbonization appear to put the climate-economy system in a potentially damaging oscillatory regime.

A Multi-Scale, Integrated Approach to Representing Watershed Systems

NASA Astrophysics Data System (ADS)

Ivanov, Valeriy; Kim, Jongho; Fatichi, Simone; Katopodes, Nikolaos

2014-05-01

Understanding and predicting process dynamics across a range of scales are fundamental challenges for basic hydrologic research and practical applications. This is particularly true when larger-spatial-scale processes, such as surface-subsurface flow and precipitation, need to be translated to fine space-time scale dynamics of processes, such as channel hydraulics and sediment transport, that are often of primary interest. Inferring characteristics of fine-scale processes from uncertain coarse-scale climate projection information poses additional challenges. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion, and sediment transport, tRIBS+VEGGIE-FEaST. The model targets to take the advantage of the current generation of wealth of data representing watershed topography, vegetation, soil, and landuse, as well as to explore the hydrological effects of physical factors and their feedback mechanisms over a range of scales. We illustrate how the modeling system connects precipitation-hydrologic runoff partition process to the dynamics of flow, erosion, and sedimentation, and how the soil's substrate condition can impact the latter processes, resulting in a non-unique response. We further illustrate an approach to using downscaled climate change information with a process-based model to infer the moments of hydrologic variables in future climate conditions and explore the impact of climate information uncertainty.

Effect of the alien invasive bivalve Corbicula fluminea on the nutrient dynamics under climate change scenarios

NASA Astrophysics Data System (ADS)

Coelho, J. P.; Lillebø, A. I.; Crespo, D.; Leston, S.; Dolbeth, M.

2018-05-01

The main aim of this study was to evaluate the impact of the alien invasive bivalve Corbicula fluminea (Müller, 1774) in the nutrient dynamics of temperate estuarine systems (oligohaline areas) under climate change scenarios. The scenarios simulated shifts in climatic conditions, following salinity (0 or 5) and temperature (24 or 30 °C) changes, usual during drought and heat wave events. The effect of the individual size/age (different size classes with fixed biomass) and density (various densities of <1 cm clams) on the bioturbation-associated nutrient dynamics were also evaluated under an 18-day laboratory experimental setup. Results highlight the significant effect of C. fluminea on the ecosystem nutrient dynamics, enhancing the efflux of both phosphate and dissolved inorganic nitrogen (DIN) from the sediments to the water column. Both drought and heat wave events will have an impact on the DIN dynamics within C. fluminea colonized systems, favouring a higher NH4-N efflux. The population structure of C. fluminea will have a decisive role on the impact of the species, with stronger nutrient effluxes associated with a predominantly juvenile population structure.

Climate Literacy: Progress in Climate and Global Change Undergraduate Courses in Meteorology and Earth System Science Programs at Jackson State University

NASA Astrophysics Data System (ADS)

Reddy, S. R.; Tuluri, F.; Fadavi, M.

2017-12-01

JSU Meteorology Program will be offering AMS Climate Studies undergraduate course under MET 210: Climatology in spring 2013. AMS Climate Studies is offered as a 3 credit hour laboratory course with 2 lectures and 1 lab sessions per week. Although this course places strong intellectual demands upon each student, the instructors' objective is to help each student to pass the course with an adequate understanding of the fundamentals and advanced and advanced courses. AMS Climate Studies is an introductory college-level course developed by the American Meteorological Society for implementation at undergraduate institutions nationwide. The course places students in a dynamic and highly motivational educational environment where they investigate Earth's climate system using real-world environmental data. The AMS Climate Studies course package consists of a textbook, investigations manual, course website, and course management system-compatible files. Instructors can use these resources in combinations that make for an exciting learning experience for their students. This is a content course in Earth Science. It introduces a new concept that views Earth as a synergistic physical system applied concepts of climatology, for him/her to understand basic atmospheric/climate processes, physical and dynamical climatology, regional climatology, past and future climates and statistical analysis using climate data and to be prepared to profit from studying more of interrelated phenomenon governed by complex processes involving the atmosphere, the hydrosphere, the biosphere, and the solid Earth. The course emphasizes that the events that shape the physical, chemical, and biological processes of the Earth do not occur in isolation. Rather, there is a delicate relationship between the events that occur in the ocean, atmosphere, and the solid Earth. The course provides a multidimensional approach in solving scientific issues related to Earth-related sciences,

Regional Approach for Linking Ecosystem Services and Livelihood Strategies Under Climate Change of Pastoral Communities in the Mongolian Steppe Ecosystem

NASA Astrophysics Data System (ADS)

Ojima, D. S.; Galvin, K.; Togtohyn, C.

2012-12-01

Dramatic changes due to climate and land use dynamics in the Mongolian Plateau affecting ecosystem services and agro-pastoral systems in Mongolia. Recently, market forces and development strategies are affecting land and water resources of the pastoral communities which are being further stressed due to climatic changes. Evaluation of pastoral systems, where humans depend on livestock and grassland ecosystem services, have demonstrated the vulnerability of the social-ecological system to climate change. Current social-ecological changes in ecosystem services are affecting land productivity and carrying capacity, land-atmosphere interactions, water resources, and livelihood strategies. The general trend involves greater intensification of resource exploitation at the expense of traditional patterns of extensive range utilization. Thus we expect climate-land use-land cover relationships to be crucially modified by the social-economic forces. The analysis incorporates information about the social-economic transitions taking place in the region which affect land-use, food security, and ecosystem dynamics. The region of study extends from the Mongolian plateau in Mongolia. Our research indicate that sustainability of pastoral systems in the region needs to integrate the impact of climate change on ecosystem services with socio-economic changes shaping the livelihood strategies of pastoral systems in the region. Adaptation strategies which incorporate integrated analysis of landscape management and livelihood strategies provides a framework which links ecosystem services to critical resource assets. Analysis of the available livelihood assets provides insights to the adaptive capacity of various agents in a region or in a community. Sustainable development pathways which enable the development of these adaptive capacity elements will lead to more effective adaptive management strategies for pastoral land use and herder's living standards. Pastoralists will have the opportunity to utilize seasonal resources and enhance their ability to process and manufacture products from the available ecosystem services in these dynamic social-ecological systems.

A Simple Exploration of Complexity at the Climate-Weather-Social-Conflict Nexus

NASA Astrophysics Data System (ADS)

Shaw, M.

2017-12-01

The conceptualization, exploration, and prediction of interplay between climate, weather, important resources, and social and economic - so political - human behavior is cast, and analyzed, in terms familiar from statistical physics and nonlinear dynamics. A simple threshold toy model is presented which emulates human tendencies to either actively engage in responses deriving, in part, from environmental circumstances or to maintain some semblance of status quo, formulated based on efforts drawn from the sociophysics literature - more specifically vis a vis a model akin to spin glass depictions of human behavior - with threshold/switching of individual and collective dynamics influenced by relatively more detailed weather and land surface model (hydrological) analyses via a land data assimilation system (a custom rendition of the NASA GSFC Land Information System). Parameters relevant to human systems' - e.g., individual and collective switching - sensitivity to hydroclimatology are explored towards investigation of overall system behavior; i.e., fixed points/equilibria, oscillations, and bifurcations of systems composed of human interactions and responses to climate and weather through, e.g., agriculture. We discuss implications in terms of conceivable impacts of climate change and associated natural disasters on socioeconomics, politics, and power transfer, drawing from relatively recent literature concerning human conflict.

Probabilistic empirical prediction of seasonal climate: evaluation and potential applications

NASA Astrophysics Data System (ADS)

Dieppois, B.; Eden, J.; van Oldenborgh, G. J.

2017-12-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a new evaluation of an established empirical system used to predict seasonal climate across the globe. Forecasts for surface air temperature, precipitation and sea level pressure are produced by the KNMI Probabilistic Empirical Prediction (K-PREP) system every month and disseminated via the KNMI Climate Explorer (climexp.knmi.nl). K-PREP is based on multiple linear regression and built on physical principles to the fullest extent with predictive information taken from the global CO2-equivalent concentration, large-scale modes of variability in the climate system and regional-scale information. K-PREP seasonal forecasts for the period 1981-2016 will be compared with corresponding dynamically generated forecasts produced by operational forecast systems. While there are many regions of the world where empirical forecast skill is extremely limited, several areas are identified where K-PREP offers comparable skill to dynamical systems. We discuss two key points in the future development and application of the K-PREP system: (a) the potential for K-PREP to provide a more useful basis for reference forecasts than those based on persistence or climatology, and (b) the added value of including K-PREP forecast information in multi-model forecast products, at least for known regions of good skill. We also discuss the potential development of stakeholder-driven applications of the K-PREP system, including empirical forecasts for circumboreal fire activity.

Sun's influence on climate: Explored with SDO

NASA Astrophysics Data System (ADS)

Lundstedt, H.

2010-09-01

Stunning images and movies recorded of the Sun, with Solar Dynamics Observatory (SDO), makes one wonder: How would this change our view on the Sun-Earth climate coupling? SDO shows a much more variable Sun, on all spatial and temporal scales. Detailed pictures of solar storms are foreseen to improve our understanding of the direct Sun-Earth coupling. Dynamo models, described by dynamical systems using input from helioseismic observations, are foreseen to improve our knowledge of the the Sun's cyclic influence on climate. Both the direct-, and the cycle-influence will be discussed in view of the new SDO observations.

National Centers for Environmental Prediction

Science.gov Websites

: Influence of convective parameterization on the systematic errors of Climate Forecast System (CFS) model ; Climate Dynamics, 41, 45-61, 2013. Saha, S., S. Pokhrel and H. S. Chaudhari : Influence of Eurasian snow Organization Search Enter text Search Navigation Bar End Cap Search EMC Go Branches Global Climate and Weather

Assessing climate change impacts, benefits of mitigation, and uncertainties on major global forest regions under multiple socioeconomic and emissions scenarios

Treesearch

John B Kim; Erwan Monier; Brent Sohngen; G Stephen Pitts; Ray Drapek; James McFarland; Sara Ohrel; Jefferson Cole

2016-01-01

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a...

The aerosol-monsoon climate system of Asia: A new paradigm

NASA Astrophysics Data System (ADS)

Lau, William K. M.

2016-02-01

This commentary is based on a series of recent lectures on aerosol-monsoon interactions I gave at the Beijing Normal University in August 2015. A main theme of the lectures is on a new paradigm of "An Aerosol-Monsoon-Climate-System", which posits that aerosol, like rainfall, cloud, and wind, is an integral component of the monsoon climate system, influencing monsoon weather and climate on all timescales. Here, salient issues discussed in my lectures and my personal perspective regarding interactions between atmospheric dynamics and aerosols from both natural and anthropogenic sources are summarized. My hope is that under this new paradigm, we can break down traditional disciplinary barriers, advance a deeper understanding of weather and climate in monsoon regions, as well as entrain a new generation of geoscientists to strive for a sustainable future for one of the most complex and challenging human-natural climate sub-system of the earth.

Engineering a Sustainable Blue Planet: Exploring the dynamics

NASA Astrophysics Data System (ADS)

Lall, U.

2004-12-01

Man's hand as a geomorphic agent is now endemic. The dynamics of water and other material cycles is now significantly impacted at all scales: from hillsides to watersheds to the earth, and from urban flash flood events to mean long term flow. Locally and regionally, climatic exigencies serve to spur either ruin (in the poorest societies) or a flurry of human infrastructure development. Thus, at the local scale, geomorphology depends on man's struggle for survival, and the associated interaction with nature's vagaries. Of course, we now recognize that man induced changes in land surface attributes (related to agriculture or deforestation) and in atmospheric composition translate into relatively unforeseeable climate changes, i.e., nature at a planetary scale has a different face. Despite the recognition of these interacting factors, a conceptual model that treats the dynamics of man and nature as separable and separate, dominates the earth sciences. We study global climate change and its impacts as sequential outcomes of a carbon emission scenario, and not as endogenous processes of the earth-man system with mutual feedbacks. The definition of a man-nature dynamical system is feasible as an abstraction. I explore such a definition through examples, one at the global scale, and one at a local scale. These examples are formulated in the context of meeting the challenge of poverty reduction through the provision of water for health and food, while considering vulnerability to a dynamic climate and to changes in the environment.

Using Web GIS "Climate" for Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Gordova, Yulia; Martynova, Yulia; Shulgina, Tamara

2015-04-01

A work is devoted to the application of an information-computational Web GIS "Climate" developed by joint team of the Institute of Monitoring of Climatic and Ecological Systems SB RAS and Tomsk State University to raise awareness about current and future climate change as a basis for further adaptation. Web-GIS "Climate» (http://climate.scert.ru/) based on modern concepts of Web 2.0 provides opportunities to study regional climate change and its consequences by providing access to climate and weather models, a large set of geophysical data and means of processing and visualization. Also, the system is used for the joint development of software applications by distributed research teams, research based on these applications and undergraduate and graduate students training. In addition, the system capabilities allow creating information resources to raise public awareness about climate change, its causes and consequences, which is a necessary step for the subsequent adaptation to these changes. Basic information course on climate change is placed in the public domain and is aimed at local population. Basic concepts and problems of modern climate change and its possible consequences are set out and illustrated in accessible language. Particular attention is paid to regional climate changes. In addition to the information part, the course also includes a selection of links to popular science network resources on current issues in Earth Sciences and a number of practical tasks to consolidate the material. These tasks are performed for a particular territory. Within the tasks users need to analyze the prepared within the "Climate" map layers and answer questions of direct interest to the public: "How did the minimum value of winter temperatures change in your area?", "What are the dynamics of maximum summer temperatures?", etc. Carrying out the analysis of the dynamics of climate change contributes to a better understanding of climate processes and further adaptation. Passing this course raises awareness of the general public, as well as prepares the user for subsequent registration in the system and work with its tools in conducting independent research. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grants 13-05-12034 and 14-05-00502.

Avoiding the Water-Climate-Poverty Trap: Adaptive Risk Management for Bangladesh's Coastal Embankments

NASA Astrophysics Data System (ADS)

Hall, J. W.

2015-12-01

Our recent research on water security (Sadoff et al., 2015, Dadson et al., 2015) has revealed the dynamic relationship between water security and human well-being. A version of this dynamic is materialising in the coastal polder areas of Khulna, Bangladesh. Repeated coastal floods increase salinity, wipe out agricultural yields for several years and increase out-migration. As a tool to help inform and target future cycles of investment in improvements to the coastal embankments, in this paper we propose a dynamical model of biophysical processes and human well-being, which downscales our previous research to the Khulna region. State variables in the model include agricultural production, population, life expectancy and child mortality. Possible infrastructure interventions include embankment improvements, groundwater wells and drainage infrastructure. Hazard factors include flooding, salinization and drinking water pollution. Our system model can be used to inform adaptation decision making by testing the dynamical response of the system to a range of possible policy interventions, under uncertain future conditions. The analysis is intended to target investment and enable adaptive resource reallocation based on learning about the system response to interventions over the seven years of our research programme. The methodology and paper will demonstrate the complex interplay of factors that determine system vulnerability to climate change. The role of climate change uncertainties (in terms of mean sea level rise and storm surge frequency) will be evaluated alongside multiple other uncertain factors that determine system response. Adaptive management in a 'learning system' will be promoted as a mechanism for coping with climate uncertainties. References:Dadson, S., Hall, J.W., Garrick, D., Sadoff, C. and Grey, D. Water security, risk and economic growth: lessons from a dynamical systems model, Global Environmental Change, in review.Sadoff, C.W., Hall, J.W., Grey, D., Aerts, J.C.J.H., Ait-Kadi, M., Brown, C., Cox, A., Dadson, S., Garrick, D., Kelman, J., McCornick, P., Ringler, C., Rosegrant, M., Whittington, D. and Wiberg, D. Securing Water, Sustaining Growth: Report of the GWP/OECD Task Force on Water Security and Sustainable Growth, University of Oxford, April 2015, 180pp.

GFDL's unified regional-global weather-climate modeling system with variable resolution capability for severe weather predictions and regional climate simulations

NASA Astrophysics Data System (ADS)

Lin, S. J.

2015-12-01

The NOAA/Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions (e.g., tornado outbreak events and cat-5 hurricanes) and ultra-high-resolution (1-km) regional climate simulations within a consistent global modeling framework. The fundation of this flexible regional-global modeling system is the non-hydrostatic extension of the vertically Lagrangian dynamical core (Lin 2004, Monthly Weather Review) known in the community as FV3 (finite-volume on the cubed-sphere). Because of its flexability and computational efficiency, the FV3 is one of the final candidates of NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched (single) grid capability, a two-way (regional-global) multiple nested grid capability, and the combination of the stretched and two-way nests, so as to make convection-resolving regional climate simulation within a consistent global modeling system feasible using today's High Performance Computing System. One of our main scientific goals is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornadoes using a global model that was originally designed for century long climate simulations. As a unified weather-climate modeling system, we evaluated the performance of the model with horizontal resolution ranging from 1 km to as low as 200 km. In particular, for downscaling studies, we have developed various tests to ensure that the large-scale circulation within the global varaible resolution system is well simulated while at the same time the small-scale can be accurately captured within the targeted high resolution region.

Disentangling the effects of feedback structure and climate on Poaceae annual airborne pollen fluctuations and the possible consequences of climate change.

PubMed

García de León, David; García-Mozo, Herminia; Galán, Carmen; Alcázar, Purificación; Lima, Mauricio; González-Andújar, José L

2015-10-15

Pollen allergies are the most common form of respiratory allergic disease in Europe. Most studies have emphasized the role of environmental processes, as the drivers of airborne pollen fluctuations, implicitly considering pollen production as a random walk. This work shows that internal self-regulating processes of the plants (negative feedback) should be included in pollen dynamic systems in order to give a better explanation of the observed pollen temporal patterns. This article proposes a novel methodological approach based on dynamic systems to investigate the interaction between feedback structure of plant populations and climate in shaping long-term airborne Poaceae pollen fluctuations and to quantify the effects of climate change on future airborne pollen concentrations. Long-term historical airborne Poaceae pollen data (30 years) from Cordoba city (Southern Spain) were analyzed. A set of models, combining feedback structure, temperature and actual evapotranspiration effects on airborne Poaceae pollen were built and compared, using a model selection approach. Our results highlight the importance of first-order negative feedback and mean annual maximum temperature in driving airborne Poaceae pollen dynamics. The best model was used to predict the effects of climate change under two standardized scenarios representing contrasting temporal patterns of economic development and CO2 emissions. Our results predict an increase in pollen levels in southern Spain by 2070 ranging from 28.5% to 44.3%. The findings from this study provide a greater understanding of airborne pollen dynamics and how climate change might impact the future evolution of airborne Poaceae pollen concentrations and thus the future evolution of related pollen allergies. Copyright © 2015 Elsevier B.V. All rights reserved.

Implementation of Malaria Dynamic Models in Municipality Level Early Warning Systems in Colombia. Part I: Description of Study Sites

PubMed Central

Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M.; Quiñónes, Martha L.; Jiménez, Mónica M.; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J.; Thomson, Madeleine C.

2014-01-01

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. PMID:24891460

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H.; Moore, Kara A.; Zimmermann, Niklaus E.

2016-01-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasise several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. PMID:26872305

Benchmarking novel approaches for modelling species range dynamics.

PubMed

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. © 2016 John Wiley & Sons Ltd.

Modeling of larch forest dynamics under a changing climate in eastern Siberia

NASA Astrophysics Data System (ADS)

Nakai, T.; Kumagai, T.; Iijima, Y.; Ohta, T.; Kotani, A.; Maximov, T. C.; Hiyama, T.

2017-12-01

According to the projection by an earth system model under RCP8.5 scenario, boreal forest in eastern Siberia (near Yakutsk) is predicted to experience significant changes in climate, in which the mean annual air temperature is projected to be positive and the annual precipitation will be doubled by the end of 21st century. Since the forest in this region is underlain by continuous permafrost, both increasing temperature and precipitation can affect the dynamics of forest through the soil water processes. To investigate such effects, we adopted a newly developed terrestrial ecosystem dynamics model named S-TEDy (SEIB-DGVM-originated Terrestrial Ecosystem Dynamics model), which mechanistically simulates "the way of life" of each individual tree and resulting tree mortality under the future climate conditions. This model was first developed for the simulation of the dynamics of a tropical rainforest in the Borneo Island, and successfully reproduced higher mortality of large trees due to a prolonged drought induced by ENSO event of 1997-1998. To apply this model to a larch forest in eastern Siberia, we are developing a soil submodel to consider the effect of thawing-freezing processes. We will present a simulation results using the future climate projection.

Dynamics of exoplanetary systems, links to their habitability

NASA Astrophysics Data System (ADS)

Bolmont, E.; Raymond, S. N.; Selsis, F.

2014-12-01

Our knowledge of planets' orbital dynamics, which was based on Solar System studies, has been challenged by the diversity of exoplanetary systems. Around cool and ultra cool dwarfs, the influence of tides on the orbital and spin evolution of planets can strongly affect their climate and their capacity to host surface liquid water. We illustrate the role of tides and dynamics with the extreme case of planets orbiting around brown dwarfs. In multiple planet systems, the eccentricity is excited by planet-planet interactions. Planets are therefore heated up from the inside by the tidally-induced friction. This process can heat a habitable zone planet to such a level that surface liquid water cannot exist. We also talk about the newly discovered potentially habitable Earth-sized planet Kepler-186f. Given the poorly estimated age of the system, the planet could still be evolving towards synchronization and have a high obliquity or be pseudo-synchronized with a zero obliquity. These two configurations would have a different effect on the climate of this planet.

Post-1980 shifts in the sensitivity of boreal tree growth to North Atlantic Ocean dynamics and seasonal climate. Tree growth responses to North Atlantic Ocean dynamics

NASA Astrophysics Data System (ADS)

Ols, Clémentine; Trouet, Valerie; Girardin, Martin P.; Hofgaard, Annika; Bergeron, Yves; Drobyshev, Igor

2018-06-01

The mid-20th century changes in North Atlantic Ocean dynamics, e.g. slow-down of the Atlantic meridional overturning thermohaline circulation (AMOC), have been considered as early signs of tipping points in the Earth climate system. We hypothesized that these changes have significantly altered boreal forest growth dynamics in northeastern North America (NA) and northern Europe (NE), two areas geographically adjacent to the North Atlantic Ocean. To test our hypothesis, we investigated tree growth responses to seasonal large-scale oceanic and atmospheric indices (the AMOC, North Atlantic Oscillation (NAO), and Arctic Oscillation (AO)) and climate (temperature and precipitation) from 1950 onwards, both at the regional and local levels. We developed a network of 6876 black spruce (NA) and 14437 Norway spruce (NE) tree-ring width series, extracted from forest inventory databases. Analyses revealed post-1980 shifts from insignificant to significant tree growth responses to summer oceanic and atmospheric dynamics both in NA (negative responses to NAO and AO indices) and NE (positive response to NAO and AMOC indices). The strength and sign of these responses varied, however, through space with stronger responses in western and central boreal Quebec and in central and northern boreal Sweden, and across scales with stronger responses at the regional level than at the local level. Emerging post-1980 associations with North Atlantic Ocean dynamics synchronized with stronger tree growth responses to local seasonal climate, particularly to winter temperatures. Our results suggest that ongoing and future anomalies in oceanic and atmospheric dynamics may impact forest growth and carbon sequestration to a greater extent than previously thought. Cross-scale differences in responses to North Atlantic Ocean dynamics highlight complex interplays in the effects of local climate and ocean-atmosphere dynamics on tree growth processes and advocate for the use of different spatial scales in climate-growth research to better understand factors controlling tree growth.

Land Cover Applications, Landscape Dynamics, and Global Change

USGS Publications Warehouse

Tieszen, Larry L.

2007-01-01

The Land Cover Applications, Landscape Dynamics, and Global Change project at U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) seeks to integrate remote sensing and simulation models to better understand and seek solutions to national and global issues. Modeling processes related to population impacts, natural resource management, climate change, invasive species, land use changes, energy development, and climate mitigation all pose significant scientific opportunities. The project activities use remotely sensed data to support spatial monitoring, provide sensitivity analyses across landscapes and large regions, and make the data and results available on the Internet with data access and distribution, decision support systems, and on-line modeling. Applications support sustainable natural resource use, carbon cycle science, biodiversity conservation, climate change mitigation, and robust simulation modeling approaches that evaluate ecosystem and landscape dynamics.

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed Central

Palmer, T. N.

2014-01-01

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic–dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only. PMID:24842038

More reliable forecasts with less precise computations: a fast-track route to cloud-resolved weather and climate simulators?

PubMed

Palmer, T N

2014-06-28

This paper sets out a new methodological approach to solving the equations for simulating and predicting weather and climate. In this approach, the conventionally hard boundary between the dynamical core and the sub-grid parametrizations is blurred. This approach is motivated by the relatively shallow power-law spectrum for atmospheric energy on scales of hundreds of kilometres and less. It is first argued that, because of this, the closure schemes for weather and climate simulators should be based on stochastic-dynamic systems rather than deterministic formulae. Second, as high-wavenumber elements of the dynamical core will necessarily inherit this stochasticity during time integration, it is argued that the dynamical core will be significantly over-engineered if all computations, regardless of scale, are performed completely deterministically and if all variables are represented with maximum numerical precision (in practice using double-precision floating-point numbers). As the era of exascale computing is approached, an energy- and computationally efficient approach to cloud-resolved weather and climate simulation is described where determinism and numerical precision are focused on the largest scales only.

A sensitive slope: estimating landscape patterns of forest resilience in a changing climate

Treesearch

Jill F. Johnstone; Eliot J.B. McIntire; Eric J. Pedersen; Gregory King; Michael J.F. Pisaric

2010-01-01

Changes in Earth's environment are expected to stimulate changes in the composition and structure of ecosystems, but it is still unclear how the dynamics of these responses will play out over time. In long-lived forest systems, communities of established individuals may be resistant to respond to directional climate change, but may be highly sensitive to climate...

Arctic systems in the Quaternary: ecological collision, faunal mosaics and the consequences of a wobbling climate.

PubMed

Hoberg, E P; Cook, J A; Agosta, S J; Boeger, W; Galbreath, K E; Laaksonen, S; Kutz, S J; Brooks, D R

2017-07-01

Climate oscillations and episodic processes interact with evolution, ecology and biogeography to determine the structure and complex mosaic that is the biosphere. Parasites and parasite-host assemblages are key components in a general explanatory paradigm for global biodiversity. We explore faunal assembly in the context of Quaternary time frames of the past 2.6 million years, a period dominated by episodic shifts in climate. Climate drivers cross a continuum from geological to contemporary timescales and serve to determine the structure and distribution of complex biotas. Cycles within cycles are apparent, with drivers that are layered, multifactorial and complex. These cycles influence the dynamics and duration of shifts in environmental structure on varying temporal and spatial scales. An understanding of the dynamics of high-latitude systems, the history of the Beringian nexus (the intermittent land connection linking Eurasia and North America) and downstream patterns of diversity depend on teasing apart the complexity of biotic assembly and persistence. Although climate oscillations have dominated the Quaternary, contemporary dynamics are driven by tipping points and shifting balances emerging from anthropogenic forces that are disrupting ecological structure. Climate change driven by anthropogenic forcing has supplanted a history of episodic variation and is eliminating ecological barriers and constraints on development and distribution for pathogen transmission. A framework to explore interactions of episodic processes on faunal structure and assembly is the Stockholm Paradigm, which appropriately shifts the focus from cospeciation to complexity and contingency in explanations of diversity.

Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)

DOE PAGES

Sakaguchi, K.; Zeng, X.; Leung, L. R.; ...

2016-12-21

Land carbon sensitivity to atmospheric CO 2 concentration (β L) and climate warming (γ L) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in the late twentieth century, β L is not substantially different between the two models but γ L of CNDV is stronger (more negative) than that of CN. The main reason for themore » difference in γL is not the concurrent change in vegetation cover driving the carbon dynamics, but rather the smaller nitrogen constraint on plant growth in CNDV compared with CN, which arises from the deviation of CNDV's near-equilibrium vegetation distribution from CN’s prescribed, historical land cover. The smaller nitrogen constraint makes the enhanced nitrogen mineralization with warming less effective in stimulating plant productivity to counter moisture stress in a warmer climate, leading to a more negative γ L. This represents a new indirect pathway that has not been identified for dynamic vegetation in the coupled carbon-nitrogen cycle to affect the terrestrial carbon-climate feedbacks in the earth system.« less

Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)

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

Sakaguchi, K.; Zeng, X.; Leung, L. R.

Land carbon sensitivity to atmospheric CO 2 concentration (β L) and climate warming (γ L) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in the late twentieth century, β L is not substantially different between the two models but γ L of CNDV is stronger (more negative) than that of CN. The main reason for themore » difference in γL is not the concurrent change in vegetation cover driving the carbon dynamics, but rather the smaller nitrogen constraint on plant growth in CNDV compared with CN, which arises from the deviation of CNDV's near-equilibrium vegetation distribution from CN’s prescribed, historical land cover. The smaller nitrogen constraint makes the enhanced nitrogen mineralization with warming less effective in stimulating plant productivity to counter moisture stress in a warmer climate, leading to a more negative γ L. This represents a new indirect pathway that has not been identified for dynamic vegetation in the coupled carbon-nitrogen cycle to affect the terrestrial carbon-climate feedbacks in the earth system.« less

Mesoscale weather and climate modeling with the global non-hydrostatic Goddard Earth Observing System Model (GEOS-5) at cloud-permitting resolutions

NASA Astrophysics Data System (ADS)

Putman, W. M.; Suarez, M.

2009-12-01

The Goddard Earth Observing System Model (GEOS-5), an earth system model developed in the NASA Global Modeling and Assimilation Office (GMAO), has integrated the non-hydrostatic finite-volume dynamical core on the cubed-sphere grid. The extension to a non-hydrostatic dynamical framework and the quasi-uniform cubed-sphere geometry permits the efficient exploration of global weather and climate modeling at cloud permitting resolutions of 10- to 4-km on today's high performance computing platforms. We have explored a series of incremental increases in global resolution with GEOS-5 from it's standard 72-level 27-km resolution (~5.5 million cells covering the globe from the surface to 0.1 hPa) down to 3.5-km (~3.6 billion cells). We will present results from a series of forecast experiments exploring the impact of the non-hydrostatic dynamics at transition resolutions of 14- to 7-km, and the influence of increased horizontal/vertical resolution on convection and physical parameterizations within GEOS-5. Regional and mesoscale features of 5- to 10-day weather forecasts will be presented and compared with satellite observations. Our results will highlight the impact of resolution on the structure of cloud features including tropical convection and tropical cyclone predicability, cloud streets, von Karman vortices, and the marine stratocumulus cloud layer. We will also present experiment design and early results from climate impact experiments for global non-hydrostatic models using GEOS-5. Our climate experiments will focus on support for the Year of Tropical Convection (YOTC). We will also discuss a seasonal climate time-slice experiment design for downscaling coarse resolution century scale climate simulations to global non-hydrostatic resolutions of 14- to 7-km with GEOS-5.

Dynamic Risk Quantification and Management: Core needs and strategies for adapting water resources systems to a changing environment (Invited)

NASA Astrophysics Data System (ADS)

Lall, U.

2009-12-01

The concern with anthropogenic climate change has spurred significant interest in strategies for climate change adaptation in water resource systems planning and management. The thesis of this talk is that this is a subset of strategies that need to sustainably design and operate structural and non-structural systems for managing resources in a changing environment. Even with respect to a changing climate, the largest opportunity for immediate adaptation to a changing climate may be provided by an improved understanding and prediction capability for seasonal to interannual and decadal climate variability. I shall lay out some ideas as to how this can be done and provide an example for reservoir water allocation and management, and one for flood risk management.

Quantifying climate feedbacks in polar regions.

PubMed

Goosse, Hugues; Kay, Jennifer E; Armour, Kyle C; Bodas-Salcedo, Alejandro; Chepfer, Helene; Docquier, David; Jonko, Alexandra; Kushner, Paul J; Lecomte, Olivier; Massonnet, François; Park, Hyo-Seok; Pithan, Felix; Svensson, Gunilla; Vancoppenolle, Martin

2018-05-15

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range of feedbacks, offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.

Climate models with delay differential equations

NASA Astrophysics Data System (ADS)

Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M.

2017-11-01

A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

Climate models with delay differential equations.

PubMed

Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M

2017-11-01

A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.

Climate variability and predictability associated with the Indo-Pacific Oceanic Channel Dynamics in the CCSM4 Coupled System Model

NASA Astrophysics Data System (ADS)

Yuan, Dongliang; Xu, Peng; Xu, Tengfei

2017-01-01

An experiment using the Community Climate System Model (CCSM4), a participant of the Coupled Model Intercomparison Project phase-5 (CMIP5), is analyzed to assess the skills of this model in simulating and predicting the climate variabilities associated with the oceanic channel dynamics across the Indo-Pacific Oceans. The results of these analyses suggest that the model is able to reproduce the observed lag correlation between the oceanic anomalies in the southeastern tropical Indian Ocean and those in the cold tongue in the eastern equatorial Pacific Ocean at a time lag of 1 year. This success may be largely attributed to the successful simulation of the interannual variations of the Indonesian Throughflow, which carries the anomalies of the Indian Ocean Dipole (IOD) into the western equatorial Pacific Ocean to produce subsurface temperature anomalies, which in turn propagate to the eastern equatorial Pacific to generate ENSO. This connection is termed the "oceanic channel dynamics" and is shown to be consistent with the observational analyses. However, the model simulates a weaker connection between the IOD and the interannual variability of the Indonesian Throughflow transport than found in the observations. In addition, the model overestimates the westerly wind anomalies in the western-central equatorial Pacific in the year following the IOD, which forces unrealistic upwelling Rossby waves in the western equatorial Pacific and downwelling Kelvin waves in the east. This assessment suggests that the CCSM4 coupled climate system has underestimated the oceanic channel dynamics and overestimated the atmospheric bridge processes.

Foreword: The dynamics of change in Alaska’s boreal forests: Resilience and vulnerability in response to climate warming

USGS Publications Warehouse

McGuire, A. David; Chapin, F. Stuart; Ruess, Roger W.

2016-01-01

Long-term research by the Bonanza Creek (BNZ) Long Term Ecological Research (LTER) program has documented natural patterns of interannual and successional variability of the boreal forest in interior Alaska against which we can detect changes in system behavior. Between 2004 and 2010 the BNZ LTER program focused on understanding the dynamics of change through studying the resilience and vulnerability of Alaska's boreal forest in response to climate warming. The overarching question in this endeavor has been “How are boreal ecosystems responding, both gradually and abruptly, to climate warming, and what new landscape patterns are emerging?”

Constraining Centennial-Scale Ecosystem-Climate Interactions with a Pre-colonial Forest Reconstruction across the Upper Midwest and Northeastern United States

NASA Astrophysics Data System (ADS)

Matthes, J. H.; Dietze, M.; Fox, A. M.; Goring, S. J.; McLachlan, J. S.; Moore, D. J.; Poulter, B.; Quaife, T. L.; Schaefer, K. M.; Steinkamp, J.; Williams, J. W.

2014-12-01

Interactions between ecological systems and the atmosphere are the result of dynamic processes with system memories that persist from seconds to centuries. Adequately capturing long-term biosphere-atmosphere exchange within earth system models (ESMs) requires an accurate representation of changes in plant functional types (PFTs) through time and space, particularly at timescales associated with ecological succession. However, most model parameterization and development has occurred using datasets than span less than a decade. We tested the ability of ESMs to capture the ecological dynamics observed in paleoecological and historical data spanning the last millennium. Focusing on an area from the Upper Midwest to New England, we examined differences in the magnitude and spatial pattern of PFT distributions and ecotones between historic datasets and the CMIP5 inter-comparison project's large-scale ESMs. We then conducted a 1000-year model inter-comparison using six state-of-the-art biosphere models at sites that bridged regional temperature and precipitation gradients. The distribution of ecosystem characteristics in modeled climate space reveals widely disparate relationships between modeled climate and vegetation that led to large differences in long-term biosphere-atmosphere fluxes for this region. Model simulations revealed that both the interaction between climate and vegetation and the representation of ecosystem dynamics within models were important controls on biosphere-atmosphere exchange.

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

PubMed

Post, Eric; Forchhammer, Mads C

2004-06-22

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

Compositing climate change vulnerability of a Mediterranean region using spatiotemporally dynamic proxies for ecological and socioeconomic impacts and stabilities.

PubMed

Demirkesen, Ali Can; Evrendilek, Fatih

2017-01-01

The study presents a new methodology to quantify spatiotemporal dynamics of climate change vulnerability at a regional scale adopting a new conceptual model of vulnerability as a function of climate change impacts, ecological stability, and socioeconomic stability. Spatiotemporal trends of equally weighted proxy variables for the three vulnerability components were generated to develop a composite climate change vulnerability index (CCVI) for a Mediterranean region of Turkey combining Landsat time series data, digital elevation model (DEM)-derived data, ordinary kriging, and geographical information system. Climate change impact was based on spatiotemporal trends of August land surface temperature (LST) between 1987 and 2016. Ecological stability was based on DEM, slope, aspect, and spatiotemporal trends of normalized difference vegetation index (NDVI), while socioeconomic stability was quantified as a function of spatiotemporal trends of land cover, population density, per capita gross domestic product, and illiteracy. The zones ranked on the five classes of no-to-extreme vulnerability were identified where highly and moderately vulnerable lands covered 0.02% (12 km 2 ) and 11.8% (6374 km 2 ) of the study region, respectively, mostly occurring in the interior central part. The adoption of this composite CCVI approach is expected to lead to spatiotemporally dynamic policy recommendations towards sustainability and tailor preventive and mitigative measures to locally specific characteristics of coupled ecological-socioeconomic systems.

Fast Response of the Tropics to an Abrupt Loss of Arctic Sea Ice via Ocean Dynamics

NASA Astrophysics Data System (ADS)

Wang, Kun; Deser, Clara; Sun, Lantao; Tomas, Robert A.

2018-05-01

The role of ocean dynamics in the transient adjustment of the coupled climate system to an abrupt loss of Arctic sea ice is investigated using experiments with Community Climate System Model version 4 in two configurations: a thermodynamic slab mixed layer ocean and a full-depth ocean that includes both dynamics and thermodynamics. Ocean dynamics produce a distinct sea surface temperature warming maximum in the eastern equatorial Pacific, accompanied by an equatorward intensification of the Intertropical Convergence Zone and Hadley Circulation. These tropical responses are established within 25 years of ice loss and contrast markedly with the quasi-steady antisymmetric coupled response in the slab-ocean configuration. A heat budget analysis reveals the importance of anomalous vertical advection tied to a monotonic temperature increase below 200 m for the equatorial sea surface temperature warming maximum in the fully coupled model. Ocean dynamics also rapidly modify the midlatitude atmospheric response to sea ice loss.

Arctic climate response to geoengineering with stratospheric sulfate aerosols

NASA Astrophysics Data System (ADS)

McCusker, K. E.; Battisti, D. S.; Bitz, C. M.

2010-12-01

Recent warming and record summer sea-ice area minimums have spurred expressions of concern for arctic ecosystems, permafrost, and polar bear populations, among other things. Geoengineering by stratospheric sulfate aerosol injections to deliberately cancel the anthropogenic temperature rise has been put forth as a possible solution to restoring Arctic (and global) climate to modern conditions. However, climate is particularly sensitive in the northern high latitudes, responding easily to radiative forcing changes. To that end, we explore the extent to which tropical injections of stratospheric sulfate aerosol can accomplish regional cancellation in the Arctic. We use the Community Climate System Model version 3 global climate model to execute simulations with combinations of doubled CO2 and imposed stratospheric sulfate burdens to investigate the effects on high latitude climate. We further explore the sensitivity of the polar climate to ocean dynamics by running a suite of simulations with and without ocean dynamics, transiently and to equilibrium respectively. We find that, although annual, global mean temperature cancellation is accomplished, there is over-cooling on land in Arctic summer, but residual warming in Arctic winter, which is largely due to atmospheric circulation changes. Furthermore, the spatial extent of these features and their concurrent impacts on sea-ice properties are modified by the inclusion of ocean dynamical feedbacks.

Vulnerability to forest loss through altered postfire recovery dynamics in a warming climate in the Klamath Mountains.

PubMed

Tepley, Alan J; Thompson, Jonathan R; Epstein, Howard E; Anderson-Teixeira, Kristina J

2017-10-01

In the context of ongoing climatic warming, certain landscapes could be near a tipping point where relatively small changes to their fire regimes or their postfire forest recovery dynamics could bring about extensive forest loss, with associated effects on biodiversity and carbon-cycle feedbacks to climate change. Such concerns are particularly valid in the Klamath Region of northern California and southwestern Oregon, where severe fire initially converts montane conifer forests to systems dominated by broadleaf trees and shrubs. Conifers eventually overtop the competing vegetation, but until they do, these systems could be perpetuated by a cycle of reburning. To assess the vulnerability of conifer forests to increased fire activity and altered forest recovery dynamics in a warmer, drier climate, we characterized vegetation dynamics following severe fire in nine fire years over the last three decades across the climatic aridity gradient of montane conifer forests. Postfire conifer recruitment was limited to a narrow window, with 89% of recruitment in the first 4 years, and height growth tended to decrease as the lag between the fire year and the recruitment year increased. Growth reductions at longer lags were more pronounced at drier sites, where conifers comprised a smaller portion of live woody biomass. An interaction between seed-source availability and climatic aridity drove substantial variation in the density of regenerating conifers. With increasing climatic water deficit, higher propagule pressure (i.e., smaller patch sizes for high-severity fire) was needed to support a given conifer seedling density, which implies that projected future increases in aridity could limit postfire regeneration across a growing portion of the landscape. Under a more severe prospective warming scenario, by the end of the century more than half of the area currently capable of supporting montane conifer forest could become subject to minimal conifer regeneration in even moderate-sized (10s of ha) high-severity patches. © 2017 John Wiley & Sons Ltd.

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, E.; Sokolov, A. P.; Schlosser, C. A.; Scott, J. R.; Gao, X.

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an earth system model of intermediate complexity, with a two-dimensional zonal-mean atmosphere, to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three dimensional atmospheric model; and a statistical downscaling, where a pattern scaling algorithm uses climate-change patterns from 17 climate models. This framework allows for key sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections; climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate); natural variability; and structural uncertainty. Results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also nd that dierent initial conditions lead to dierences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider all sources of uncertainty when modeling climate impacts over Northern Eurasia.

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

Monier, Erwan; Sokolov, Andrei; Schlosser, Adam; Scott, Jeffery; Gao, Xiang

2013-12-01

We present probabilistic projections of 21st century climate change over Northern Eurasia using the Massachusetts Institute of Technology (MIT) Integrated Global System Model (IGSM), an integrated assessment model that couples an Earth system model of intermediate complexity with a two-dimensional zonal-mean atmosphere to a human activity model. Regional climate change is obtained by two downscaling methods: a dynamical downscaling, where the IGSM is linked to a three-dimensional atmospheric model, and a statistical downscaling, where a pattern scaling algorithm uses climate change patterns from 17 climate models. This framework allows for four major sources of uncertainty in future projections of regional climate change to be accounted for: emissions projections, climate system parameters (climate sensitivity, strength of aerosol forcing and ocean heat uptake rate), natural variability, and structural uncertainty. The results show that the choice of climate policy and the climate parameters are the largest drivers of uncertainty. We also find that different initial conditions lead to differences in patterns of change as large as when using different climate models. Finally, this analysis reveals the wide range of possible climate change over Northern Eurasia, emphasizing the need to consider these sources of uncertainty when modeling climate impacts over Northern Eurasia.

The World Climate Exercise: Is (Simulated) Experience Our Best Teacher?

NASA Astrophysics Data System (ADS)

Rath, K.; Rooney-varga, J. N.; Jones, A.; Johnston, E.; Sterman, J.

2015-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

Climate Literacy in the Classroom: Supporting Teachers in the Transition to NGSS

NASA Astrophysics Data System (ADS)

Rogers, M. J. B.; Merrill, J.; Harcourt, P.; Petrone, C.; Shea, N.; Mead, H.

2014-12-01

Meeting the challenge of climate change will clearly require 'deep learning' - learning that motivates a search for underlying meaning, a willingness to exert the sustained effort needed to understand complex problems, and innovative problem-solving. This type of learning is dependent on the level of the learner's engagement with the material, their intrinsic motivation to learn, intention to understand, and relevance of the material to the learner. Here, we present evidence for deep learning about climate change through a simulation-based role-playing exercise, World Climate. The exercise puts participants into the roles of delegates to the United Nations climate negotiations and asks them to create an international climate deal. They find out the implications of their decisions, according to the best available science, through the same decision-support computer simulation used to provide feedback for the real-world negotiations, C-ROADS. World Climate provides an opportunity for participants have an immersive, social experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the dynamics of the climate system, through an interactive computer simulation. Evaluation results so far have shown that the exercise is highly engaging and memorable and that it motivates large majorities of participants (>70%) to take action on climate change. In addition, we have found that it leads to substantial gains in understanding key systems thinking concepts (e.g., the stock-flow behavior of atmospheric CO2), as well as improvements in understanding of climate change causes and impacts. While research is still needed to better understand the impacts of simulation-based role-playing exercises like World Climate on behavior change, long-term understanding, transfer of systems thinking skills across topics, and the importance of social learning during the exercise, our results to date indicate that it is a powerful, active learning tool that has strong potential to foster deep learning about climate change.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Projecting Future Water Levels of the Laurentian Great Lakes

NASA Astrophysics Data System (ADS)

Bennington, V.; Notaro, M.; Holman, K.

2013-12-01

The Laurentian Great Lakes are the largest freshwater system on Earth, containing 84% of North America's freshwater. The lakes are a valuable economic and recreational resource, valued at over 62 billion in annual wages and supporting a 7 billion fishery. Shipping, recreation, and coastal property values are significantly impacted by water level variability, with large economic consequences. Great Lakes water levels fluctuate both seasonally and long-term, responding to natural and anthropogenic climate changes. Due to the integrated nature of water levels, a prolonged small change in any one of the net basin supply components: over-lake precipitation, watershed runoff, or evaporation from the lake surface, may result in important trends in water levels. We utilize the Abdus Salam International Centre for Theoretical Physics's Regional Climate Model Version 4.5.6 to dynamically downscale three global global climate models that represent a spread of potential future climate change for the region to determine whether the climate models suggest a robust response of the Laurentian Great Lakes to anthropogenic climate change. The Model for Interdisciplinary Research on Climate Version 5 (MIROC5), the National Centre for Meteorological Research Earth system model (CNRM-CM5), and the Community Climate System Model Version 4 (CCSM4) project different regional temperature increases and precipitation change over the next century and are used as lateral boundary conditions. We simulate the historical (1980-2000) and late-century periods (2080-2100). Upon model evaluation we will present dynamically downscaled projections of net basin supply changes for each of the Laurentian Great Lakes.

Soil organic carbon dynamics jointly controlled by climate, carbon inputs, soil properties and soil carbon fractions.

PubMed

Luo, Zhongkui; Feng, Wenting; Luo, Yiqi; Baldock, Jeff; Wang, Enli

2017-10-01

Soil organic carbon (SOC) dynamics are regulated by the complex interplay of climatic, edaphic and biotic conditions. However, the interrelation of SOC and these drivers and their potential connection networks are rarely assessed quantitatively. Using observations of SOC dynamics with detailed soil properties from 90 field trials at 28 sites under different agroecosystems across the Australian cropping regions, we investigated the direct and indirect effects of climate, soil properties, carbon (C) inputs and soil C pools (a total of 17 variables) on SOC change rate (r C , Mg C ha -1  yr -1 ). Among these variables, we found that the most influential variables on r C were the average C input amount and annual precipitation, and the total SOC stock at the beginning of the trials. Overall, C inputs (including C input amount and pasture frequency in the crop rotation system) accounted for 27% of the relative influence on r C , followed by climate 25% (including precipitation and temperature), soil C pools 24% (including pool size and composition) and soil properties (such as cation exchange capacity, clay content, bulk density) 24%. Path analysis identified a network of intercorrelations of climate, soil properties, C inputs and soil C pools in determining r C . The direct correlation of r C with climate was significantly weakened if removing the effects of soil properties and C pools, and vice versa. These results reveal the relative importance of climate, soil properties, C inputs and C pools and their complex interconnections in regulating SOC dynamics. Ignorance of the impact of changes in soil properties, C pool composition and C input (quantity and quality) on SOC dynamics is likely one of the main sources of uncertainty in SOC predictions from the process-based SOC models. © 2017 John Wiley & Sons Ltd.

Tectonics of the central Andes

NASA Technical Reports Server (NTRS)

Bloom, Arthur L.; Isacks, Bryan L.; Fielding, Eric J.; Fox, Andrew N.; Gubbels, Timothy L.

1989-01-01

Acquisition of nearly complete coverage of Thematic Mapper data for the central Andes between about 15 to 34 degrees S has stimulated a comprehensive and unprecedented study of the interaction of tectonics and climate in a young and actively developing major continental mountain belt. The current state of the synoptic mapping of key physiographic, tectonic, and climatic indicators of the dynamics of the mountain/climate system are briefly reviewed.

El Niño/Southern Oscillation response to global warming

PubMed Central

Latif, M.; Keenlyside, N. S.

2009-01-01

The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO2, accelerating global warming. PMID:19060210

El Nino/Southern Oscillation response to global warming.

PubMed

Latif, M; Keenlyside, N S

2009-12-08

The El Niño/Southern Oscillation (ENSO) phenomenon, originating in the Tropical Pacific, is the strongest natural interannual climate signal and has widespread effects on the global climate system and the ecology of the Tropical Pacific. Any strong change in ENSO statistics will therefore have serious climatic and ecological consequences. Most global climate models do simulate ENSO, although large biases exist with respect to its characteristics. The ENSO response to global warming differs strongly from model to model and is thus highly uncertain. Some models simulate an increase in ENSO amplitude, others a decrease, and others virtually no change. Extremely strong changes constituting tipping point behavior are not simulated by any of the models. Nevertheless, some interesting changes in ENSO dynamics can be inferred from observations and model integrations. Although no tipping point behavior is envisaged in the physical climate system, smooth transitions in it may give rise to tipping point behavior in the biological, chemical, and even socioeconomic systems. For example, the simulated weakening of the Pacific zonal sea surface temperature gradient in the Hadley Centre model (with dynamic vegetation included) caused rapid Amazon forest die-back in the mid-twenty-first century, which in turn drove a nonlinear increase in atmospheric CO(2), accelerating global warming.

Regional Approach for Managing for Resilience Linking Ecosystem Services and Livelihood Strategies for Agro-Pastoral Communities in the Mongolian Steppe Ecosystem

NASA Astrophysics Data System (ADS)

Ojima, D. S.; Togtohyn, C.; Qi, J.; Galvin, K.

2011-12-01

Dramatic changes due to climate and land use dynamics in the Mongolian Plateau are affecting ecosystem services and agro-pastoral livelihoods in Mongolia and China. Recently, evaluation of pastoral systems, where humans depend on livestock and grassland ecosystem services, have demonstrated the vulnerability of the social-ecological system to climate change. Current social-ecological changes in ecosystem services are affecting land productivity and carrying capacity, land-atmosphere interactions, water resources, and livelihood strategies. Regional dust events, changes in hydrological cycle, and land use changes contribute to changing interactions between ecosystem and landscape processes which then affect social-ecological systems. The general trend involves greater intensification of resource exploitation at the expense of traditional patterns of extensive range utilization. Thus we expect climate-land use-land cover relationships to be crucially modified by the socio-economic forces. The analysis incorporates information of the socio-economic transitions taking place in the region which affect land-use, food security, and ecosystem dynamics. The region of study extends from the Mongolian plateau in Mongolia and China to the fertile northeast China plain. Sustainability of agro-pastoral systems in the region needs to integrate the impact of climate change on ecosystem services with socio-economic changes shaping the livelihood strategies of pastoral systems in the region. Adaptation strategies which incorporate landscape management provides a potential framework to link ecosystem services across space and time more effectively to meet the needs of agro-pastoral land use, herd quality, and herder's living standards. Under appropriate adaptation strategies agro-pastoralists will have the opportunity to utilize seasonal resources and enhance their ability to process and manufacture products from the available ecosystem services in these dynamic social-ecological systems.

What can we learn about the dynamics of DO-events from studying the high resolution ice core records?

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter

2017-04-01

The causes for and possible predictions of rapid climate changes are poorly understood. The most pronounced changes observed, beside the glacial terminations, are the Dansgaard-Oeschger events. Present day general circulation climate models simulating glacial conditions are not capable of reproducing these rapid shifts. It is thus not known if they are due to bifurcations in the structural stability of the climate or if they are induced by stochastic fluctuations. By analyzing a high resolution ice core record we exclude the bifurcation scenario, which strongly suggests that they are noise induced and thus have very limited predictability. Ref: Peter Ditlevsen, "Tipping points in the climate system", in Nonlinear and Stochastic Climate Dynamics, Cambridge University Press (C. Franzke and T. O'Kane, eds.) (2016) P. D. Ditlevsen and S. Johnsen, "Tipping points: Early warning and wishful thinking", Geophys. Res. Lett., 37, L19703, 2010

Climate Change Adaptation in the Western U.S.: the Case for Dynamic Rule Curves in Water Resources Management

NASA Astrophysics Data System (ADS)

Lee, S.; Hamlet, A. F.; Burges, S. J.

2008-12-01

Climate change in the Western U.S. will bring systematic hydrologic changes affecting many water resources systems. Successful adaptation to these changes, which will be ongoing through the 21st century, will require the 'rebalancing' of competing system objectives such as water supply, flood control, hydropower production, and environmental services in response to hydrologic (and other) changes. Although fixed operating policies for the operation of reservoirs has been a traditional approach to water management in the 20th century, the rapid pace of projected climate shifts (~0.5 F per decade), and the prohibitive costs of recursive policy intervention to mitigate impacts, suggest that more sophisticated approaches will be needed to cope with climate change on a long term basis. The use of 'dynamic rule curves' is an approach that maintains some of the key characteristics of current water management practice (reservoir rule curves) while avoiding many of the fundamental drawbacks of traditional water resources management strategies in a non-stationary climate. In this approach, water resources systems are optimized for each operational period using ensemble streamflow and/or water demand forecasts. The ensemble of optimized reservoir storage traces are then analyzed to produce a set of unique reservoir rule curves for each operational period reflecting the current state of the system. The potential advantage of this approach is that hydrologic changes associated with climate change (such as systematically warmer temperatures) can be captured explicitly in operational hydrologic forecasts, which would in turn inform the optimized reservoir management solutions, creating water resources systems that are largely 'self tending' as the climate system evolves. Furthermore, as hydrologic forecasting systems improve (e.g. in response to improved ENSO forecasting or other scientific advances), so does the performance of reservoir operations. An example of the approach is given for flood control in the Columbia River basin.

On the use of finite difference matrix-vector products in Newton-Krylov solvers for implicit climate dynamics with spectral elements

DOE PAGES

Woodward, Carol S.; Gardner, David J.; Evans, Katherine J.

2015-01-01

Efficient solutions of global climate models require effectively handling disparate length and time scales. Implicit solution approaches allow time integration of the physical system with a step size governed by accuracy of the processes of interest rather than by stability of the fastest time scales present. Implicit approaches, however, require the solution of nonlinear systems within each time step. Usually, a Newton's method is applied to solve these systems. Each iteration of the Newton's method, in turn, requires the solution of a linear model of the nonlinear system. This model employs the Jacobian of the problem-defining nonlinear residual, but thismore » Jacobian can be costly to form. If a Krylov linear solver is used for the solution of the linear system, the action of the Jacobian matrix on a given vector is required. In the case of spectral element methods, the Jacobian is not calculated but only implemented through matrix-vector products. The matrix-vector multiply can also be approximated by a finite difference approximation which may introduce inaccuracy in the overall nonlinear solver. In this paper, we review the advantages and disadvantages of finite difference approximations of these matrix-vector products for climate dynamics within the spectral element shallow water dynamical core of the Community Atmosphere Model.« less

Research Review, 1983

NASA Technical Reports Server (NTRS)

1984-01-01

The Global Modeling and Simulation Branch (GMSB) of the Laboratory for Atmospheric Sciences (GLAS) is engaged in general circulation modeling studies related to global atmospheric and oceanographic research. The research activities discussed are organized into two disciplines: Global Weather/Observing Systems and Climate/Ocean-Air Interactions. The Global Weather activities are grouped in four areas: (1) Analysis and Forecast Studies, (2) Satellite Observing Systems, (3) Analysis and Model Development, (4) Atmospheric Dynamics and Diagnostic Studies. The GLAS Analysis/Forecast/Retrieval System was applied to both FGGE and post FGGE periods. The resulting analyses have already been used in a large number of theoretical studies of atmospheric dynamics, forecast impact studies and development of new or improved algorithms for the utilization of satellite data. Ocean studies have focused on the analysis of long-term global sea surface temperature data, for use in the study of the response of the atmosphere to sea surface temperature anomalies. Climate research has concentrated on the simulation of global cloudiness, and on the sensitivities of the climate to sea surface temperature and ground wetness anomalies.

Stability, Bistability, and Critical Thresholds in Fire-prone Forested Landscapes: How Frequency and Intensity of Disturbance Interact and Influence Forest Cover

NASA Astrophysics Data System (ADS)

Miller, A. D.

2015-12-01

Many aspects of disturbance processes can have large impacts on the composition of plant communities, and associated changes in land cover type in turn have biogeochemical feedbacks to climate. In particular, changes to disturbance regimes can potentially change the number and stability of equilibrial states, and plant community states can differ dramatically in their carbon (C) dynamics, energy balance, and hydrology. Using the Klamath region of northern California as a model system, we present a theoretical analysis of how changes to climate and associated fire dynamics can disrupt high-carbon, long-lived conifer forests and replace them with shrub-chaparral communities that have much lower biomass and are more pyrogenic. Specifically, we develop a tractable model of plant community dynamics, structured by size class, life-history traits, lottery-type competition, and species-specific responses to disturbance. We assess the stability of different states in terms of disturbance frequency and intensity, and quantitatively partition long-term low-density population growth rates into mechanisms that influence critical transitions from stable to bistable behavior. Our findings show how different aspects of disturbance act and interact to control competitive outcomes and stable states, hence ecosystem-atmosphere C exchange. Forests tend to dominate in low frequency and intensity regimes, while shrubs dominate at high fire frequency and intensity. In other regimes, the system is bistable, and the fate of the system depends both on initial conditions and random chance. Importantly, the system can cross a critical threshold where hysteresis prevents easy return to the prior forested state. We conclude that changes in disturbance-recovery dynamics driven by projected climate change can shift this system away from forest dominated in the direction of shrub-dominated landscape. This will result in a large net C release from the landscape, and alter biophysical ecosystem-climate interactions.

Host and parasite thermal ecology jointly determine the effect of climate warming on epidemic dynamics.

PubMed

Gehman, Alyssa-Lois M; Hall, Richard J; Byers, James E

2018-01-23

Host-parasite systems have intricately coupled life cycles, but each interactor can respond differently to changes in environmental variables like temperature. Although vital to predicting how parasitism will respond to climate change, thermal responses of both host and parasite in key traits affecting infection dynamics have rarely been quantified. Through temperature-controlled experiments on an ectothermic host-parasite system, we demonstrate an offset in the thermal optima for survival of infected and uninfected hosts and parasite production. We combine experimentally derived thermal performance curves with field data on seasonal host abundance and parasite prevalence to parameterize an epidemiological model and forecast the dynamical responses to plausible future climate-warming scenarios. In warming scenarios within the coastal southeastern United States, the model predicts sharp declines in parasite prevalence, with local parasite extinction occurring with as little as 2 °C warming. The northern portion of the parasite's current range could experience local increases in transmission, but assuming no thermal adaptation of the parasite, we find no evidence that the parasite will expand its range northward under warming. This work exemplifies that some host populations may experience reduced parasitism in a warming world and highlights the need to measure host and parasite thermal performance to predict infection responses to climate change.

Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models

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

Kravitz, Ben; MacMartin, Douglas G.; Rasch, Philip J.

We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state. We use this technique to determine the steady-state responses of low cloud fraction and latent heat flux to heating perturbations over 22 regions spanning Earth's oceans. We show that the response characteristics are similar to thosemore » of step-change simulations, but in this new method the responses for 22 regions can be characterized simultaneously. Moreover, we can estimate the timescale over which the steady-state response emerges. The proposed methodology could be useful for a wide variety of purposes in climate science, including characterization of teleconnections and uncertainty quantification to identify the effects of climate model tuning parameters.« less

Technical note: Simultaneous fully dynamic characterization of multiple input–output relationships in climate models

DOE PAGES

Kravitz, Ben; MacMartin, Douglas G.; Rasch, Philip J.; ...

2017-02-17

We introduce system identification techniques to climate science wherein multiple dynamic input–output relationships can be simultaneously characterized in a single simulation. This method, involving multiple small perturbations (in space and time) of an input field while monitoring output fields to quantify responses, allows for identification of different timescales of climate response to forcing without substantially pushing the climate far away from a steady state. We use this technique to determine the steady-state responses of low cloud fraction and latent heat flux to heating perturbations over 22 regions spanning Earth's oceans. We show that the response characteristics are similar to thosemore » of step-change simulations, but in this new method the responses for 22 regions can be characterized simultaneously. Moreover, we can estimate the timescale over which the steady-state response emerges. The proposed methodology could be useful for a wide variety of purposes in climate science, including characterization of teleconnections and uncertainty quantification to identify the effects of climate model tuning parameters.« less

Towards a unified Global Weather-Climate Prediction System

NASA Astrophysics Data System (ADS)

Lin, S. J.

2016-12-01

The Geophysical Fluid Dynamics Laboratory has been developing a unified regional-global modeling system with variable resolution capabilities that can be used for severe weather predictions and kilometer scale regional climate simulations within a unified global modeling system. The foundation of this flexible modeling system is the nonhydrostatic Finite-Volume Dynamical Core on the Cubed-Sphere (FV3). A unique aspect of FV3 is that it is "vertically Lagrangian" (Lin 2004), essentially reducing the equation sets to two dimensions, and is the single most important reason why FV3 outperforms other non-hydrostatic cores. Owning to its accuracy, adaptability, and computational efficiency, the FV3 has been selected as the "engine" for NOAA's Next Generation Global Prediction System (NGGPS). We have built into the modeling system a stretched grid, a two-way regional-global nested grid, and an optimal combination of the stretched and two-way nests capability, making kilometer-scale regional simulations within a global modeling system feasible. Our main scientific goal is to enable simulations of high impact weather phenomena (such as tornadoes, thunderstorms, category-5 hurricanes) within an IPCC-class climate modeling system previously regarded as impossible. In this presentation I will demonstrate that, with the FV3, it is computationally feasible to simulate not only super-cell thunderstorms, but also the subsequent genesis of tornado-like vortices using a global model that was originally designed for climate simulations. The development and tuning strategy between traditional weather and climate models are fundamentally different due to different metrics. We were able to adapt and use traditional "climate" metrics or standards, such as angular momentum conservation, energy conservation, and flux balance at top of the atmosphere, and gain insight into problems of traditional weather prediction model for medium-range weather prediction, and vice versa. Therefore, the unification in weather and climate models can happen not just at the algorithm or parameterization level, but also in the metric and tuning strategy used for both applications, and ultimately, with benefits to both weather and climate applications.

Quantifying climate feedbacks in polar regions

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

Goosse, Hugues; Kay, Jennifer E.; Armour, Kyle C.

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range ofmore » feedbacks, thus offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.« less

Quantifying climate feedbacks in polar regions

DOE PAGES

Goosse, Hugues; Kay, Jennifer E.; Armour, Kyle C.; ...

2018-05-15

The concept of feedback is key in assessing whether a perturbation to a system is amplified or damped by mechanisms internal to the system. In polar regions, climate dynamics are controlled by both radiative and non-radiative interactions between the atmosphere, ocean, sea ice, ice sheets and land surfaces. Precisely quantifying polar feedbacks is required for a process-oriented evaluation of climate models, a clear understanding of the processes responsible for polar climate changes, and a reduction in uncertainty associated with model projections. This quantification can be performed using a simple and consistent approach that is valid for a wide range ofmore » feedbacks, thus offering the opportunity for more systematic feedback analyses and a better understanding of polar climate changes.« less

Montane ecosystem productivity responds more to global circulation patterns than climatic trends.

PubMed

Desai, A R; Wohlfahrt, G; Zeeman, M J; Katata, G; Eugster, W; Montagnani, L; Gianelle, D; Mauder, M; Schmid, H-P

2016-02-01

Regional ecosystem productivity is highly sensitive to inter-annual climate variability, both within and outside the primary carbon uptake period. However, Earth system models lack sufficient spatial scales and ecosystem processes to resolve how these processes may change in a warming climate. Here, we show, how for the European Alps, mid-latitude Atlantic ocean winter circulation anomalies drive high-altitude summer forest and grassland productivity, through feedbacks among orographic wind circulation patterns, snowfall, winter and spring temperatures, and vegetation activity. Therefore, to understand future global climate change influence to regional ecosystem productivity, Earth systems models need to focus on improvements towards topographic downscaling of changes in regional atmospheric circulation patterns and to lagged responses in vegetation dynamics to non-growing season climate anomalies.

Montane ecosystem productivity responds more to global circulation patterns than climatic trends

NASA Astrophysics Data System (ADS)

Desai, A. R.; Wohlfahrt, G.; Zeeman, M. J.; Katata, G.; Eugster, W.; Montagnani, L.; Gianelle, D.; Mauder, M.; Schmid, H.-P.

2016-02-01

Regional ecosystem productivity is highly sensitive to inter-annual climate variability, both within and outside the primary carbon uptake period. However, Earth system models lack sufficient spatial scales and ecosystem processes to resolve how these processes may change in a warming climate. Here, we show, how for the European Alps, mid-latitude Atlantic ocean winter circulation anomalies drive high-altitude summer forest and grassland productivity, through feedbacks among orographic wind circulation patterns, snowfall, winter and spring temperatures, and vegetation activity. Therefore, to understand future global climate change influence to regional ecosystem productivity, Earth systems models need to focus on improvements towards topographic downscaling of changes in regional atmospheric circulation patterns and to lagged responses in vegetation dynamics to non-growing season climate anomalies.

A laboratory experiment simulating the dynamics of topographic relief: methodology and results

NASA Astrophysics Data System (ADS)

Crave, A.; Lague, D.; Davy, P.; Bonnet, S.; Laguionie, P.

2002-12-01

Theoretical analysis and numerical models of landscape evolution have advanced several scenarios for the long-term evolution of terrestrial topography. These scenarios require quantitative evaluation. Analyses of topography, sediment fluxes, and the physical mechanisms of erosion and sediment transport can provide some constraints on the range of plausible models. But in natural systems the boundary conditions (tectonic uplift, climate, base level) are often not well constrained and the spatial heterogeneity of substrate, climate, vegetation, and prevalent processes commonly confounds attempts at extrapolation of observations to longer timescales. In the laboratory, boundary conditions are known and heterogeneity and complexity can be controlled. An experimental approach can thus provide valuable constraints on the dynamics of geomorphic systems, provided that (1) the elementary processes are well calibrated and (2) the topography and sediment fluxes are sufficiently well documented. We have built an experimental setup of decimeter scale that is designed to develop a complete drainage network by the growth and propagation of erosion instabilities in response to tectonic and climatic perturbations. Uplift and precipitation rates can be changed over an order of magnitude. Telemetric lasers and 3D stereo-photography allow the precise quantification of the topographic evolution of the experimental surface. In order to calibrate the principal processes of erosion and transport we have used three approaches: (1) theoretical derivation of erosion laws deduced from the geometrical properties of experimental surfaces at steady-state under different rates of tectonic uplift; (2) comparison of the experimental transient dynamics with a numerical simulation model to test the validity of the predicted erosion laws; and (3) detailed analysis of particle detachment and transport in a millimeter sheet flow on a two-meter long flume under precisely controlled water discharge, slope and flow width. The analogy with real geomorphic systems is limited by the imperfect downscaling in both time and space of the experiments. However, these simple experiments have allowed us to probe (1) the importance of a threshold for particle mobilization to the relationship between steady-state elevation and uplift rate, (2) the role of initial drainage network organization in the transient dynamics of tectonically perturbed systems and (3) the sediment flux dynamics of climatically perturbed systems.

FOREWORD: International Conference on Planetary Boundary Layer and Climate Change

NASA Astrophysics Data System (ADS)

Djolov, G.; Esau, I.

2010-05-01

One of the greatest achievements of climate science has been the establisment of the concept of climate change on a multitude of time scales. The Earth's complex climate system does not allow a straightforward interpretation of dependences between the external parameter perturbation, internal stochastic system dynamics and the long-term system response. The latter is usually referred to as climate change in a narrow sense (IPCC, 2007). The focused international conference "Planetary Boundary Layers and Climate Change" has addressed only time scales and dynamical aspects of climate change with possible links to the turbulent processes in the Planetary Boundary Layer (PBL). Although limited, the conference topic is by no means singular. One should clearly understand that the PBL is the layer where 99% of biosphere and human activity are concentrated. The PBL is the layer where the energy fluxes, which are followed by changes in cryosphere and other known feedbacks, are maximized. At the same time, the PBL processes are of a naturally small scale. What is the averaged long-term effect of the small-scale processes on the long-term climate dynamics? Can this effect be recognized in existing long-term paleo-climate data records? Can it be modeled? What is the current status of our theoretical understanding of this effect? What is the sensitivity of the climate model projections to the representation of small-scale processes? Are there significant indirect effects, e.g. through transport of chemical components, of the PBL processes on climate? These and other linked questions have been addressed during the conference. The Earth's climate has changed many times during the planet's history, with events ranging from ice ages to long periods of warmth. Historically, natural factors such as the amount of energy released from the Sun, volcanic eruptions and changes in the Earth's orbit have affected the Earth's climate. Beginning late in the 18th century, human activities associated with the Industrial Revolution such as the addition of greenhouse gases and aerosols has changed the composition of the atmosphere. These changes are likely to have influenced temperature, precipitation, storms and sea level (IPCC, 2007). However, these features of the climate also vary naturally, so determining what fraction of climate changes are due to natural variability versus human activities is challenging and not yet a solved problem. Africa is vulnerable to climate change as its ability to adaptat and mitigate is considerably dampened (IPCC, 2007). Climate change may impede a nations ability to achieve sustainable development and the Millennium Development Goals, and because of that Africa (particularly sub-tropical Africa) will experience increased levels of water stress and reduced agricultural yields of up to 50% by 2020. An example of the scale of the region's vulnerability was demonstrated during the last very dry year (1991/92) when 30% of the southern African population was put on food aid and more than one million people were displaced. Climate change in Africa is essentially dependent on our understanding of the PBL processes both due to the indispensible role of the atmospheric convection in the African climate and due to its tele-connections to other regions, e.g. the tropical Pacific and Indian monsoon regions. Although numerous publications attribute the observed changes to one or another modification of the convective patterns, further progress is impeded by imperfections of the small-scale process parameterizations in the models. The uncertainties include parameter uncertainties of known physical processes, which could be reduced through better observations/modelling, as well as uncertainties in our knowledge of physical processes themselves (or structural uncertainties), which could be reduced only through theoretical development and design of new, original observations/experiments (Oppenheimer et al., Science, 2007). Arguably, the structural uncertainties is hard to reduce and this could be one of the reasons determining slow progress in narrowing the climate model uncertainty range over the last 30 years (Knutti and Hagerl, Nature Geoscience, 2008). One of the most prominent structural uncertainties in the ongoing transient climate change is related to poor understanding and hence incorrect modelling of the turbulent physics and dynamics processes in the planetary boundary layer. Nevertheless, the climate models continue to rely on physically incorrect boundary layer parameterizations (Cuxart et al., BLM, 2006), whose erroneous dynamical response in the climate models may lead to significant abnormalities in simulated climate. At present, international efforts in theoretical understanding of the turbulent mixing have resulted in significant progress in turbulence simulation, measurements and parameterizations. However, this understanding has not yet found its way to the climate research community. Vice versa, climate research is not usually addressed by the boundary layer research community. The gap needs to be closed in order to crucially complete the scientific basis of climate change studies. The focus of the proposed forum could be formulated as follows: The planetary boundary layer determines several key parameters controlling the Earth's climate system but being a dynamic sub-system, just a layer of turbulent mixing in the atmosphere/ocean, it is also controlled by the climate system and its changes. Such a dynamic relationship causes a planetary boundary layer feedback (PBL-feedback) which could be defined as the response of the surface air temperature on changes in the vertical turbulent mixing. The forum participants have discussed both climatological and fluid dynamic aspects of this response, in order to quantify their role in the Earth's transient heat uptake and its representation in climate models. The choice of the forum location and dates are motivated by the role of tropical oceans and convection in the climate system and the prominent demonstration of the climate sensitivity to the ocean heat uptake observed off Cape Town. The international conference responded to the urgent need of advancing our understanding of the complex climate system and development of adequate measures for saving the planet from environmental disaster. It also fits well with the Republic of South African government's major political decision to include the responses to global change/climate change at the very top of science and technology policy. The conference participants are grateful to the Norway Research Council and the National Research Foundation (NRF) RSA who supported the Conference through the project "Analysis and Possibility for Control of Atmospheric Boundary Layer Processes to Facilitate Adaptation to Environmental Changes" realized in the framework of the Programme for Research and Co-operation Phase II between the two countries. Kirstenbosh Biodiversity Institute and Botanical Gardens, Cape Town contribution of securing one of the most beautiful Conference venues in the world and technical support is also highly appreciated. G. Djolov and I. Esau Editors Conference_Photo Conference Organising Comittee Djolov, G.South AfricaUniversity of Pretoria Esau, I.NorwayNansen Environmental and Remote Sensing Center Hewitson, B.South AfricaUniversity of Cape Town McGregor, J.AustraliaCSIRO Marine and Atmospheric Research Midgley, G.South AfricaSouth African National Botanical Institute Mphepya, J.South AfricaSouth African Weather Service Piketh, S.South AfricaUniversity of the Witwatersrand Pielke, R.USAUniversity of Colorado, Boulder Pienaar, K.South AfricaUniversity of the North West Rautenbach, H.South AfricaUniversity of Pretoria Zilitinkevich, S.FinlandUniversity of Helsinki The conference was organized by: University of Pretoria Nansen Environmental and Remote Sensing Center With support and sponsorship from: Norwegian Research Council (grant N 197649) Kirstenbosh Biodiversity Institute and Botanical Gardens

Constructing the reduced dynamical models of interannual climate variability from spatial-distributed time series

NASA Astrophysics Data System (ADS)

Mukhin, Dmitry; Gavrilov, Andrey; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

We suggest a method for empirical forecast of climate dynamics basing on the reconstruction of reduced dynamical models in a form of random dynamical systems [1,2] derived from observational time series. The construction of proper embedding - the set of variables determining the phase space the model works in - is no doubt the most important step in such a modeling, but this task is non-trivial due to huge dimension of time series of typical climatic fields. Actually, an appropriate expansion of observational time series is needed yielding the number of principal components considered as phase variables, which are to be efficient for the construction of low-dimensional evolution operator. We emphasize two main features the reduced models should have for capturing the main dynamical properties of the system: (i) taking into account time-lagged teleconnections in the atmosphere-ocean system and (ii) reflecting the nonlinear nature of these teleconnections. In accordance to these principles, in this report we present the methodology which includes the combination of a new way for the construction of an embedding by the spatio-temporal data expansion and nonlinear model construction on the basis of artificial neural networks. The methodology is aplied to NCEP/NCAR reanalysis data including fields of sea level pressure, geopotential height, and wind speed, covering Northern Hemisphere. Its efficiency for the interannual forecast of various climate phenomena including ENSO, PDO, NAO and strong blocking event condition over the mid latitudes, is demonstrated. Also, we investigate the ability of the models to reproduce and predict the evolution of qualitative features of the dynamics, such as spectral peaks, critical transitions and statistics of extremes. This research was supported by the Government of the Russian Federation (Agreement No. 14.Z50.31.0033 with the Institute of Applied Physics RAS) [1] Y. I. Molkov, E. M. Loskutov, D. N. Mukhin, and A. M. Feigin, "Random dynamical models from time series," Phys. Rev. E, vol. 85, no. 3, p. 036216, 2012. [2] D. Mukhin, D. Kondrashov, E. Loskutov, A. Gavrilov, A. Feigin, and M. Ghil, "Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models," J. Clim., vol. 28, no. 5, pp. 1962-1976, 2015.

Nonlinear Dynamical Modes as a Basis for Short-Term Forecast of Climate Variability

NASA Astrophysics Data System (ADS)

Feigin, A. M.; Mukhin, D.; Gavrilov, A.; Seleznev, A.; Loskutov, E.

2017-12-01

We study abilities of data-driven stochastic models constructed by nonlinear dynamical decomposition of spatially distributed data to quantitative (short-term) forecast of climate characteristics. We compare two data processing techniques: (i) widely used empirical orthogonal function approach, and (ii) nonlinear dynamical modes (NDMs) framework [1,2]. We also make comparison of two kinds of the prognostic models: (i) traditional autoregression (linear) model and (ii) model in the form of random ("stochastic") nonlinear dynamical system [3]. We apply all combinations of the above-mentioned data mining techniques and kinds of models to short-term forecasts of climate indices based on sea surface temperature (SST) data. We use NOAA_ERSST_V4 dataset (monthly SST with space resolution 20 × 20) covering the tropical belt and starting from the year 1960. We demonstrate that NDM-based nonlinear model shows better prediction skill versus EOF-based linear and nonlinear models. Finally we discuss capability of NDM-based nonlinear model for long-term (decadal) prediction of climate variability. [1] D. Mukhin, A. Gavrilov, E. Loskutov , A.Feigin, J.Kurths, 2015: Principal nonlinear dynamical modes of climate variability, Scientific Reports, rep. 5, 15510; doi: 10.1038/srep15510. [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J., 2016: Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101. [3] Ya. Molkov, D. Mukhin, E. Loskutov, A. Feigin, 2012: Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.

Predictability of Extreme Climate Events via a Complex Network Approach

NASA Astrophysics Data System (ADS)

Muhkin, D.; Kurths, J.

2017-12-01

We analyse climate dynamics from a complex network approach. This leads to an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. This concept is then applied to Monsoon data; in particular, we develop a general framework to predict extreme events by combining a non-linear synchronization technique with complex networks. Applying this method, we uncover a new mechanism of extreme floods in the eastern Central Andes which could be used for operational forecasts. Moreover, we analyze the Indian Summer Monsoon (ISM) and identify two regions of high importance. By estimating an underlying critical point, this leads to an improved prediction of the onset of the ISM; this scheme was successful in 2016 and 2017.

DYNAMICO, an atmospheric dynamical core for high-performance climate modeling

NASA Astrophysics Data System (ADS)

Dubos, Thomas; Meurdesoif, Yann; Spiga, Aymeric; Millour, Ehouarn; Fita, Lluis; Hourdin, Frédéric; Kageyama, Masa; Traore, Abdoul-Khadre; Guerlet, Sandrine; Polcher, Jan

2017-04-01

Institut Pierre Simon Laplace has developed a very scalable atmospheric dynamical core, DYNAMICO, based on energy-conserving finite-difference/finite volume numerics on a quasi-uniform icosahedral-hexagonal mesh. Scalability is achieved by combining hybrid MPI/OpenMP parallelism to asynchronous I/O. This dynamical core has been coupled to radiative transfer physics tailored to the atmosphere of Saturn, allowing unprecedented simulations of the climate of this giant planet. For terrestrial climate studies DYNAMICO is being integrated into the IPSL Earth System Model IPSL-CM. Preliminary aquaplanet and AMIP-style simulations yield reasonable results when compared to outputs from IPSL-CM5. The observed performance suggests that an order of magnitude may be gained with respect to IPSL-CM CMIP5 simulations either on the duration of simulations or on their resolution. Longer simulations would be of interest for the study of paleoclimate, while higher resolution could improve certain aspects of the modeled climate such as extreme events, as will be explored in the HighResMIP project. Following IPSL's strategic vision of building a unified global-regional modelling system, a fully-compressible, non-hydrostatic prototype of DYNAMICO has been developed, enabling future convection-resolving simulations. Work supported by ANR project "HEAT", grant number CE23_2014_HEAT Dubos, T., Dubey, S., Tort, M., Mittal, R., Meurdesoif, Y., and Hourdin, F.: DYNAMICO-1.0, an icosahedral hydrostatic dynamical core designed for consistency and versatility, Geosci. Model Dev., 8, 3131-3150, doi:10.5194/gmd-8-3131-2015, 2015.

A platform to integrate climate information and rural telemedicine in Malawi

NASA Astrophysics Data System (ADS)

Lowe, R.; Chadza, T.; Chirombo, J.; Fonda, C.; Muyepa, A.; Nkoloma, M.; Pietrosemoli, E.; Radicella, S. M.; Tompkins, A. M.; Zennaro, M.

2012-04-01

It is commonly accepted that climate plays a role in the transmission of many infectious diseases, particularly those transmitted by mosquitoes such as malaria, which is one of the most important causes of mortality and morbidity in developing countries. Due to time lags involved in the climate-disease transmission system, lagged observed climate variables could provide some predictive lead for forecasting disease epidemics. This lead time could be extended by using forecasts of the climate in disease prediction models. This project aims to implement a platform for the dissemination of climate-driven disease risk forecasts, using a telemedicine approach. A pilot project has been established in Malawi, where a 162 km wireless link has been installed, spanning from Blantyre City to remote health facilities in the district of Mangochi in the Southern region, bordering Lake Malawi. This long Wi-Fi technology allows rural health facilities to upload real-time disease cases as they occur to an online health information system (DHIS2); a national medical database repository administered by the Ministry of Health. This technology provides a real-time data logging system for disease incidence monitoring and facilitates the flow of information between local and national levels. This platform allows statistical and dynamical disease prediction models to be rapidly updated with real-time climate and epidemiological information. This permits health authorities to target timely interventions ahead of an imminent increase in malaria incidence. By integrating meteorological and health information systems in a statistical-dynamical prediction model, we show that a long-distance Wi-Fi link is a practical and inexpensive means to enable the rapid analysis of real-time information in order to target disease prevention and control measures and mobilise resources at the local level.

High-resolution climate and land surface interactions modeling over Belgium: current state and decennial scale projections

NASA Astrophysics Data System (ADS)

Jacquemin, Ingrid; Henrot, Alexandra-Jane; Beckers, Veronique; Berckmans, Julie; Debusscher, Bos; Dury, Marie; Minet, Julien; Hamdi, Rafiq; Dendoncker, Nicolas; Tychon, Bernard; Hambuckers, Alain; François, Louis

2016-04-01

The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs (from a 4 km resolution simulation) for the recent past and the decennial projections. Evidently, these simulations lead to a first analysis of the impact of climate change on carbon stocks (e.g., biomass, soil carbon) and fluxes (e.g., gross and net primary productivities (GPP and NPP) and net ecosystem production (NEP)). The surface scheme is based on two land use/land cover databases, ECOPLAN for the Flemish region and, for the Walloon region, the COS-Wallonia database and the Belgian agricultural statistics for agricultural land. Land use and land cover are fixed through time (reference year: 2007) in these simulations, but a first attempt of coupling between CARAIB and CRAFTY will be made to establish dynamic land use change scenarios for the next decades. A simulation with variable land use would allow an analysis of land use change impacts not only on crop yields and the land carbon budget, but also on climate relevant parameters, such as surface albedo, roughness length and evapotranspiration towards a coupling with the RCM.

Greenland ice sheet beyond 2100: Simulating its evolution and influence using the coupled climate-ice sheet model EC-Earth - PISM

NASA Astrophysics Data System (ADS)

Yang, S.; Christensen, J. H.; Madsen, M. S.; Ringgaard, I. M.; Petersen, R. A.; Langen, P. P.

2017-12-01

Greenland ice sheet (GrIS) is observed undergoing a rapid change in the recent decades, with an increasing area of surface melting and ablation and a speeding mass loss. Predicting the GrIS changes and their climate consequences relies on the understanding of the interaction of the GrIS with the climate system on both global and local scales, and requires climate model systems incorporating with an explicit and physically consistent ice sheet module. In this work we study the GrIS evolution and its interaction with the climate system using a fully coupled global climate model with a dynamical ice sheet model for the GrIS. The coupled model system, EC-EARTH - PISM, consisting of the atmosphere-ocean-sea ice model system EC-EARTH, and the Parallel Ice Sheet Model (PISM), has been employed for a 1400-year simulation forced by CMIP5 historical forcing from 1850 to 2005 and continued along an extended RCP8.5 scenario with the forcing peaking at 2200 and stabilized hereafter. The simulation reveals that, following the anthropogenic forcing increase, the global mean surface temperature rapidly rises about 10 °C in the 21st and 22nd century. After the forcing stops increasing after 2200, the temperature change slows down and eventually stabilizes at about 12.5 °C above the preindustrial level. In response to the climate warming, the GrIS starts losing mass slowly in the 21st century, but the ice retreat accelerates substantially after 2100 and ice mass loss continues hereafter at a constant rate of approximately 0.5 m sea level rise equivalence per 100 years, even as the warming rate gradually levels off. Ultimately the volume and extent of GrIS reduce to less than half of its preindustrial value. To understand the interaction of GrIS with the climate system, the characteristics of atmospheric and oceanic circulation in the warm climate are analyzed. The circulation patterns associated with the negative surface mass balance that leads to GrIS retreat are investigated. The impact of the simulated surface warming on the ice flow and ice dynamics is explored.

Development and application of earth system models.

PubMed

Prinn, Ronald G

2013-02-26

The global environment is a complex and dynamic system. Earth system modeling is needed to help understand changes in interacting subsystems, elucidate the influence of human activities, and explore possible future changes. Integrated assessment of environment and human development is arguably the most difficult and most important "systems" problem faced. To illustrate this approach, we present results from the integrated global system model (IGSM), which consists of coupled submodels addressing economic development, atmospheric chemistry, climate dynamics, and ecosystem processes. An uncertainty analysis implies that without mitigation policies, the global average surface temperature may rise between 3.5 °C and 7.4 °C from 1981-2000 to 2091-2100 (90% confidence limits). Polar temperatures, absent policy, are projected to rise from about 6.4 °C to 14 °C (90% confidence limits). Similar analysis of four increasingly stringent climate mitigation policy cases involving stabilization of greenhouse gases at various levels indicates that the greatest effect of these policies is to lower the probability of extreme changes. The IGSM is also used to elucidate potential unintended environmental consequences of renewable energy at large scales. There are significant reasons for attention to climate adaptation in addition to climate mitigation that earth system models can help inform. These models can also be applied to evaluate whether "climate engineering" is a viable option or a dangerous diversion. We must prepare young people to address this issue: The problem of preserving a habitable planet will engage present and future generations. Scientists must improve communication if research is to inform the public and policy makers better.

A multistage decision support framework to guide tree species management under climate change via habitat suitability and colonization models, and a knowledge-based scoring system

Treesearch

Anantha M. Prasad; Louis R. Iverson; Stephen N. Matthews; Matthew P. Peters

2016-01-01

Context. No single model can capture the complex species range dynamics under changing climates--hence the need for a combination approach that addresses management concerns. Objective. A multistage approach is illustrated to manage forested landscapes under climate change. We combine a tree species habitat model--DISTRIB II, a species colonization model--SHIFT, and...

Implementation of malaria dynamic models in municipality level early warning systems in Colombia. Part I: description of study sites.

PubMed

Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M; Quiñónes, Martha L; Jiménez, Mónica M; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J; Thomson, Madeleine C

2014-07-01

As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. © The American Society of Tropical Medicine and Hygiene.

Modeling U.S. water resources under climate change

NASA Astrophysics Data System (ADS)

Blanc, Elodie; Strzepek, Kenneth; Schlosser, Adam; Jacoby, Henry; Gueneau, Arthur; Fant, Charles; Rausch, Sebastian; Reilly, John

2014-04-01

Water is at the center of a complex and dynamic system involving climatic, biological, hydrological, physical, and human interactions. We demonstrate a new modeling system that integrates climatic and hydrological determinants of water supply with economic and biological drivers of sectoral and regional water requirement while taking into account constraints of engineered water storage and transport systems. This modeling system is an extension of the Massachusetts Institute of Technology (MIT) Integrated Global System Model framework and is unique in its consistent treatment of factors affecting water resources and water requirements. Irrigation demand, for example, is driven by the same climatic conditions that drive evapotranspiration in natural systems and runoff, and future scenarios of water demand for power plant cooling are consistent with energy scenarios driving climate change. To illustrate the modeling system we select "wet" and "dry" patterns of precipitation for the United States from general circulation models used in the Climate Model Intercomparison Project (CMIP3). Results suggest that population and economic growth alone would increase water stress in the United States through mid-century. Climate change generally increases water stress with the largest increases in the Southwest. By identifying areas of potential stress in the absence of specific adaptation responses, the modeling system can help direct attention to water planning that might then limit use or add storage in potentially stressed regions, while illustrating how avoiding climate change through mitigation could change likely outcomes.

Decomposition of the complex system into nonlinear spatio-temporal modes: algorithm and application to climate data mining

NASA Astrophysics Data System (ADS)

Feigin, Alexander; Gavrilov, Andrey; Loskutov, Evgeny; Mukhin, Dmitry

2015-04-01

Proper decomposition of the complex system into well separated "modes" is a way to reveal and understand the mechanisms governing the system behaviour as well as discover essential feedbacks and nonlinearities. The decomposition is also natural procedure that provides to construct adequate and concurrently simplest models of both corresponding sub-systems, and of the system in whole. In recent works two new methods of decomposition of the Earth's climate system into well separated modes were discussed. The first method [1-3] is based on the MSSA (Multichannel Singular Spectral Analysis) [4] for linear expanding vector (space-distributed) time series and makes allowance delayed correlations of the processes recorded in spatially separated points. The second one [5-7] allows to construct nonlinear dynamic modes, but neglects delay of correlations. It was demonstrated [1-3] that first method provides effective separation of different time scales, but prevent from correct reduction of data dimension: slope of variance spectrum of spatio-temporal empirical orthogonal functions that are "structural material" for linear spatio-temporal modes, is too flat. The second method overcomes this problem: variance spectrum of nonlinear modes falls essentially sharply [5-7]. However neglecting time-lag correlations brings error of mode selection that is uncontrolled and increases with growth of mode time scale. In the report we combine these two methods in such a way that the developed algorithm allows constructing nonlinear spatio-temporal modes. The algorithm is applied for decomposition of (i) multi hundreds years globally distributed data generated by the INM RAS Coupled Climate Model [8], and (ii) 156 years time series of SST anomalies distributed over the globe [9]. We compare efficiency of different methods of decomposition and discuss the abilities of nonlinear spatio-temporal modes for construction of adequate and concurrently simplest ("optimal") models of climate systems. 1. Feigin A.M., Mukhin D., Gavrilov A., Volodin E.M., and Loskutov E.M. (2013) "Separation of spatial-temporal patterns ("climatic modes") by combined analysis of really measured and generated numerically vector time series", AGU 2013 Fall Meeting, Abstract NG33A-1574. 2. Alexander Feigin, Dmitry Mukhin, Andrey Gavrilov, Evgeny Volodin, and Evgeny Loskutov (2014) "Approach to analysis of multiscale space-distributed time series: separation of spatio-temporal modes with essentially different time scales", Geophysical Research Abstracts, Vol. 16, EGU2014-6877. 3. Dmitry Mukhin, Dmitri Kondrashov, Evgeny Loskutov, Andrey Gavrilov, Alexander Feigin, and Michael Ghil (2014) "Predicting critical transitions in ENSO models, Part II: Spatially dependent models", Journal of Climate (accepted, doi: 10.1175/JCLI-D-14-00240.1). 4. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 5. Dmitry Mukhin, Andrey Gavrilov, Evgeny M Loskutov and Alexander M Feigin (2014) "Nonlinear Decomposition of Climate Data: a New Method for Reconstruction of Dynamical Modes", AGU 2014 Fall Meeting, Abstract NG43A-3752. 6. Andrey Gavrilov, Dmitry Mukhin, Evgeny Loskutov, and Alexander Feigin (2015) "Empirical decomposition of climate data into nonlinear dynamic modes", Geophysical Research Abstracts, Vol. 17, EGU2015-627. 7. Dmitry Mukhin, Andrey Gavrilov, Evgeny Loskutov, Alexander Feigin, and Juergen Kurths (2015) "Reconstruction of principal dynamical modes from climatic variability: nonlinear approach", Geophysical Research Abstracts, Vol. 17, EGU2015-5729. 8. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm. 9. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/.

Extreme climatic events change the dynamics and invasibility of semi-arid annual plant communities.

PubMed

Jiménez, Milagros A; Jaksic, Fabian M; Armesto, Juan J; Gaxiola, Aurora; Meserve, Peter L; Kelt, Douglas A; Gutiérrez, Julio R

2011-12-01

Extreme climatic events represent disturbances that change the availability of resources. We studied their effects on annual plant assemblages in a semi-arid ecosystem in north-central Chile. We analysed 130 years of precipitation data using generalised extreme-value distribution to determine extreme events, and multivariate techniques to analyse 20 years of plant cover data of 34 native and 11 exotic species. Extreme drought resets the dynamics of the system and renders it susceptible to invasion. On the other hand, by favouring native annuals, moderately wet events change species composition and allow the community to be resilient to extreme drought. The probability of extreme drought has doubled over the last 50 years. Therefore, investigations on the interaction of climate change and biological invasions are relevant to determine the potential for future effects on the dynamics of semi-arid annual plant communities. 2011 Blackwell Publishing Ltd/CNRS.

Potential impacts of climate change on carbon dynamics in a rain-fed agro-ecosystem on the Loess Plateau of China.

PubMed

Qiu, Linjing; Hao, Mingde; Wu, Yiping

2017-01-15

Although many studies have been conducted on crop yield in rain-fed agriculture, the possible impacts of climate change on the carbon (C) dynamics of rain-fed rotation systems, particularly their direction and magnitude at the long-term scale, are still poorly understood. In this study, the sensitivity of C dynamics of a typical rotation system to elevated CO 2 and changed temperature and precipitation were first tested using the CENTURY model, based on data collected from a 30-year field experiment of a corn-wheat-wheat-millet (CWWM) rotation system in the tableland of the Loess Plateau. The possible responses of crop biomass C and soil organic C (SOC) accumulation were then evaluated under scenarios representing the Representative Concentration Pathways (RCPs) 4.5 and 8.5. The results indicated that elevated CO 2 and increased precipitation exerted positive effect on biomass C in CWWM rotation system, while increasing the temperature by 1°C, 2°C and 4°C had negative effects on biomass C due to opposite responses of corn and winter wheat to warming. SOC accumulation was enhanced by increased CO 2 concentration and precipitation but impaired by increased temperature. Under future RCP scenarios with dynamic CO 2 , the biomass C of corn exhibited decrease during the period of 2046-2075 under RCP4.5 and the period of 2016-2075 under RCP8.5 due to reduced precipitation and a warmer climate. In contrast, winter wheat would benefit from increased CO 2 and temperature and was projected to have larger biomass C under both RCP scenarios. Although the climate condition had large differences between RCP4.5 and RCP8.5, the projected SOC had similar trends under two scenarios due to CO 2 fertilizer effect and precipitation fluctuation. These results implied that crop biomass C and SOC accumulation in a warmer environment are strongly related to precipitation, and increase in field water storage should be emphasized in coping with future climate. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

The changing global carbon cycle: Linking plant-soil carbon dynamics to global consequences

USGS Publications Warehouse

Chapin, F. S.; McFarland, J.; McGuire, David A.; Euskirchen, E.S.; Ruess, Roger W.; Kielland, K.

2009-01-01

Synthesis. Current climate systems models that include only NPP and HR are inadequate under conditions of rapid change. Many of the recent advances in biogeochemical understanding are sufficiently mature to substantially improve representation of ecosystem C dynamics in these models.

Potential climate change impacts on water availability and cooling water demand in the Lusatian Lignite Mining Region, Central Europe

NASA Astrophysics Data System (ADS)

Pohle, Ina; Koch, Hagen; Gädeke, Anne; Grünewald, Uwe; Kaltofen, Michael; Redetzky, Michael

2014-05-01

In the catchments of the rivers Schwarze Elster, Spree and Lusatian Neisse, hydrologic and socioeconomic systems are coupled via a complex water management system in which water users, reservoirs and water transfers are included. Lignite mining and electricity production are major water users in the region: To allow for open pit lignite mining, ground water is depleted and released into the river system while cooling water is used in the thermal power plants. In order to assess potential climate change impacts on water availability in the catchments as well as on the water demand of the thermal power plants, a climate change impact assessment was performed using the hydrological model SWIM and the long term water management model WBalMo. The potential impacts of climate change were considered by using three regional climate change scenarios of the statistical regional climate model STAR assuming a further temperature increase of 0, 2 or 3 K by the year 2050 in the region respectively. Furthermore, scenarios assuming decreasing mining activities in terms of a decreasing groundwater depression cone, lower mining water discharges, and reduced cooling water demand of the thermal power plants are considered. In the standard version of the WBalMo model cooling water demand is considered as static with regard to climate variables. However, changes in the future cooling water demand over time according to the plans of the local mining and power plant operator are considered. In order to account for climate change impacts on the cooling water demand of the thermal power plants, a dynamical approach for calculating water demand was implemented in WBalMo. As this approach is based on air temperature and air humidity, the projected air temperature and air humidity of the climate scenarios at the locations of the power plants are included in the calculation. Due to increasing temperature and decreasing precipitation declining natural and managed discharges, and hence a lower water availability in the region, were simulated by SWIM and WBalMo respectively. Next to changing climate conditions, also the different mining scenarios have considerable impacts on natural and managed discharges. Using the dynamic approach for cooling water demand, the simulated water demands are lower in winter, but higher in summer compared to the static approach. As a consequence of changes in the seasonal pattern of the cooling water demand of the power plants, lower summer discharges downstream of the thermal power plants are simulated using the dynamical approach. Due to the complex water management system in the region included in the water management model WBalMo, also the simulation of reservoir releases and volumes is impacted by the choice of either the static or the dynamic approach for calculating the cooling water demand of the thermal power plants.

Climate and dengue transmission: evidence and implications.

PubMed

Morin, Cory W; Comrie, Andrew C; Ernst, Kacey

2013-01-01

Climate influences dengue ecology by affecting vector dynamics, agent development, and mosquito/human interactions. Although these relationships are known, the impact climate change will have on transmission is unclear. Climate-driven statistical and process-based models are being used to refine our knowledge of these relationships and predict the effects of projected climate change on dengue fever occurrence, but results have been inconsistent. We sought to identify major climatic influences on dengue virus ecology and to evaluate the ability of climate-based dengue models to describe associations between climate and dengue, simulate outbreaks, and project the impacts of climate change. We reviewed the evidence for direct and indirect relationships between climate and dengue generated from laboratory studies, field studies, and statistical analyses of associations between vectors, dengue fever incidence, and climate conditions. We assessed the potential contribution of climate-driven, process-based dengue models and provide suggestions to improve their performance. Relationships between climate variables and factors that influence dengue transmission are complex. A climate variable may increase dengue transmission potential through one aspect of the system while simultaneously decreasing transmission potential through another. This complexity may at least partly explain inconsistencies in statistical associations between dengue and climate. Process-based models can account for the complex dynamics but often omit important aspects of dengue ecology, notably virus development and host-species interactions. Synthesizing and applying current knowledge of climatic effects on all aspects of dengue virus ecology will help direct future research and enable better projections of climate change effects on dengue incidence.

Evaluating the utility of dynamical downscaling in agricultural impacts projections

PubMed Central

Glotter, Michael; Elliott, Joshua; McInerney, David; Best, Neil; Foster, Ian; Moyer, Elisabeth J.

2014-01-01

Interest in estimating the potential socioeconomic costs of climate change has led to the increasing use of dynamical downscaling—nested modeling in which regional climate models (RCMs) are driven with general circulation model (GCM) output—to produce fine-spatial-scale climate projections for impacts assessments. We evaluate here whether this computationally intensive approach significantly alters projections of agricultural yield, one of the greatest concerns under climate change. Our results suggest that it does not. We simulate US maize yields under current and future CO2 concentrations with the widely used Decision Support System for Agrotechnology Transfer crop model, driven by a variety of climate inputs including two GCMs, each in turn downscaled by two RCMs. We find that no climate model output can reproduce yields driven by observed climate unless a bias correction is first applied. Once a bias correction is applied, GCM- and RCM-driven US maize yields are essentially indistinguishable in all scenarios (<10% discrepancy, equivalent to error from observations). Although RCMs correct some GCM biases related to fine-scale geographic features, errors in yield are dominated by broad-scale (100s of kilometers) GCM systematic errors that RCMs cannot compensate for. These results support previous suggestions that the benefits for impacts assessments of dynamically downscaling raw GCM output may not be sufficient to justify its computational demands. Progress on fidelity of yield projections may benefit more from continuing efforts to understand and minimize systematic error in underlying climate projections. PMID:24872455

Climate simulation of the twenty-first century with interactive land-use changes

NASA Astrophysics Data System (ADS)

Voldoire, Aurore; Eickhout, Bas; Schaeffer, Michiel; Royer, Jean-François; Chauvin, Fabrice

2007-08-01

To include land-use dynamics in a general circulation model (GCM), the physical system has to be linked to a system that represents socio-economy. This issue is addressed by coupling an integrated assessment model, IMAGE2.2, to an ocean atmosphere GCM, CNRM-CM3. In the new system, IMAGE2.2 provides CNRM-CM3 with all the external forcings that are scenario dependent: greenhouse gas (GHGs) concentrations, sulfate aerosols charge and land cover. Conversely, the GCM gives IMAGE changes in mean temperature and precipitation. With this new system, we have run an adapted scenario of the IPCC SRES scenario family. We have chosen a single scenario with maximum land-use changes (SRES A2), to illustrate some important feedback issues. Even in this two-way coupled model set-up, land use in this scenario is mainly driven by demographic and agricultural practices, which overpowers a potential influence of climate feedbacks on land-use patterns. This suggests that for scenarios in which socio-economically driven land-use change is very large, land-use changes can be incorporated in GCM simulations as a one-way driving force, without taking into account climate feedbacks. The dynamics of natural vegetation is more closely linked to climate but the time-scale of changes is of the order of a century. Thus, the coupling between natural vegetation and climate could generate important feedbacks but these effects are relevant mainly for multi-centennial simulations.

Data-driven Climate Modeling and Prediction

NASA Astrophysics Data System (ADS)

Kondrashov, D. A.; Chekroun, M.

2016-12-01

Global climate models aim to simulate a broad range of spatio-temporal scales of climate variability with state vector having many millions of degrees of freedom. On the other hand, while detailed weather prediction out to a few days requires high numerical resolution, it is fairly clear that a major fraction of large-scale climate variability can be predicted in a much lower-dimensional phase space. Low-dimensional models can simulate and predict this fraction of climate variability, provided they are able to account for linear and nonlinear interactions between the modes representing large scales of climate dynamics, as well as their interactions with a much larger number of modes representing fast and small scales. This presentation will highlight several new applications by Multilayered Stochastic Modeling (MSM) [Kondrashov, Chekroun and Ghil, 2015] framework that has abundantly proven its efficiency in the modeling and real-time forecasting of various climate phenomena. MSM is a data-driven inverse modeling technique that aims to obtain a low-order nonlinear system of prognostic equations driven by stochastic forcing, and estimates both the dynamical operator and the properties of the driving noise from multivariate time series of observations or a high-end model's simulation. MSM leads to a system of stochastic differential equations (SDEs) involving hidden (auxiliary) variables of fast-small scales ranked by layers, which interact with the macroscopic (observed) variables of large-slow scales to model the dynamics of the latter, and thus convey memory effects. New MSM climate applications focus on development of computationally efficient low-order models by using data-adaptive decomposition methods that convey memory effects by time-embedding techniques, such as Multichannel Singular Spectrum Analysis (M-SSA) [Ghil et al. 2002] and recently developed Data-Adaptive Harmonic (DAH) decomposition method [Chekroun and Kondrashov, 2016]. In particular, new results by DAH-MSM modeling and prediction of Arctic Sea Ice, as well as decadal predictions of near-surface Earth temperatures will be presented.

Adapting regional watershed management to climate change in Bavaria and Québec

NASA Astrophysics Data System (ADS)

Ludwig, Ralf; Muerth, Markus; Schmid, Josef; Jobst, Andreas; Caya, Daniel; Gauvin St-Denis, Blaise; Chaumont, Diane; Velazquez, Juan-Alberto; Turcotte, Richard; Ricard, Simon

2013-04-01

The international research project QBic3 (Quebec-Bavarian Collaboration on Climate Change) aims at investigating the potential impacts of climate change on the hydrology of regional scale catchments in Southern Quebec (Canada) and Bavaria (Germany). For this purpose, a hydro-meteorological modeling chain has been established, applying climatic forcing from both dynamical and statistical climate model data to an ensemble of hydrological models of varying complexity. The selection of input data, process descriptions and scenarios allows for the inter-comparison of the uncertainty ranges on selected runoff indicators; a methodology to display the relative importance of each source of uncertainty is developed and results for past runoff (1971-2000) and potential future changes (2041-2070) are obtained. Finally, the impact of hydrological changes on the operational management of dams, reservoirs and transfer systems is investigated and shown for the Bavarian case studies, namely the potential change in i) hydro-power production for the Upper Isar watershed and ii) low flow augmentation and water transfer rates at the Donau-Main transfer system in Central Franconia. Two overall findings will be presented and discussed in detail: a) the climate change response of selected hydrological indicators, especially those related to low flows, is strongly affected by the choice of the hydrological model. It can be shown that an assessment of the changes in the hydrological cycle is best represented by a complex physically based hydrological model, computationally less demanding models (usually simple, lumped and conceptual) can give a significant level of trust for selected indicators. b) the major differences in the projected climate forcing stemming from the ensemble of dynamic climate models (GCM/RCM) versus the statistical-stochastical WETTREG2010 approach. While the dynamic ensemble reveals a moderate modification of the hydrological processes in the investigated catchments, the WETTREG2010 driven runs show a severe detraction for all water operations, mainly related to a strong decline in projected precipitation in all seasons (except winter).

Progress in Earth System Modeling since the ENIAC Calculation

NASA Astrophysics Data System (ADS)

Fung, I.

2009-05-01

The success of the first numerical weather prediction experiment on the ENIAC computer in 1950 was hinged on the expansion of the meteorological observing network, which led to theoretical advances in atmospheric dynamics and subsequently the implementation of the simplified equations on the computer. This paper briefly reviews the progress in Earth System Modeling and climate observations, and suggests a strategy to sustain and expand the observations needed to advance climate science and prediction.

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

Duane, Greg; Tsonis, Anastasios; Kocarev, Ljupco

This collaborative reserach has several components but the main idea is that when imperfect copies of a given nonlinear dynamical system are coupled, they may synchronize for some set of coupling parameters. This idea is to be tested for several IPCC-like models each one with its own formulation and representing an “imperfect” copy of the true climate system. By computing the coupling parameters, which will lead the models to a synchronized state, a consensus on climate change simulations may be achieved.

Sustainability of socio-hydro system with changing value and preference to an uncertain future climate and economic conditions.

NASA Astrophysics Data System (ADS)

Roobavannan, Mahendran; Kandasamy, Jaya; Vigneswaran, Saravanamuththu; Sivapalan, Murugesu

2016-04-01

Water-human systems are coupled and display co-evolutionary dynamics influenced by society's values and preference. This has been observed in the Murrumbidgee basin, Australia where water usage initially focused on agriculture production and until mid-1990's favoured agriculture. This turned around as society became more concerned about the degradation of ecosystems and ultimately water was reallocated back towards the environment. This new water management adversely impacted the agriculture sector and created economic stress in the basin. The basin communities were able to transform and cope with water allocation favouring the environment through sectoral transformation facilitated by movement of capital in a free economy, supported by appropriate strategies and funding. This was helped by the adaptive capacity of people through reemployment in other economic sectors of the basin economy, unemployment for a period of time and migration out of the basin, and crop diversification. This study looks to the future and focuses on how water managers could be informed and prepare for un-foreseen issues coming out of societies changing values and preferences and emerging as different systems in the basin interact with each other at different times and speed. The issues of this type that concern the Murray Darling Basin Authority include a renewed focus and priority on food production due to food scarcity; increased impact and frequency of natural disasters (eg. climate change); regional economic diversification due to the growth of peri-urban development in the basin; institutional capacity for water reform due to new political paradigms (eg. new water sharing plans); and improvement in science and technology (eg. farm practices, water efficiency, water reuse). To undertake this, the study uses a coupled socio-hydrological dynamical system that model the major drivers of changing economic conditions, society values and preference, climatic condition and science and technology. The dynamical system is represented by a suite of differential equations that can evolve with time. The mathematical property (Eigen values and vectors) of complex dynamical system is used to understand the system dynamics and look for signs of system collapse. Bifurcation analysis of the dynamical system defines the limits of different model parameters (safe zone) where system collapse is avoided and to maintain a sustainable society. The safe zone is interpreted in a manner that allows water managers to understand the possible ways of influencing the water-human system and understanding the consequences. Keywords: socio-hydrology, value and preference, dynamical system modelling, water management.

A Bottom-up Vulnerability Analysis of Water Systems with Decentralized Decision Making and Demographic Shifts- the Case of Jordan.

NASA Astrophysics Data System (ADS)

Lachaut, T.; Yoon, J.; Klassert, C. J. A.; Talozi, S.; Mustafa, D.; Knox, S.; Selby, P. D.; Haddad, Y.; Gorelick, S.; Tilmant, A.

2016-12-01

Probabilistic approaches to uncertainty in water systems management can face challenges of several types: non stationary climate, sudden shocks such as conflict-driven migrations, or the internal complexity and dynamics of large systems. There has been a rising trend in the development of bottom-up methods that place focus on the decision side instead of probability distributions and climate scenarios. These approaches are based on defining acceptability thresholds for the decision makers and considering the entire range of possibilities over which such thresholds are crossed. We aim at improving the knowledge on the applicability and relevance of this approach by enlarging its scope beyond climate uncertainty and single decision makers; thus including demographic shifts, internal system dynamics, and multiple stakeholders at different scales. This vulnerability analysis is part of the Jordan Water Project and makes use of an ambitious multi-agent model developed by its teams with the extensive cooperation of the Ministry of Water and Irrigation of Jordan. The case of Jordan is a relevant example for migration spikes, rapid social changes, resource depletion and climate change impacts. The multi-agent modeling framework used provides a consistent structure to assess the vulnerability of complex water resources systems with distributed acceptability thresholds and stakeholder interaction. A proof of concept and preliminary results are presented for a non-probabilistic vulnerability analysis that involves different types of stakeholders, uncertainties other than climatic and the integration of threshold-based indicators. For each stakeholder (agent) a vulnerability matrix is constructed over a multi-dimensional domain, which includes various hydrologic and/or demographic variables.

Development and application of earth system models

PubMed Central

Prinn, Ronald G.

2013-01-01

The global environment is a complex and dynamic system. Earth system modeling is needed to help understand changes in interacting subsystems, elucidate the influence of human activities, and explore possible future changes. Integrated assessment of environment and human development is arguably the most difficult and most important “systems” problem faced. To illustrate this approach, we present results from the integrated global system model (IGSM), which consists of coupled submodels addressing economic development, atmospheric chemistry, climate dynamics, and ecosystem processes. An uncertainty analysis implies that without mitigation policies, the global average surface temperature may rise between 3.5 °C and 7.4 °C from 1981–2000 to 2091–2100 (90% confidence limits). Polar temperatures, absent policy, are projected to rise from about 6.4 °C to 14 °C (90% confidence limits). Similar analysis of four increasingly stringent climate mitigation policy cases involving stabilization of greenhouse gases at various levels indicates that the greatest effect of these policies is to lower the probability of extreme changes. The IGSM is also used to elucidate potential unintended environmental consequences of renewable energy at large scales. There are significant reasons for attention to climate adaptation in addition to climate mitigation that earth system models can help inform. These models can also be applied to evaluate whether “climate engineering” is a viable option or a dangerous diversion. We must prepare young people to address this issue: The problem of preserving a habitable planet will engage present and future generations. Scientists must improve communication if research is to inform the public and policy makers better. PMID:22706645

Modelling interactions between mitigation, adaptation and sustainable development

NASA Astrophysics Data System (ADS)

Reusser, D. E.; Siabatto, F. A. P.; Garcia Cantu Ros, A.; Pape, C.; Lissner, T.; Kropp, J. P.

2012-04-01

Managing the interdependence of climate mitigation, adaptation and sustainable development requires a good understanding of the dominant socioecological processes that have determined the pathways in the past. Key variables include water and food availability which depend on climate and overall ecosystem services, as well as energy supply and social, political and economic conditions. We present our initial steps to build a system dynamic model of nations that represents a minimal set of relevant variables of the socio- ecological development. The ultimate goal of the modelling exercise is to derive possible future scenarios and test those for their compatibility with sustainability boundaries. Where dynamics go beyond sustainability boundaries intervention points in the dynamics can be searched.

The Monash University Interactive Simple Climate Model

NASA Astrophysics Data System (ADS)

Dommenget, D.

2013-12-01

The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.

A reconstruction of global hydroclimate and dynamical variables over the Common Era.

PubMed

Steiger, Nathan J; Smerdon, Jason E; Cook, Edward R; Cook, Benjamin I

2018-05-22

Hydroclimate extremes critically affect human and natural systems, but there remain many unanswered questions about their causes and how to interpret their dynamics in the past and in climate change projections. These uncertainties are due, in part, to the lack of long-term, spatially resolved hydroclimate reconstructions and information on the underlying physical drivers for many regions. Here we present the first global reconstructions of hydroclimate and associated climate dynamical variables over the past two thousand years. We use a data assimilation approach tailored to reconstruct hydroclimate that optimally combines 2,978 paleoclimate proxy-data time series with the physical constraints of an atmosphere-ocean climate model. The global reconstructions are annually or seasonally resolved and include two spatiotemporal drought indices, near-surface air temperature, an index of North Atlantic variability, the location of the intertropical convergence zone, and monthly Niño indices. This database, called the Paleo Hydrodynamics Data Assimilation product (PHYDA), will provide a critical new platform for investigating the causes of past climate variability and extremes, while informing interpretations of future hydroclimate projections.

A dynamic, climate-driven model of Rift Valley fever.

PubMed

Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P

2016-03-31

Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.

Integration of Linear Dynamic Emission and Climate Models with Air Traffic Simulations

NASA Technical Reports Server (NTRS)

Sridhar, Banavar; Ng, Hok K.; Chen, Neil Y.

2012-01-01

Future air traffic management systems are required to balance the conflicting objectives of maximizing safety and efficiency of traffic flows while minimizing the climate impact of aviation emissions and contrails. Integrating emission and climate models together with air traffic simulations improve the understanding of the complex interaction between the physical climate system, carbon and other greenhouse gas emissions and aviation activity. This paper integrates a national-level air traffic simulation and optimization capability with simple climate models and carbon cycle models, and climate metrics to assess the impact of aviation on climate. The capability can be used to make trade-offs between extra fuel cost and reduction in global surface temperature change. The parameters in the simulation can be used to evaluate the effect of various uncertainties in emission models and contrails and the impact of different decision horizons. Alternatively, the optimization results from the simulation can be used as inputs to other tools that monetize global climate impacts like the FAA s Aviation Environmental Portfolio Management Tool for Impacts.

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.

Agroclimate.Org: Tools and Information for a Climate Resilient Agriculture in the Southeast USA

NASA Astrophysics Data System (ADS)

Fraisse, C.

2014-12-01

AgroClimate (http://agroclimate.org) is a web-based system developed to help the agricultural industry in the southeastern USA reduce risks associated with climate variability and change. It includes climate related information and dynamic application tools that interact with a climate and crop database system. Information available includes climate monitoring and forecasts combined with information about crop management practices that help increase the resiliency of the agricultural industry in the region. Recently we have included smartphone apps in the AgroClimate suite of tools, including irrigation management and crop disease alert systems. Decision support tools available in AgroClimate include: (a) Climate risk: expected (probabilistic) and historical climate information and freeze risk; (b) Crop yield risk: expected yield based on soil type, planting date, and basic management practices for selected commodities and historical county yield databases; (c) Crop diseases: disease risk monitoring and forecasting for strawberry and citrus; (d) Crop development: monitoring and forecasting of growing degree-days and chill accumulation; (e) Drought: monitoring and forecasting of selected drought indices, (f) Footprints: Carbon and water footprint calculators. The system also provides background information about the main drivers of climate variability and basic information about climate change in the Southeast USA. AgroClimate has been widely used as an educational tool by the Cooperative Extension Services in the region and also by producers. It is now being replicated internationally with version implemented in Mozambique and Paraguay.

The Effects of Ecoregion Dynamics on Agroregions for Permanent Crops in the Continental US Under Future Climate Change Scenarios

NASA Astrophysics Data System (ADS)

Maddalena, D. M.; L'Heureux, J.; Hoffman, F. M.

2017-12-01

Fruit and Tree Nut production in the US averaged 14% of total annual production, or roughly $28 billion in total revenue for the most recent 5 year period (2011 - 2015). The success of these crops is highly dependent on environmental conditions. Cold snaps before winter dormancy, early frosts in spring, and lack of sufficient chilling hours can reduce productivity, inflict wood damage, and lead to economic loss. Climate change can increase the likelihood of these threats and may have long-term implications for the areas where these crops are grown due to the migration of ecoregions as climate patters shift. We delineate ecoregions using multi-attribute spatio-temporal clustering and calculate chilling unit accumulation under past, present, and future climate scenarios using measured and modeled data. These results are then compared to current agroregions in the US to calculate risk dynamics, potential economic loss, and to map future agroregion scenarios. Our results offer considerations for food system sustainability under a shifting climate.

Climate Sensitivity of the Community Climate System Model, Version 4

DOE PAGES

Bitz, Cecilia M.; Shell, K. M.; Gent, P. R.; ...

2012-05-01

Equilibrium climate sensitivity of the Community Climate System Model Version 4 (CCSM4) is 3.20°C for 1° horizontal resolution in each component. This is about a half degree Celsius higher than in the previous version (CCSM3). The transient climate sensitivity of CCSM4 at 1° resolution is 1.72°C, which is about 0.2°C higher than in CCSM3. These higher climate sensitivities in CCSM4 cannot be explained by the change to a preindustrial baseline climate. We use the radiative kernel technique to show that from CCSM3 to CCSM4, the global mean lapse-rate feedback declines in magnitude, and the shortwave cloud feedback increases. These twomore » warming effects are partially canceled by cooling due to slight decreases in the global mean water-vapor feedback and longwave cloud feedback from CCSM3 to CCSM4. A new formulation of the mixed-layer, slab ocean model in CCSM4 attempts to reproduce the SST and sea ice climatology from an integration with a full-depth ocean, and it is integrated with a dynamic sea ice model. These new features allow an isolation of the influence of ocean dynamical changes on the climate response when comparing integrations with the slab ocean and full-depth ocean. The transient climate response of the full-depth ocean version is 0.54 of the equilibrium climate sensitivity when estimated with the new slab ocean model version for both CCSM3 and CCSM4. We argue the ratio is the same in both versions because they have about the same zonal mean pattern of change in ocean surface heat flux, which broadly resembles the zonal mean pattern of net feedback strength.« less

Using SMAP data to improve drought early warning over the US Great Plains

NASA Astrophysics Data System (ADS)

Fu, R.; Fernando, N.; Tang, W.

2015-12-01

A drought prone region such as the Great Plains of the United States (US GP) requires credible and actionable drought early warning. Such information cannot simply be extracted from available climate forecasts because of their large uncertainties at regional scales, and unclear connections to the needs of the decision makers. In particular, current dynamic seasonal predictions and climate projections, such as those produced by the NOAA North American Multi-Model Ensemble experiment (NMME) are much more reliable for winter and spring than for the summer season for the US GP. To mitigate the weaknesses of dynamic prediction/projections, we have identified three key processes behind the spring-to-summer dry memory through observational studies, as the scientific basis for a statistical drought early warning system. This system uses percentile soil moisture anomalies in spring as a key input to provide a probabilistic summer drought early warning. The latter outperforms the dynamic prediction over the US Southern Plains and has been used by the Texas state water agency to support state drought preparedness. A main source of uncertainty for this drought early warning system is the soil moisture input obtained from the NOAA Climate Forecasting System (CFS). We are testing use of the beta version of NASA Soil Moisture Active Passive (SMAP) soil moisture data, along with the Soil Moisture and Ocean Salinity (SMOS), and the long-term Essential Climate Variable Soil Moisture (ECV-SM) soil moisture data, to reduce this uncertainty. Preliminary results based on ECV-SM suggests satellite based soil moisture data could improve early warning of rainfall anomalies over the western US GP with less dense vegetation. The skill degrades over the eastern US GP where denser vegetation is found. We evaluate our SMAP-based drought early warning for 2015 summer against observations.

Graceful Failure and Societal Resilience Analysis Via Agent-Based Modeling and Simulation

NASA Astrophysics Data System (ADS)

Schopf, P. S.; Cioffi-Revilla, C.; Rogers, J. D.; Bassett, J.; Hailegiorgis, A. B.

2014-12-01

Agent-based social modeling is opening up new methodologies for the study of societal response to weather and climate hazards, and providing measures of resiliency that can be studied in many contexts, particularly in coupled human and natural-technological systems (CHANTS). Since CHANTS are complex adaptive systems, societal resiliency may or may not occur, depending on dynamics that lack closed form solutions. Agent-based modeling has been shown to provide a viable theoretical and methodological approach for analyzing and understanding disasters and societal resiliency in CHANTS. Our approach advances the science of societal resilience through computational modeling and simulation methods that complement earlier statistical and mathematical approaches. We present three case studies of social dynamics modeling that demonstrate the use of these agent based models. In Central Asia, we exmaine mutltiple ensemble simulations with varying climate statistics to see how droughts and zuds affect populations, transmission of wealth across generations, and the overall structure of the social system. In Eastern Africa, we explore how successive episodes of drought events affect the adaptive capacity of rural households. Human displacement, mainly, rural to urban migration, and livelihood transition particularly from pastoral to farming are observed as rural households interacting dynamically with the biophysical environment and continually adjust their behavior to accommodate changes in climate. In the far north case we demonstrate one of the first successful attempts to model the complete climate-permafrost-infrastructure-societal interaction network as a complex adaptive system/CHANTS implemented as a ``federated'' agent-based model using evolutionary computation. Analysis of population changes resulting from extreme weather across these and other cases provides evidence for the emergence of new steady states and shifting patterns of resilience.

The influence of climate on peatland extent in Western Siberia since the Last Glacial Maximum

PubMed Central

Alexandrov, G. A.; Brovkin, V. A.; Kleinen, T.

2016-01-01

Boreal and subarctic peatlands are an important dynamical component of the earth system. They are sensitive to climate change, and could either continue to serve as a carbon sink or become a carbon source. Climatic thresholds for switching peatlands from sink to source are not well defined, and therefore, incorporating peatlands into Earth system models is a challenging task. Here we introduce a climatic index, warm precipitation excess, to delineate the potential geographic distribution of boreal peatlands for a given climate and landscape morphology. This allows us to explain the present-day distribution of peatlands in Western Siberia, their absence during the Last Glacial Maximum, their expansion during the mid-Holocene, and to form a working hypothesis about the trend to peatland degradation in the southern taiga belt of Western Siberia under an RCP 8.5 scenario for the projected climate in year 2100. PMID:27095029

The influence of climate on peatland extent in Western Siberia since the Last Glacial Maximum.

PubMed

Alexandrov, G A; Brovkin, V A; Kleinen, T

2016-04-20

Boreal and subarctic peatlands are an important dynamical component of the earth system. They are sensitive to climate change, and could either continue to serve as a carbon sink or become a carbon source. Climatic thresholds for switching peatlands from sink to source are not well defined, and therefore, incorporating peatlands into Earth system models is a challenging task. Here we introduce a climatic index, warm precipitation excess, to delineate the potential geographic distribution of boreal peatlands for a given climate and landscape morphology. This allows us to explain the present-day distribution of peatlands in Western Siberia, their absence during the Last Glacial Maximum, their expansion during the mid-Holocene, and to form a working hypothesis about the trend to peatland degradation in the southern taiga belt of Western Siberia under an RCP 8.5 scenario for the projected climate in year 2100.

Ocean Data Assimilation in Support of Climate Applications: Status and Perspectives.

PubMed

Stammer, D; Balmaseda, M; Heimbach, P; Köhl, A; Weaver, A

2016-01-01

Ocean data assimilation brings together observations with known dynamics encapsulated in a circulation model to describe the time-varying ocean circulation. Its applications are manifold, ranging from marine and ecosystem forecasting to climate prediction and studies of the carbon cycle. Here, we address only climate applications, which range from improving our understanding of ocean circulation to estimating initial or boundary conditions and model parameters for ocean and climate forecasts. Because of differences in underlying methodologies, data assimilation products must be used judiciously and selected according to the specific purpose, as not all related inferences would be equally reliable. Further advances are expected from improved models and methods for estimating and representing error information in data assimilation systems. Ultimately, data assimilation into coupled climate system components is needed to support ocean and climate services. However, maintaining the infrastructure and expertise for sustained data assimilation remains challenging.

Hydro-climatic Changes: Potential Non-linear Responses of Phosphorus Dynamic in Aquatic/Semi-aquatic Systems

NASA Astrophysics Data System (ADS)

Pant, H. K.

2007-12-01

Depending on resilience, threshold and lag times, hydro-climatic changes can cause nonlinear and/or irreversible changes in phosphorus (P) dynamic, and instigate P enrichment in aquatic/semi-aquatic systems. Thus, studying direct/indirect effects of expected global climate change on bioavailability of organic P in aquatic systems are in critical need, to help manage or increase the resilience of the ecosystem. The central hypothesis of this study is that P dynamic in aquatic, especially freshwater, ecosystem is likely to behave nonlinearly due to expected changes in sediment and water acidity, redox status, etc., because of potential hydro-climatic changes in the decades to come, thus, could face irreversible adverse changes. Devising possible biological and chemical treatments for the removal of P from eutrophic lakes, estuaries, etc, as well as helping in predicting the movement and fate of P under changing hydro-climatic conditions would be crucial to manage aquatic ecosystem in the near future. The critical question is not how much P is stored in any given aquatic/semi-aquatic system, but how the resilience and nonlinearity relate to the stability of stored P are affected due to the levels of environmental stressors, which are expected to fluctuate due to global change in the decades to come. Studies related to 31P Nuclear Magnetic Resonance Spectroscopy analysis, and multiple hydraulic retention cycles showed that, in general, frequent drying and reflooding of a semi-aquatic system such as wetland could significantly increase the bioavailability of P due to degradation of relatively less stable organic P, e.g., glycerophosphate and nucleoside monophosphate. Moreover, nutrients flux from sediments to the water column depended on the concentration gradients of the sediment-water interface and redox status. Shift in equilibrium P concentration of the water column as the water level rises, may cause release of adsorbed P from the sediments. Restoration of a eutrophic system may involve stepwise efforts including control of catchment nutrient inputs, internal nutrient loading, and biomanipulation, however, flooding, previously non-flooded areas, could export massive amount of P to nearby aquatic bodies, in turn, may cause collapse of the ecosystem.

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.

Growing Land-Sea Temperature Contrast and the Intensification of Arctic Cyclones

NASA Astrophysics Data System (ADS)

Day, Jonathan J.; Hodges, Kevin I.

2018-04-01

Cyclones play an important role in the coupled dynamics of the Arctic climate system on a range of time scales. Modeling studies suggest that storminess will increase in Arctic summer due to enhanced land-sea thermal contrast along the Arctic coastline, in a region known as the Arctic Frontal Zone (AFZ). However, the climate models used in these studies are poor at reproducing the present-day Arctic summer cyclone climatology and so their projections of Arctic cyclones and related quantities, such as sea ice, may not be reliable. In this study we perform composite analysis of Arctic cyclone statistics using AFZ variability as an analog for climate change. High AFZ years are characterized both by increased cyclone frequency and dynamical intensity, compared to low years. Importantly, the size of the response in this analog suggests that General Circulation Models may underestimate the response of Arctic cyclones to climate change, given a similar change in baroclinicity.

Impacts of Climate Anomalies on the Vegetation Patterns in the Arid and Semi-Arid Zones of Uzbekistan

NASA Astrophysics Data System (ADS)

Dildora, Aralova; Toderich, Kristina; Dilshod, Gafurov

2016-08-01

Steadily rising temperature anomalies in last decades are causing changes in vegetation patterns for sensitive to climate change in arid and semi-arid dryland ecosystems. After desiccation of the Aral Sea, Uzbekistan has been left with the challenge to develop drought and heat stress monitoring system and tools (e.g., to monitor vegetation status and/crop pattern dynamics) with using remote sensing technologies in broad scale. This study examines several climate parameters, NDVI and drought indexes within geostatistical method to predict further vegetation status in arid and semi-arid zones of landscapes. This approaches aimed to extract and utilize certain variable environmental data (temperature and precipitation) for assessment and inter-linkages of vegetation cover dynamics, specifically related to predict degraded and recovered zones or desertification process in the drylands due to scarcity of water resources and high risks of climate anomalies in fragile ecosystem of Uzbekistan.

Potential impacts of climate change on the ecology of dengue and its mosquito vector the Asian tiger mosquito (Aedes albopictus)

NASA Astrophysics Data System (ADS)

Erickson, R. A.; Hayhoe, K.; Presley, S. M.; Allen, L. J. S.; Long, K. R.; Cox, S. B.

2012-09-01

Shifts in temperature and precipitation patterns caused by global climate change may have profound impacts on the ecology of certain infectious diseases. We examine the potential impacts of climate change on the transmission and maintenance dynamics of dengue, a resurging mosquito-vectored infectious disease. In particular, we project changes in dengue season length for three cities: Atlanta, GA; Chicago, IL and Lubbock, TX. These cities are located on the edges of the range of the Asian tiger mosquito within the United States of America and were chosen as test cases. We use a disease model that explicitly incorporates mosquito population dynamics and high-resolution climate projections. Based on projected changes under the Special Report on Emissions Scenarios (SRES) A1fi (higher) and B1 (lower) emission scenarios as simulated by four global climate models, we found that the projected warming shortened mosquito lifespan, which in turn decreased the potential dengue season. These results illustrate the difficulty in predicting how climate change may alter complex systems.

Forest production dynamics along a wood density spectrum in eastern US forests

Treesearch

C.W. Woodall; M.B. Russell; B.F. Walters; A.W. D' Amato; K. Zhu; S.S. Saatchi

2015-01-01

Emerging plant economics spectrum theories were confirmed across temperate forest systems of the eastern US where the use of a forest stand's mean wood density elucidated forest volume and biomass production dynamics integrating aspects of climate, tree mortality/growth, and rates of site occupancy.

Integrating legacy data to understand agroecosystem regional dynamics to catastrophic events

USDA-ARS?s Scientific Manuscript database

Multi-year extreme drought events are part of the history of the Earth system. Legacy data on the climate drivers, geomorphic features, and agroecosystem responses across a dynamically changing landscape throughout a region can provide important insights to a future where large-scale catastrophic ev...

Geodynamic contributions to global climatic change

NASA Technical Reports Server (NTRS)

Bills, Bruce G.

1992-01-01

Orbital and rotational variations perturb the latitudinal and seasonal pattern of incident solar radiation, producing major climatic change on time scales of 10(exp 4)-10(exp 6) years. The orbital variations are oblivious to internal structure and processes, but the rotational variations are not. A program of investigation whose objective would be to explore and quantify three aspects of orbital, rotational, and climatic interactions is described. An important premise of this investigation is the synergism between geodynamics and paleoclimate. Better geophysical models of precessional dynamics are needed in order to accurately reconstruct the radiative input to climate models. Some of the paleoclimate proxy records contain information relevant to solid Earth processes, on time scales which are difficult to constrain otherwise. Specific mechanisms which will be addressed include: (1) climatic consequences of deglacial polar motion; and (2) precessional and climatic consequences of glacially induced perturbations in the gravitational oblateness and partial decoupling of the mantle and core. The approach entails constructing theoretical models of the rotational, deformational, radiative, and climatic response of the Earth to known orbital perturbations, and comparing these with extensive records of paleoclimate proxy data. Several of the mechanisms of interest may participate in previously unrecognized feed-back loops in the climate dynamics system. A new algorithm for estimating climatically diagnostic locations and seasons from the paleoclimate time series is proposed.

Gaseous mercury fluxes in peatlands and the potential influence of climate change

Treesearch

Kristine M. Haynes; Evan S. Kane; Lynette Potvin; Erik A. Lilleskov; Randall K. Kolka; Carl P.J. Mitchell

2017-01-01

Climate change has the potential to significantly impact the stability of large stocks of mercury (Hg) stored in peatland systems due to increasing temperatures, altered water table regimes and subsequent shifts in vascular plant communities. However, the Hg exchange dynamics between the atmosphere and peatlands are not well understood. At the PEATcosm Mesocosm...

Future changes in coastal upwelling ecosystems with global warming: The case of the California Current System.

PubMed

Xiu, Peng; Chai, Fei; Curchitser, Enrique N; Castruccio, Frederic S

2018-02-12

Coastal upwelling ecosystems are among the most productive ecosystems in the world, meaning that their response to climate change is of critical importance. Our understanding of climate change impacts on marine ecosystems is largely limited to the open ocean, mainly because coastal upwelling is poorly reproduced by current earth system models. Here, a high-resolution model is used to examine the response of nutrients and plankton dynamics to future climate change in the California Current System (CCS). The results show increased upwelling intensity associated with stronger alongshore winds in the coastal region, and enhanced upper-ocean stratification in both the CCS and open ocean. Warming of the open ocean forces isotherms downwards, where they make contact with water masses with higher nutrient concentrations, thereby enhancing the nutrient flux to the deep source waters of the CCS. Increased winds and eddy activity further facilitate upward nutrient transport to the euphotic zone. However, the plankton community exhibits a complex and nonlinear response to increased nutrient input, as the food web dynamics tend to interact differently. This analysis highlights the difficulty in understanding how the marine ecosystem responds to a future warming climate, given to range of relevant processes operating at different scales.

Qualitative assessment of climate-driven ecological shifts in the Caspian Sea

PubMed Central

Beyraghdar Kashkooli, Omid; Gröger, Joachim; Núñez-Riboni, Ismael

2017-01-01

The worldwide occurrence of complex climate-induced ecological shifts in marine systems is one of the major challenges in sustainable bio-resources management. The occurrence of ecological environment-driven shifts was studied in the Southern Caspian Sea using the “shiftogram” method on available fisheries-related (i.e. commercially important bentho-pelagic fish stocks) ecological and climatic variables. As indicators of potential environmentally driven shift patterns we used indices for the North Atlantic Oscillation, the Southern Oscillation, the Siberian High, the East Atlantic-West Russia pattern, as well as Sea Surface Temperature and surface chlorophyll-a concentration. Given the explorative findings from the serial shift analyses, the cascading and serial order of multiple shift events in climatic-ecologic conditions of the southern Caspian Sea suggested a linkage between external forces and dynamics of ecosystem components and structures in the following order: global-scale climate forces lead to local environmental processes, which in turn lead to biological components dynamics. For the first time, this study indicates that ecological shifts are an integral component of bentho-pelagic subsystem regulatory processes and dynamics. Qualitative correspondence of biological responses of bentho-pelagic stocks to climatic events is one of the supporting evidences that overall Caspian ecosystem structures and functioning might have–at least partially–been impacted by global-scale climatic or local environmental shifts. These findings may help to foster a regional Ecosystem-based Approach to Management (EAM) as an integral part of bentho-pelagic fisheries management plans. PMID:28475609

Climate impacts on environmental risks evaluated from space: a conceptual approach to the case of Rift Valley Fever in Senegal.

PubMed

Tourre, Yves M; Lacaux, Jean-Pierre; Vignolles, Cécile; Lafaye, Murielle

2009-11-11

Climate and environment vary across many spatio-temporal scales, including the concept of climate change, which impact on ecosystems, vector-borne diseases and public health worldwide. To develop a conceptual approach by mapping climatic and environmental conditions from space and studying their linkages with Rift Valley Fever (RVF) epidemics in Senegal. Ponds in which mosquitoes could thrive were identified from remote sensing using high-resolution SPOT-5 satellite images. Additional data on pond dynamics and rainfall events (obtained from the Tropical Rainfall Measuring Mission) were combined with hydrological in-situ data. Localisation of vulnerable hosts such as penned cattle (from QuickBird satellite) were also used. Dynamic spatio-temporal distribution of Aedes vexans density (one of the main RVF vectors) is based on the total rainfall amount and ponds' dynamics. While Zones Potentially Occupied by Mosquitoes are mapped, detailed risk areas, i.e. zones where hazards and vulnerability occur, are expressed in percentages of areas where cattle are potentially exposed to mosquitoes' bites. This new conceptual approach, using precise remote-sensing techniques, simply relies upon rainfall distribution also evaluated from space. It is meant to contribute to the implementation of operational early warning systems for RVF based on both natural and anthropogenic climatic and environmental changes. In a climate change context, this approach could also be applied to other vector-borne diseases and places worldwide.

Evaluations of high-resolution dynamically downscaled ensembles over the contiguous United States Climate Dynamics

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

Zobel, Zachary; Wang, Jiali; Wuebbles, Donald J.

This study uses Weather Research and Forecast (WRF) model to evaluate the performance of six dynamical downscaled decadal historical simulations with 12-km resolution for a large domain (7200 x 6180 km) that covers most of North America. The initial and boundary conditions are from three global climate models (GCMs) and one reanalysis data. The GCMs employed in this study are the Geophysical Fluid Dynamics Laboratory Earth System Model with Generalized Ocean Layer Dynamics component, Community Climate System Model, version 4, and the Hadley Centre Global Environment Model, version 2-Earth System. The reanalysis data is from the National Centers for Environmentalmore » Prediction-US. Department of Energy Reanalysis II. We analyze the effects of bias correcting, the lateral boundary conditions and the effects of spectral nudging. We evaluate the model performance for seven surface variables and four upper atmospheric variables based on their climatology and extremes for seven subregions across the United States. The results indicate that the simulation’s performance depends on both location and the features/variable being tested. We find that the use of bias correction and/or nudging is beneficial in many situations, but employing these when running the RCM is not always an improvement when compared to the reference data. The use of an ensemble mean and median leads to a better performance in measuring the climatology, while it is significantly biased for the extremes, showing much larger differences than individual GCM driven model simulations from the reference data. This study provides a comprehensive evaluation of these historical model runs in order to make informed decisions when making future projections.« less

The anthroposphere as an anticipatory system: Open questions on steering the climate.

PubMed

Scolozzi, Rocco; Geneletti, Davide

2017-02-01

Climate change research and action counteracting it affect everyone and would involve cross-societal transformations reshaping the anthroposphere in its entirety. Scrutinizing climate-related science and policies, we recognize attempts to steer the evolution of climate according to expected (or modelled) futures. Such attempts would turn the anthroposphere into a large "anticipatory system", in which human society seeks to anticipate and, possibly, to govern climate dynamics. The chief aim of this discussion paper is to open a critical debate on the climate change paradigm (CCP) drawing on a strategic and systemic framework grounded in the concept of anticipatory system sensu Rosen (1991). The proposed scheme is ambitiously intended to turn an intricate issue into a complex but structured problem that is to say, to make such complexity clear and manageable. This framework emerges from concepts borrowed from different scientific fields (including future studies and system dynamics) and its background lies in a simple quantitative literature overview, relying upon a broad level of analysis. The proposed framework will assist researchers and policy makers in thinking of CCP in terms of an anticipatory system, and in disentangling its interrelated (and sometimes intricate) aspects. In point of fact, several strategic questions related to CCP were not subjected to an adequate transdisciplinary discussion: what are the interplays between physical processes and social-political interventions, who is the observer (what he/she is looking for), and which paradigm is being used (or who defines the desirable future). The proposed scheme allows to structure such various topics in an arrangement which is easier to communicate, highlighting the linkages in between, and making them intelligible and open to verification and discussion. Furthermore, ideally developments will help scientists and policy makers address the strategic gaps between the evidence-based climatological assessments and the plurality of possible answers as applied to the geopolitical contingencies. Copyright © 2016 Elsevier B.V. All rights reserved.

Adapting crop rotations to climate change in regional impact modelling assessments.

PubMed

Teixeira, Edmar I; de Ruiter, John; Ausseil, Anne-Gaelle; Daigneault, Adam; Johnstone, Paul; Holmes, Allister; Tait, Andrew; Ewert, Frank

2018-03-01

The environmental and economic sustainability of future cropping systems depends on adaptation to climate change. Adaptation studies commonly rely on agricultural systems models to integrate multiple components of production systems such as crops, weather, soil and farmers' management decisions. Previous adaptation studies have mostly focused on isolated monocultures. However, in many agricultural regions worldwide, multi-crop rotations better represent local production systems. It is unclear how adaptation interventions influence crops grown in sequences. We develop a catchment-scale assessment to investigate the effects of tactical adaptations (choice of genotype and sowing date) on yield and underlying crop-soil factors of rotations. Based on locally surveyed data, a silage-maize followed by catch-crop-wheat rotation was simulated with the APSIM model for the RCP 8.5 emission scenario, two time periods (1985-2004 and 2080-2100) and six climate models across the Kaituna catchment in New Zealand. Results showed that direction and magnitude of climate change impacts, and the response to adaptation, varied spatially and were affected by rotation carryover effects due to agronomical (e.g. timing of sowing and harvesting) and soil (e.g. residual nitrogen, N) aspects. For example, by adapting maize to early-sowing dates under a warmer climate, there was an advance in catch crop establishment which enhanced residual soil N uptake. This dynamics, however, differed with local environment and choice of short- or long-cycle maize genotypes. Adaptation was insufficient to neutralize rotation yield losses in lowlands but consistently enhanced yield gains in highlands, where other constraints limited arable cropping. The positive responses to adaptation were mainly due to increases in solar radiation interception across the entire growth season. These results provide deeper insights on the dynamics of climate change impacts for crop rotation systems. Such knowledge can be used to develop improved regional impact assessments for situations where multi-crop rotations better represent predominant agricultural systems. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Integrating research tools to support the management of social-ecological systems under climate change

USGS Publications Warehouse

Miller, Brian W.; Morisette, Jeffrey T.

2014-01-01

Developing resource management strategies in the face of climate change is complicated by the considerable uncertainty associated with projections of climate and its impacts and by the complex interactions between social and ecological variables. The broad, interconnected nature of this challenge has resulted in calls for analytical frameworks that integrate research tools and can support natural resource management decision making in the face of uncertainty and complex interactions. We respond to this call by first reviewing three methods that have proven useful for climate change research, but whose application and development have been largely isolated: species distribution modeling, scenario planning, and simulation modeling. Species distribution models provide data-driven estimates of the future distributions of species of interest, but they face several limitations and their output alone is not sufficient to guide complex decisions for how best to manage resources given social and economic considerations along with dynamic and uncertain future conditions. Researchers and managers are increasingly exploring potential futures of social-ecological systems through scenario planning, but this process often lacks quantitative response modeling and validation procedures. Simulation models are well placed to provide added rigor to scenario planning because of their ability to reproduce complex system dynamics, but the scenarios and management options explored in simulations are often not developed by stakeholders, and there is not a clear consensus on how to include climate model outputs. We see these strengths and weaknesses as complementarities and offer an analytical framework for integrating these three tools. We then describe the ways in which this framework can help shift climate change research from useful to usable.

Human Health and Climate Change: Leverage Points for Adaptation in Urban Environments

PubMed Central

Proust, Katrina; Newell, Barry; Brown, Helen; Capon, Anthony; Browne, Chris; Burton, Anthony; Dixon, Jane; Mu, Lisa; Zarafu, Monica

2012-01-01

The design of adaptation strategies that promote urban health and well-being in the face of climate change requires an understanding of the feedback interactions that take place between the dynamical state of a city, the health of its people, and the state of the planet. Complexity, contingency and uncertainty combine to impede the growth of such systemic understandings. In this paper we suggest that the collaborative development of conceptual models can help a group to identify potential leverage points for effective adaptation. We describe a three-step procedure that leads from the development of a high-level system template, through the selection of a problem space that contains one or more of the group’s adaptive challenges, to a specific conceptual model of a sub-system of importance to the group. This procedure is illustrated by a case study of urban dwellers’ maladaptive dependence on private motor vehicles. We conclude that a system dynamics approach, revolving around the collaborative construction of a set of conceptual models, can help communities to improve their adaptive capacity, and so better meet the challenge of maintaining, and even improving, urban health in the face of climate change. PMID:22829795

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.

Universal Inverse Power-Law Distribution for Fractal Fluctuations in Dynamical Systems: Applications for Predictability of Inter-Annual Variability of Indian and USA Region Rainfall

NASA Astrophysics Data System (ADS)

Selvam, A. M.

2017-01-01

Dynamical systems in nature exhibit self-similar fractal space-time fluctuations on all scales indicating long-range correlations and, therefore, the statistical normal distribution with implicit assumption of independence, fixed mean and standard deviation cannot be used for description and quantification of fractal data sets. The author has developed a general systems theory based on classical statistical physics for fractal fluctuations which predicts the following. (1) The fractal fluctuations signify an underlying eddy continuum, the larger eddies being the integrated mean of enclosed smaller-scale fluctuations. (2) The probability distribution of eddy amplitudes and the variance (square of eddy amplitude) spectrum of fractal fluctuations follow the universal Boltzmann inverse power law expressed as a function of the golden mean. (3) Fractal fluctuations are signatures of quantum-like chaos since the additive amplitudes of eddies when squared represent probability densities analogous to the sub-atomic dynamics of quantum systems such as the photon or electron. (4) The model predicted distribution is very close to statistical normal distribution for moderate events within two standard deviations from the mean but exhibits a fat long tail that are associated with hazardous extreme events. Continuous periodogram power spectral analyses of available GHCN annual total rainfall time series for the period 1900-2008 for Indian and USA stations show that the power spectra and the corresponding probability distributions follow model predicted universal inverse power law form signifying an eddy continuum structure underlying the observed inter-annual variability of rainfall. On a global scale, man-made greenhouse gas related atmospheric warming would result in intensification of natural climate variability, seen immediately in high frequency fluctuations such as QBO and ENSO and even shorter timescales. Model concepts and results of analyses are discussed with reference to possible prediction of climate change. Model concepts, if correct, rule out unambiguously, linear trends in climate. Climate change will only be manifested as increase or decrease in the natural variability. However, more stringent tests of model concepts and predictions are required before applications to such an important issue as climate change. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate (O'Gorman in Curr Clim Change Rep 1:49-59, 2015).

Sustainability Indicators for Coupled Human-Earth Systems

NASA Astrophysics Data System (ADS)

Motesharrei, S.; Rivas, J. R.; Kalnay, E.

2014-12-01

Over the last two centuries, the Human System went from having a small impact on the Earth System (including the Climate System) to becoming dominant, because both population and per capita consumption have grown extremely fast, especially since about 1950. We therefore argue that Human System Models must be included into Earth System Models through bidirectional couplings with feedbacks. In particular, population should be modeled endogenously, rather than exogenously as done currently in most Integrated Assessment Models. The growth of the Human System threatens to overwhelm the Carrying Capacity of the Earth System, and may be leading to catastrophic climate change and collapse. We propose a set of Ecological and Economic "Sustainability Indicators" that can employ large data-sets for developing and assessing effective mitigation and adaptation policies. Using the Human and Nature Dynamical Model (HANDY) and Coupled Human-Climate-Water Model (COWA), we carry out experiments with this set of Sustainability Indicators and show that they are applicable to various coupled systems including Population, Climate, Water, Energy, Agriculture, and Economy. Impact of nonrenewable resources and fossil fuels could also be understood using these indicators. We demonstrate interconnections of Ecological and Economic Indicators. Coupled systems often include feedbacks and can thus display counterintuitive dynamics. This makes it difficult for even experts to see coming catastrophes from just the raw data for different variables. Sustainability Indicators boil down the raw data into a set of simple numbers that cross their sustainability thresholds with a large time-lag before variables enter their catastrophic regimes. Therefore, we argue that Sustainability Indicators constitute a powerful but simple set of tools that could be directly used for making policies for sustainability.

Development of incremental dynamical downscaling and analysis system for regional scale climate change projections

NASA Astrophysics Data System (ADS)

Wakazuki, Yasutaka; Hara, Masayuki; Fujita, Mikiko; Ma, Xieyao; Kimura, Fujio

2013-04-01

Regional scale climate change projections play an important role in assessments of influences of global warming and include statistical (SD) and dynamical downscaling (DD) approaches. One of DD methods is developed basing on the pseudo-global-warming (PGW) method developed by Kimura and Kitoh (2007) in this study. In general, DD uses regional climate model (RCM) with lateral boundary data. In PGW method, the climatological mean difference estimated by GCMs are added to the objective analysis data (ANAL), and the data are used as the lateral boundary data in the future climate simulations. The ANAL is also used as the lateral boundary conditions of the present climate simulation. One of merits of the PGW method is that influences of biases of GCMs in RCM simulations are reduced. However, the PGW method does not treat climate changes in relative humidity, year-to-year variation, and short-term disturbances. The developing new downscaling method is named as the incremental dynamical downscaling and analysis system (InDDAS). The InDDAS treat climate changes in relative humidity and year-to-year variations. On the other hand, uncertainties of climate change projections estimated by many GCMs are large and are not negligible. Thus, stochastic regional scale climate change projections are expected for assessments of influences of global warming. Many RCM runs must be performed to make stochastic information. However, the computational costs are huge because grid size of RCM runs should be small to resolve heavy rainfall phenomena. Therefore, the number of runs to make stochastic information must be reduced. In InDDAS, climatological differences added to ANAL become statistically pre-analyzed information. The climatological differences of many GCMs are divided into mean climatological difference (MD) and departures from MD. The departures are analyzed by principal component analysis, and positive and negative perturbations (positive and negative standard deviations multiplied by departure patterns (eigenvectors)) with multi modes are added to MD. Consequently, the most likely future states are calculated with climatological difference of MD. For example, future states in cases that temperature increase is large and small are calculated with MD plus positive and negative perturbations of the first mode.

GRACE, time-varying gravity, Earth system dynamics and climate change

NASA Astrophysics Data System (ADS)

Wouters, B.; Bonin, J. A.; Chambers, D. P.; Riva, R. E. M.; Sasgen, I.; Wahr, J.

2014-11-01

Continuous observations of temporal variations in the Earth's gravity field have recently become available at an unprecedented resolution of a few hundreds of kilometers. The gravity field is a product of the Earth's mass distribution, and these data—provided by the satellites of the Gravity Recovery And Climate Experiment (GRACE)—can be used to study the exchange of mass both within the Earth and at its surface. Since the launch of the mission in 2002, GRACE data has evolved from being an experimental measurement needing validation from ground truth, to a respected tool for Earth scientists representing a fixed bound on the total change and is now an important tool to help unravel the complex dynamics of the Earth system and climate change. In this review, we present the mission concept and its theoretical background, discuss the data and give an overview of the major advances GRACE has provided in Earth science, with a focus on hydrology, solid Earth sciences, glaciology and oceanography.

GRACE, time-varying gravity, Earth system dynamics and climate change.

PubMed

Wouters, B; Bonin, J A; Chambers, D P; Riva, R E M; Sasgen, I; Wahr, J

2014-11-01

Continuous observations of temporal variations in the Earth's gravity field have recently become available at an unprecedented resolution of a few hundreds of kilometers. The gravity field is a product of the Earth's mass distribution, and these data-provided by the satellites of the Gravity Recovery And Climate Experiment (GRACE)-can be used to study the exchange of mass both within the Earth and at its surface. Since the launch of the mission in 2002, GRACE data has evolved from being an experimental measurement needing validation from ground truth, to a respected tool for Earth scientists representing a fixed bound on the total change and is now an important tool to help unravel the complex dynamics of the Earth system and climate change. In this review, we present the mission concept and its theoretical background, discuss the data and give an overview of the major advances GRACE has provided in Earth science, with a focus on hydrology, solid Earth sciences, glaciology and oceanography.

Satellite remote sensing assessment of climate impact on forest vegetation dynamics

NASA Astrophysics Data System (ADS)

Zoran, M.

2009-04-01

Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modelling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2007 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Climate-based models for pulsed resources improve predictability of consumer population dynamics: outbreaks of house mice in forest ecosystems.

PubMed

Holland, E Penelope; James, Alex; Ruscoe, Wendy A; Pech, Roger P; Byrom, Andrea E

2015-01-01

Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts) are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (ΔT) for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer-resource dynamics to predict invasive house mouse (Mus musculus) outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year's advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer-resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events.

Preface: Impacts of extreme climate events and disturbances on carbon dynamics

USGS Publications Warehouse

Xiao, Jingfeng; Liu, Shuguang; Stoy, Paul C.

2016-01-01

The impacts of extreme climate events and disturbances (ECE&D) on the carbon cycle have received growing attention in recent years. This special issue showcases a collection of recent advances in understanding the impacts of ECE&D on carbon cycling. Notable advances include quantifying how harvesting activities impact forest structure, carbon pool dynamics, and recovery processes; observed drastic increases of the concentrations of dissolved organic carbon and dissolved methane in thermokarst lakes in western Siberia during a summer warming event; disentangling the roles of herbivores and fire on forest carbon dioxide flux; direct and indirect impacts of fire on the global carbon balance; and improved atmospheric inversion of regional carbon sources and sinks by incorporating disturbances. Combined, studies herein indicate several major research needs. First, disturbances and extreme events can interact with one another, and it is important to understand their overall impacts and also disentangle their effects on the carbon cycle. Second, current ecosystem models are not skillful enough to correctly simulate the underlying processes and impacts of ECE&D (e.g., tree mortality and carbon consequences). Third, benchmark data characterizing the timing, location, type, and magnitude of disturbances must be systematically created to improve our ability to quantify carbon dynamics over large areas. Finally, improving the representation of ECE&D in regional climate/earth system models and accounting for the resulting feedbacks to climate are essential for understanding the interactions between climate and ecosystem dynamics.

Ground Water and Climate Change

NASA Technical Reports Server (NTRS)

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

Ground water and climate change

USGS Publications Warehouse

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

2012-01-01

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

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

NASA Astrophysics Data System (ADS)

Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths.

Climate variation drives dengue dynamics

PubMed Central

Xu, Lei; Stige, Leif C.; Chan, Kung-Sik; Zhou, Jie; Yang, Jun; Sang, Shaowei; Wang, Ming; Yang, Zhicong; Yan, Ziqiang; Jiang, Tong; Lu, Liang; Yue, Yujuan; Liu, Xiaobo; Lin, Hualiang; Xu, Jianguo; Liu, Qiyong; Stenseth, Nils Chr.

2017-01-01

Dengue, a viral infection transmitted between people by mosquitoes, is one of the most rapidly spreading diseases in the world. Here, we report the analyses covering 11 y (2005–2015) from the city of Guangzhou in southern China. Using the first 8 y of data to develop an ecologically based model for the dengue system, we reliably predict the following 3 y of dengue dynamics—years with exceptionally extensive dengue outbreaks. We demonstrate that climate conditions, through the effects of rainfall and temperature on mosquito abundance and dengue transmission rate, play key roles in explaining the temporal dynamics of dengue incidence in the human population. Our study thus contributes to a better understanding of dengue dynamics and provides a predictive tool for preventive dengue reduction strategies. PMID:27940911

Advancing coupled human-earth system models: The integrated Earth System Model Project

NASA Astrophysics Data System (ADS)

Thomson, A. M.; Edmonds, J. A.; Collins, W.; Thornton, P. E.; Hurtt, G. C.; Janetos, A. C.; Jones, A.; Mao, J.; Chini, L. P.; Calvin, K. V.; Bond-Lamberty, B. P.; Shi, X.

2012-12-01

As human and biogeophysical models develop, opportunities for connections between them evolve and can be used to advance our understanding of human-earth systems interaction in the context of a changing climate. One such integration is taking place with the Community Earth System Model (CESM) and the Global Change Assessment Model (GCAM). A multi-disciplinary, multi-institution team has succeeded in integrating the GCAM integrated assessment model of human activity into CESM to dynamically represent the feedbacks between changing climate and human decision making, in the context of greenhouse gas mitigation policies. The first applications of this capability have focused on the feedbacks between climate change impacts on terrestrial ecosystem productivity and human decisions affecting future land use change, which are in turn connected to human decisions about energy systems and bioenergy production. These experiments have been conducted in the context of the RCP4.5 scenario, one of four pathways of future radiative forcing being used in CMIP5, which constrains future human-induced greenhouse gas emissions from energy and land activities to stabilize radiative forcing at 4.5 W/m2 (~650 ppm CO2 -eq) by 2100. When this pathway is run in GCAM with the climate feedback on terrestrial productivity from CESM, there are implications for both the land use and energy system changes required for stabilization. Early findings indicate that traditional definitions of radiative forcing used in scenario development are missing a critical component of the biogeophysical consequences of land use change and their contribution to effective radiative forcing. Initial full coupling of the two global models has important implications for how climate impacts on terrestrial ecosystems changes the dynamics of future land use change for agriculture and forestry, particularly in the context of a climate mitigation policy designed to reduce emissions from land use as well as energy systems. While these initial experiments have relied on offline coupling methodologies, current and future experiments are utilizing a single model code developed to integrate GCAM into CESM as a component of the land model. This unique capability facilitates many new applications to scientific questions arising from human and biogeophysical systems interaction. Future developments will further integrate the energy system decisions and greenhouse gas emissions as simulated in GCAM with the appropriate climate and land system components of CESM.

Improved Analysis of Earth System Models and Observations using Simple Climate Models

NASA Astrophysics Data System (ADS)

Nadiga, B. T.; Urban, N. M.

2016-12-01

Earth system models (ESM) are the most comprehensive tools we have to study climate change and develop climate projections. However, the computational infrastructure required and the cost incurred in running such ESMs precludes direct use of such models in conjunction with a wide variety of tools that can further our understanding of climate. Here we are referring to tools that range from dynamical systems tools that give insight into underlying flow structure and topology to tools that come from various applied mathematical and statistical techniques and are central to quantifying stability, sensitivity, uncertainty and predictability to machine learning tools that are now being rapidly developed or improved. Our approach to facilitate the use of such models is to analyze output of ESM experiments (cf. CMIP) using a range of simpler models that consider integral balances of important quantities such as mass and/or energy in a Bayesian framework.We highlight the use of this approach in the context of the uptake of heat by the world oceans in the ongoing global warming. Indeed, since in excess of 90% of the anomalous radiative forcing due greenhouse gas emissions is sequestered in the world oceans, the nature of ocean heat uptake crucially determines the surface warming that is realized (cf. climate sensitivity). Nevertheless, ESMs themselves are never run long enough to directly assess climate sensitivity. So, we consider a range of models based on integral balances--balances that have to be realized in all first-principles based models of the climate system including the most detailed state-of-the art climate simulations. The models range from simple models of energy balance to those that consider dynamically important ocean processes such as the conveyor-belt circulation (Meridional Overturning Circulation, MOC), North Atlantic Deep Water (NADW) formation, Antarctic Circumpolar Current (ACC) and eddy mixing. Results from Bayesian analysis of such models using both ESM experiments and actual observations are presented. One such result points to the importance of direct sequestration of heat below 700 m, a process that is not allowed for in the simple models that have been traditionally used to deduce climate sensitivity.

integrated Earth System Model

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

Jones, Andew; Di Vittorio, Alan; Collins, William

The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human-Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human-Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems.« less

The integration of climate change, spatial dynamics, and habitat fragmentation: A conceptual overview.

PubMed

Holyoak, Marcel; Heath, Sacha K

2016-01-01

A growing number of studies have looked at how climate change alters the effects of habitat fragmentation and degradation on both single and multiple species; some raise concern that biodiversity loss and its effects will be exacerbated. The published literature on spatial dynamics (such as dispersal and metapopulation dynamics), habitat fragmentation and climate change requires synthesis and a conceptual framework to simplify thinking. We propose a framework that integrates how climate change affects spatial population dynamics and the effects of habitat fragmentation in terms of: (i) habitat quality, quantity and distribution; (ii) habitat connectivity; and (iii) the dynamics of habitat itself. We use the framework to categorize existing autecological studies and investigate how each is affected by anthropogenic climate change. It is clear that a changing climate produces changes in the geographic distribution of climatic conditions, and the amount and quality of habitat. The most thorough published studies show how such changes impact metapopulation persistence, source-sink dynamics, changes in species' geographic range and community composition. Climate-related changes in movement behavior and quantity, quality and distribution of habitat have also produced empirical changes in habitat connectivity for some species. An underexplored area is how habitat dynamics that are driven by climatic processes will affect species that live in dynamic habitats. We end our discussion by suggesting ways to improve current attempts to integrate climate change, spatial population dynamics and habitat fragmentation effects, and suggest distinct areas of study that might provide opportunities for more fully integrative work. © 2015 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

Challenges of Representing Sub-Grid Physics in an Adaptive Mesh Refinement Atmospheric Model

NASA Astrophysics Data System (ADS)

O'Brien, T. A.; Johansen, H.; Johnson, J. N.; Rosa, D.; Benedict, J. J.; Keen, N. D.; Collins, W.; Goodfriend, E.

2015-12-01

Some of the greatest potential impacts from future climate change are tied to extreme atmospheric phenomena that are inherently multiscale, including tropical cyclones and atmospheric rivers. Extremes are challenging to simulate in conventional climate models due to existing models' coarse resolutions relative to the native length-scales of these phenomena. Studying the weather systems of interest requires an atmospheric model with sufficient local resolution, and sufficient performance for long-duration climate-change simulations. To this end, we have developed a new global climate code with adaptive spatial and temporal resolution. The dynamics are formulated using a block-structured conservative finite volume approach suitable for moist non-hydrostatic atmospheric dynamics. By using both space- and time-adaptive mesh refinement, the solver focuses computational resources only where greater accuracy is needed to resolve critical phenomena. We explore different methods for parameterizing sub-grid physics, such as microphysics, macrophysics, turbulence, and radiative transfer. In particular, we contrast the simplified physics representation of Reed and Jablonowski (2012) with the more complex physics representation used in the System for Atmospheric Modeling of Khairoutdinov and Randall (2003). We also explore the use of a novel macrophysics parameterization that is designed to be explicitly scale-aware.

Analysis of the El Niño/La Niña-Southern Oscillation variability and malaria in the Estado Sucre, Venezuela.

PubMed

Delgado-Petrocelli, Laura; Córdova, Karenia; Camardiel, Alberto; Aguilar, Víctor H; Hernández, Denise; Ramos, Santiago

2012-09-01

The last decade has seen an unprecedented, worldwide acceleration of environmental and climate changes. These processes impact the dynamics of natural systems, which include components associated with human communities such as vector-borne diseases. The dynamics of environmental and climate variables, altered by global change as reported by the Intergovernmental Panel on Climate Change, affect the distribution of many tropical diseases. Complex systems, e.g. the El Niño/La Niña-Southern Oscillation (ENSO), in which environmental variables operate synergistically, can provoke the reemergence and emergence of vector-borne diseases at new sites. This research investigated the influence of ENSO events on malaria incidence by determining the relationship between climate variations, expressed as warm, cold and neutral phases, and their relation to the number of malaria cases in some north-eastern municipalities of Venezuela (Estado Sucre) during the period 1990-2000. Significant differences in malaria incidence were found, particularly in the La Niña ENSO phases (cold) of moderate intensity. These findings should be taken into account for surveillance and control in the future as they shed light on important indicators that can lead to reduced vulnerability to malaria.

Pacific-Australia Climate Change Science and Adaptation Planning program: supporting climate science and enhancing climate services in Pacific Island Countries

NASA Astrophysics Data System (ADS)

Kuleshov, Yuriy; Jones, David; Hendon, Harry; Charles, Andrew; Shelton, Kay; de Wit, Roald; Cottrill, Andrew; Nakaegawa, Toshiyuki; Atalifo, Terry; Prakash, Bipendra; Seuseu, Sunny; Kaniaha, Salesa

2013-04-01

Over the past few years, significant progress in developing climate science for the Pacific has been achieved through a number of research projects undertaken under the Australian government International Climate Change Adaptation Initiative (ICCAI). Climate change has major impact on Pacific Island Countries and advancement in understanding past, present and futures climate in the region is vital for island nation to develop adaptation strategies to their rapidly changing environment. This new science is now supporting new services for a wide range of stakeholders in the Pacific through the National Meteorological Agencies of the region. Seasonal climate prediction is particularly important for planning in agriculture, tourism and other weather-sensitive industries, with operational services provided by all National Meteorological Services in the region. The interaction between climate variability and climate change, for example during droughts or very warm seasons, means that much of the early impacts of climate change are being felt through seasonal variability. A means to reduce these impacts is to improve forecasts to support decision making. Historically, seasonal climate prediction has been developed based on statistical past relationship. Statistical methods relate meteorological variables (e.g. temperature and rainfall) to indices which describe large-scale environment (e.g. ENSO indices) using historical data. However, with observed climate change, statistical approaches based on historical data are getting less accurate and less reliable. Recognising the value of seasonal forecasts, we have used outputs of a dynamical model POAMA (Predictive Ocean Atmosphere Model for Australia), to develop web-based information tools (http://poama.bom.gov.au/experimental/pasap/index.shtml) which are now used by climate services in 15 partner countries in the Pacific for preparing seasonal climate outlooks. Initial comparison conducted during 2012 has shown that the predictive skill of POAMA is consistently higher than skill of statistical-based method. Presently, under the Pacific-Australia Climate Change Science and Adaptation Planning (PACCSAP) program, we are developing dynamical model-based seasonal climate prediction for climate extremes. Of particular concern are tropical cyclones which are the most destructive weather systems that impact on coastal areas of Australia and Pacific Island Countries. To analyse historical cyclone data, we developed a consolidate archive for the Southern Hemisphere and North-Western Pacific (http://www.bom.gov.au/cyclone/history/tracks/). Using dynamical climate models (POAMA and Japan Meteorological Agency's model), we work on improving accuracy of seasonal forecasts of tropical cyclone activity for the regions of Western Pacific. Improved seasonal climate prediction based on dynamical models will further enhance climate services in Australia and Pacific Island Countries.

Extrinsic regime shifts drive abrupt changes in regeneration dynamics at upper treeline in the Rocky Mountains, U.S.A.

PubMed

Elliott, Grant P

2012-07-01

Given the widespread and often dramatic influence of climate change on terrestrial ecosystems, it is increasingly common for abrupt threshold changes to occur, yet explicitly testing for climate and ecological regime shifts is lacking in climatically sensitive upper treeline ecotones. In this study, quantitative evidence based on empirical data is provided to support the key role of extrinsic, climate-induced thresholds in governing the spatial and temporal patterns of tree establishment in these high-elevation environments. Dendroecological techniques were used to reconstruct a 420-year history of regeneration dynamics within upper treeline ecotones along a latitudinal gradient (approximately 44-35 degrees N) in the Rocky Mountains. Correlation analysis was used to assess the possible influence of minimum and maximum temperature indices and cool-season (November-April) precipitation on regional age-structure data. Regime-shift analysis was used to detect thresholds in tree establishment during the entire period of record (1580-2000), temperature variables significantly Correlated with establishment during the 20th century, and cool-season precipitation. Tree establishment was significantly correlated with minimum temperature during the spring (March-May) and cool season. Regime-shift analysis identified an abrupt increase in regional tree establishment in 1950 (1950-1954 age class). Coincident with this period was a shift toward reduced cool-season precipitation. The alignment of these climate conditions apparently triggered an abrupt increase in establishment that was unprecedented during the period of record. Two main findings emerge from this research that underscore the critical role of climate in governing regeneration dynamics within upper treeline ecotones. (1) Regional climate variability is capable of exceeding bioclimatic thresholds, thereby initiating synchronous and abrupt changes in the spatial and temporal patterns of tree establishment at broad regional scales. (2) The importance of climate parameters exceeding critical threshold values and triggering a regime shift in tree establishment appears to be contingent on the alignment of favorable temperature and moisture regimes. This research suggests that threshold changes in the climate system can fundamentally alter regeneration dynamics within upper treeline ecotones and, through the use of regime-shift analysis, reveals important climate-vegetation linkages.

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

Collins, William D.; Craig, Anthony P.; Truesdale, John E.

The integrated Earth System Model (iESM) has been developed as a new tool for pro- jecting the joint human/climate system. The iESM is based upon coupling an Integrated Assessment Model (IAM) and an Earth System Model (ESM) into a common modeling in- frastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species, land use and land cover change, and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human dimension modeling of an IAM and a fully coupled ESM within a sin- gle simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore- omitted feedbacks between natural and societal drivers, we can improve scientific under- standing of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper de- scribes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.« less

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

Collins, W. D.; Craig, A. P.; Truesdale, J. E.

The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper describes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.« less

Using a dynamic vegetation model for future projections of crop yields: application to Belgium in the framework of the VOTES and MASC projects

NASA Astrophysics Data System (ADS)

Jacquemin, Ingrid; Henrot, Alexandra-Jane; Fontaine, Corentin M.; Dendoncker, Nicolas; Beckers, Veronique; Debusscher, Bos; Tychon, Bernard; Hambuckers, Alain; François, Louis

2016-04-01

Dynamic vegetation models (DVM) were initially designed to describe the dynamics of natural ecosystems as a function of climate and soil, to study the role of the vegetation in the carbon cycle. These models are now directly coupled with climate models in order to evaluate feedbacks between vegetation and climate. But DVM characteristics allow numerous other applications, leading to amelioration of some of their modules (e.g., evaluating sensitivity of the hydrological module to land surface changes) and developments (e.g., coupling with other models like agent-based models), to be used in ecosystem management and land use planning studies. It is in this dynamic context about DVMs that we have adapted the CARAIB (CARbon Assimilation In the Biosphere) model. One of the main improvements is the implementation of a crop module, allowing the assessment of climate change impacts on crop yields. We try to validate this module at different scales: - from the plot level, with the use of eddy-covariance data from agricultural sites in the FLUXNET network, such as Lonzée (Belgium) or other Western European sites (Grignon, Dijkgraaf,…), - to the country level, for which we compare the crop yield calculated by CARAIB to the crop yield statistics for Belgium and for different agricultural regions of the country. Another challenge for the CARAIB DVM was to deal with the landscape dynamics, which is not directly possible due to the lack of consideration of anthropogenic factors in the system. In the framework of the VOTES and the MASC projects, CARAIB is coupled with an agent-based model (ABM), representing the societal component of the system. This coupled module allows the use of climate and socio-economic scenarios, particularly interesting for studies which aim at ensuring a sustainable approach. This module has particularly been exploited in the VOTES project, where the objective was to provide a social, biophysical and economic assessment of the ecosystem services in four municipalities under urban pressure in the center of Belgium. The biophysical valuation was carried out with the coupled module, allowing a quantitative evaluation of key ecosystem services as a function of three climatic and socio-economic scenarios.

A vital link: water and vegetation in the Anthropocene

NASA Astrophysics Data System (ADS)

Gerten, D.

2013-10-01

This paper argues that the interplay of water, carbon and vegetation dynamics fundamentally links some global trends in the current and conceivable future Anthropocene, such as cropland expansion, freshwater use, and climate change and its impacts. Based on a review of recent literature including geographically explicit simulation studies with the process-based LPJmL global biosphere model, it demonstrates that the connectivity of water and vegetation dynamics is vital for water security, food security and (terrestrial) ecosystem dynamics alike. The water limitation of net primary production of both natural and agricultural plants - already pronounced in many regions - is shown to increase in many places under projected climate change, though this development is partially offset by water-saving direct CO2 effects. Natural vegetation can to some degree adapt dynamically to higher water limitation, but agricultural crops usually require some form of active management to overcome it - among them irrigation, soil conservation and eventually shifts of cropland to areas that are less water-limited due to more favourable climatic conditions. While crucial to secure food production for a growing world population, such human interventions in water-vegetation systems have, as also shown, repercussions on the water cycle. Indeed, land use changes are shown to be the second-most important influence on the terrestrial water balance in recent times. Furthermore, climate change (warming and precipitation changes) will in many regions increase irrigation demand and decrease water availability, impeding rainfed and irrigated food production (if not CO2 effects counterbalance this impact - which is unlikely at least in poorly managed systems). Drawing from these exemplary investigations, some research perspectives on how to further improve our knowledge of human-water-vegetation interactions in the Anthropocene are outlined.

Indices and Dynamics of Global Hydroclimate Over the Past Millennium from Data Assimilation

NASA Astrophysics Data System (ADS)

Steiger, N. J.; Smerdon, J. E.

2017-12-01

Reconstructions based on data assimilation (DA) are at the forefront of model-data syntheses in that such reconstructions optimally fuse proxy data with climate models. DA-based paleoclimate reconstructions have the benefit of being physically-consistent across the reconstructed climate variables and are capable of providing dynamical information about past climate phenomena. Here we use a new implementation of DA, that includes updated proxy system models and climate model bias correction procedures, to reconstruct global hydroclimate on seasonal and annual timescales over the last millennium. This new global hydroclimate product includes reconstructions of the Palmer Drought Severity Index, the Standardized Precipitation Evapotranspiration Index, and global surface temperature along with dynamical variables including the Nino 3.4 index, the latitudinal location of the intertropical convergence zone, and an index of the Atlantic Multidecadal Oscillation. Here we present a validation of the reconstruction product and also elucidate the causes of severe drought in North America and in equatorial Africa. Specifically, we explore the connection between droughts in North America and modes of ocean variability in the Pacific and Atlantic oceans. We also link drought over equatorial Africa to shifts of the intertropical convergence zone and modes of ocean variability.

Solar System Chaos and its climatic and biogeochemical consequences

NASA Astrophysics Data System (ADS)

Ikeda, M.; Tada, R.; Ozaki, K.; Olsen, P. E.

2017-12-01

Insolation changes caused by changes in Earth's orbital parameters are the main driver of climatic variations, whose pace has been used for astronomically-calibrated geologic time scales of high accuracy to understand Earth system dynamics. However, the astrophysical models beyond several tens of million years ago have large uncertainty due to chaotic behavior of the Solar System, and its impact on amplitude modulation of multi-Myr-scale orbital variations and consequent climate changes has become the subject of debate. Here we show the geologic constraints on the past chaotic behavior of orbital cycles from early Mesozoic monsoon-related records; the 30-Myr-long lake level records of the lacustrine sequence in Newark-Hartford basins (North America) and 70-Myr-long biogenic silica (BSi) burial flux record of pelagic deep-sea chert sequence in Inuyama area (Japan). BSi burial flux of chert could be considered as proportional to the dissolved Si (DSi) input from chemical weathering on timescales longer than the residence time of DSi ( 100 kyr), because chert could represent a major sink for oceanic dissolved silica (Ikeda et al., 2017).These geologic records show multi-Myr cycles with similar frequency modulations of eccentricity solution of astronomical model La2010d (Laskar et al., 2011) compared with other astronomical solutions, but not exactly same. Our geologic records provide convincing evidence for the past chaotic dynamical behaviour of the Solar System and new and challenging additional constraints for astrophysical models. In addition, we find that ˜10 Myr cycle detected in monsoon proxies and their amplitude modulation of ˜2 Myr cycle may be related to the amplitude modulation of ˜2 Myr eccentricity cycle through non-linear process(es) of Earth system dynamics, suggesting possible impact of the chaotic behavior of Solar planets on climate change. Further impact of multi-Myr orbital cycles on global biogeochemical cycles will be discussed.

Using the CLEAN educational resource collection for building three-dimensional lessons to teach the climate system

NASA Astrophysics Data System (ADS)

Gold, A. U.; Sullivan, S. M.; Manning, C. L. B.; Ledley, T. S.; Youngman, E.; Taylor, J.; Niepold, F., III; Kirk, K.; Lockwood, J.; Bruckner, M. Z.; Fox, S.

2017-12-01

The impacts of climate change are a critical societal challenge of the 21st century. Educating students about the globally connected climate system is key in supporting the development of mitigation and adaptation strategies. Systems thinking is required for students to understand the complex, dynamic climate systems and the role that humans play within them. The interdisciplinary nature of climate science challenges educators, who often don't have formal training in climate science, to identify resources that are scientifically accurate before weaving them together into units that teach about the climate system. The Climate Literacy and Energy Awareness Network (CLEAN) supports this work by providing over 700 peer-reviewed, classroom-ready resources on climate and energy topics. The resource collection itself provide only limited instructional guidance, so educators need to weave the resources together to build multi-dimensional lessons that develop systems thinking skills. The Next Generation Science Standards (NGSS) science standards encourage educators to teach science in a 3-dimensional approach that trains students in systems thinking. The CLEAN project strives to help educators design NGSS-style, three-dimensional lessons about the climate system. Two approaches are currently being modeled on the CLEAN web portal. The first is described in the CLEAN NGSS "Get Started Guide" which follows a step-by-step process starting with the Disciplinary Core Idea and then interweaves the Cross-Cutting Concepts (CCC) and the Science and Engineering Practices (SEP) based on the teaching strategy chosen for the lesson or unit topic. The second model uses a climate topic as a starting place and the SEP as the guide through a four-step lesson sequence called "Earth Systems Investigations". Both models use CLEAN reviewed lessons as the core activity but provide the necessary framework for classroom implementation. Sample lessons that were developed following these two approaches are provided on the CLEAN web portal (cleanet.org).

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

NASA Astrophysics Data System (ADS)

González, D. L., II; Angus, M. P.; Tetteh, I. K.; Bello, G. A.; Padmanabhan, K.; Pendse, S. V.; Srinivas, S.; Yu, J.; Semazzi, F.; Kumar, V.; Samatova, N. F.

2014-04-01

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and Dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall, including well-known associations from prior climate knowledge, as well as promising discoveries that invite further research by the climate science community.

Heinrich Events as an integral part of glacial-interglacial climate dynamics

NASA Astrophysics Data System (ADS)

Barker, S.; Knorr, G.; Zhang, X.; Gong, X.; Lohmann, G.; Bazin, L.

2017-12-01

Since their discovery in the 1980s Heinrich Events have provided a playground for climate scientists trying to understand the interactions between ice sheets and the ocean. Subsequently it has become clear that these interactions extend to almost all parts of the global climate system, from temperature, winds and rainfall to deep ocean currents and atmospheric CO2. Furthermore it remains unclear as to whether these dramatic events are a cause or consequence (or both) of regional to global perturbations in a range of parameters, including meridional overturning circulation within the Atlantic. Here we will discuss some of these aspects to highlight ongoing and future research related to Heinrich events and abrupt change more generally. We will discuss some of the possible triggers for H-events, including abrupt versus more gradual forcing mechanisms and conversely the potential influence of such events on the wider climate system, including deglacial climate change.

Uncertainty quantification and validation of combined hydrological and macroeconomic analyses.

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

Hernandez, Jacquelynne; Parks, Mancel Jordan; Jennings, Barbara Joan

2010-09-01

Changes in climate can lead to instabilities in physical and economic systems, particularly in regions with marginal resources. Global climate models indicate increasing global mean temperatures over the decades to come and uncertainty in the local to national impacts means perceived risks will drive planning decisions. Agent-based models provide one of the few ways to evaluate the potential changes in behavior in coupled social-physical systems and to quantify and compare risks. The current generation of climate impact analyses provides estimates of the economic cost of climate change for a limited set of climate scenarios that account for a small subsetmore » of the dynamics and uncertainties. To better understand the risk to national security, the next generation of risk assessment models must represent global stresses, population vulnerability to those stresses, and the uncertainty in population responses and outcomes that could have a significant impact on U.S. national security.« less

The Role of Ocean Dynamical Thermostat in Delaying the El Niño–Like Response over the Equatorial Pacific to Climate Warming

DOE PAGES

Luo, Yiyong; Lu, Jian; Liu, Fukai; ...

2017-03-27

The role of the ocean dynamics in the response of the equatorial Pacific Ocean to climate warming is investigated using both an atmosphere-ocean coupled climate system and its ocean component. Results show that the initial response (fast pattern) to an uniform heating imposed on to the ocean is a warming centered to the west of the dateline owing to the conventional ocean dynamical thermostat (ODT) mechanism in the eastern equatorial Pacific-a cooling effect arising from the up-gradient upwelling. In time, the warming pattern gradually propagates eastward, becoming more El Niño-like (slow pattern). The transition from the fast to the slowmore » patterns is likely resulted from i) the gradual warming of the equatorial thermocline temperature, which is associated with the arrival of the relatively warmer extratropical waters advected along the subsurface branch of the subtropical cells (STC) and ii) the reduction of the STC strength itself. A mixed layer heat budget analysis finds that it is the total ocean dynamical effect rather than the conventional ODT that holds the key for understanding the pattern of the SST in the equatorial Pacific and that the surface heat flux works mainly to compensate the ocean dynamics. Further passive tracer experiments with the ocean component of the coupled system verify the role of the ocean dynamical processes in initiating a La Niña-like SST warming and in setting the pace of the transition to an El Niño-like warming and identify an oceanic origin for the slow eastern Pacific warming independent of the weakening trade wind.« less

The Role of Ocean Dynamical Thermostat in Delaying the El Niño–Like Response over the Equatorial Pacific to Climate Warming

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

Luo, Yiyong; Lu, Jian; Liu, Fukai

The role of the ocean dynamics in the response of the equatorial Pacific Ocean to climate warming is investigated using both an atmosphere-ocean coupled climate system and its ocean component. Results show that the initial response (fast pattern) to an uniform heating imposed on to the ocean is a warming centered to the west of the dateline owing to the conventional ocean dynamical thermostat (ODT) mechanism in the eastern equatorial Pacific-a cooling effect arising from the up-gradient upwelling. In time, the warming pattern gradually propagates eastward, becoming more El Niño-like (slow pattern). The transition from the fast to the slowmore » patterns is likely resulted from i) the gradual warming of the equatorial thermocline temperature, which is associated with the arrival of the relatively warmer extratropical waters advected along the subsurface branch of the subtropical cells (STC) and ii) the reduction of the STC strength itself. A mixed layer heat budget analysis finds that it is the total ocean dynamical effect rather than the conventional ODT that holds the key for understanding the pattern of the SST in the equatorial Pacific and that the surface heat flux works mainly to compensate the ocean dynamics. Further passive tracer experiments with the ocean component of the coupled system verify the role of the ocean dynamical processes in initiating a La Niña-like SST warming and in setting the pace of the transition to an El Niño-like warming and identify an oceanic origin for the slow eastern Pacific warming independent of the weakening trade wind.« less

The influence of land-use change and landscape dynamics on the climate system: relevance to climate-change policy beyond the radiative effect of greenhouse gases.

PubMed

Pielke, Roger A; Marland, Gregg; Betts, Richard A; Chase, Thomas N; Eastman, Joseph L; Niles, John O; Niyogi, Dev Dutta S; Running, Steven W

2002-08-15

Our paper documents that land-use change impacts regional and global climate through the surface-energy budget, as well as through the carbon cycle. The surface-energy budget effects may be more important than the carbon-cycle effects. However, land-use impacts on climate cannot be adequately quantified with the usual metric of 'global warming potential'. A new metric is needed to quantify the human disturbance of the Earth's surface-energy budget. This 'regional climate change potential' could offer a new metric for developing a more inclusive climate protocol. This concept would also implicitly provide a mechanism to monitor potential local-scale environmental changes that could influence biodiversity.

2000 years of cultural adaptation to climate change in the Southwestern United States.

PubMed

Blinman, Eric

2008-11-01

Modern concerns with climate change often overlook the extensive history of both climate change and human adaptation over the millennia. While questions of human-climate system causation are important, especially to the extent that our current behavior is driving environmental change, human societies have experienced multiple climate changes in the past, independent of causation. The histories of cultural adaptation to those changes can help us understand the dynamic interaction between climate and society, expanding the possibilities for "proactive adaptation" that may be available to us today. The underlying principles of cultural adaptation are generally independent of the source of the climate change, and the lessons of the past can suggest social and economic paths that can lead toward sustainability and away from collapse.

Variance decomposition shows the importance of human-climate feedbacks in the Earth system

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.

2017-12-01

The human and Earth systems are intricately linked: climate influences agricultural production, renewable energy potential, and water availability, for example, while anthropogenic emissions from industry and land use change alter temperature and precipitation. Such feedbacks have the potential to significantly alter future climate change. Current climate change projections contain significant uncertainties, however, and because Earth System Models do not generally include dynamic human (demography, economy, energy, water, land use) components, little is known about how climate feedbacks contribute to that uncertainty. Here we use variance decomposition of a novel coupled human-earth system model to show that the influence of human-climate feedbacks can be as large as 17% of the total variance in the near term for global mean temperature rise, and 11% in the long term for cropland area. The near-term contribution of energy and land use feedbacks to the climate on global mean temperature rise is as large as that from model internal variability, a factor typically considered in modeling studies. Conversely, the contribution of climate feedbacks to cropland extent, while non-negligible, is less than that from socioeconomics, policy, or model. Previous assessments have largely excluded these feedbacks, with the climate community focusing on uncertainty due to internal variability, scenario, and model and the integrated assessment community focusing on uncertainty due to socioeconomics, technology, policy, and model. Our results set the stage for a new generation of models and hypothesis testing to determine when and how bidirectional feedbacks between human and Earth systems should be considered in future assessments of climate change.

The World Climate Project: Bringing the UN Climate Negotiations to Classrooms, Boardrooms, and Living Rooms Near You

NASA Astrophysics Data System (ADS)

Rath, K.; Rooney-varga, J. N.; Jones, A.; Johnston, E.; Sterman, J.

2015-12-01

As a simulation-based role-playing exercise, World Climate provides an opportunity for participants to have an immersive experience in which they learn first-hand about both the social dynamics of climate change decision-making, through role-play, and the geophysical dynamics of the climate system, through an interactive computer simulation. In June 2015, we launched the World Climate Project with the intent of bringing this powerful tool to students, citizens, and decision-makers across government, NGO, and private sectors around the world. Within a period of six weeks from the launch date, 440 educators from 36 states and 56 countries have enrolled in the initiative, offering the potential to reach tens of thousands of participants around the world. While this project is clearly in its infancy, we see several characteristics that may be contributing to widespread interest in it. These factors include the ease-of-use, real-world relevance, and scientific rigor of the decision-support simulation, C-ROADS, that frames the World Climate Exercise. Other characteristics of World Climate include its potential to evoke an emotional response that is arousing and inspirational and its use of positive framing and a call to action. Similarly, the World Climate Project takes a collaborative approach, enabling educators to be innovators and valued contributors and regularly communicating with people who join the initiative through webinars, social media, and resources.

Monitoring and Modeling the Tibetan Plateau's climate system and its impact on East Asia.

PubMed

Ma, Yaoming; Ma, Weiqiang; Zhong, Lei; Hu, Zeyong; Li, Maoshan; Zhu, Zhikun; Han, Cunbo; Wang, Binbin; Liu, Xin

2017-03-13

The Tibetan Plateau is an important water source in Asia. As the "Third Pole" of the Earth, the Tibetan Plateau has significant dynamic and thermal effects on East Asian climate patterns, the Asian monsoon process and atmospheric circulation in the Northern Hemisphere. However, little systematic knowledge is available regarding the changing climate system of the Tibetan Plateau and the mechanisms underlying its impact on East Asia. This study was based on "water-cryosphere-atmosphere-biology" multi-sphere interactions, primarily considering global climate change in relation to the Tibetan Plateau -East Asia climate system and its mechanisms. This study also analyzed the Tibetan Plateau to clarify global climate change by considering multi-sphere energy and water processes. Additionally, the impacts of climate change in East Asia and the associated impact mechanisms were revealed, and changes in water cycle processes and water conversion mechanisms were studied. The changes in surface thermal anomalies, vegetation, local circulation and the atmospheric heat source on the Tibetan Plateau were studied, specifically, their effects on the East Asian monsoon and energy balance mechanisms. Additionally, the relationships between heating mechanisms and monsoon changes were explored.

Monitoring and Modeling the Tibetan Plateau’s climate system and its impact on East Asia

PubMed Central

Ma, Yaoming; Ma, Weiqiang; Zhong, Lei; Hu, Zeyong; Li, Maoshan; Zhu, Zhikun; Han, Cunbo; Wang, Binbin; Liu, Xin

2017-01-01

The Tibetan Plateau is an important water source in Asia. As the “Third Pole” of the Earth, the Tibetan Plateau has significant dynamic and thermal effects on East Asian climate patterns, the Asian monsoon process and atmospheric circulation in the Northern Hemisphere. However, little systematic knowledge is available regarding the changing climate system of the Tibetan Plateau and the mechanisms underlying its impact on East Asia. This study was based on “water-cryosphere-atmosphere-biology” multi-sphere interactions, primarily considering global climate change in relation to the Tibetan Plateau -East Asia climate system and its mechanisms. This study also analyzed the Tibetan Plateau to clarify global climate change by considering multi-sphere energy and water processes. Additionally, the impacts of climate change in East Asia and the associated impact mechanisms were revealed, and changes in water cycle processes and water conversion mechanisms were studied. The changes in surface thermal anomalies, vegetation, local circulation and the atmospheric heat source on the Tibetan Plateau were studied, specifically, their effects on the East Asian monsoon and energy balance mechanisms. Additionally, the relationships between heating mechanisms and monsoon changes were explored. PMID:28287648

[Lake eutrophication modeling in considering climatic factors change: a review].

PubMed

Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng

2012-11-01

Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.

Long-term environmental drivers of DOC fluxes: Linkages between management, hydrology and climate in a subtropical coastal estuary

NASA Astrophysics Data System (ADS)

Regier, Peter; Briceño, Henry; Jaffé, Rudolf

2016-12-01

Urban and agricultural development of the South Florida peninsula has disrupted historic freshwater flow in the Everglades, a hydrologically connected ecosystem stretching from central Florida to the Gulf of Mexico, USA. Current system-scale restoration efforts aim to restore natural hydrologic regimes to reestablish pre-drainage ecosystem functioning through increased water availability, quality and timing. Aquatic transport of carbon in this ecosystem, primarily as dissolved organic carbon (DOC), plays a critical role in biogeochemical cycling and food-web dynamics, and will be affected both by water management policies and climate change. To better understand DOC dynamics in South Florida estuaries and how hydrology, climate and water management may affect them, 14 years of monthly data collected in the Shark River estuary were used to examine DOC flux dynamics in a broader environmental context. Multivariate statistical methods were applied to long-term datasets for hydrology, water quality and climate to untangle the interconnected environmental drivers that control DOC export at monthly and annual scales. DOC fluxes were determined to be primarily controlled by hydrology but also by seasonality and long-term climate patterns and episodic weather events. A four-component model (salinity, rainfall, inflow, Atlantic Multidecadal Oscillation) capable of predicting DOC fluxes (R2 = 0.84, p < 0.0001, n = 155) was established and applied to potential climate change scenarios for the Everglades to assess DOC flux response to climate and restoration variables. The majority of scenario runs indicated that DOC export from the Everglades is expected to decrease due to future changes in rainfall, water management and salinity.

To Tip or Not to Tip: The Case of the Congo Basin Rainforest Realm

NASA Astrophysics Data System (ADS)

Pietsch, S.; Bednar, J. E.; Fath, B. D.; Winter, P. A.

2017-12-01

The future response of the Congo basin rainforest, the second largest tropical carbon reservoir, to climate change is still under debate. Different Climate projections exist stating increase and decrease in rainfall and different changes in rainfall patterns. Within this study we assess all options of climate change possibilities to define the climatic thresholds of Congo basin rainforest stability and assess the limiting conditions for rainforest persistence. We use field data from 199 research plots from the Western Congo basin to calibrate and validate a complex BioGeoChemistry model (BGC-MAN) and assess model performance against an array of possible future climates. Next, we analyze the reasons for the occurrence of tipping points, their spatial and temporal probability of occurrence, will present effects of hysteresis and derive probabilistic spatial-temporal resilience landscapes for the region. Additionally, we will analyze attractors of forest growth dynamics and assess common linear measures for early warning signals of sudden shifts in system dynamics for their robustness in the context of the Congo Basin case, and introduce the correlation integral as a nonlinear measure of risk assessment.

Influence of feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

NASA Astrophysics Data System (ADS)

van Walsum, P. E. V.

2011-11-01

Climate change impact modelling of hydrologic responses is hampered by climate-dependent model parameterizations. Reducing this dependency was one of the goals of extending the regional hydrologic modelling system SIMGRO with a two-way coupling to the crop growth simulation model WOFOST. The coupling includes feedbacks to the hydrologic model in terms of the root zone depth, soil cover, leaf area index, interception storage capacity, crop height and crop factor. For investigating whether such feedbacks lead to significantly different simulation results, two versions of the model coupling were set up for a test region: one with exogenous vegetation parameters, the "static" model, and one with endogenous simulation of the crop growth, the "dynamic" model WOFOST. The used parameterization methods of the static/dynamic vegetation models ensure that for the current climate the simulated long-term average of the actual evapotranspiration is the same for both models. Simulations were made for two climate scenarios. Owing to the higher temperatures in combination with a higher CO2-concentration of the atmosphere, a forward time shift of the crop development is simulated in the dynamic model; the used arable land crop, potatoes, also shows a shortening of the growing season. For this crop, a significant reduction of the potential transpiration is simulated compared to the static model, in the example by 15% in a warm, dry year. In consequence, the simulated crop water stress (the unit minus the relative transpiration) is lower when the dynamic model is used; also the simulated increase of crop water stress due to climate change is lower; in the example, the simulated increase is 15 percentage points less (of 55) than when a static model is used. The static/dynamic models also simulate different absolute values of the transpiration. The difference is most pronounced for potatoes at locations with ample moisture supply; this supply can either come from storage release of a good soil or from capillary rise. With good supply of moisture, the dynamic model simulates up to 10% less actual evapotranspiration than the static one in the example. This can lead to cases where the dynamic model predicts a slight increase of the recharge in a climate scenario, where the static model predicts a decrease. The use of a dynamic model also affects the simulated demand for surface water from external sources; especially the timing is affected. The proposed modelling approach uses postulated relationships that require validation with controlled field trials. In the Netherlands there is a lack of experimental facilities for performing such validations.

Early warning of climate tipping points

NASA Astrophysics Data System (ADS)

Lenton, Timothy M.

2011-07-01

A climate 'tipping point' occurs when a small change in forcing triggers a strongly nonlinear response in the internal dynamics of part of the climate system, qualitatively changing its future state. Human-induced climate change could push several large-scale 'tipping elements' past a tipping point. Candidates include irreversible melt of the Greenland ice sheet, dieback of the Amazon rainforest and shift of the West African monsoon. Recent assessments give an increased probability of future tipping events, and the corresponding impacts are estimated to be large, making them significant risks. Recent work shows that early warning of an approaching climate tipping point is possible in principle, and could have considerable value in reducing the risk that they pose.

Impacts of East Asian Sulfate Aerosols on Local and Remote Climate

NASA Astrophysics Data System (ADS)

Bartlett, R. E.; Bollasina, M. A.

2017-12-01

Anthropogenic aerosols exert significant climate forcing, which increases with emissions following trends of growing population and industry. Globally, aerosols cause a net cooling, counteracting greenhouse gas warming; however, regional impacts vary since emissions are spatially and temporally heterogeneous. While European and North American emissions have decreased in recent decades, Asian, particularly East Asian, emissions continued to rise into the 21st century. In addition to links between Asian anthropogenic aerosols and significant local climate impacts - for example, changes to the Asian monsoon system - studies have also shown influences on remote climate. Sulfate aerosols are particularly important for East Asia, remaining at constant levels higher than column burdens of other aerosol species. If a concerted effort - as laid out by government policies aiming to improve air quality - is made, the effects of anthropogenic aerosols (due to their short atmospheric lifetime) could be quickly reversed. Thus, it is vital to understand the climate impact aerosols have had up to now to aid in determining what will happen in the future. We use transient climate modelling experiments with the Community Earth System Model to investigate the impacts of East Asian sulfate aerosols in the present day compared to 1950 (i.e. before rapid industrialisation in this region), focusing on dynamical mechanisms leading to the occurrence of such impacts, and how their influence can spread to remote regions. We find, in addition to significant monsoon impacts, noticeable shifts in large-scale circulation features such as the ITCZ and the Pacific Walker cell. Through diabatic heating responses, changes to upper-level atmospheric dynamics are evident, leading to downstream effects on surface climate - for example, surface cooling over Europe. Understanding of these impacts is vital when considering how the good intentions of air quality improvement might inadvertently have significant impacts on future climate on regional scales.

Flexible Environments for Grand-Challenge Simulation in Climate Science

NASA Astrophysics Data System (ADS)

Pierrehumbert, R.; Tobis, M.; Lin, J.; Dieterich, C.; Caballero, R.

2004-12-01

Current climate models are monolithic codes, generally in Fortran, aimed at high-performance simulation of the modern climate. Though they adequately serve their designated purpose, they present major barriers to application in other problems. Tailoring them to paleoclimate of planetary simulations, for instance, takes months of work. Theoretical studies, where one may want to remove selected processes or break feedback loops, are similarly hindered. Further, current climate models are of little value in education, since the implementation of textbook concepts and equations in the code is obscured by technical detail. The Climate Systems Center at the University of Chicago seeks to overcome these limitations by bringing modern object-oriented design into the business of climate modeling. Our ultimate goal is to produce an end-to-end modeling environment capable of configuring anything from a simple single-column radiative-convective model to a full 3-D coupled climate model using a uniform, flexible interface. Technically, the modeling environment is implemented as a Python-based software component toolkit: key number-crunching procedures are implemented as discrete, compiled-language components 'glued' together and co-ordinated by Python, combining the high performance of compiled languages and the flexibility and extensibility of Python. We are incrementally working towards this final objective following a series of distinct, complementary lines. We will present an overview of these activities, including PyOM, a Python-based finite-difference ocean model allowing run-time selection of different Arakawa grids and physical parameterizations; CliMT, an atmospheric modeling toolkit providing a library of 'legacy' radiative, convective and dynamical modules which can be knitted into dynamical models, and PyCCSM, a version of NCAR's Community Climate System Model in which the coupler and run-control architecture are re-implemented in Python, augmenting its flexibility and adaptability.

Synchronization and Causality Across Time-scales: Complex Dynamics and Extremes in El Niño/Southern Oscillation

NASA Astrophysics Data System (ADS)

Jajcay, N.; Kravtsov, S.; Tsonis, A.; Palus, M.

2017-12-01

A better understanding of dynamics in complex systems, such as the Earth's climate is one of the key challenges for contemporary science and society. A large amount of experimental data requires new mathematical and computational approaches. Natural complex systems vary on many temporal and spatial scales, often exhibiting recurring patterns and quasi-oscillatory phenomena. The statistical inference of causal interactions and synchronization between dynamical phenomena evolving on different temporal scales is of vital importance for better understanding of underlying mechanisms and a key for modeling and prediction of such systems. This study introduces and applies information theory diagnostics to phase and amplitude time series of different wavelet components of the observed data that characterizes El Niño. A suite of significant interactions between processes operating on different time scales was detected, and intermittent synchronization among different time scales has been associated with the extreme El Niño events. The mechanisms of these nonlinear interactions were further studied in conceptual low-order and state-of-the-art dynamical, as well as statistical climate models. Observed and simulated interactions exhibit substantial discrepancies, whose understanding may be the key to an improved prediction. Moreover, the statistical framework which we apply here is suitable for direct usage of inferring cross-scale interactions in nonlinear time series from complex systems such as the terrestrial magnetosphere, solar-terrestrial interactions, seismic activity or even human brain dynamics.

Downscaling climate information for local disease mapping.

PubMed

Bernardi, M; Gommes, R; Grieser, J

2006-06-01

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

The Equations of Oceanic Motions

NASA Astrophysics Data System (ADS)

Müller, Peter

2006-10-01

Modeling and prediction of oceanographic phenomena and climate is based on the integration of dynamic equations. The Equations of Oceanic Motions derives and systematically classifies the most common dynamic equations used in physical oceanography, from large scale thermohaline circulations to those governing small scale motions and turbulence. After establishing the basic dynamical equations that describe all oceanic motions, M|ller then derives approximate equations, emphasizing the assumptions made and physical processes eliminated. He distinguishes between geometric, thermodynamic and dynamic approximations and between the acoustic, gravity, vortical and temperature-salinity modes of motion. Basic concepts and formulae of equilibrium thermodynamics, vector and tensor calculus, curvilinear coordinate systems, and the kinematics of fluid motion and wave propagation are covered in appendices. Providing the basic theoretical background for graduate students and researchers of physical oceanography and climate science, this book will serve as both a comprehensive text and an essential reference.

Climate impacts on environmental risks evaluated from space: a conceptual approach to the case of Rift Valley Fever in Senegal

PubMed Central

Tourre, Yves M.; Lacaux, Jean-Pierre; Vignolles, Cécile; Lafaye, Murielle

2009-01-01

Background Climate and environment vary across many spatio-temporal scales, including the concept of climate change, which impact on ecosystems, vector-borne diseases and public health worldwide. Objectives To develop a conceptual approach by mapping climatic and environmental conditions from space and studying their linkages with Rift Valley Fever (RVF) epidemics in Senegal. Design Ponds in which mosquitoes could thrive were identified from remote sensing using high-resolution SPOT-5 satellite images. Additional data on pond dynamics and rainfall events (obtained from the Tropical Rainfall Measuring Mission) were combined with hydrological in-situ data. Localisation of vulnerable hosts such as penned cattle (from QuickBird satellite) were also used. Results Dynamic spatio-temporal distribution of Aedes vexans density (one of the main RVF vectors) is based on the total rainfall amount and ponds’ dynamics. While Zones Potentially Occupied by Mosquitoes are mapped, detailed risk areas, i.e. zones where hazards and vulnerability occur, are expressed in percentages of areas where cattle are potentially exposed to mosquitoes’ bites. Conclusions This new conceptual approach, using precise remote-sensing techniques, simply relies upon rainfall distribution also evaluated from space. It is meant to contribute to the implementation of operational early warning systems for RVF based on both natural and anthropogenic climatic and environmental changes. In a climate change context, this approach could also be applied to other vector-borne diseases and places worldwide. PMID:20052381

Multiple methods for multiple futures: Integrating qualitative scenario planning and quantitative simulation modeling for natural resource decision making

USGS Publications Warehouse

Symstad, Amy J.; Fisichelli, Nicholas A.; Miller, Brian W.; Rowland, Erika; Schuurman, Gregor W.

2017-01-01

Scenario planning helps managers incorporate climate change into their natural resource decision making through a structured “what-if” process of identifying key uncertainties and potential impacts and responses. Although qualitative scenarios, in which ecosystem responses to climate change are derived via expert opinion, often suffice for managers to begin addressing climate change in their planning, this approach may face limits in resolving the responses of complex systems to altered climate conditions. In addition, this approach may fall short of the scientific credibility managers often require to take actions that differ from current practice. Quantitative simulation modeling of ecosystem response to climate conditions and management actions can provide this credibility, but its utility is limited unless the modeling addresses the most impactful and management-relevant uncertainties and incorporates realistic management actions. We use a case study to compare and contrast management implications derived from qualitative scenario narratives and from scenarios supported by quantitative simulations. We then describe an analytical framework that refines the case study’s integrated approach in order to improve applicability of results to management decisions. The case study illustrates the value of an integrated approach for identifying counterintuitive system dynamics, refining understanding of complex relationships, clarifying the magnitude and timing of changes, identifying and checking the validity of assumptions about resource responses to climate, and refining management directions. Our proposed analytical framework retains qualitative scenario planning as a core element because its participatory approach builds understanding for both managers and scientists, lays the groundwork to focus quantitative simulations on key system dynamics, and clarifies the challenges that subsequent decision making must address.

Explicit Convection over the Western Pacific Warm Pool in the Community Atmospheric Model.

NASA Astrophysics Data System (ADS)

Ziemiaski, Micha Z.; Grabowski, Wojciech W.; Moncrieff, Mitchell W.

2005-05-01

This paper reports on the application of the cloud-resolving convection parameterization (CRCP) to the Community Atmospheric Model (CAM), the atmospheric component of the Community Climate System Model (CCSM). The cornerstone of CRCP is the use of a two-dimensional zonally oriented cloud-system-resolving model to represent processes on mesoscales at the subgrid scale of a climate model. Herein, CRCP is applied at each climate model column over the tropical western Pacific warm pool, in a domain spanning 10°S-10°N, 150°-170°E. Results from the CRCP simulation are compared with CAM in its standard configuration.The CRCP simulation shows significant improvements of the warm pool climate. The cloud condensate distribution is much improved as well as the bias of the tropopause height. More realistic structure of the intertropical convergence zone (ITCZ) during the boreal winter and better representation of the variability of convection are evident. In particular, the diurnal cycle of precipitation has phase and amplitude in good agreement with observations. Also improved is the large-scale organization of the tropical convection, especially superclusters associated with Madden-Julian oscillation (MJO)-like systems. Location and propagation characteristics, as well as lower-tropospheric cyclonic and upper-tropospheric anticyclonic gyres, are more realistic than in the standard CAM. Finally, the simulations support an analytic theory of dynamical coupling between organized convection and equatorial beta-plane vorticity dynamics associated with MJO-like systems.

Impact of Seasonal Variability in Water, Plant and Soil Nutrient Dynamics in Agroecosystems

NASA Astrophysics Data System (ADS)

Pelak, N. F., III; Revelli, R.; Porporato, A. M.

2017-12-01

Agroecosystems cover a significant fraction of the Earth's surface, making their water and nutrient cycles a major component of global cycles across spatial and temporal scales. Most agroecosystems experience seasonality via variations in precipitation, temperature, and radiation, in addition to human activities which also occur seasonally, such as fertilization, irrigation, and harvesting. These seasonal drivers interact with the system in complex ways which are often poorly characterized. Crop models, which are widely used for research, decision support, and prediction of crop yields, are among the best tools available to analyze these systems. Though normally constructed as a set of dynamical equations forced by hydroclimatic variability, they are not often analyzed using dynamical systems theory and methods from stochastic ecohydrology. With the goal of developing this viewpoint and thus elucidating the roles of key feedbacks and forcings on system stability and on optimal fertilization and irrigation strategies, we develop a minimal dynamical system which contains the key components of a crop model, coupled to a carbon and nitrogen cycling model, driven by seasonal fluctuations in water and nutrient availability, temperature, and radiation. External drivers include seasonally varying climatic conditions and random rainfall forcing, irrigation and fertilization as well as harvesting. The model is used to analyze the magnitudes and interactions of the effects of seasonality on carbon and nutrient cycles, crop productivity, nutrient export of agroecosystems, and optimal management strategies with reference to productivity, sustainability and profitability. The impact of likely future climate scenarios on these systems is also discussed.

Extracting Leading Nonlinear Modes of Changing Climate From Global SST Time Series

NASA Astrophysics Data System (ADS)

Mukhin, D.; Gavrilov, A.; Loskutov, E. M.; Feigin, A. M.; Kurths, J.

2017-12-01

Data-driven modeling of climate requires adequate principal variables extracted from observed high-dimensional data. For constructing such variables it is needed to find spatial-temporal patterns explaining a substantial part of the variability and comprising all dynamically related time series from the data. The difficulties of this task rise from the nonlinearity and non-stationarity of the climate dynamical system. The nonlinearity leads to insufficiency of linear methods of data decomposition for separating different processes entangled in the observed time series. On the other hand, various forcings, both anthropogenic and natural, make the dynamics non-stationary, and we should be able to describe the response of the system to such forcings in order to separate the modes explaining the internal variability. The method we present is aimed to overcome both these problems. The method is based on the Nonlinear Dynamical Mode (NDM) decomposition [1,2], but takes into account external forcing signals. An each mode depends on hidden, unknown a priori, time series which, together with external forcing time series, are mapped onto data space. Finding both the hidden signals and the mapping allows us to study the evolution of the modes' structure in changing external conditions and to compare the roles of the internal variability and forcing in the observed behavior. The method is used for extracting of the principal modes of SST variability on inter-annual and multidecadal time scales accounting the external forcings such as CO2, variations of the solar activity and volcanic activity. The structure of the revealed teleconnection patterns as well as their forecast under different CO2 emission scenarios are discussed.[1] Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. [2] Gavrilov, A., Mukhin, D., Loskutov, E., Volodin, E., Feigin, A., & Kurths, J. (2016). Method for reconstructing nonlinear modes with adaptive structure from multidimensional data. Chaos: An Interdisciplinary Journal of Nonlinear Science, 26(12), 123101.

Carbon-climate-human interactions in an integrated human-Earth system model

NASA Astrophysics Data System (ADS)

Calvin, K. V.; Bond-Lamberty, B. P.; Jones, A. D.; Shi, X.

2016-12-01

The C4MIP and CMIP5 results highlighted large uncertainties in climate projections, driven to a large extent by limited understanding of the interactions between terrestrial carbon-cycle and climate feedbacks, and their associated uncertainties. These feedbacks are dominated by uncertainties in soil processes, disturbance dynamics, ecosystem response to climate change, and agricultural productivity, and land-use change. This research addresses three questions: (1) how do terrestrial feedbacks vary across different levels of climate change, (2) what is the relative contribution of CO2 fertilization and climate change, and (3) how robust are the results across different models and methods? We used a coupled modeling framework that integrates an Integrated Assessment Model (modeling economic and energy activity) with an Earth System Model (modeling the natural earth system) to examine how business-as-usual (RCP 8.5) climate change will affect ecosystem productivity, cropland extent, and other aspects of the human-Earth system. We find that higher levels of radiative forcing result in higher productivity growth, that increases in CO2 concentrations are the dominant contributors to that growth, and that our productivity increases fall in the middle of the range when compared to other CMIP5 models and the AgMIP models. These results emphasize the importance of examining both the anthropogenic and natural components of the earth system, and their long-term interactive feedbacks.

Earth System Model Needs for Including the Interactive Representation of Nitrogen Deposition and Drought Effects on Forested Ecosystems

DOE PAGES

Drewniak, Beth; Gonzalez-Meler, Miquel

2017-07-27

One of the biggest uncertainties of climate change is determining the response of vegetation to many co-occurring stressors. In particular, many forests are experiencing increased nitrogen deposition and are expected to suffer in the future from increased drought frequency and intensity. Interactions between drought and nitrogen deposition are antagonistic and non-additive, which makes predictions of vegetation response dependent on multiple factors. The tools we use (Earth system models) to evaluate the impact of climate change on the carbon cycle are ill equipped to capture the physiological feedbacks and dynamic responses of ecosystems to these types of stressors. In this manuscript,more » we review the observed effects of nitrogen deposition and drought on vegetation as they relate to productivity, particularly focusing on carbon uptake and partitioning. We conclude there are several areas of model development that can improve the predicted carbon uptake under increasing nitrogen deposition and drought. This includes a more flexible framework for carbon and nitrogen partitioning, dynamic carbon allocation, better representation of root form and function, age and succession dynamics, competition, and plant modeling using trait-based approaches. These areas of model development have the potential to improve the forecasting ability and reduce the uncertainty of climate models.« less

Earth System Model Needs for Including the Interactive Representation of Nitrogen Deposition and Drought Effects on Forested Ecosystems

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

Drewniak, Beth; Gonzalez-Meler, Miquel

One of the biggest uncertainties of climate change is determining the response of vegetation to many co-occurring stressors. In particular, many forests are experiencing increased nitrogen deposition and are expected to suffer in the future from increased drought frequency and intensity. Interactions between drought and nitrogen deposition are antagonistic and non-additive, which makes predictions of vegetation response dependent on multiple factors. The tools we use (Earth system models) to evaluate the impact of climate change on the carbon cycle are ill equipped to capture the physiological feedbacks and dynamic responses of ecosystems to these types of stressors. In this manuscript,more » we review the observed effects of nitrogen deposition and drought on vegetation as they relate to productivity, particularly focusing on carbon uptake and partitioning. We conclude there are several areas of model development that can improve the predicted carbon uptake under increasing nitrogen deposition and drought. This includes a more flexible framework for carbon and nitrogen partitioning, dynamic carbon allocation, better representation of root form and function, age and succession dynamics, competition, and plant modeling using trait-based approaches. These areas of model development have the potential to improve the forecasting ability and reduce the uncertainty of climate models.« less

Adapting agriculture to climate change.

PubMed

Howden, S Mark; Soussana, Jean-François; Tubiello, Francesco N; Chhetri, Netra; Dunlop, Michael; Meinke, Holger

2007-12-11

The strong trends in climate change already evident, the likelihood of further changes occurring, and the increasing scale of potential climate impacts give urgency to addressing agricultural adaptation more coherently. There are many potential adaptation options available for marginal change of existing agricultural systems, often variations of existing climate risk management. We show that implementation of these options is likely to have substantial benefits under moderate climate change for some cropping systems. However, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. We argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. Dealing with the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of scales and issues, for example, from the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. Science, too, has to adapt. Multidisciplinary problems require multidisciplinary solutions, i.e., a focus on integrated rather than disciplinary science and a strengthening of the interface with decision makers. A crucial component of this approach is the implementation of adaptation assessment frameworks that are relevant, robust, and easily operated by all stakeholders, practitioners, policymakers, and scientists.

Toward an integrated monitoring framework to assess the effects of tropical forest degradation and recovery on carbon stocks and biodiversity

Treesearch

Mercedes M. C. Bustamante; Iris Roitman; T. Mitchell Aide; Ane Alencar; Liana O. Anderson; Luiz Aragao; Gregory P. Asner; Jos Barlow; Erika Berenguer; Jeffrey Chambers; Marcos H. Costa; Thierry Fanin; Laerte G. Ferreira; Joice Ferreira; Michael Keller; William E. Magnusson; Lucia Morales-Barquero; Douglas Morton; Jean P. H. B. Ometto; Michael Palace; Carlos A. Peres; Divino Silverio; Susan Trumbore; Ima C. G. Vieira

2015-01-01

Tropical forests harbor a significant portion of global biodiversity and are a critical component of the climate system. Reducing deforestation and forest degradation contributes to global climate-change mitigation efforts, yet emissions and removals from forest dynamics are still poorly quantified. We reviewed the main challenges to estimate changes in carbon stocks...

The integrated Earth system model version 1: formulation and functionality

DOE PAGES

Collins, W. D.; Craig, A. P.; Truesdale, J. E.; ...

2015-07-23

The integrated Earth system model (iESM) has been developed as a new tool for projecting the joint human/climate system. The iESM is based upon coupling an integrated assessment model (IAM) and an Earth system model (ESM) into a common modeling infrastructure. IAMs are the primary tool for describing the human–Earth system, including the sources of global greenhouse gases (GHGs) and short-lived species (SLS), land use and land cover change (LULCC), and other resource-related drivers of anthropogenic climate change. ESMs are the primary scientific tools for examining the physical, chemical, and biogeochemical impacts of human-induced changes to the climate system. Themore » iESM project integrates the economic and human-dimension modeling of an IAM and a fully coupled ESM within a single simulation system while maintaining the separability of each model if needed. Both IAM and ESM codes are developed and used by large communities and have been extensively applied in recent national and international climate assessments. By introducing heretofore-omitted feedbacks between natural and societal drivers, we can improve scientific understanding of the human–Earth system dynamics. Potential applications include studies of the interactions and feedbacks leading to the timing, scale, and geographic distribution of emissions trajectories and other human influences, corresponding climate effects, and the subsequent impacts of a changing climate on human and natural systems. This paper describes the formulation, requirements, implementation, testing, and resulting functionality of the first version of the iESM released to the global climate community.« less

Collaborative Research: Robust Climate Projections and Stochastic Stability of Dynamical Systems

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

Ghil, Michael; McWilliams, James; Neelin, J. David

The project was completed along the lines of the original proposal, with additional elements arising as new results were obtained. The originally proposed three thrusts were expanded to include an additional, fourth one. (i) The e ffects of stochastic perturbations on climate models have been examined at the fundamental level by using the theory of deterministic and random dynamical systems, in both nite and in nite dimensions. (ii) The theoretical results have been implemented first on a delay-diff erential equation (DDE) model of the El-Nino/Southern-Oscillation (ENSO) phenomenon. (iii) More detailed, physical aspects of model robustness have been considered, as proposed,more » within the stripped-down ICTP-AGCM (formerly SPEEDY) climate model. This aspect of the research has been complemented by both observational and intermediate-model aspects of mid-latitude and tropical climate. (iv) An additional thrust of the research relied on new and unexpected results of (i) and involved reduced-modeling strategies and associated prediction aspects have been tested within the team's empirical model reduction (EMR) framework. Finally, more detailed, physical aspects have been considered within the stripped-down SPEEDY climate model. The results of each of these four complementary e fforts are presented in the next four sections, organized by topic and by the team members concentrating on the topic under discussion.« less

The Aerosol-Monsoon Climate System of Asia

NASA Technical Reports Server (NTRS)

Lau, William K. M.; Kyu-Myong, Kim

2012-01-01

In Asian monsoon countries such as China and India, human health and safety problems caused by air-pollution are worsening due to the increased loading of atmospheric pollutants stemming from rising energy demand associated with the rapid pace of industrialization and modernization. Meanwhile, uneven distribution of monsoon rain associated with flash flood or prolonged drought, has caused major loss of human lives, and damages in crop and properties with devastating societal impacts on Asian countries. Historically, air-pollution and monsoon research are treated as separate problems. However a growing number of recent studies have suggested that the two problems may be intrinsically intertwined and need to be studied jointly. Because of complexity of the dynamics of the monsoon systems, aerosol impacts on monsoons and vice versa must be studied and understood in the context of aerosol forcing in relationship to changes in fundamental driving forces of the monsoon climate system (e.g. sea surface temperature, land-sea contrast etc.) on time scales from intraseasonal variability (weeks) to climate change ( multi-decades). Indeed, because of the large contributions of aerosols to the global and regional energy balance of the atmosphere and earth surface, and possible effects of the microphysics of clouds and precipitation, a better understanding of the response to climate change in Asian monsoon regions requires that aerosols be considered as an integral component of a fully coupled aerosol-monsoon system on all time scales. In this paper, using observations and results from climate modeling, we will discuss the coherent variability of the coupled aerosol-monsoon climate system in South Asia and East Asia, including aerosol distribution and types, with respect to rainfall, moisture, winds, land-sea thermal contrast, heat sources and sink distributions in the atmosphere in seasonal, interannual to climate change time scales. We will show examples of how elevated absorbing aerosols (dust and black carbon) may interact with monsoon dynamics to produce feedback effects on the atmospheric water cycle, leading to in accelerated melting of snowpacks over the Himalayas and Tibetan Plateau, and subsequent changes in evolution of the pre-monsoon and peak monsoon rainfall, moisture and wind distributions in South Asia and East Asia.

A biologically-based individual tree model for managing the longleaf pine ecosystem

Treesearch

Rick Smith; Greg Somers

1998-01-01

Duration: 1995-present Objective: Develop a longleaf pine dynamics model and simulation system to define desirable ecosystem management practices in existing and future longleaf pine stands. Methods: Naturally-regenerated longleaf pine trees are being destructively sampled to measure their recent growth and dynamics. Soils and climate data will be combined with the...

"Time-dependent flow-networks"

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Molkentin, Nora; Lopez, Cristobal; Hernandez-Garcia, Emilio; Marwan, Norbert; Kurths, Jürgen

2015-04-01

Complex networks have been successfully applied to various systems such as society, technology, and recently climate. Links in a climate network are defined between two geographical locations if the correlation between the time series of some climate variable is higher than a threshold. Therefore, network links are considered to imply information or heat exchange. However, the relationship between the oceanic and atmospheric flows and the climate network's structure is still unclear. Recently, a theoretical approach verifying the correlation between ocean currents and surface air temperature networks has been introduced, where the Pearson correlation networks were constructed from advection-diffusion dynamics on an underlying flow. Since the continuous approach has its limitations, i.e. high computational complexity and fixed variety of the flows in the underlying system, we introduce a new, method of flow-networks for changing in time velocity fields including external forcing in the system, noise and temperature-decay. Method of the flow-network construction can be divided into several steps: first we obtain the linear recursive equation for the temperature time-series. Then we compute the correlation matrix for time-series averaging the tensor product over all realizations of the noise, which we interpret as a weighted adjacency matrix of the flow-network and analyze using network measures. We apply the method to different types of moving flows with geographical relevance such as meandering flow. Analyzing the flow-networks using network measures we find that our approach can highlight zones of high velocity by degree and transition zones by betweenness, while the combination of these network measures can uncover how the flow propagates within time. Flow-networks can be powerful tool to understand the connection between system's dynamics and network's topology analyzed using network measures in order to shed light on different climatic phenomena.

500-year climate cycles stacking of recent centennial warming documented in an East Asian pollen record

PubMed Central

Xu, Deke; Lu, Houyuan; Chu, Guoqiang; Wu, Naiqin; Shen, Caiming; Wang, Can; Mao, Limi

2014-01-01

Here we presented a high-resolution 5350-year pollen record from a maar annually laminated lake in East Asia (EA). Pollen record reflected the dynamics of vertical vegetation zones and temperature change. Spectral analysis on pollen percentages/concentrations of Pinus and Quercus, and a temperature proxy, revealed ~500-year quasi-periodic cold-warm fluctuations during the past 5350 years. This ~500-year cyclic climate change occurred in EA during the mid-late Holocene and even the last 150 years dominated by anthropogenic forcing. It was almost in phase with a ~500-year periodic change in solar activity and Greenland temperature change, suggesting that ~500-year small variations in solar output played a prominent role in the mid-late Holocene climate dynamics in EA, linked to high latitude climate system. Its last warm phase might terminate in the next several decades to enter another ~250-year cool phase, and thus this future centennial cyclic temperature minimum could partially slow down man-made global warming. PMID:24402348

Hourly test reference weather data in the changing climate of Finland for building energy simulations.

PubMed

Jylhä, Kirsti; Ruosteenoja, Kimmo; Jokisalo, Juha; Pilli-Sihvola, Karoliina; Kalamees, Targo; Mäkelä, Hanna; Hyvönen, Reijo; Drebs, Achim

2015-09-01

Dynamic building energy simulations need hourly weather data as input. The same high temporal resolution is required for assessments of future heating and cooling energy demand. The data presented in this article concern current typical values and estimated future changes in outdoor air temperature, wind speed, relative humidity and global, diffuse and normal solar radiation components. Simulated annual and seasonal delivered energy consumptions for heating of spaces, heating of ventilation supply air and cooling of spaces in the current and future climatic conditions are also presented for an example house, with district heating and a mechanical space cooling system. We provide details on how the synthetic future weather files were created and utilised as input data for dynamic building energy simulations by the IDA Indoor Climate and Energy program and also for calculations of heating and cooling degree-day sums. The information supplied here is related to the research article titled "Energy demand for the heating and cooling of residential houses in Finland in a changing climate" [1].

Two-way against one-way nesting for climate downscaling in Europe and the Mediterranean region using LMDZ4

NASA Astrophysics Data System (ADS)

Li, Shan; Li, Laurent; Le Treut, Hervé

2016-04-01

In the 21st century, the estimated surface temperature warming projected by General Circulation Models (GCMs) is between 0.3 and 4.8 °C, depending on the scenario considered. GCMs exhibit a good representation of climate on a global scale, but they are not able to reproduce regional climate processes with the same level of accuracy. Society and policymakers need model projections to define climate change adaptation and mitigation policies on a global, regional and local scale. Climate downscaling is mostly conducted with a regional model nested into the outputs of a global model. This one-way nesting approach is generally used in the climate community without feedbacks from Regional Climate Models (RCMs) to GCMs. This lack of interaction between the two models may affect regional modes of variability, in particular those with a boundary conflict. The objective of this study is to evaluate a two-way nesting configuration that makes an interactive coupling between the RCM and the GCM, an approach against the traditional configuration of one-way nesting system. An additional aim of this work is to examine if the two-way nesting system can improve the RCM performance. The atmospheric component of the IPSL integrated climate model (LMDZ) is configured at both regional (LMDZ-regional) and global (LMDZ-global) scales. The two models have the same configuration for the dynamical framework and the physical forcings. The climatology values of sea surface temperature (SST) are prescribed for the two models. The stretched-grid of LMDZ-global is applied to a region defined by Europe, the Mediterranean, North Africa and Western North Atlantic. To ensure a good statistical significance of results, all simulations last at least 80 years. The nesting process of models is performed by a relaxation procedure of a time scale of 90 minutes. In the case of two-way nesting, the exchange between the two models is every two hours. The relaxation procedure induces a boundary conflict, particularly in the eastern boundary for temperature and geopotential height. A correlation analysis on the synoptic scale evaluates the relationship between the GCM and the RCM. The beginning of the simulations shows a great consistency of the two models. When dominant dynamics apply, RCM inherits most of the GCM signal with a consistent spatial structure. On the contrary, when the atmospheric circulation is weak, there are not that many effects transferred from the GCM to the RCM. When the RCM has its own dynamics, the boundary conflict is more pronounced. Winter season is chosen for the two-way nesting test due to the predominant role of the atmospheric dynamics in winter. The new approach of a two-way nesting system reduces boundary bias, having a influence in some cases in climate model projections. The effect of two-way nesting is enhanced when using a finer grid.

Understanding the Dynamics of Socio-Hydrological Environment: a Conceptual Framework

NASA Astrophysics Data System (ADS)

Woyessa, Y.; Welderufael, W.; Edossa, D.

2011-12-01

Human actions affect ecological systems and the services they provide through various activities, such as land use, water use, pollution and climate change. Climate change is perhaps one of the most important sustainable development challenges that threaten to undo many of the development efforts being made to reach the targets set for the Millennium Development Goals. Understanding the change of ecosystems under different scenarios of climate and biophysical conditions could assist in bringing the issue of ecosystem services into decision making process. Similarly, the impacts of land use change on ecosystems and biodiversity have received considerable attention from ecologists and hydrologists alike. Land use change in a catchment can impact on water supply by altering hydrological processes, such as infiltration, groundwater recharge, base flow and direct runoff. In the past a variety of models were used for predicting land-use changes. Recently the focus has shifted away from using mathematically oriented models to agent-based modelling (ABM) approach to simulate land use scenarios. A conceptual framework is being developed which integrates climate change scenarios and the human dimension of land use decision into a hydrological model in order to assess its impacts on the socio-hydrological dynamics of a river basin. The following figures present the framework for the analysis and modelling of the socio-hydrological dynamics. Keywords: climate change, land use, river basin

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

Characterising groundwater dynamics in Western Victoria, Australia using Menyanthes software

NASA Astrophysics Data System (ADS)

Woldeyohannes, Yohannes; Webb, John

2010-05-01

Water table across much of the western Victoria, Australia have been declining for at least the last 10-15 years, and this is attributed to the consistently low rainfall for these years, but over the same period of time there has been substantial change in land use, with grazing land replaced by cropping and tree plantations appearing in some areas. Hence, it is important to determine the relative effect the climate and land use factors on the water table changes. Monitoring changes in groundwater levels to climate variables and/or land use change is helpful in indicating the degree of threat faced to agricultural and public assets. The dynamics of the groundwater system in the western Victoria, mainly on the basalt plain, have been modelled to determine the climatic influence in water table fluctuations. In this study, a standardized computer package Menyanthes was used for quantifying the influence of climatic variables on the groundwater level, statistically estimating trends in groundwater levels and identify the properties that determine the dynamics of groundwater system. This method is optimized for use on hydrological problems and is based on the use of continuous time transfer function noise model, which estimates the Impulse response function of the system from the temporal correlation between time series of groundwater level and precipitation surplus. In this approach, the spatial differences in the groundwater system are determined by the system properties, while temporal variation is driven by the dynamics of the input into the system. 80 time series models are analysed and the model output parameter values characterized by their moments. The zero-order moment Mo of a distribution function is its area and M1 is related to the mean of the impulse response function. The relation is M1/Mo. It is a measure of the system's memory. It takes approximately 3 times the mean time (M1/Mo) for the effect of a shower to disappear completely from the system. Overall, the model fitted the data well, explaining 89% (median value of R2) of variation in groundwater level using the climatic variables (rainfall and evaporation) left without significant trend (-0.046 m/yr, on average), which is within the range of variable input standard error. The average estimated system response (memory to disappear) is 5.2 years which is less than by 1/10th of the previously estimated time using Ground Water Flow System approach. The average Mo is 1.45 m, which means that a precipitation of 365 mm/yr will eventually lead to a ground water level rise of 1.45 m on the location. The Menyanthes result is compared with HARTT (Hydrograph Analysis and Time Trends) method. The trend and Mo estimate using Menyanthes and HARTT show comparable result. From a time series analysis there is no indication that the groundwater table was rising/falling due to changes in landuse, at least not during the observation period.

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

NASA Technical Reports Server (NTRS)

Funk, Chris; Peterson, Pete; Shukla, Shraddhanand; Husak, Gregory; Landsfeld, Marty; Hoell, Andrew; Pedreros, Diego; Roberts, J. B.; Robertson, F. R.; Tadesse, Tsegae;

Assessment of Climate Impact Changes on Forest Vegetation Dynamics by Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Zoran, Maria

Climate variability represents the ensemble of net radiation, precipitation, wind and temper-ature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Forest vegetation phenology constitutes an efficient bio-indicator of climate and anthropogenic changes impacts and a key parameter for understanding and modelling vegetation-climate in-teractions. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vege-tation Index (NDVIs), which requires NDVI time-series with good time resolution, over homo-geneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2008 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and to-pography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

Gharbia, Salem S; Smullen, Trevor; Gill, Laurence; Johnston, Paul; Pilla, Francesco

2018-08-15

Evapotranspiration integrates energy and mass transfer between the Earth's surface and atmosphere and is the most active mechanism linking the atmosphere, hydrosphsophere, lithosphere and biosphere. This study focuses on the fine resolution modeling and projection of spatially distributed potential evapotranspiration on the large catchment scale as response to climate change. Six potential evapotranspiration designed algorithms, systematically selected based on a structured criteria and data availability, have been applied and then validated to long-term mean monthly data for the Shannon River catchment with a 50m 2 cell size. The best validated algorithm was therefore applied to evaluate the possible effect of future climate change on potential evapotranspiration rates. Spatially distributed potential evapotranspiration projections have been modeled based on climate change projections from multi-GCM ensembles for three future time intervals (2020, 2050 and 2080) using a range of different Representative Concentration Pathways producing four scenarios for each time interval. Finally, seasonal results have been compared to baseline results to evaluate the impact of climate change on the potential evapotranspiration and therefor on the catchment dynamical water balance. The results present evidence that the modeled climate change scenarios would have a significant impact on the future potential evapotranspiration rates. All the simulated scenarios predicted an increase in potential evapotranspiration for each modeled future time interval, which would significantly affect the dynamical catchment water balance. This study addresses the gap in the literature of using GIS-based algorithms to model fine-scale spatially distributed potential evapotranspiration on the large catchment systems based on climatological observations and simulations in different climatological zones. Providing fine-scale potential evapotranspiration data is very crucial to assess the dynamical catchment water balance to setup management scenarios for the water abstractions. This study illustrates a transferable systematic method to design GIS-based algorithms to simulate spatially distributed potential evapotranspiration on the large catchment systems. Copyright © 2018 Elsevier B.V. All rights reserved.

Modeling Climate and Societal Resilience in the Mediterranean During the Last Millennium

NASA Astrophysics Data System (ADS)

Wagner, S.; Xoplaki, E.; Luterbacher, J.; Zorita, E.; Fleitmann, D.; Preiser-Kapeller, J.; Toreti, A., , Dr; Sargent, A. M.; Bozkurt, D.; White, S.; Haldon, J. F.; Akçer-Ön, S.; Izdebski, A.

2017-12-01

Past civilisations were influenced by complex external and internal forces, including changes in the environment, climate, politics and economy. A geographical hotspot of the interplay between those agents is the Mediterranean, a cradle of cultural and scientific development. We analyse a novel compilation of high-quality hydroclimate proxy records and spatial reconstructions from the Mediterranean and compare them with two Earth System Model simulations (CCSM4, MPI-ESM-P) for three historical time intervals - the Crusaders, 1095-1290 CE; the Mamluk regime in Transjordan, 1260-1516 CE; and the Ottoman crisis and Celâlî Rebellion, 1580-1610 CE - when environmental and climatic stress tested the resilience of complex societies. ESMs provide important information on the dynamical mechanisms and underlying processes that led to anomalous hydroclimatic conditions of the past. We find that the multidecadal precipitation and drought variations in the Central and Eastern Mediterranean during the three periods cannot be explained by external forcings (solar variations, tropical volcanism); rather they were driven by internal climate dynamics. The integrated analysis of palaeoclimate proxies, climate reconstructions and model simulations sheds light on our understanding of past climate change and its societal impact. Finally, our research emphasises the need to further study the societal dimension of environmental and climate change in the past, in order to properly understand the role that climate has played in human history.

What might we learn from climate forecasts?

PubMed Central

Smith, Leonard A.

2002-01-01

Most climate models are large dynamical systems involving a million (or more) variables on big computers. Given that they are nonlinear and not perfect, what can we expect to learn from them about the earth's climate? How can we determine which aspects of their output might be useful and which are noise? And how should we distribute resources between making them “better,” estimating variables of true social and economic interest, and quantifying how good they are at the moment? Just as “chaos” prevents accurate weather forecasts, so model error precludes accurate forecasts of the distributions that define climate, yielding uncertainty of the second kind. Can we estimate the uncertainty in our uncertainty estimates? These questions are discussed. Ultimately, all uncertainty is quantified within a given modeling paradigm; our forecasts need never reflect the uncertainty in a physical system. PMID:11875200

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).

Aging Water Infrastructure and Nutrient Control at WWTPs: U.S. Environmental Protection Agency Research Program

EPA Science Inventory

What are… the effects of major influencing factors (climate change, population dynamics, etc.) on future system demands? the innovative technologies that can cost-effectively improve performance and extend the life of existing systems? the new designs and management approaches...

Climate change and human health: a One Health approach.

PubMed

Patz, Jonathan A; Hahn, Micah B

2013-01-01

Climate change adds complexity and uncertainty to human health issues such as emerging infectious diseases, food security, and national sustainability planning that intensify the importance of interdisciplinary and collaborative research. Collaboration between veterinary, medical, and public health professionals to understand the ecological interactions and reactions to flux in a system can facilitate clearer understanding of climate change impacts on environmental, animal, and human health. Here we present a brief introduction to climate science and projections for the next century and a review of current knowledge on the impacts of climate-driven environmental change on human health. We then turn to the links between ecological and evolutionary responses to climate change and health. The literature on climate impacts on biological systems is rich in both content and historical data, but the connections between these changes and human health is less understood. We discuss five mechanisms by which climate changes impacts on biological systems will be felt by the human population: Modifications in Vector, Reservoir, and Pathogen Lifecycles; Diseases of Domestic and Wild Animals and Plants; Disruption of Synchrony Between Interacting Species; Trophic Cascades; and Alteration or Destruction of Habitat. Each species responds to environmental changes differently, and in order to predict the movement of disease through ecosystems, we have to rely on expertise from the fields of veterinary, medical, and public health, and these health professionals must take into account the dynamic nature of ecosystems in a changing climate.

Understanding the Impacts of Climate Change and Land Use Dynamics Using a Fully Coupled Hydrologic Feedback Model between Surface and Subsurface Systems

NASA Astrophysics Data System (ADS)

Park, C.; Lee, J.; Koo, M.

2011-12-01

Climate is the most critical driving force of the hydrologic system of the Earth. Since the industrial revolution, the impacts of anthropogenic activities to the Earth environment have been expanded and accelerated. Especially, the global emission of carbon dioxide into the atmosphere is known to have significantly increased temperature and affected the hydrologic system. Many hydrologists have contributed to the studies regarding the climate change on the hydrologic system since the Intergovernmental Panel on Climate Change (IPCC) was created in 1988. Among many components in the hydrologic system groundwater and its response to the climate change and anthropogenic activities are not fully understood due to the complexity of subsurface conditions between the surface and the groundwater table. A new spatio-temporal hydrologic model has been developed to estimate the impacts of climate change and land use dynamics on the groundwater. The model consists of two sub-models: a surface model and a subsurface model. The surface model involves three surface processes: interception, runoff, and evapotranspiration, and the subsurface model does also three subsurface processes: soil moisture balance, recharge, and groundwater flow. The surface model requires various input data including land use, soil types, vegetation types, topographical elevations, and meteorological data. The surface model simulates daily hydrological processes for rainfall interception, surface runoff varied by land use change and crop growth, and evapotranspiration controlled by soil moisture balance. The daily soil moisture balance is a key element to link two sub-models as it calculates infiltration and groundwater recharge by considering a time delay routing through a vadose zone down to the groundwater table. MODFLOW is adopted to simulate groundwater flow and interaction with surface water components as well. The model is technically flexible to add new model or modify existing model as it is developed with an object-oriented language - Python. The model also can easily be localized by simple modification of soil and crop properties. The actual application of the model after calibration was successful and results showed reliable water balance and interaction between the surface and subsurface hydrologic systems.

Regional climate projection of the Maritime Continent using the MIT Regional Climate Model

NASA Astrophysics Data System (ADS)

IM, E. S.; Eltahir, E. A. B.

2014-12-01

Given that warming of the climate system is unequivocal (IPCC AR5), accurate assessment of future climate is essential to understand the impact of climate change due to global warming. Modelling the climate change of the Maritime Continent is particularly challenge, showing a high degree of uncertainty. Compared to other regions, model agreement of future projections in response to anthropogenic emission forcings is much less. Furthermore, the spatial and temporal behaviors of climate projections seem to vary significantly due to a complex geographical condition and a wide range of scale interactions. For the fine-scale climate information (27 km) suitable for representing the complexity of climate change over the Maritime Continent, dynamical downscaling is performed using the MIT regional climate model (MRCM) during two thirty-year period for reference (1970-1999) and future (2070-2099) climate. Initial and boundary conditions are provided by Community Earth System Model (CESM) simulations under the emission scenarios projected by MIT Integrated Global System Model (IGSM). Changes in mean climate as well as the frequency and intensity of extreme climate events are investigated at various temporal and spatial scales. Our analysis is primarily centered on the different behavior of changes in convective and large-scale precipitation over land vs. ocean during dry vs. wet season. In addition, we attempt to find the added value to downscaled results over the Maritime Continent through the comparison between MRCM and CESM projection. Acknowledgements.This research was supported by the National Research Foundation Singapore through the Singapore MIT Alliance for Research and Technology's Center for Environmental Sensing and Modeling interdisciplinary research program.

Toward GEOS-6, A Global Cloud System Resolving Atmospheric Model

NASA Technical Reports Server (NTRS)

Putman, William M.

2010-01-01

NASA is committed to observing and understanding the weather and climate of our home planet through the use of multi-scale modeling systems and space-based observations. Global climate models have evolved to take advantage of the influx of multi- and many-core computing technologies and the availability of large clusters of multi-core microprocessors. GEOS-6 is a next-generation cloud system resolving atmospheric model that will place NASA at the forefront of scientific exploration of our atmosphere and climate. Model simulations with GEOS-6 will produce a realistic representation of our atmosphere on the scale of typical satellite observations, bringing a visual comprehension of model results to a new level among the climate enthusiasts. In preparation for GEOS-6, the agency's flagship Earth System Modeling Framework [JDl] has been enhanced to support cutting-edge high-resolution global climate and weather simulations. Improvements include a cubed-sphere grid that exposes parallelism; a non-hydrostatic finite volume dynamical core, and algorithm designed for co-processor technologies, among others. GEOS-6 represents a fundamental advancement in the capability of global Earth system models. The ability to directly compare global simulations at the resolution of spaceborne satellite images will lead to algorithm improvements and better utilization of space-based observations within the GOES data assimilation system

Simulation of Greenhouse Climate Monitoring and Control with Wireless Sensor Network and Event-Based Control

PubMed Central

Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

2009-01-01

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results. PMID:22389597

Simulation of greenhouse climate monitoring and control with wireless sensor network and event-based control.

PubMed

Pawlowski, Andrzej; Guzman, Jose Luis; Rodríguez, Francisco; Berenguel, Manuel; Sánchez, José; Dormido, Sebastián

2009-01-01

Monitoring and control of the greenhouse environment play a decisive role in greenhouse production processes. Assurance of optimal climate conditions has a direct influence on crop growth performance, but it usually increases the required equipment cost. Traditionally, greenhouse installations have required a great effort to connect and distribute all the sensors and data acquisition systems. These installations need many data and power wires to be distributed along the greenhouses, making the system complex and expensive. For this reason, and others such as unavailability of distributed actuators, only individual sensors are usually located in a fixed point that is selected as representative of the overall greenhouse dynamics. On the other hand, the actuation system in greenhouses is usually composed by mechanical devices controlled by relays, being desirable to reduce the number of commutations of the control signals from security and economical point of views. Therefore, and in order to face these drawbacks, this paper describes how the greenhouse climate control can be represented as an event-based system in combination with wireless sensor networks, where low-frequency dynamics variables have to be controlled and control actions are mainly calculated against events produced by external disturbances. The proposed control system allows saving costs related with wear minimization and prolonging the actuator life, but keeping promising performance results. Analysis and conclusions are given by means of simulation results.

Hydrologic drivers of tree biodiversity: The impact of climate change (Invited)

NASA Astrophysics Data System (ADS)

Rodriguez-Iturbe, I.; Konar, M.; Muneepeerakul, R.; Azaele, S.; Bertuzzo, E.; Rinaldo, A.

2009-12-01

Biodiversity of forests is of major importance for society. The possible impact of climate change on the characteristics of tree diversity is a topic of crucial importance with relevant implications for conservation campaigns and resource management. Here we present the main results of the expected biodiversity changes in the Mississippi-Missouri River Basin (MMRS) and two of its subregions under different scenarios of possible climate change. A mechanistic neutral metapopulation model is developed to study the main drivers of large scale biodiversity signatures in the MMRS system. The region is divided into 824 Direct Tributary Areas (DTAs), each one characterized by its own habitat capacity. Data for the spatial occurrence of the 231 species present in the system is taken from the US Forest Service Inventory and Analysis Database. The model has permeable boundaries to account for immigration from the regions surrounding the MMRS. The model accounts for key aspects of ecological dynamics (e.g., birth, death, speciation, and migration) and is fundamentally driven by the mean annual precipitation characteristic of each of the DTAs in the system. It is found that such a simple model, with only four parameters, yields an excellent representation of the observed local species richness (LSR), between-community (β) diversity, and species rank-occupancy function. The mean annual rainfall of each DTA is then changed according to the climate scenarios and new habitat capacities are thus obtained throughout the MMRS and its subregions. The resulting large-scale biodiversity signatures are computed and compared with those of the present scenario, showing that there are very important changes arising from the climate change conditions. For the dry scenarios, it is shown that there is a considerable decrease of species richness, both at local and regional scales, and a contraction of species' geographic ranges. These findings link the hydrologic and ecological dynamics of the MMRS under climate change conditions and are important for a comprehensive evaluation of the climate change impacts over the United States.

Complex Networks Dynamics Based on Events-Phase Synchronization and Intensity Correlation Applied to The Anomaly Patterns and Extremes in The Tropical African Climate System

NASA Astrophysics Data System (ADS)

Oluoch, K.; Marwan, N.; Trauth, M.; Loew, A.; Kurths, J.

2012-04-01

The African continent lie almost entirely within the tropics and as such its (tropical) climate systems are predominantly governed by the heterogeneous, spatial and temporal variability of the Hadley and Walker circulations. The variabilities in these meridional and zonal circulations lead to intensification or suppression of the intensities, durations and frequencies of the Inter-tropical Convergence Zone (ICTZ) migration, trade winds and subtropical high-pressure regions and the continental monsoons. The above features play a central role in determining the African rainfall spatial and temporal variability patterns. The current understanding of these climate features and their influence on the rainfall patterns is not sufficiently understood. Like many real-world systems, atmospheric-oceanic processes exhibit non-linear properties that can be better explored using non-linear (NL) methods of time-series analysis. Over the recent years, the complex network approach has evolved as a powerful new player in understanding spatio-temporal dynamics and evolution of complex systems. Together with NL techniques, it is continuing to find new applications in many areas of science and technology including climate research. We would like to use these two powerful methods to understand the spatial structure and dynamics of African rainfall anomaly patterns and extremes. The method of event synchronization (ES) developed by Quiroga et al., 2002 and first applied to climate networks by Malik et al., 2011 looks at correlations with a dynamic time lag and as such, it is a more intuitive way to correlate a complex and heterogeneous system like climate networks than a fixed time delay most commonly used. On the other hand, the short comings of ES is its lack of vigorous test statistics for the significance level of the correlations, and the fact that only the events' time indices are synchronized while all information about how the relative intensities propagate within network framework is lost. The new method we present is motivated by the ES and borrows ideas from signal processing where a signal is represented by its intensity and frequency. Even though the anomaly signals are not periodic, the idea of phase synchronization is not far fetched. It brings into one umbrella, the traditionally known linear Intensity correlation methods like Pearson correlation, spear-man's rank or non-linear ones like mutual information with the ES for non-linear temporal synchronization. The intensity correlation is only performed where there is a temporal synchronization. The former just measures how constant the intensity differences are. In other words, how monotonic are the two functions. The overall measure of correlation and synchronization is the product of the two coefficients. Complex networks constructed by this technique has all the advantages inherent in each of the techniques it borrows. But, it is more superior and able to uncover many known and unknown dynamical features in rainfall field or any variable of interest. The main aim of this work is to develop a method that can identify the footprints of coherent or incoherent structures within the ICTZ, the African and the Indian monsoons and the ENSO signal on the tropical African continent and their temporal evolution.

Climate change impacts in Zhuoshui watershed, Taiwan

NASA Astrophysics Data System (ADS)

Chao, Yi-Chiung; Liu, Pei-Ling; Cheng, Chao-Tzuen; Li, Hsin-Chi; Wu, Tingyeh; Chen, Wei-Bo; Shih, Hung-Ju

2017-04-01

There are 5.3 typhoons hit Taiwan per year on average in last decade. Typhoon Morakot in 2009, the most severe typhoon, causes huge damage in Taiwan, including 677 casualty and roughly NT 110 billion (3.3 billion USD) in economic loss. Some researches documented that typhoon frequency will decrease but increase in intensity in western North Pacific region. It is usually preferred to use high resolution dynamical model to get better projection of extreme events; because coarse resolution models cannot simulate intense extreme events. Under that consideration, dynamical downscaling climate data was chosen to describe typhoon satisfactorily. One of the aims for Taiwan Climate Change Projection and Information Platform (TCCIP) is to demonstrate the linkage between climate change data and watershed impact models. The purpose is to understand relative disasters induced by extreme rainfall (typhoons) under climate change in watersheds including landslides, debris flows, channel erosion and deposition, floods, and economic loss. The study applied dynamic downscaling approach to release climate change projected typhoon events under RCP 8.5, the worst-case scenario. The Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) and FLO-2D models, then, were used to simulate hillslope disaster impacts in the upstream of Zhuoshui River. CCHE1D model was used to elevate the sediment erosion or deposition in channel. FVCOM model was used to asses a flood impact in urban area in the downstream. Finally, whole potential loss associate with these typhoon events was evaluated by the Taiwan Typhoon Loss Assessment System (TLAS) under climate change scenario. Results showed that the total loss will increase roughly by NT 49.7 billion (1.6 billion USD) in future in Zhuoshui watershed in Taiwan. The results of this research could help to understand future impact; however model bias still exists. Because typhoon track is a critical factor to consider regional disaster risk and the projection of typhoon is still highly uncertain and typhoon number is very limited in a single model simulation. Since Taiwan is a small island, different typhoon tracks induce different level of disaster impacts in watersheds. Therefore, more samples dynamic downscaled typhoon events are needed for analysis to improve and increase reliability in future. Considering dynamical downscaling methods consume massive computing power, developing a new statistical downscaling approach and new method to release daily climate change data to hourly data could be a short-term solution.

Dynamic modeling of the Ganga river system: impacts of future climate and socio-economic change on flows and nitrogen fluxes in India and Bangladesh.

PubMed

Whitehead, P G; Sarkar, S; Jin, L; Futter, M N; Caesar, J; Barbour, E; Butterfield, D; Sinha, R; Nicholls, R; Hutton, C; Leckie, H D

2015-06-01

This study investigates the potential impacts of future climate and socio-economic change on the flow and nitrogen fluxes of the Ganga river system. This is the first basin scale water quality study for the Ganga considering climate change at 25 km resolution together with socio-economic scenarios. The revised dynamic, process-based INCA model was used to simulate hydrology and water quality within the complex multi-branched river basins. All climate realizations utilized in the study predict increases in temperature and rainfall by the 2050s with significant increase by the 2090s. These changes generate associated increases in monsoon flows and increased availability of water for groundwater recharge and irrigation, but also more frequent flooding. Decreased concentrations of nitrate and ammonia are expected due to increased dilution. Different future socio-economic scenarios were found to have a significant impact on water quality at the downstream end of the Ganga. A less sustainable future resulted in a deterioration of water quality due to the pressures from higher population growth, land use change, increased sewage treatment discharges, enhanced atmospheric nitrogen deposition, and water abstraction. However, water quality was found to improve under a more sustainable strategy as envisaged in the Ganga clean-up plan.

Considerations in Managing the Fill Rate of the Grand Ethiopian Renaissance Dam Reservoir Using a System Dynamics Approach.

NASA Technical Reports Server (NTRS)

Keith, Bruce; Ford, David N.; Horton, Radley M.

2016-01-01

The purpose of this study is to evaluate simulated fill rate scenarios for the Grand Ethiopian Renaissance Dam while taking into account plausible climate change outcomes for the Nile River Basin. The region lacks a comprehensive equitable water resource management strategy, which creates regional security concerns and future possible conflicts. We employ climate estimates from 33 general circulation models within a system dynamics model as a step in moving toward a feasible regional water resource management strategy. We find that annual reservoir fill rates of 8-15% are capable of building hydroelectric capacity in Ethiopia while concurrently ensuring a minimum level of stream flow disruption into Egypt before 2039. Insofar as climate change estimates suggest a modest average increase in stream flow into the Aswan, climate changes through 2039 are unlikely to affect the fill rate policies. However, larger fill rates will have a more detrimental effect on stream flow into the Aswan, particularly beyond a policy of 15%. While this study demonstrates that a technical solution for reservoir fill rates is feasible, the corresponding policy challenge is political. Implementation of water resource management strategies in the Nile River Basin specifically and Africa generally will necessitate a national and regional willingness to cooperate.

The Sensitivity of the North American Monsoon to Deglacial Climate Change in Proxies and Models

NASA Astrophysics Data System (ADS)

Bhattacharya, T.; Tierney, J. E.

2017-12-01

The North American Monsoon (NAM), which brings summer rainfall to the arid US Southwest and northwestern Mexico, remains one of the least understood monsoon systems. Model simulations produce divergent NAM responses to future anthropogenic warming, and many paleoclimatic records from the NAM region are more sensitive to winter rainfall than the summertime circulation. As a result, we have an incomplete understanding of NAM sensitivity to past and future global climate change. Our work seeks to improve understanding of NAM dynamics using new proxy records and model simulations. We have developed quantitative reconstructions of NAM strength since the LGM ( 21 ka BP) using leaf wax biomarkers (e.g. dD of n-acids) from marine sediment cores in the Gulf of California. We contrast these proxy records with idealized GCM simulations (i.e. CESM1.2) to diagnose the mechanisms behind NAM responses to LGM boundary conditions and abrupt deglacial climate events. Our results suggest that ice-sheet induced changes in atmospheric circulation acted in concert with local changes in Gulf of California SSTs to modulate the late glacial NAM. This work has important implications for our understanding of NAM dynamics, its relationship with other monsoon systems, and its sensitivity to past and future global climate change.

Final Report Collaborative Project. Improving the Representation of Coastal and Estuarine Processes in Earth System Models

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

Bryan, Frank; Dennis, John; MacCready, Parker

This project aimed to improve long term global climate simulations by resolving and enhancing the representation of the processes involved in the cycling of freshwater through estuaries and coastal regions. This was a collaborative multi-institution project consisting of physical oceanographers, climate model developers, and computational scientists. It specifically targeted the DOE objectives of advancing simulation and predictive capability of climate models through improvements in resolution and physical process representation. The main computational objectives were: 1. To develop computationally efficient, but physically based, parameterizations of estuary and continental shelf mixing processes for use in an Earth System Model (CESM). 2. Tomore » develop a two-way nested regional modeling framework in order to dynamically downscale the climate response of particular coastal ocean regions and to upscale the impact of the regional coastal processes to the global climate in an Earth System Model (CESM). 3. To develop computational infrastructure to enhance the efficiency of data transfer between specific sources and destinations, i.e., a point-to-point communication capability, (used in objective 1) within POP, the ocean component of CESM.« less

Observationally-based Metrics of Ocean Carbon and Biogeochemical Variables are Essential for Evaluating Earth System Model Projections

NASA Astrophysics Data System (ADS)

Russell, J. L.; Sarmiento, J. L.

2017-12-01

The Southern Ocean is central to the climate's response to increasing levels of atmospheric greenhouse gases as it ventilates a large fraction of the global ocean volume. Global coupled climate models and earth system models, however, vary widely in their simulations of the Southern Ocean and its role in, and response to, the ongoing anthropogenic forcing. Due to its complex water-mass structure and dynamics, Southern Ocean carbon and heat uptake depend on a combination of winds, eddies, mixing, buoyancy fluxes and topography. Understanding how the ocean carries heat and carbon into its interior and how the observed wind changes are affecting this uptake is essential to accurately projecting transient climate sensitivity. Observationally-based metrics are critical for discerning processes and mechanisms, and for validating and comparing climate models. As the community shifts toward Earth system models with explicit carbon simulations, more direct observations of important biogeochemical parameters, like those obtained from the biogeochemically-sensored floats that are part of the Southern Ocean Carbon and Climate Observations and Modeling project, are essential. One goal of future observing systems should be to create observationally-based benchmarks that will lead to reducing uncertainties in climate projections, and especially uncertainties related to oceanic heat and carbon uptake.

Hydrology: The interdisciplinary science of water

NASA Astrophysics Data System (ADS)

Vogel, Richard M.; Lall, Upmanu; Cai, Ximing; Rajagopalan, Balaji; Weiskel, Peter K.; Hooper, Richard P.; Matalas, Nicholas C.

2015-06-01

We live in a world where biophysical and social processes are tightly coupled. Hydrologic systems change in response to a variety of natural and human forces such as climate variability and change, water use and water infrastructure, and land cover change. In turn, changes in hydrologic systems impact socioeconomic, ecological, and climate systems at a number of scales, leading to a coevolution of these interlinked systems. The Harvard Water Program, Hydrosociology, Integrated Water Resources Management, Ecohydrology, Hydromorphology, and Sociohydrology were all introduced to provide distinct, interdisciplinary perspectives on water problems to address the contemporary dynamics of human interaction with the hydrosphere and the evolution of the Earth's hydrologic systems. Each of them addresses scientific, social, and engineering challenges related to how humans influence water systems and vice versa. There are now numerous examples in the literature of how holistic approaches can provide a structure and vision of the future of hydrology. We review selected examples, which taken together, describe the type of theoretical and applied integrated hydrologic analyses and associated curricular content required to address the societal issue of water resources sustainability. We describe a modern interdisciplinary science of hydrology needed to develop an in-depth understanding of the dynamics of the connectedness between human and natural systems and to determine effective solutions to resolve the complex water problems that the world faces today. Nearly, every theoretical hydrologic model introduced previously is in need of revision to accommodate how climate, land, vegetation, and socioeconomic factors interact, change, and evolve over time.

Hydrology: The interdisciplinary science of water

USGS Publications Warehouse

Vogel, Richard M.; Lall, Upmanu; Cai, Ximing; Rajagopalan, Balaji; Weiskel, Peter K.; Hooper, Richard P.; Matalas, Nicholas C.

2015-01-01

We live in a world where biophysical and social processes are tightly coupled. Hydrologic systems change in response to a variety of natural and human forces such as climate variability and change, water use and water infrastructure, and land cover change. In turn, changes in hydrologic systems impact socioeconomic, ecological, and climate systems at a number of scales, leading to a coevolution of these interlinked systems. The Harvard Water Program, Hydrosociology, Integrated Water Resources Management, Ecohydrology, Hydromorphology, and Sociohydrology were all introduced to provide distinct, interdisciplinary perspectives on water problems to address the contemporary dynamics of human interaction with the hydrosphere and the evolution of the Earth’s hydrologic systems. Each of them addresses scientific, social, and engineering challenges related to how humans influence water systems and vice versa. There are now numerous examples in the literature of how holistic approaches can provide a structure and vision of the future of hydrology. We review selected examples, which taken together, describe the type of theoretical and applied integrated hydrologic analyses and associated curricular content required to address the societal issue of water resources sustainability. We describe a modern interdisciplinary science of hydrology needed to develop an in-depth understanding of the dynamics of the connectedness between human and natural systems and to determine effective solutions to resolve the complex water problems that the world faces today. Nearly, every theoretical hydrologic model introduced previously is in need of revision to accommodate how climate, land, vegetation, and socioeconomic factors interact, change, and evolve over time.

Collaborative Project. Understanding the effects of tides and eddies on the ocean dynamics, sea ice cover and decadal/centennial climate prediction using the Regional Arctic Climate Model (RACM)

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

Hutchings, Jennifer; Joseph, Renu

2013-09-14

The goal of this project is to develop an eddy resolving ocean model (POP) with tides coupled to a sea ice model (CICE) within the Regional Arctic System Model (RASM) to investigate the importance of ocean tides and mesoscale eddies in arctic climate simulations and quantify biases associated with these processes and how their relative contribution may improve decadal to centennial arctic climate predictions. Ocean, sea ice and coupled arctic climate response to these small scale processes will be evaluated with regard to their influence on mass, momentum and property exchange between oceans, shelf-basin, ice-ocean, and ocean-atmosphere. The project willmore » facilitate the future routine inclusion of polar tides and eddies in Earth System Models when computing power allows. As such, the proposed research addresses the science in support of the BER’s Climate and Environmental Sciences Division Long Term Measure as it will improve the ocean and sea ice model components as well as the fully coupled RASM and Community Earth System Model (CESM) and it will make them more accurate and computationally efficient.« less

Dynamics of change in Alaska's boreal forests: resilience and vulnerability in response to climate warming

Treesearch

A. David McGuire; F.S. Chapin; R.W. Ruess

2010-01-01

Long-term research by the Bonanza Creek (BNZ) Long Term Ecological Research (LTER) program has documented natural patterns of interannual and successional variability of the boreal forest in interior Alaska against which we can detect changes in system behavior. Between 2004 and 2010 the BNZ LTER program focused on understanding the dynamics of change through studying...

The origins of computer weather prediction and climate modeling

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

Lynch, Peter

2008-03-20

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. Amore » fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.« less

The origins of computer weather prediction and climate modeling

NASA Astrophysics Data System (ADS)

Lynch, Peter

2008-03-01

Numerical simulation of an ever-increasing range of geophysical phenomena is adding enormously to our understanding of complex processes in the Earth system. The consequences for mankind of ongoing climate change will be far-reaching. Earth System Models are capable of replicating climate regimes of past millennia and are the best means we have of predicting the future of our climate. The basic ideas of numerical forecasting and climate modeling were developed about a century ago, long before the first electronic computer was constructed. There were several major practical obstacles to be overcome before numerical prediction could be put into practice. A fuller understanding of atmospheric dynamics allowed the development of simplified systems of equations; regular radiosonde observations of the free atmosphere and, later, satellite data, provided the initial conditions; stable finite difference schemes were developed; and powerful electronic computers provided a practical means of carrying out the prodigious calculations required to predict the changes in the weather. Progress in weather forecasting and in climate modeling over the past 50 years has been dramatic. In this presentation, we will trace the history of computer forecasting through the ENIAC integrations to the present day. The useful range of deterministic prediction is increasing by about one day each decade, and our understanding of climate change is growing rapidly as Earth System Models of ever-increasing sophistication are developed.

The Effects of Temperature and Precipitation on the Yield of Zea Mays L. I the Southeastern United States

NASA Astrophysics Data System (ADS)

Stooksbury, David Emory

Three families of straightforward maize (Zea mays L.) yield/climate models using monthly temperature and precipitation terms are produced. One family of models uses USDA's Crop Reporting Districts (CRD) as its scale of aggregation. The other two families of models use three different district aggregates based on climate or yield patterns. The climate and yield districts are determined by using a two-stage cluster analysis. The CRD-based family of models perform as well as the climate and yield based models. All models explain between 80% and 90% of the variance in maize yield. The most important climate term affecting maize yield in the South is the daily maximum temperature at pollination time. The higher the maximum temperature, the lower the yield. Above normal minimum temperature during pollination increases yield in the Middle South. Weather that favors early planting and rapid vegetative growth increases yield. Ideal maize yield weather includes a dry period during planting followed by a warm period during vegetative growth. Moisture variables are important only during the planting and harvest periods when above normal precipitation delays field work and thereby reduces yield. The model results indicate that the dire predictions about the fate of Southern agriculture in a trace gas warmed world may not be true. This is due to the overwhelming influence of the daily maximum temperature on yield. An optimum aggregate for climate impact studies was not found. I postulate that this is due to the dynamic nature of the American maize production system. For most climate impact studies on a dynamic agricultural system, there does not need to be a concern about the model aggregation.

Incorporating teleconnection information into reservoir operating policies using Stochastic Dynamic Programming and a Hidden Markov Model

NASA Astrophysics Data System (ADS)

Turner, Sean; Galelli, Stefano; Wilcox, Karen

2015-04-01

Water reservoir systems are often affected by recurring large-scale ocean-atmospheric anomalies, known as teleconnections, that cause prolonged periods of climatological drought. Accurate forecasts of these events -- at lead times in the order of weeks and months -- may enable reservoir operators to take more effective release decisions to improve the performance of their systems. In practice this might mean a more reliable water supply system, a more profitable hydropower plant or a more sustainable environmental release policy. To this end, climate indices, which represent the oscillation of the ocean-atmospheric system, might be gainfully employed within reservoir operating models that adapt the reservoir operation as a function of the climate condition. This study develops a Stochastic Dynamic Programming (SDP) approach that can incorporate climate indices using a Hidden Markov Model. The model simulates the climatic regime as a hidden state following a Markov chain, with the state transitions driven by variation in climatic indices, such as the Southern Oscillation Index. Time series analysis of recorded streamflow data reveals the parameters of separate autoregressive models that describe the inflow to the reservoir under three representative climate states ("normal", "wet", "dry"). These models then define inflow transition probabilities for use in a classic SDP approach. The key advantage of the Hidden Markov Model is that it allows conditioning the operating policy not only on the reservoir storage and the antecedent inflow, but also on the climate condition, thus potentially allowing adaptability to a broader range of climate conditions. In practice, the reservoir operator would effect a water release tailored to a specific climate state based on available teleconnection data and forecasts. The approach is demonstrated on the operation of a realistic, stylised water reservoir with carry-over capacity in South-East Australia. Here teleconnections relating to both the El Niño Southern Oscillation and the Indian Ocean Dipole influence local hydro-meteorological processes; statistically significant lag correlations have already been established. Simulation of the derived operating policies, which are benchmarked against standard policies conditioned on the reservoir storage and the antecedent inflow, demonstrates the potential of the proposed approach. Future research will further develop the model for sensitivity analysis and regional studies examining the economic value of incorporating long range forecasts into reservoir operation.

Towards the Goal of Modular Climate Data Services: An Overview of NCPP Applications and Software

NASA Astrophysics Data System (ADS)

Koziol, B. W.; Cinquini, L.; Treshansky, A.; Murphy, S.; DeLuca, C.

2013-12-01

In August 2013, the National Climate Predictions and Projections Platform (NCPP) organized a workshop focusing on the quantitative evaluation of downscaled climate data products (QED-2013). The QED-2013 workshop focused on real-world application problems drawn from several sectors (e.g. hydrology, ecology, environmental health, agriculture), and required that downscaled downscaled data products be dynamically accessed, generated, manipulated, annotated, and evaluated. The cyberinfrastructure elements that were integrated to support the workshop included (1) a wiki-based project hosting environment (Earth System CoG) with an interface to data services provided by an Earth System Grid Federation (ESGF) data node; (2) metadata tools provided by the Earth System Documentation (ES-DOC) collaboration; and (3) a Python-based library OpenClimateGIS (OCGIS) for subsetting and converting NetCDF-based climate data to GIS and tabular formats. Collectively, this toolset represents a first deployment of a 'ClimateTranslator' that enables users to access, interpret, and apply climate information at local and regional scales. This presentation will provide an overview of these components above, how they were used in the workshop, and discussion of current and potential integration. The long-term strategy for this software stack is to offer the suite of services described on a customizable, per-project basis. Additional detail on the three components is below. (1) Earth System CoG is a web-based collaboration environment that integrates data discovery and access services with tools for supporting governance and the organization of information. QED-2013 utilized these capabilities to share with workshop participants a suite of downscaled datasets, associated images derived from those datasets, and metadata files describing the downscaling techniques involved. The collaboration side of CoG was used for workshop organization, discussion, and results. (2) The ES-DOC Questionnaire, Viewer, and Comparator are web-based tools for the creation and use of model and experiment documentation. Workshop participants used the Questionnaire to generate metadata on regional downscaling models and statistical downscaling methods, and the Viewer to display the results. A prototype Comparator was available to compare properties across dynamically downscaled models. (3) OCGIS is a Python (v2.7) package designed for geospatial manipulation, subsetting, computation, and translation of Climate and Forecasting (CF)-compliant climate datasets - either stored in local NetCDF files, or files served through THREDDS data servers.

Spatiotemporal causal modeling for the management of Dengue Fever

NASA Astrophysics Data System (ADS)

Yu, Hwa-Lung; Huang, Tailin; Lee, Chieh-Han

2015-04-01

Increasing climatic extremes have caused growing concerns about the health effects and disease outbreaks. The association between climate variation and the occurrence of epidemic diseases play an important role on a country's public health systems. Part of the impacts are direct casualties associated with the increasing frequency and intensity of typhoons, the proliferation of disease vectors and the short-term increase of clinic visits on gastro-intestinal discomforts, diarrhea, dermatosis, or psychological trauma. Other impacts come indirectly from the influence of disasters on the ecological and socio-economic systems, including the changes of air/water quality, living environment and employment condition. Previous risk assessment studies on dengue fever focus mostly on climatic and non-climatic factors and their association with vectors' reproducing pattern. The public-health implication may appear simple. Considering the seasonal changes and regional differences, however, the causality of the impacts is full of uncertainties. Without further investigation, the underlying dengue fever risk dynamics may not be assessed accurately. The objective of this study is to develop an epistemic framework for assessing dynamic dengue fever risk across space and time. The proposed framework integrates cross-departmental data, including public-health databases, precipitation data over time and various socio-economic data. We explore public-health issues induced by typhoon through literature review and spatiotemporal analytic techniques on public health databases. From those data, we identify relevant variables and possible causal relationships, and their spatiotemporal patterns derived from our proposed spatiotemporal techniques. Eventually, we create a spatiotemporal causal network and a framework for modeling dynamic dengue fever risk.

Climate change and drinking water production in The Netherlands: a flexible approach.

PubMed

Ramaker, T A B; Meuleman, A F M; Bernhardi, L; Cirkel, G

2005-01-01

Climate change increases water system dynamics through temperature changes, changes in precipitation patterns, evaporation, water quality and water storage in ice packs. Water system dependent economical stakeholders, such as drinking water companies in The Netherlands, have to cope with consequences of climate change, e.g. floods and water shortages in river systems, upconing brackish ground water, salt water intrusion, increasing peak demands and microbiological activity. In the past decades, however, both water systems and drinking water production have become more and more inflexible; water systems have been heavily regulated and the drinking water supply has grown into an inflexible, but cheap and reliable, system. Flexibility and adaptivity are solutions to overcome climate change related consequences. Flexible adaptive strategies for drinking water production comprise new sources for drinking water production, application of storage concepts in the short term, and a redesign of large centralised systems, including flexible treatment plants, in the long term. Transition to flexible concepts will take decades because investment depreciation periods of assets are long. This implies that long-term strategies within an indicated time path have to be developed. These strategies must be based on thorough knowledge of current assets to seize opportunities for change.

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.

Quantification of scaling exponents and dynamical complexity of microwave refractivity in a tropical climate

NASA Astrophysics Data System (ADS)

Fuwape, Ibiyinka A.; Ogunjo, Samuel T.

2016-12-01

Radio refractivity index is used to quantify the effect of atmospheric parameters in communication systems. Scaling and dynamical complexities of radio refractivity across different climatic zones of Nigeria have been studied. Scaling property of the radio refractivity across Nigeria was estimated from the Hurst Exponent obtained using two different scaling methods namely: The Rescaled Range (R/S) and the detrended fluctuation analysis(DFA). The delay vector variance (DVV), Largest Lyapunov Exponent (λ1) and Correlation Dimension (D2) methods were used to investigate nonlinearity and the results confirm the presence of deterministic nonlinear profile in the radio refractivity time series. The recurrence quantification analysis (RQA) was used to quantify the degree of chaoticity in the radio refractivity across the different climatic zones. RQA was found to be a good measure for identifying unique fingerprint and signature of chaotic time series data. Microwave radio refractivity was found to be persistent and chaotic in all the study locations. The dynamics of radio refractivity increases in complexity and chaoticity from the Coastal region towards the Sahelian climate. The design, development and deployment of robust and reliable microwave communication link in the region will be greatly affected by the chaotic nature of radio refractivity in the region.

Understanding past, contemporary, and future dynamics of plants, populations, and communities using Sonoran Desert winter annuals.

PubMed

Huxman, Travis E; Kimball, Sarah; Angert, Amy L; Gremer, Jennifer R; Barron-Gafford, Greg A; Venable, D Lawrence

2013-07-01

Global change requires plant ecologists to predict future states of biological diversity to aid the management of natural communities, thus introducing a number of significant challenges. One major challenge is considering how the many interacting features of biological systems, including ecophysiological processes, plant life histories, and species interactions, relate to performance in the face of a changing environment. We have employed a functional trait approach to understand the individual, population, and community dynamics of a model system of Sonoran Desert winter annual plants. We have used a comprehensive approach that connects physiological ecology and comparative biology to population and community dynamics, while emphasizing both ecological and evolutionary processes. This approach has led to a fairly robust understanding of past and contemporary dynamics in response to changes in climate. In this community, there is striking variation in physiological and demographic responses to both precipitation and temperature that is described by a trade-off between water-use efficiency (WUE) and relative growth rate (RGR). This community-wide trade-off predicts both the demographic and life history variation that contribute to species coexistence. Our framework has provided a mechanistic explanation to the recent warming, drying, and climate variability that has driven a surprising shift in these communities: cold-adapted species with more buffered population dynamics have increased in relative abundance. These types of comprehensive approaches that acknowledge the hierarchical nature of biology may be especially useful in aiding prediction. The emerging, novel and nonstationary climate constrains our use of simplistic statistical representations of past plant behavior in predicting the future, without understanding the mechanistic basis of change.

Climate Literacy: Progress in AMS Climate Studies Undergraduate Course in Meteorology Program at Jackson State University

NASA Astrophysics Data System (ADS)

Reddy, S. R.

2013-12-01

AMS Climate Studies is an introductory college-level course developed by the American Meteorological Society for implementation at undergraduate institutions nationwide and increasing involvement of under-represented groups The course places students in a dynamic and highly motivational educational environment where they investigate Earth's climate system using real-world environmental data. The AMS Climate Studies course package consists of a textbook, investigations manual, course website, and course management system-compatible files. Instructors can use these resources in combinations that make for an exciting learning experience for their students. The AMS Climate Studies Diversity Project Workshop participation is on a first-come, first-serve basis as determined by the date-of-receipt of the License Order Form. To grow AMS Diversity Programs to their fullest extent, institutions are encouraged to nominate course instructors who did not previously attend Diversity Project workshops. Until three months before the workshop, two-thirds of the workshop positions would be reserved for institutions new to AMS Diversity Projects. The AMS five day course implementation workshop was held in Washington, DC, during May 24-29, 2012. It covered essential course topics in climate science and global climate change, and strategies for course implementation. Talks would feature climate science and sustainability experts from Federal agencies and area research institutions, such as NASA, NOAA, University of Maryland, Howard University, George Mason University, and other Washington, DC, area institutions. The workshop would also include visits to NASA Goddard Space Flight Center and NOAA's Climate Prediction Center. JSU Meteorology Program will be offering AMS Climate Studies undergraduate course under MET 210: Climatology in spring 2014. AMS Climate Studies is offered as a 3 credit hour laboratory course with 2 lectures and 1 lab sessions per week. Although this course places strong intellectual demands upon each student, the instructors' objective is to help each student to pass the course with an adequate understanding of the fundamentals and advanced and applied concepts of climatology, and climate change for him/her to understand basic atmospheric/climate processes, physical and dynamical climatology, regional and global climatology, past and future climates and statistical analysis using climate data and to be prepared to profit from studying more advanced courses.

Humpback whale diets respond to variance in ocean climate and ecosystem conditions in the California Current.

PubMed

Fleming, Alyson H; Clark, Casey T; Calambokidis, John; Barlow, Jay

2016-03-01

Large, migratory predators are often cited as sentinel species for ecosystem processes and climate-related changes, but their utility as indicators is dependent upon an understanding of their response to environmental variability. Documentation of the links between climate variability, ecosystem change and predator dynamics is absent for most top predators. Identifying species that may be useful indicators and elucidating these mechanistic links provides insight into current ecological dynamics and may inform predictions of future ecosystem responses to climatic change. We examine humpback whale response to environmental variability through stable isotope analysis of diet over a dynamic 20-year period (1993-2012) in the California Current System (CCS). Humpback whale diets captured two major shifts in oceanographic and ecological conditions in the CCS. Isotopic signatures reflect a diet dominated by krill during periods characterized by positive phases of the North Pacific Gyre Oscillation (NPGO), cool sea surface temperature (SST), strong upwelling and high krill biomass. In contrast, humpback whale diets are dominated by schooling fish when the NPGO is negative, SST is warmer, seasonal upwelling is delayed and anchovy and sardine populations display increased biomass and range expansion. These findings demonstrate that humpback whales trophically respond to ecosystem shifts, and as a result, their foraging behavior is a synoptic indicator of oceanographic and ecological conditions across the CCS. Multi-decadal examination of these sentinel species thus provides insight into biological consequences of interannual climate fluctuations, fundamental to advancing ecosystem predictions related to global climate change. Published 2015. This article is a U.S. Government work and is in the public domain in the USA.

CTFS/ForestGEO: A global network to monitor forest interactions with a changing climate

NASA Astrophysics Data System (ADS)

Anderson-Teixeira, K. J.; Muller-Landau, H.; McMahon, S.; Davies, S. J.

2013-12-01

Forests are an influential component of the global carbon cycle and strongly influence Earth's climate. Climate change is altering the dynamics of forests globally, which may result in significant climate feedbacks. Forest responses to climate change entail both short-term ecophysiological responses and longer-term directional shifts in community composition. These short- and long-term responses of forest communities to climate change may be better understood through long-term monitoring of large forest plots globally using standardized methodology. Here, we describe a global network of forest research plots (CTFS/ForestGEO) of utility for understanding forest responses to climate change and consequent feedbacks to the climate system. CTFS/ForestGEO is an international network consisting of 51 sites ranging in size from 2-150 ha (median size: 25 ha) and spanning from 25°S to 52°N latitude. At each site, every individual > 1cm DBH is mapped and identified, and recruitment, growth, and mortality are monitored every 5 years. Additional measurements include aboveground productivity, carbon stocks, soil nutrients, plant functional traits, arthropod and vertebrates monitoring, DNA barcoding, airborne and ground-based LiDAR, micrometeorology, and weather monitoring. Data from this network are useful for understanding how forest ecosystem structure and function respond to spatial and temporal variation in abiotic drivers, parameterizing and evaluating ecosystem and earth system models, aligning airborne and ground-based measurements, and identifying directional changes in forest productivity and composition. For instance, CTFS/ForestGEO data have revealed that solar radiation and night-time temperature are important drivers of aboveground productivity in moist tropical forests; that tropical forests are mixed in terms of productivity and biomass trends over the past couple decades; and that the composition of Panamanian forests has shifted towards more drought-tolerant species. Ongoing monitoring will be vital to understanding global forest dynamics in an era of climate change.

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

Testing For The Linearity of Responses To Multiple Anthropogenic Climate Forcings

NASA Astrophysics Data System (ADS)

Forest, C. E.; Stone, P. H.; Sokolov, A. P.

To test whether climate forcings are additive, we compare climate model simulations in which anthropogenic forcings are applied individually and in combination. Tests are performed with different values for climate system properties (climate sensitivity and rate of heat uptake by the deep ocean) as well as for different strengths of the net aerosol forcing, thereby testing for the dependence of linearity on these properties. The MIT 2D Land-Ocean Climate Model used in this study consists of a zonally aver- aged statistical-dynamical atmospheric model coupled to a mixed-layer Q-flux ocean model, with heat anomalies diffused into the deep ocean. Following our previous stud- ies, the anthropogenic forcings are the changes in concentrations of greenhouse gases (1860-1995), sulfate aerosol (1860-1995), and stratospheric and tropospheric ozone (1979-1995). The sulfate aerosol forcing is applied as a surface albedo change. For an aerosol forcing of -1.0 W/m2 and an effective ocean diffusitivity of 2.5 cm2/s, the nonlinearity of the response of global-mean surface temperatures to the combined forcing shows a strong dependence on climate sensitivity. The fractional change in decadal averages ([(TG + TS + TO) - TGSO]/TGSO) for the 1986-1995 period compared to pre-industrial times are 0.43, 0.90, and 1.08 with climate sensitiv- ities of 3.0, 4.5, and 6.2 C, respectively. The values of TGSO for these three cases o are 0.52, 0.62, and 0.76 C. The dependence of linearity on climate system properties, o the role of climate system feedbacks, and the implications for the detection of climate system's response to individual forcings will be presented. Details of the model and forcings can be found at http://web.mit.edu/globalchange/www/.

Testing for the linearity of responses to multiple anthropogenic climate forcings

NASA Astrophysics Data System (ADS)

Forest, C. E.; Stone, P. H.; Sokolov, A. P.

2001-12-01

To test whether climate forcings are additive, we compare climate model simulations in which anthropogenic forcings are applied individually and in combination. Tests are performed with different values for climate system properties (climate sensitivity and rate of heat uptake by the deep ocean) as well as for different strengths of the net aerosol forcing, thereby testing for the dependence of linearity on these properties. The MIT 2D Land-Ocean Climate Model used in this study consists of a zonally averaged statistical-dynamical atmospheric model coupled to a mixed-layer Q-flux ocean model, with heat anomalies diffused into the deep ocean. Following our previous studies, the anthropogenic forcings are the changes in concentrations of greenhouse gases (1860-1995), sulfate aerosol (1860-1995), and stratospheric and tropospheric ozone (1979-1995). The sulfate aerosol forcing is applied as a surface albedo change. For an aerosol forcing of -1.0 W/m2 and an effective ocean diffusitivity of 2.5 cm2/s, the nonlinearity of the response of global-mean surface temperatures to the combined forcing shows a strong dependence on climate sensitivity. The fractional change in decadal averages ([(Δ TG + Δ TS + Δ TO) - Δ TGSO ]/ Δ TGSO) for the 1986-1995 period compared to pre-industrial times are 0.43, 0.90, and 1.08 with climate sensitivities of 3.0, 4.5, and 6.2 oC, respectively. The values of Δ TGSO for these three cases are 0.52, 0.62, and 0.76 oC. The dependence of linearity on climate system properties, the role of climate system feedbacks, and the implications for the detection of climate system's response to individual forcings will be presented. Details of the model and forcings can be found at http://web.mit.edu/globalchange/www/.

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).

Changing crops in response to climate: virtual Nang Rong, Thailand in an agent based simulation

PubMed Central

Malanson, George P.; Verdery, Ashton M.; Walsh, Stephen J.; Sawangdee, Yothin; Heumann, Benjamin W.; McDaniel, Philip M.; Frizzelle, Brian G.; Williams, Nathalie E.; Yao, Xiaozheng; Entwisle, Barbara; Rindfuss, Ronald R.

2014-01-01

The effects of extended climatic variability on agricultural land use were explored for the type of system found in villages of northeastern Thailand. An agent based model developed for the Nang Rong district was used to simulate land allotted to jasmine rice, heavy rice, cassava, and sugar cane. The land use choices in the model depended on likely economic outcomes, but included elements of bounded rationality in dependence on household demography. The socioeconomic dynamics are endogenous in the system, and climate changes were added as exogenous drivers. Villages changed their agricultural effort in many different ways. Most villages reduced the amount of land under cultivation, primarily with reduction in jasmine rice, but others did not. The variation in responses to climate change indicates potential sensitivity to initial conditions and path dependence for this type of system. The differences between our virtual villages and the real villages of the region indicate effects of bounded rationality and limits on model applications. PMID:25061240

Ecological optimality in water-limited natural soil-vegetation systems. I - Theory and hypothesis

NASA Technical Reports Server (NTRS)

Eagleson, P. S.

1982-01-01

The solution space of an approximate statistical-dynamic model of the average annual water balance is explored with respect to the hydrologic parameters of both soil and vegetation. Within the accuracy of this model it is shown that water-limited natural vegetation systems are in stable equilibrium with their climatic and pedologic environments when the canopy density and species act to minimize average water demand stress. Theory shows a climatic limit to this equilibrium above which it is hypothesized that ecological pressure is toward maximization of biomass productivity. It is further hypothesized that natural soil-vegetation systems will develop gradually and synergistically, through vegetation-induced changes in soil structure, toward a set of hydraulic soil properties for which the minimum stress canopy density of a given species is maximum in a given climate. Using these hypotheses, only the soil effective porosity need be known to determine the optimum soil and vegetation parameters in a given climate.

Towards Supporting Climate Scientists and Impact Assessment Analysts with the Big Data Europe Platform

NASA Astrophysics Data System (ADS)

Klampanos, Iraklis; Vlachogiannis, Diamando; Andronopoulos, Spyros; Cofiño, Antonio; Charalambidis, Angelos; Lokers, Rob; Konstantopoulos, Stasinos; Karkaletsis, Vangelis

2016-04-01

The EU, Horizon 2020, project Big Data Europe (BDE) aims to support European companies and institutions in effectively managing and making use of big data in activities critical to their progress and success. BDE focuses on seven areas of societal impact: Health, Food and Agriculture, Energy, Transport, Climate, Social Sciences and Security. By reaching out to partners and stakeholders, BDE aims to elicit data-intensive requirements for, and deliver an ICT platform to cover aspects of publishing and consuming semantically interoperable, large-scale, multi-lingual data assets and knowledge. In this presentation we will describe the first BDE pilot for Climate, focusing on SemaGrow, its core component, which provides data querying and management based on data semantics. Over the last few decades, extended scientific effort in understanding climate change has resulted in a huge volume of model and observational data. Large international global and regional model inter-comparison projects have focused on creating a framework in support of climate model diagnosis, validation, documentation and data access. The application of climate model ensembles, a system consisting of different possible realisations of a climate model, has further significantly increased the amount of climate and weather data generated. The provision of such models satisfies the crucial objective of assessing potential impacts of climate change on well-being for adaptation, prevention and mitigation. One of the methodologies applied by the climate research and impact assessment communities is that of dynamical downscaling. This calculates values of atmospheric variables in smaller spatial and temporal scales, given a global model. On the company or institution level, this process can be greatly improved in terms of querying, data ingestion from various sources and formats, automatic data mapping, etc. The first Climate BDE pilot will facilitate the process of dynamical downscaling by providing a semantics-based interface to climate open data, eg{} to ESGF services, searching, downloading and indexing climate model and observational data, according to user requirements, such as coverage and experimental scenarios, executing dynamical downscaling models on institutional computing resources, and establishing a framework for metadata mappings and data lineage. The objectives of this pilot will be met building on the SemaGrow system and tools, which have been developed as part of the SemaGrow project in order to scale data intensive techniques up to extremely large data volumes and improve real time performance for agricultural experiments and analyses. SemaGrow is a query resolution and ingestion system for data and semantics. It is able to extract semantic features from data, index them and expose APIs to other BDE platform components. Moreover, SemaGrow provides tools for transforming and managing data in various formats (e.g. NetCDF), and their metadata. It can also interface between users and distributed, external data sources via SPARQL endpoints. This has been demonstrated as part of the SemaGrow project, on diverse and large-scale scientific use-cases. SemaGrow is an active data service in agINFRA, a data infrastructure for agriculture. https://github.com/semagrow/semagrow Big Data Europe (http://www.big-data-europe.eu) - grant agreement no.644564. Earth System Grid Federation: http://esgf.llnl.gov http://www.semagrow.eu http://aginfra.eu

Nonlinear dynamical modes of climate variability: from curves to manifolds

NASA Astrophysics Data System (ADS)

Gavrilov, Andrey; Mukhin, Dmitry; Loskutov, Evgeny; Feigin, Alexander

2016-04-01

The necessity of efficient dimensionality reduction methods capturing dynamical properties of the system from observed data is evident. Recent study shows that nonlinear dynamical mode (NDM) expansion is able to solve this problem and provide adequate phase variables in climate data analysis [1]. A single NDM is logical extension of linear spatio-temporal structure (like empirical orthogonal function pattern): it is constructed as nonlinear transformation of hidden scalar time series to the space of observed variables, i. e. projection of observed dataset onto a nonlinear curve. Both the hidden time series and the parameters of the curve are learned simultaneously using Bayesian approach. The only prior information about the hidden signal is the assumption of its smoothness. The optimal nonlinearity degree and smoothness are found using Bayesian evidence technique. In this work we do further extension and look for vector hidden signals instead of scalar with the same smoothness restriction. As a result we resolve multidimensional manifolds instead of sum of curves. The dimension of the hidden manifold is optimized using also Bayesian evidence. The efficiency of the extension is demonstrated on model examples. Results of application to climate data are demonstrated and discussed. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep15510

Comparisons with observational and experimental manipulation data imply needed conceptual changes to ESM land models

NASA Astrophysics Data System (ADS)

Riley, W. J.; Zhu, Q.; Tang, J.

2016-12-01

The land models integrated in Earth System Models (ESMs) are critical components necessary to predict soil carbon dynamics and carbon-climate interactions under a changing climate. Yet, these models have been shown to have poor predictive power when compared with observations and ignore many processes known to the observational communities to influence above and belowground carbon dynamics. Here I will report work to tightly couple observations and perturbation experiment results with development of an ESM land model (ALM), focusing on nutrient constraints of the terrestrial C cycle. Using high-frequency flux tower observations and short-term nitrogen and phosphorus perturbation experiments, we show that conceptualizing plant and soil microbe interactions as a multi-substrate, multi-competitor kinetic network allows for accurate prediction of nutrient acquisition. Next, using multiple-year FACE and fertilization response observations at many forest sites, we show that capturing the observed responses requires representation of dynamic allocation to respond to the resulting stresses. Integrating the mechanisms implied by these observations into ALM leads to much lower observational bias and to very different predictions of long-term soil and aboveground C stocks and dynamics, and therefore C-climate feedbacks. I describe how these types of observational constraints are being integrated into the open-source International Land Model Benchmarking (ILAMB) package, and end with the argument that consolidating as many observations of all sorts for easy use by modelers is an important goal to improve C-climate feedback predictions.

The importance of terrestrial weathering for climate system modelling on extended timescales: a study with the UVic ESCM

NASA Astrophysics Data System (ADS)

Brault, Marc-Olivier; Matthews, Damon; Mysak, Lawrence

2016-04-01

The chemical erosion of carbonate and silicate rocks is a key process in the global carbon cycle and, through its coupling with calcium carbonate deposition in the ocean, is the primary sink of carbon on geologic timescales. The dynamic interdependence of terrestrial weathering rates with atmospheric temperature and carbon dioxide concentrations is crucial to the regulation of Earth's climate over multi-millennial timescales. However any attempts to develop a modeling context for terrestrial weathering as part of a dynamic climate system are limited, mostly because of the difficulty in adapting the multi-millennial timescales of the implied negative feedback mechanism with those of the atmosphere and ocean. Much of the earlier work on this topic is therefore based on box-model approaches, abandoning spatial variability for the sake of computational efficiency and the possibility to investigate the impact of weathering on climate change over time frames much longer than those allowed by traditional climate system models. As a result we still have but a rudimentary understanding of the chemical weathering feedback mechanism and its effects on ocean biogeochemistry and atmospheric CO2. Here, we introduce a spatially-explicit, rock weathering model into the University of Victoria Earth System Climate Model (UVic ESCM). We use a land map which takes into account a number of different rock lithologies, changes in sea level, as well as an empirical model of the temperature and NPP dependency of weathering rates for the different rock types. We apply this new model to the last deglacial period (c. 21000BP to 13000BP) as well as a future climate change scenario (c. 1800AD to 6000AD+), comparing the results of our 2-D version of the weathering feedback mechanism to simulations using only the box-model parameterizations of Meissner et al. [2012]. These simulations reveal the importance of two-dimensional factors (i.e., changes in sea level and rock type distribution) in the role of the weathering negative feedback mechanism on multi-millennial timescales.

Modeling the Response of Human Altered Natural Barrier Island Dynamics Along Assateague Island National Seashore to Climate Change

NASA Astrophysics Data System (ADS)

Carroll, A.; McNamara, D.; Schupp, C.

2009-12-01

Assateague Island National Seashore comprises a long barrier island located off the coasts of Maryland and Virginia. Geological evidence suggests that over recent centuries Assateague Island has steadily transgressed up the continental shelf in response to rising sea level. More recently, the natural barrier island dynamics governing Assateague’s evolution have been altered by human activity in three ways: the construction of a jetty and the subsequent interruption of alongshore sediment transport on the north end of Assateague and both the ongoing and abandoned maintenance of a continuous dune system along portions of Assateague with the concomitant modification to overwash dynamics. It is unclear how these varied human alterations to the natural barrier island dynamics will influence the response of Assateague to climate change induced shifts in forcing such as increased rates of sea level rise and changing storm patterns. We use LIDAR detected morphological data of Assateague Island as initial conditions in an alongshore extended model for barrier island dynamics including beach erosion, island overwash and inlet cutting during storms, and beach accretion, tidal delta growth and dune and vegetation growth between storms to explore the response of the various human altered segments of Assateague Island to forcing changes. Traditional models exploring barrier island evolution contain only cross-shore dynamics therefore lacking important alongshore-spatial dynamics in aeolian and surf zone sediment transport. Results show that including alongshore dynamics alter the steady state of Assateague relative to simulations that only include cross-shore dynamics. Results will also be presented exploring the potential for regime shifts in steady state behavior under various scenarios for the rate of sea level rise and storm climate and varying management strategies.

Managing the climate commons at the nexus of ecology, behaviour and economics

NASA Astrophysics Data System (ADS)

Tavoni, Alessandro; Levin, Simon

2014-12-01

Sustainably managing coupled ecological-economic systems requires not only an understanding of the environmental factors that affect them, but also knowledge of the interactions and feedback cycles that operate between resource dynamics and activities attributable to human intervention. The socioeconomic dynamics, in turn, call for an investigation of the behavioural drivers behind human action. We argue that a multidisciplinary approach is needed in order to tackle the increasingly pressing and intertwined environmental challenges faced by modern societies. Academic contributions to climate change policy have been constrained by methodological and terminological differences, so we discuss how programmes aimed at cross-disciplinary education and involvement in governance may help to unlock scholars' potential to propose new solutions.

The importance of within-system spatial variation in drivers of marine ecosystem regime shifts

PubMed Central

Fisher, J. A. D.; Casini, M.; Frank, K. T.; Möllmann, C.; Leggett, W. C.; Daskalov, G.

2015-01-01

Comparative analyses of the dynamics of exploited marine ecosystems have led to differing hypotheses regarding the primary causes of observed regime shifts, while many ecosystems have apparently not undergone regime shifts. These varied responses may be partly explained by the decade-old recognition that within-system spatial heterogeneity in key climate and anthropogenic drivers may be important, as recent theoretical examinations have concluded that spatial heterogeneity in environmental characteristics may diminish the tendency for regime shifts. Here, we synthesize recent, empirical within-system spatio-temporal analyses of some temperate and subarctic large marine ecosystems in which regime shifts have (and have not) occurred. Examples from the Baltic Sea, Black Sea, Bengula Current, North Sea, Barents Sea and Eastern Scotian Shelf reveal the largely neglected importance of considering spatial variability in key biotic and abiotic influences and species movements in the context of evaluating and predicting regime shifts. We highlight both the importance of understanding the scale-dependent spatial dynamics of climate influences and key predator–prey interactions to unravel the dynamics of regime shifts, and the utility of spatial downscaling of proposed mechanisms (as evident in the North Sea and Barents Sea) as a means of evaluating hypotheses originally derived from among-system comparisons.

The response of soil organic carbon of a rich fen peatland in interior Alaska to projected climate change

USGS Publications Warehouse

Fan, Zhaosheng; McGuire, Anthony David; Turetsky, Merritt R.; Harden, Jennifer W.; Waddington, James Michael; Kane, Evan S.

2013-01-01

It is important to understand the fate of carbon in boreal peatland soils in response to climate change because a substantial change in release of this carbon as CO2 and CH4 could influence the climate system. The goal of this research was to synthesize the results of a field water table manipulation experiment conducted in a boreal rich fen into a process-based model to understand how soil organic carbon (SOC) of the rich fen might respond to projected climate change. This model, the peatland version of the dynamic organic soil Terrestrial Ecosystem Model (peatland DOS-TEM), was calibrated with data collected during 2005–2011 from the control treatment of a boreal rich fen in the Alaska Peatland Experiment (APEX). The performance of the model was validated with the experimental data measured from the raised and lowered water-table treatments of APEX during the same period. The model was then applied to simulate future SOC dynamics of the rich fen control site under various CO2 emission scenarios. The results across these emissions scenarios suggest that the rate of SOC sequestration in the rich fen will increase between year 2012 and 2061 because the effects of warming increase heterotrophic respiration less than they increase carbon inputs via production. However, after 2061, the rate of SOC sequestration will be weakened and, as a result, the rich fen will likely become a carbon source to the atmosphere between 2062 and 2099. During this period, the effects of projected warming increase respiration so that it is greater than carbon inputs via production. Although changes in precipitation alone had relatively little effect on the dynamics of SOC, changes in precipitation did interact with warming to influence SOC dynamics for some climate scenarios.

Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records.

PubMed

Foreman, Brady Z; Straub, Kyle M

2017-09-01

Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 10 4 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation.

Autogenic geomorphic processes determine the resolution and fidelity of terrestrial paleoclimate records

PubMed Central

Foreman, Brady Z.; Straub, Kyle M.

2017-01-01

Terrestrial paleoclimate records rely on proxies hosted in alluvial strata whose beds are deposited by unsteady and nonlinear geomorphic processes. It is broadly assumed that this renders the resultant time series of terrestrial paleoclimatic variability noisy and incomplete. We evaluate this assumption using a model of oscillating climate and the precise topographic evolution of an experimental alluvial system. We find that geomorphic stochasticity can create aliasing in the time series and spurious climate signals, but these issues are eliminated when the period of climate oscillation is longer than a key time scale of internal dynamics in the geomorphic system. This emergent autogenic geomorphic behavior imparts regularity to deposition and represents a natural discretization interval of the continuous climate signal. We propose that this time scale in nature could be in excess of 104 years but would still allow assessments of the rates of climate change at resolutions finer than the existing age model techniques in isolation. PMID:28924607

Complex systems approach to fire dynamics and climate change impacts

NASA Astrophysics Data System (ADS)

Pueyo, S.

2012-04-01

I present some recent advances in complex systems theory as a contribution to understanding fire regimes and forecasting their response to a changing climate, qualitatively and quantitatively. In many regions of the world, fire sizes have been found to follow, approximately, a power-law frequency distribution. As noted by several authors, this distribution also arises in the "forest fire" model used by physicists to study mechanisms that give rise to scale invariance (the power law is a scale-invariant distribution). However, this model does not give and does not pretend to give a realistic description of fire dynamics. For example, it gives no role to weather and climate. Pueyo (2007) developed a variant of the "forest fire" model that is also simple but attempts to be more realistic. It also results into a power law, but the parameters of this distribution change through time as a function of weather and climate. Pueyo (2007) observed similar patterns of response to weather in data from boreal forest fires, and used the fitted response functions to forecast fire size distributions in a possible climate change scenario, including the upper extreme of the distribution. For some parameter values, the model in Pueyo (2007) displays a qualitatively different behavior, consisting of simple percolation. In this case, fire is virtually absent, but megafires sweep through the ecosystem a soon as environmental forcings exceed a critical threshold. Evidence gathered by Pueyo et al. (2010) suggests that this is realistic for tropical rainforests (specifically, well-conserved upland rainforests). Some climate models suggest that major tropical rainforest regions are going to become hotter and drier if climate change goes ahead unchecked, which could cause such abrupt shifts. Not all fire regimes are well described by this model. Using data from a tropical savanna region, Pueyo et al. (2010) found that the dynamics in this area do not match its assumptions, even though fire sizes are also well fitted by a power law. A possible interpretation is that the spatial structure of fire in savannas is strongly constrained by the spatial structure of their environment. Instead of resulting from ecosystem self-organization as in the model, in this case the scale invariance in fire events would be just a reflection of scale invariance in the environment in which the ecosystem lives. These results suggest at least three major types of fire dynamics: endogenous scaling, percolating, and exogenous scaling, in addition to intermediate options. The world's biomes can be classified based on the type of dynamics that is most likely to apply in each of them, and forecasts can be carried out with the tools developed for each of these types.

A user-friendly earth system model of low complexity: the ESCIMO system dynamics model of global warming towards 2100

NASA Astrophysics Data System (ADS)

Randers, Jorgen; Golüke, Ulrich; Wenstøp, Fred; Wenstøp, Søren

2016-11-01

We have made a simple system dynamics model, ESCIMO (Earth System Climate Interpretable Model), which runs on a desktop computer in seconds and is able to reproduce the main output from more complex climate models. ESCIMO represents the main causal mechanisms at work in the Earth system and is able to reproduce the broad outline of climate history from 1850 to 2015. We have run many simulations with ESCIMO to 2100 and beyond. In this paper we present the effects of introducing in 2015 six possible global policy interventions that cost around USD 1000 billion per year - around 1 % of world GDP. We tentatively conclude (a) that these policy interventions can at most reduce the global mean surface temperature - GMST - by up to 0.5 °C in 2050 and up to 1.0 °C in 2100 relative to no intervention. The exception is injection of aerosols into the stratosphere, which can reduce the GMST by more than 1.0 °C in a decade but creates other serious problems. We also conclude (b) that relatively cheap human intervention can keep global warming in this century below +2 °C relative to preindustrial times. Finally, we conclude (c) that run-away warming is unlikely to occur in this century but is likely to occur in the longer run. The ensuing warming is slow, however. In ESCIMO, it takes several hundred years to lift the GMST to +3 °C above preindustrial times through gradual self-reinforcing melting of the permafrost. We call for research to test whether more complex climate models support our tentative conclusions from ESCIMO.

GRACE storage-runoff hystereses reveal the dynamics of ...

EPA Pesticide Factsheets

Watersheds function as integrated systems where climate and geology govern the movement of water. In situ instrumentation can provide local-scale insights into the non-linear relationship between streamflow and water stored in a watershed as snow, soil moisture, and groundwater. However, there is a poor understanding of these processes at the regional scale—primarily because of our inability to measure water stores and fluxes in the subsurface. Now NASA’s Gravity Recovery and Climate Experiment (GRACE) satellites quantify changes in the amount of water stored across and through the Earth, providing measurements of regional hydrologic behavior. Here we apply GRACE data to characterize for the first time how regional watersheds function as simple, dynamic systems through a series of hysteresis loops. While the physical processes underlying the loops are inherently complex, the vertical integration of terrestrial water in the GRACE signal provides process-based insights into the dynamic and non-linear function of regional-scale watersheds. We use this process-based understanding with GRACE data to effectively forecast seasonal runoff (mean R2 of 0.91) and monthly runoff (mean R2 of 0.77) in three regional-scale watersheds (>150,000 km2) of the Columbia River Basin, USA. Data from the Gravity Recovery and Climate Experiment (GRACE) satellites provide a novel dataset for understanding changes in the amount of water stored across and through the surface of the Ear

A System Dynamics Modeling of Water Supply and Demand in Las Vegas Valley

NASA Astrophysics Data System (ADS)

Parajuli, R.; Kalra, A.; Mastino, L.; Velotta, M.; Ahmad, S.

2017-12-01

The rise in population and change in climate have posed the uncertainties in the balance between supply and demand of water. The current study deals with the water management issues in Las Vegas Valley (LVV) using Stella, a system dynamics modeling software, to model the feedback based relationship between supply and demand parameters. Population parameters were obtained from Center for Business and Economic Research while historical water demand and conservation practices were modeled as per the information provided by local authorities. The water surface elevation of Lake Mead, which is the prime source of water supply to the region, was modeled as the supply side whereas the water demand in LVV was modeled as the demand side. The study was done from the period of 1989 to 2049 with 1989 to 2012 as the historical one and the period from 2013 to 2049 as the future period. This study utilizes Coupled Model Intercomparison Project data sets (2013-2049) (CMIP3&5) to model different future climatic scenarios. The model simulates the past dynamics of supply and demand, and then forecasts the future water budget for the forecasted future population and future climatic conditions. The results can be utilized by the water authorities in understanding the future water status and hence plan suitable conservation policies to allocate future water budget and achieve sustainable water management.

Climate and wildfires in the North American boreal forest.

PubMed

Macias Fauria, Marc; Johnson, E A

2008-07-12

The area burned in the North American boreal forest is controlled by the frequency of mid-tropospheric blocking highs that cause rapid fuel drying. Climate controls the area burned through changing the dynamics of large-scale teleconnection patterns (Pacific Decadal Oscillation/El Niño Southern Oscillation and Arctic Oscillation, PDO/ENSO and AO) that control the frequency of blocking highs over the continent at different time scales. Changes in these teleconnections may be caused by the current global warming. Thus, an increase in temperature alone need not be associated with an increase in area burned in the North American boreal forest. Since the end of the Little Ice Age, the climate has been unusually moist and variable: large fire years have occurred in unusual years, fire frequency has decreased and fire-climate relationships have occurred at interannual to decadal time scales. Prolonged and severe droughts were common in the past and were partly associated with changes in the PDO/ENSO system. Under these conditions, large fire years become common, fire frequency increases and fire-climate relationships occur at decadal to centennial time scales. A suggested return to the drier climate regimes of the past would imply major changes in the temporal dynamics of fire-climate relationships and in area burned, a reduction in the mean age of the forest, and changes in species composition of the North American boreal forest.

Accelerating Climate Simulations Through Hybrid Computing

NASA Technical Reports Server (NTRS)

Zhou, Shujia; Sinno, Scott; Cruz, Carlos; Purcell, Mark

2009-01-01

Unconventional multi-core processors (e.g., IBM Cell B/E and NYIDIDA GPU) have emerged as accelerators in climate simulation. However, climate models typically run on parallel computers with conventional processors (e.g., Intel and AMD) using MPI. Connecting accelerators to this architecture efficiently and easily becomes a critical issue. When using MPI for connection, we identified two challenges: (1) identical MPI implementation is required in both systems, and; (2) existing MPI code must be modified to accommodate the accelerators. In response, we have extended and deployed IBM Dynamic Application Virtualization (DAV) in a hybrid computing prototype system (one blade with two Intel quad-core processors, two IBM QS22 Cell blades, connected with Infiniband), allowing for seamlessly offloading compute-intensive functions to remote, heterogeneous accelerators in a scalable, load-balanced manner. Currently, a climate solar radiation model running with multiple MPI processes has been offloaded to multiple Cell blades with approx.10% network overhead.

Late Glacial to Early Holocene socio-ecological responses to climatic instability within the Mediterranean basin

NASA Astrophysics Data System (ADS)

Fernández-López de Pablo, Javier; Jones, Samantha E.; Burjachs, Francesc

2018-03-01

The period spanning the Late Glacial and the Early Holocene (≈19-8.2 ka) witnessed a dramatic sequence of climate and palaeoenvironmental changes (Rasmussen et al., 2014). Interestingly, some of the most significant transformations ever documented in human Prehistory took place during this period such as the intensification of hunter-gatherer economic systems, the domestication process of wild plants and animals, and the spread of farming across Eurasia. Understanding the role of climate and environmental dynamics on long-term cultural and economic trajectories, as well as specific human responses to episodes of rapid climate change, still remains as one of the main challenges of archaeological research (Kintigh et al., 2014).

Uncertainties in data-model comparisons: Spatio-temporal scales for past climates

NASA Astrophysics Data System (ADS)

Lohmann, G.

2016-12-01

Data-model comparisons are hindered by uncertainties like varying reservoir ages or potential seasonality bias of the recorder systems, but also due to the models' difficulty to represent the spatio-temporal variability patterns. For the Holocene we detect a sensitivity to horizontal resolution in the atmosphere, the representation of atmospheric dynamics, as well as the dynamics of the western boundary currents in the ocean. These features can create strong spatial heterogeneity in the North Atlantic and Pacific Oceans over long timescales (unlike a diffusive spatio-temporal scale separation). Futhermore, it is shown that such non-linear mechanisms could create a non-trivial response to seasonal insolation forcing via an atmospheric bridge inducing non-uniform temperature anomalies over the northern continents on multi-millennial time scales. Through the fluctuation-dissipation-theorem, climate variability and sensitivity are ultimately coupled. It is argued that some obvious biases between models and data may be linked to the missing key persistent component of the atmospheric dynamics, the North Atlantic blocking activity. It is shown that blocking is also linked to Atlantic multidecadal ocean variability and to extreme events. Interestingly, several proxies provide a measure of the frequency of extreme events, and a proper representation is a true challenge for climate models. Finally, case studies from deep paleo are presented in which changes in land-sea distribution or subscale parameterizations can cause relatively large effects on surface temperature. Such experiments can explore the phase space of solutions, but show the limitation of past climates to constrain climate sensitivity.

Climate impacts on environmental risks evaluated from space: a contribution to social benefits within the GEOSS Health Area: The case of Rift Valley Fever in Senegal

NASA Astrophysics Data System (ADS)

Tourre, Y. M.

2009-12-01

Climate and environment vary on many spatio-temporal scales, including climate change, with impacts on ecosystems, vector-borne diseases and public health worldwide. This study is to enable societal benefits from a conceptual approach by mapping climatic and environmental conditions from space and understanding the mechanisms within the Health Social Benefit GEOSS area. The case study is for Rift Valley Fever (RVF) epidemics in Senegal is presented. Ponds contributing to mosquitoes’ thriving, were identified from remote sensing using high-resolution SPOT-5 satellite images. Additional data on ponds’ dynamics and rainfall events (obtained from the Tropical Rainfall Measuring Mission) were combined with hydrological in-situ data. Localization of vulnerable hosts such as parked cattle (from QuickBird satellite) are also used. Dynamic spatio-temporal distribution of Aedes vexans density (one of the main RVF vectors) is based on the total rainfall amount and ponds’ dynamics. While Zones Potentially Occupied by Mosquitoes (ZPOM) are mapped, detailed risks areas, i.e. zones where hazards and vulnerability occur, are expressed in percentages of parks where cattle is potentially exposed to mosquitoes’ bites. This new conceptual approach, using remote-sensing techniques belonging to GEOSS, simply relies upon rainfall distribution also evaluated from space. It is meant to contribute to the implementation of integrated operational early warning system within the health application communities since climatic and environmental conditions (both natural and anthropogenic) are changing rapidly.

Climatic Effects of Regional Nuclear War

NASA Technical Reports Server (NTRS)

Oman, Luke D.

2011-01-01

We use a modern climate model and new estimates of smoke generated by fires in contemporary cities to calculate the response of the climate system to a regional nuclear war between emerging third world nuclear powers using 100 Hiroshima-size bombs (less than 0.03% of the explosive yield of the current global nuclear arsenal) on cities in the subtropics. We find significant cooling and reductions of precipitation lasting years, which would impact the global food supply. The climate changes are large and longlasting because the fuel loadings in modern cities are quite high and the subtropical solar insolation heats the resulting smoke cloud and lofts it into the high stratosphere, where removal mechanisms are slow. While the climate changes are less dramatic than found in previous "nuclear winter" simulations of a massive nuclear exchange between the superpowers, because less smoke is emitted, the changes seem to be more persistent because of improvements in representing aerosol processes and microphysical/dynamical interactions, including radiative heating effects, in newer global climate system models. The assumptions and calculations that go into these conclusions will be described.

Effects of ENSO-induced extremes on terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Xu, M.; Hoffman, F. M.

2017-12-01

The El Niño Southern Oscillation (ENSO) with its warm (El Niño) and cold phase (La Niña) has well-known global impacts on the Earth system through the mechanism of teleconnections. Not only the global mean temperature and precipitation distributions will be changed but also the climate extremes will be enhanced during ENSO events. In this study, the advanced Earth System Model ACME version 0.3 was used to simulate terrestrial biogeochemistry and global climate from 1982 to 2020 with prescribed Sea Surface Temperature (SST) from data fusions of the NOAA high resolution daily Optimum Interpolation SST (OISST), CFS v2 9-month seasonal forecast and data reconstructions. We investigated how ENSO-induced climate extremes affect land carbon dynamics both regionally and globally and the implications for the functioning of different vegetated ecosystems under the influence of climate extremes. The results show that the ENSO-induced climate extremes, especially drought and heat waves, have significant impacts on the terrestrial carbon cycle. The responses to ENSO-induced climate extremes are divergent among different vegetation types.

Theoretical electron scattering amplitudes and spin polarizations. Electron energies 100 to 1500 eV Part II. Be, N, O, Al, Cl, V, Co, Cu, As, Nb, Ag, Sn, Sb, I, and Ta targets

NASA Astrophysics Data System (ADS)

Wildhaber, M. L.; Wikle, C. K.; Anderson, C. J.; Franz, K. J.; Moran, E. H.; Dey, R.

2012-12-01

Recent decades have brought substantive changes in land use and climate across the earth, prompting a need to think of population and community ecology not as a static entity, but as a dynamic process. Increasingly there is evidence of ecological changes due to climate change. Although much of this evidence comes from ground-truth observations of biogeographic data, there is increasing reliance on models that relate climate variables to biological systems. Such models can then be used to explore potential changes to population and community level ecological systems in response to climate scenarios as obtained from global climate models (GCMs). A key issue associated with modeling ecosystem response to climate is GCM downscaling to regional and local ecological/biological response models that can be used in vulnerability and risk assessments of the potential effects of climate change. The need is for an explicit means for scaling results up or down multiple hierarchical levels and an effective assessment of the level of uncertainty surrounding current knowledge, data, and data collection methods with these goals identified as in need of acceleration in the U.S. Climate Change Science Program FY2009 Implementation Priorities. In the end, such work should provide the information needed to develop adaptation and mitigation methodologies to minimize the effects of directional and nonlinear climate change on the Nation's land, water, ecosystems, and biological populations. We are working to develop an approach that includes multi-scale and hierarchical Bayesian modeling of Missouri River sturgeon population dynamics. Statistical linkages are defined to quantify implications of climate on fish populations of the Missouri River ecosystem. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. The model must include linkages between climate and habitat, and between habitat and population. A key advantage of the hierarchical approach used in this study is that it incorporates various sources of observations and includes established scientific knowledge, and associated uncertainties. 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. The predictive modeling system being developed will be a powerful tool for evaluating management options for coping with global change consequences and assessing uncertainty of those evaluations. Specifically for the endangered pallid sturgeon (Scaphirhynchus albus), we are already able to assess potential effects of any climate scenario on growth and population size distribution. Future models will incorporate survival and reproduction. Ultimately, these models provide guidance for successful recovery and conservation of the pallid sturgeon. Here we present a basic outline of the approach we are developing and a simple pallid sturgeon example to demonstrate how multiple scales and parameter uncertainty are incorporated.

Coupling population dynamics with earth system models: the POPEM model.

PubMed

Navarro, Andrés; Moreno, Raúl; Jiménez-Alcázar, Alfonso; Tapiador, Francisco J

2017-09-16

Precise modeling of CO 2 emissions is important for environmental research. This paper presents a new model of human population dynamics that can be embedded into ESMs (Earth System Models) to improve climate modeling. Through a system dynamics approach, we develop a cohort-component model that successfully simulates historical population dynamics with fine spatial resolution (about 1°×1°). The population projections are used to improve the estimates of CO 2 emissions, thus transcending the bulk approach of existing models and allowing more realistic non-linear effects to feature in the simulations. The module, dubbed POPEM (from Population Parameterization for Earth Models), is compared with current emission inventories and validated against UN aggregated data. Finally, it is shown that the module can be used to advance toward fully coupling the social and natural components of the Earth system, an emerging research path for environmental science and pollution research.

Relating the dynamics of climatological and hydrological droughts in semiarid Botswana

NASA Astrophysics Data System (ADS)

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

2018-06-01

Dynamics of droughts have been an associated feature of climate variability particularly in semiarid regions which impact on the response of hydrological systems. This study attempts to determine drought timescale that is suitable for monitoring the effects of drought on hydrological systems which can then be used to assess the long term persistence or reversion and forecasts of the dynamics. Based on this, climatological and hydrological drought indices characterized by Standardized precipitation evapotranspiration index (SPEI) and Standardized flow index (SFI) respectively have been determined using monthly rainfall, temperature and flow data from two major river systems. The association between climatological and hydrological droughts in Botswana has been investigated using these river systems namely: Okavango that is predominantly a storage type and Limpopo which is non-storage for a period of 1975-2014. Dynamics of climatological and hydrological droughts are showing trends towards drying conditions at both river systems. It was also observed that hydrological droughts lag climatological droughts by 7 months in Limpopo and 6 months in Okavango river systems respectively. Analyses of the association between climatic and flow indices indicate that the degree of association becomes stronger with increasing timescale at the Okavango river system. However in the Limpopo river system, it was observed that high timescales of 18- and 24-months were not useful in drought monitoring. 15-months timescale was identified to best monitor drought dynamics at both locations. Therefore SPEIs and SFIs computed at 15-months timescale have been used to assess the variability and long term persistence in drought dynamics through rescaled range analysis (R/S). H-coefficients of 0.06 and 0.08 resulted for Limpopo and Okavango respectively. These H-coefficients being significantly less than 0.5 is an indication of high variability and suggests a change in dynamics from the existing conditions in these river systems. To forecast possible changes, the nonlinear autoregressive with exogenous input (NARX) artificial neural network model has been used. Results from this model agree with those of the R/S and projects generally dry conditions for the next 40 months. Results from this study are helpful not only in choosing a proper timescale but also in evaluating the futuristic drought dynamics necessary for water resources planning and management.

An improved empirical dynamic control system model of global mean sea level rise and surface temperature change

NASA Astrophysics Data System (ADS)

Wu, Qing; Luu, Quang-Hung; Tkalich, Pavel; Chen, Ge

2018-04-01

Having great impacts on human lives, global warming and associated sea level rise are believed to be strongly linked to anthropogenic causes. Statistical approach offers a simple and yet conceptually verifiable combination of remotely connected climate variables and indices, including sea level and surface temperature. We propose an improved statistical reconstruction model based on the empirical dynamic control system by taking into account the climate variability and deriving parameters from Monte Carlo cross-validation random experiments. For the historic data from 1880 to 2001, we yielded higher correlation results compared to those from other dynamic empirical models. The averaged root mean square errors are reduced in both reconstructed fields, namely, the global mean surface temperature (by 24-37%) and the global mean sea level (by 5-25%). Our model is also more robust as it notably diminished the unstable problem associated with varying initial values. Such results suggest that the model not only enhances significantly the global mean reconstructions of temperature and sea level but also may have a potential to improve future projections.

Climate-induced change of environmentally defined floristic domains: A conservation based vulnerability framework

Treesearch

Debbie Jewitt; Barend F.N. Erasmus; Peter S. Goodman; Timothy G. O' Connor; William W. Hargrove; Damian M. Maddalena; Ed. T.F. Witkowski

2015-01-01

Global climate change is having marked influences on species distributions, phenology and ecosystem composition and raises questions as to the effectiveness of current conservation strategies. Conservation planning has only recently begun to adequately account for dynamic threats such as climate change. We propose a method to incorporate climate-dynamic environmental...

The Geomorphometrics of the Rio Grande Rift: The role of tectonics, climate, and erosional processes in forming the Rio Grande river

NASA Astrophysics Data System (ADS)

Berry, M. A.; van Wijk, J.; Emry, E.; Axen, G. J.; Coblentz, D. D.

2016-12-01

Geomorphometrics provides a powerful tool for quantifying the topographic fabric of a landscape and can help with correlating surface features with underlying dynamic processes. Here we use a suite of geomorphometric metrics (including the topographic power spectra, fabric orientation/organization) to compare and contrast the geomorphology of two of the world's major rifts, the Rio Grande Rift (RGR) in western US and the East Africa Rift (EAR). The motivation for this study is the observation of fundamental differences between the characteristics of the intra-rift river drainage for the two rifts. The RGR consists of a series of NS trending rift basins, connected by accommodation or transfer zones. The Rio Grande river developed in the late Neogene, and follows these rift segments from the San Luis basin in Colorado to the Gulf of Mexico. Before the river system formed, basins are thought to have formed internally draining systems, characterized by shallow playa lakes. This is in contrast with lakes in the Tanganyika and Malawi rifts of the East African Rift that are deep and have existed for >5 My. We investigate the role of climate, tectonics and erosional processes in the formation of the through-going Rio Grande river. This occurred around the time of a slowing down of rift opening ( 10 Ma), but also climatic changes in the southwestern U.S. have been described for the late Neogene. To model our hypothesis, a tectonics and surface transport code TISC (Transport, Isostasy, Surface Transport, Climate) was used to evaluate the dynamics of a series of proto-rift basins and their connecting accommodation zones. Basin infill and drainage system development are studied as a result of varying sediment budgets, climate variables, and rift opening rate.

Climate Curriculum Modules on Volcanic Eruptions, Geoengineering, and Nuclear Winter

NASA Astrophysics Data System (ADS)

Robock, A.

2014-12-01

To support a climate dynamics multidisciplinary curriculum for graduate and senior university students, I will describe on-line modules on volcanic eruptions and climate, geoengineering, and nuclear winter. Each of these topics involves aerosols in the stratosphere and the response of the climate system, but each is distinct, and each is evolving as more research becomes available. As reported for the first time in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, volcanic eruptions are a natural analog for the climate impacts of potential anthropogenic aerosol injections into the stratosphere, either sulfates from potential attempts to cool the climate to counteract global warming, or smoke that would be produced from fires in cities and industrial targets in a nuclear war. The volcanic eruptions module would stand alone, and would also serve as a prerequisite for each of the other two modules, which could be taught independently of each other. Each module includes consideration of the physical climate system as well as impacts of the resulting climate change. Geoengineering includes both solar radiation management and carbon dioxide reduction. The geoengineering and nuclear winter modules also include consideration of policy and governance issues. Each module includes a slide set for use in lecturing, links to related resources, and student exercises. The modules will be regularly updated.

Prototype Mcs Parameterization for Global Climate Models

NASA Astrophysics Data System (ADS)

Moncrieff, M. W.

2017-12-01

Excellent progress has been made with observational, numerical and theoretical studies of MCS processes but the parameterization of those processes remain in a dire state and are missing from GCMs. The perceived complexity of the distribution, type, and intensity of organized precipitation systems has arguably daunted attention and stifled the development of adequate parameterizations. TRMM observations imply links between convective organization and large-scale meteorological features in the tropics and subtropics that are inadequately treated by GCMs. This calls for improved physical-dynamical treatment of organized convection to enable the next-generation of GCMs to reliably address a slew of challenges. The multiscale coherent structure parameterization (MCSP) paradigm is based on the fluid-dynamical concept of coherent structures in turbulent environments. The effects of vertical shear on MCS dynamics implemented as 2nd baroclinic convective heating and convective momentum transport is based on Lagrangian conservation principles, nonlinear dynamical models, and self-similarity. The prototype MCS parameterization, a minimalist proof-of-concept, is applied in the NCAR Community Climate Model, Version 5.5 (CAM 5.5). The MCSP generates convectively coupled tropical waves and large-scale precipitation features notably in the Indo-Pacific warm-pool and Maritime Continent region, a center-of-action for weather and climate variability around the globe.

Designing a dynamic data driven application system for estimating real-time load of dissolved organic carbon in a river

Treesearch

Ying Ouyang

2012-01-01

Understanding the dynamics of naturally occurring dissolved organic carbon (DOC) in a river is central to estimating surface water quality, aquatic carbon cycling, and global climate change. Currently, determination of the DOC in surface water is primarily accomplished by manually collecting samples for laboratory analysis, which requires at least 24 h. In other words...

On the spin-axis dynamics of a Moonless Earth

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

Li, Gongjie; Batygin, Konstantin, E-mail: gli@cfa.harvard.edu

2014-07-20

The variation of a planet's obliquity is influenced by the existence of satellites with a high mass ratio. For instance, Earth's obliquity is stabilized by the Moon and would undergo chaotic variations in the Moon's absence. In turn, such variations can lead to large-scale changes in the atmospheric circulation, rendering spin-axis dynamics a central issue for understanding climate. The relevant quantity for dynamically forced climate change is the rate of chaotic diffusion. Accordingly, here we re-examine the spin-axis evolution of a Moonless Earth within the context of a simplified perturbative framework. We present analytical estimates of the characteristic Lyapunov coefficientmore » as well as the chaotic diffusion rate and demonstrate that even in absence of the Moon, the stochastic change in Earth's obliquity is sufficiently slow to not preclude long-term habitability. Our calculations are consistent with published numerical experiments and illustrate the putative system's underlying dynamical structure in a simple and intuitive manner.« less

Integrated assessment in the Mediterranean: the CIRCE case studies

NASA Astrophysics Data System (ADS)

Goodess, C. M.; Agnew, M. D.; Hemming, D.; Giannakopoulos, C.

2012-04-01

The heterogeneous nature of the Mediterranean environment, combined with a wide diversity of economic, social and cultural identities, make this region particularly amenable to integrated research on climate change impacts, vulnerabilities, and adaptive response. Within the framework of the EU FP7 CIRCE project, eleven case-study locations were selected to reflect three generic environments (urban, rural and coastal), to quantify current and future climate change and to assess the potential consequences to human communities and ecosystems at the regional to local scale. The case studies (Athens, Beirut, Alexandria, Tuscany, Apulia, Tel Hadya, Judean Foothills, Gulf of Valencia, Gulf of Oran, Gulf of Gabes, West Nile Delta) were chosen to reflect the east-west and north-south contrasts across the Mediterranean, using common selection criteria. A rigorous common framework, referred to as the CIRCE Case studies Integrating Framework was developed to facilitate a structured and systematic basis for identifying and selecting indicators. Within this framework, climate dynamics is viewed as a key driver of changes in social and biogeophysical systems and is modulated by the inherent dynamics of these systems. The top-down, indicator-based approach was complemented by a bottom-up approach involving local and regional stakeholders. A participatory level of involvement was aimed for, with stakeholder dialogue on an informal basis throughout the project, culminating in a series of more formal regional stakeholder workshops. Identification and construction of physical and socio-economic indicators was the most challenging and time-consuming aspect of the case-study work. A detailed set of selection criteria was defined and the process of reviewing and refining indicators was iterative. Nonetheless, a number of data and methodological challenges were encountered. Despite these issues, indicator linkages diagrams provided a useful preparatory stage for structuring the integrated assessment for each case study. In the first and major assessment stage, impacts and vulnerability due to exposure to hazards associated with current and recent climate variability and change were explored using observed data. This then provided the context for considering future changes. The latter work was based on climate projections derived from the CIRCE global and regional climate model simulations which have the main novel characteristic of incorporating coupling between the Mediterranean Sea and atmosphere. Natural and human systems in all eleven case studies were found to be vulnerable to current climate variability and change as well as to social dynamics or drivers. The climate projections of increases in mean and extreme high temperature and decreases in precipitation are considered to be robust, although there is uncertainty with regards to the magnitude of change. They indicate that all case studies will experience continuing and increasing vulnerability to climate change in the absence of mitigation or adaptation. Projections for other extreme weather events, such as heavy precipitation and flooding, are highly uncertain, but any increase in such events would further increase vulnerability. At the same time, social dynamics and drivers such as population growth (at least in the short term and in the southern Mediterranean) are likely to further increase vulnerability.

Climate change: The necessary, the possible and the desirable Earth League climate statement on the implications for climate policy from the 5th IPCC Assessment

NASA Astrophysics Data System (ADS)

Rockström, Johan; Brasseur, Guy; Hoskins, Brian; Lucht, Wolfgang; Schellnhuber, John; Kabat, Pavel; Nakicenovic, Nebojsa; Gong, Peng; Schlosser, Peter; Máñez Costa, Maria; Humble, April; Eyre, Nick; Gleick, Peter; James, Rachel; Lucena, Andre; Masera, Omar; Moench, Marcus; Schaeffer, Roberto; Seitzinger, Sybil; van der Leeuw, Sander; Ward, Bob; Stern, Nicholas; Hurrell, James; Srivastava, Leena; Morgan, Jennifer; Nobre, Carlos; Sokona, Youba; Cremades, Roger; Roth, Ellinor; Liverman, Diana; Arnott, James

2014-12-01

The development of human civilisations has occurred at a time of stable climate. This climate stability is now threatened by human activity. The rising global climate risk occurs at a decisive moment for world development. World nations are currently discussing a global development agenda consequent to the Millennium Development Goals (MDGs), which ends in 2015. It is increasingly possible to envisage a world where absolute poverty is largely eradicated within one generation and where ambitious goals on universal access and equal opportunities for dignified lives are adopted. These grand aspirations for a world population approaching or even exceeding nine billion in 2050 is threatened by substantial global environmental risks and by rising inequality. Research shows that development gains, in both rich and poor nations, can be undermined by social, economic and ecological problems caused by human-induced global environmental change. Climate risks, and associated changes in marine and terrestrial ecosystems that regulate the resilience of the climate system, are at the forefront of these global risks. We, as citizens with a strong engagement in Earth system science and socio-ecological dynamics, share the vision of a more equitable and prosperous future for the world, yet we also see threats to this future from shifts in climate and environmental processes. Without collaborative action now, our shared Earth system may not be able to sustainably support a large proportion of humanity in the decades ahead.

Assessing the Role of Seafloor Weathering in Global Geochemical Cycling

NASA Astrophysics Data System (ADS)

Farahat, N. X.; Abbot, D. S.; Archer, D. E.

2015-12-01

Low-temperature alteration of the basaltic upper oceanic crust, known as seafloor weathering, has been proposed as a mechanism for long-term climate regulation similar to the continental climate-weathering negative feedback. Despite this potentially far-reaching impact of seafloor weathering on habitable planet evolution, existing modeling frameworks do not include the full scope of alteration reactions or recent findings of convective flow dynamics. We present a coupled fluid dynamic and geochemical numerical model of low-temperature, off-axis hydrothermal activity. This model is designed to explore the the seafloor weathering flux of carbon to the oceanic crust and its responsiveness to climate fluctuations. The model's ability to reproduce the seafloor weathering environment is evaluated by constructing numerical simulations for comparison with two low-temperature hydrothermal systems: A transect east of the Juan de Fuca Ridge and the southern Costa Rica Rift flank. We explore the sensitivity of carbon uptake by seafloor weathering on climate and geology by varying deep ocean temperature, seawater dissolved inorganic carbon, continental weathering inputs, and basaltic host rock in a suite of numerical experiments.

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

Ingmann, P.; Readings, C. J.; Knott, K.

For the post-2000 time-frame two general classes of Earth Observation missions have been identified to address user requirements (see e.g. ESA, 1995), namely Earth Watch and Earth Explorer missions. One of the candidate Earth Explorer Missions selected for Phase A study is the Atmospheric Dynamics Mission which is intended to exploit a Doppler wind lidar, ALADIN, to measure winds in clear air (ESA, 1995 and ESA, 1996). It is being studied as a candidate for flight on the International Space Station (ISS) as an externally attached payload. The primary, long-term objective of the Atmospheric Dynamics Mission is to provide observationsmore » of wind profiles (e.g. radial wind component). Such data would be assimilated into numerical forecasting models leading to an improvement in objective analyses and hence in Numerical Weather Prediction. The mission would also provide data needed to address some of the key concerns of the World Climate Research Programme (WCRP) i.e. quantification of climate variability, validation and improvement of numerical models and process studies relevant to climate change. The newly acquired data would also help realize some of the objectives of the Global Climate Observing System (GCOS)« less

Recent range expansion of a terrestrial orchid corresponds with climate-driven variation in its population dynamics.

PubMed

van der Meer, Sascha; Jacquemyn, Hans; Carey, Peter D; Jongejans, Eelke

2016-06-01

The population dynamics and distribution limits of plant species are predicted to change as the climate changes. However, it remains unclear to what extent climate variables affect population dynamics, which vital rates are most sensitive to climate change, and whether the same vital rates drive population dynamics in different populations. In this study, we used long-term demographic data from two populations of the terrestrial orchid Himantoglossum hircinum growing at the northern edge of their geographic range to quantify the influence of climate change on demographic vital rates. Integral projection models were constructed to study how climate conditions between 1991 and 2006 affected population dynamics and to assess how projected future climate change will affect the long-term viability of this species. Based on the parameterised vital rate functions and the observed climatic conditions, one of the studied populations had an average population growth rate above 1 (λ = 1.04), while the other was declining at ca. 3 % year(-1) (λ = 0.97). Variation in temperature and precipitation mainly affected population growth through their effect on survival and fecundity. Based on UK Climate Projection 2009 estimates of future climate conditions for three greenhouse gas emission scenarios, population growth rates are expected to increase in one of the studied populations. Overall, our results indicate that the observed changes in climatic conditions appeared to be beneficial to the long-term survival of the species in the UK and suggest that they may have been the driving force behind the current range expansion of H. hircinum in England.

The Dynamical Core Model Intercomparison Project (DCMIP-2016): Results of the Supercell Test Case

NASA Astrophysics Data System (ADS)

Zarzycki, C. M.; Reed, K. A.; Jablonowski, C.; Ullrich, P. A.; Kent, J.; Lauritzen, P. H.; Nair, R. D.

2016-12-01

The 2016 Dynamical Core Model Intercomparison Project (DCMIP-2016) assesses the modeling techniques for global climate and weather models and was recently held at the National Center for Atmospheric Research (NCAR) in conjunction with a two-week summer school. Over 12 different international modeling groups participated in DCMIP-2016 and focused on the evaluation of the newest non-hydrostatic dynamical core designs for future high-resolution weather and climate models. The paper highlights the results of the third DCMIP-2016 test case, which is an idealized supercell storm on a reduced-radius Earth. The supercell storm test permits the study of a non-hydrostatic moist flow field with strong vertical velocities and associated precipitation. This test assesses the behavior of global modeling systems at extremely high spatial resolution and is used in the development of next-generation numerical weather prediction capabilities. In this regime the effective grid spacing is very similar to the horizontal scale of convective plumes, emphasizing resolved non-hydrostatic dynamics. The supercell test case sheds light on the physics-dynamics interplay and highlights the impact of diffusion on model solutions.

Variable effects of climate on forest growth in relation to climate extremes, disturbance, and forest dynamics.

PubMed

Itter, Malcolm S; Finley, Andrew O; D'Amato, Anthony W; Foster, Jane R; Bradford, John B

2017-06-01

Changes in the frequency, duration, and severity of climate extremes are forecast to occur under global climate change. The impacts of climate extremes on forest productivity and health remain difficult to predict due to potential interactions with disturbance events and forest dynamics-changes in forest stand composition, density, size and age structure over time. Such interactions may lead to non-linear forest growth responses to climate involving thresholds and lag effects. Understanding how forest dynamics influence growth responses to climate is particularly important given stand structure and composition can be modified through management to increase forest resistance and resilience to climate change. To inform such adaptive management, we develop a hierarchical Bayesian state space model in which climate effects on tree growth are allowed to vary over time and in relation to past climate extremes, disturbance events, and forest dynamics. The model is an important step toward integrating disturbance and forest dynamics into predictions of forest growth responses to climate extremes. We apply the model to a dendrochronology data set from forest stands of varying composition, structure, and development stage in northeastern Minnesota that have experienced extreme climate years and forest tent caterpillar defoliation events. Mean forest growth was most sensitive to water balance variables representing climatic water deficit. Forest growth responses to water deficit were partitioned into responses driven by climatic threshold exceedances and interactions with insect defoliation. Forest growth was both resistant and resilient to climate extremes with the majority of forest growth responses occurring after multiple climatic threshold exceedances across seasons and years. Interactions between climate and disturbance were observed in a subset of years with insect defoliation increasing forest growth sensitivity to water availability. Forest growth was particularly sensitive to climate extremes during periods of high stem density following major regeneration events when average inter-tree competition was high. Results suggest the resistance and resilience of forest growth to climate extremes can be increased through management steps such as thinning to reduce competition during early stages of stand development and small-group selection harvests to maintain forest structures characteristic of older, mature stands. © 2017 by the Ecological Society of America.

Dynamic Data Driven Applications Systems (DDDAS)

DTIC Science & Technology

2012-05-03

response) – Earthquakes, hurricanes, tornados, wildfires, floods, landslides, tsunamis, … • Critical Infrastructure systems – Electric-powergrid...Multiphase Flow Weather and Climate Structural Mechanics Seismic Processing Aerodynamics Geophysical Fluids Quantum Chemistry Actinide Chemistry...Alloys • Approach and Objectives:  Consider porous SMAs:  similar macroscopic behavior but mass /weight is less, and thus attractive for

On the data-driven inference of modulatory networks in climate science: an application to West African rainfall

NASA Astrophysics Data System (ADS)

González, D. L., II; Angus, M. P.; Tetteh, I. K.; Bello, G. A.; Padmanabhan, K.; Pendse, S. V.; Srinivas, S.; Yu, J.; Semazzi, F.; Kumar, V.; Samatova, N. F.

2015-01-01

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression, and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. These relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño-Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.

On the data-driven inference of modulatory networks in climate science: An application to West African rainfall

DOE PAGES

Gonzalez, II, D. L.; Angus, M. P.; Tetteh, I. K.; ...

2015-01-13

Decades of hypothesis-driven and/or first-principles research have been applied towards the discovery and explanation of the mechanisms that drive climate phenomena, such as western African Sahel summer rainfall~variability. Although connections between various climate factors have been theorized, not all of the key relationships are fully understood. We propose a data-driven approach to identify candidate players in this climate system, which can help explain underlying mechanisms and/or even suggest new relationships, to facilitate building a more comprehensive and predictive model of the modulatory relationships influencing a climate phenomenon of interest. We applied coupled heterogeneous association rule mining (CHARM), Lasso multivariate regression,more » and dynamic Bayesian networks to find relationships within a complex system, and explored means with which to obtain a consensus result from the application of such varied methodologies. Using this fusion of approaches, we identified relationships among climate factors that modulate Sahel rainfall. As a result, these relationships fall into two categories: well-known associations from prior climate knowledge, such as the relationship with the El Niño–Southern Oscillation (ENSO) and putative links, such as North Atlantic Oscillation, that invite further research.« less

Can Regional Climate Models be used in the assessment of vulnerability and risk caused by extreme events?

NASA Astrophysics Data System (ADS)

Nunes, Ana

2015-04-01

Extreme meteorological events played an important role in catastrophic occurrences observed in the past over densely populated areas in Brazil. This motived the proposal of an integrated system for analysis and assessment of vulnerability and risk caused by extreme events in urban areas that are particularly affected by complex topography. That requires a multi-scale approach, which is centered on a regional modeling system, consisting of a regional (spectral) climate model coupled to a land-surface scheme. This regional modeling system employs a boundary forcing method based on scale-selective bias correction and assimilation of satellite-based precipitation estimates. Scale-selective bias correction is a method similar to the spectral nudging technique for dynamical downscaling that allows internal modes to develop in agreement with the large-scale features, while the precipitation assimilation procedure improves the modeled deep-convection and drives the land-surface scheme variables. Here, the scale-selective bias correction acts only on the rotational part of the wind field, letting the precipitation assimilation procedure to correct moisture convergence, in order to reconstruct South American current climate within the South American Hydroclimate Reconstruction Project. The hydroclimate reconstruction outputs might eventually produce improved initial conditions for high-resolution numerical integrations in metropolitan regions, generating more reliable short-term precipitation predictions, and providing accurate hidrometeorological variables to higher resolution geomorphological models. Better representation of deep-convection from intermediate scales is relevant when the resolution of the regional modeling system is refined by any method to meet the scale of geomorphological dynamic models of stability and mass movement, assisting in the assessment of risk areas and estimation of terrain stability over complex topography. The reconstruction of past extreme events also helps the development of a system for decision-making, regarding natural and social disasters, and reducing impacts. Numerical experiments using this regional modeling system successfully modeled severe weather events in Brazil. Comparisons with the NCEP Climate Forecast System Reanalysis outputs were made at resolutions of about 40- and 25-km of the regional climate model.

Are abrupt climate changes predictable?

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter

2013-04-01

It is taken for granted that the limited predictability in the initial value problem, the weather prediction, and the predictability of the statistics are two distinct problems. Lorenz (1975) dubbed this predictability of the first and the second kind respectively. Predictability of the first kind in a chaotic dynamical system is limited due to the well-known critical dependence on initial conditions. Predictability of the second kind is possible in an ergodic system, where either the dynamics is known and the phase space attractor can be characterized by simulation or the system can be observed for such long times that the statistics can be obtained from temporal averaging, assuming that the attractor does not change in time. For the climate system the distinction between predictability of the first and the second kind is fuzzy. This difficulty in distinction between predictability of the first and of the second kind is related to the lack of scale separation between fast and slow components of the climate system. The non-linear nature of the problem furthermore opens the possibility of multiple attractors, or multiple quasi-steady states. As the ice-core records show, the climate has been jumping between different quasi-stationary climates, stadials and interstadials through the Dansgaard-Oechger events. Such a jump happens very fast when a critical tipping point has been reached. The question is: Can such a tipping point be predicted? This is a new kind of predictability: the third kind. If the tipping point is reached through a bifurcation, where the stability of the system is governed by some control parameter, changing in a predictable way to a critical value, the tipping is predictable. If the sudden jump occurs because internal chaotic fluctuations, noise, push the system across a barrier, the tipping is as unpredictable as the triggering noise. In order to hint at an answer to this question, a careful analysis of the high temporal resolution NGRIP isotope record is presented. The result of the analysis points to a fundamental limitation in predictability of the third kind. Reference: P. D. Ditlevsen and S. Johnsen, "Tipping points: Early warning and wishful thinking", Geophys. Res. Lett., 37, 2010

Influence of climate drivers on colonization and extinction dynamics of wetland-dependent species

USGS Publications Warehouse

Ray, Andrew M.; Gould, William R.; Hossack, Blake R.; Sepulveda, Adam; Thoma, David P.; Patla, Debra A.; Daley, Rob; Al-Chokhachy, Robert K.

2016-01-01

Freshwater wetlands are particularly vulnerable to climate change. Specifically, changes in temperature, precipitation, and evapotranspiration (i.e., climate drivers) are likely to alter flooding regimes of wetlands and affect the vital rates, abundance, and distributions of wetland-dependent species. Amphibians may be among the most climate-sensitive wetland-dependent groups, as many species rely on shallow or intermittently flooded wetland habitats for breeding. Here, we integrated multiple years of high-resolution gridded climate and amphibian monitoring data from Grand Teton and Yellowstone National Parks to explicitly model how variations in climate drivers and habitat conditions affect the occurrence and breeding dynamics (i.e., annual extinction and colonization rates) of amphibians. Our results showed that models incorporating climate drivers outperformed models of amphibian breeding dynamics that were exclusively habitat based. Moreover, climate-driven variation in extinction rates, but not colonization rates, disproportionately influenced amphibian occupancy in monitored wetlands. Long-term monitoring from national parks coupled with high-resolution climate data sets will be crucial to describing population dynamics and characterizing the sensitivity of amphibians and other wetland-dependent species to climate change. Further, long-term monitoring of wetlands in national parks will help reduce uncertainty surrounding wetland resources and strengthen opportunities to make informed, science-based decisions that have far-reaching benefits.

Stratigraphic and Earth System approaches to defining the Anthropocene

NASA Astrophysics Data System (ADS)

Steffen, Will; Leinfelder, Reinhold; Zalasiewicz, Jan; Waters, Colin N.; Williams, Mark; Summerhayes, Colin; Barnosky, Anthony D.; Cearreta, Alejandro; Crutzen, Paul; Edgeworth, Matt; Ellis, Erle C.; Fairchild, Ian J.; Galuszka, Agnieszka; Grinevald, Jacques; Haywood, Alan; Ivar do Sul, Juliana; Jeandel, Catherine; McNeill, J. R.; Odada, Eric; Oreskes, Naomi; Revkin, Andrew; Richter, Daniel deB.; Syvitski, James; Vidas, Davor; Wagreich, Michael; Wing, Scott L.; Wolfe, Alexander P.; Schellnhuber, H. J.

2016-08-01

Stratigraphy provides insights into the evolution and dynamics of the Earth System over its long history. With recent developments in Earth System science, changes in Earth System dynamics can now be observed directly and projected into the near future. An integration of the two approaches provides powerful insights into the nature and significance of contemporary changes to Earth. From both perspectives, the Earth has been pushed out of the Holocene Epoch by human activities, with the mid-20th century a strong candidate for the start date of the Anthropocene, the proposed new epoch in Earth history. Here we explore two contrasting scenarios for the future of the Anthropocene, recognizing that the Earth System has already undergone a substantial transition away from the Holocene state. A rapid shift of societies toward the UN Sustainable Development Goals could stabilize the Earth System in a state with more intense interglacial conditions than in the late Quaternary climate regime and with little further biospheric change. In contrast, a continuation of the present Anthropocene trajectory of growing human pressures will likely lead to biotic impoverishment and a much warmer climate with a significant loss of polar ice.

Assessing Environmental Drivers of DOC Fluxes in the Shark River Estuary: Modeling the Effects of Climate, Hydrology and Water Management

NASA Astrophysics Data System (ADS)

Regier, P.; Briceno, H.; Jaffe, R.

2016-02-01

Urban and agricultural development of the South Florida peninsula has disrupted freshwater flow in the Everglades, a hydrologically connected ecosystem stretching from central Florida to the Gulf of Mexico. Current system-scale restoration efforts aim to restore natural hydrologic regimes to reestablish pre-drainage ecosystem functioning through increased water availability, quality and timing. However, it is uncertain how hydrologic restoration combined with climate change will affect the downstream section of the system, including the mangrove estuaries of Everglades National Park. Aquatic transport of carbon, primarily as dissolved organic carbon (DOC), plays a critical role in biogeochemical cycling and food-web dynamics, and will be affected both by water management policies and climate change. To better understand DOC dynamics in these estuaries and how hydrology, climate and water management may affect them, 14 years of monthly data collected in the Shark River estuary were used to build a DOC flux model. Multi-variate methods were applied to long-term data-sets for hydrology, water quality and climate to untangle the interconnected environmental drivers that control DOC export at intra and inter-annual scales. DOC fluxes were determined to be primarily controlled by hydrology but also by seasonality and long-term climate patterns. Next, a 4-component model (salinity, inflow, rainfall, Atlantic Multidecadal Oscillation) capable of predicting DOC fluxes (R2=0.78, p<0.0001, n=161) was established. Finally, potential climate change scenarios for the Everglades were applied to this model to assess DOC flux variations in response to climate and restoration variables. Although global predictions anticipate that DOC export will generally increase in the future, the majority of scenario runs indicated that DOC export from the Everglades is expected to decrease due to changes in rainfall, evapotranspiration, inflows and sea-level rise.

Global climate change impacts on forests and markets

Treesearch

Xiaohui Tian; Brent Sohngen; John B Kim; Sara Ohrel; Jefferson Cole

2016-01-01

This paper develops an economic analysis of climate change impacts in the global forest sector. It illustrates how potential future climate change impacts can be integrated into a dynamic forestry economics model using data from a global dynamic vegetation model, theMC2model. The results suggest that climate change will cause forest outputs (such as timber) to increase...

Importance of vegetation dynamics for future terrestrial carbon cycling

NASA Astrophysics Data System (ADS)

Ahlström, Anders; Xia, Jianyang; Arneth, Almut; Luo, Yiqi; Smith, Benjamin

2015-05-01

Terrestrial ecosystems currently sequester about one third of anthropogenic CO2 emissions each year, an important ecosystem service that dampens climate change. The future fate of this net uptake of CO2 by land based ecosystems is highly uncertain. Most ecosystem models used to predict the future terrestrial carbon cycle share a common architecture, whereby carbon that enters the system as net primary production (NPP) is distributed to plant compartments, transferred to litter and soil through vegetation turnover and then re-emitted to the atmosphere in conjunction with soil decomposition. However, while all models represent the processes of NPP and soil decomposition, they vary greatly in their representations of vegetation turnover and the associated processes governing mortality, disturbance and biome shifts. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality, and the associated turnover. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the Coupled Model Intercomparison Project Phase 5 ensemble under RCP8.5 radiative forcing. By exchanging carbon cycle processes between these 13 simulations we quantified the relative roles of three main driving processes of the carbon cycle; (I) NPP, (II) vegetation dynamics and turnover and (III) soil decomposition, in terms of their contribution to future carbon (C) uptake uncertainties among the ensemble of climate change scenarios. We found that NPP, vegetation turnover (including structural shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33%, respectively, of uncertainties in modelled global C-uptake. Uncertainty due to vegetation turnover was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by biome shifts, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Vegetation-climate feedback causes reduced precipitation in CMIP5 regional Earth system model simulation over Africa

NASA Astrophysics Data System (ADS)

Wu, Minchao; Smith, Benjamin; Schurgers, Guy; Lindström, Joe; Rummukainen, Markku; Samuelsson, Patrick

2013-04-01

Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical rainforest and reduced precipitation over the Amazon Basin (Cox et al. 2000; Betts et al. 2004; Malhi et al. 2009). Opposite effects are seen in southern Senegal, southern Mali, northern Guinea and Guinea-Bissau, positive evapotranspiration feedback enhancing the cover of trees in forest and savannah, mitigating warming and promoting local moisture recycling as rainfall. We reveal that LAI-driven evapotranspiration feedback may reduced rainfall in parts of Africa, vegetation-climate feedbacks may significantly impact the magnitude and character of simulated changes in climate as well as vegetation and ecosystems in future scenario studies of this region. They should be accounted for in future studies of climate change and its impacts on Africa. Keywords: vegetation-climate feedback, regional climate model, evapotranspiration, CORDEX. References: Betts, R.A., Cox, P.M., Collins, M., Harris, P.P., Huntingford, C. & Jones, C.D. 2004. The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming. Theoretical and Applied Climatology 78: 157-175. Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A. & Totterdell, I.J. 2000. Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408: 184-187. Samuelsson, P., Jones, C., Wilĺen, U., Gollvik, S., Hansson, U. and coauthors. 2011. The Rossby Centre Regional Climate Model RCA3:Model description and performance. Tellus 63A, 4-23. Smith, B., Prentice, I. C. and Sykes, M. T. 2001. Representation of vegetation dynamics in modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecol. Biogeog. 10, 621-637 Smith, B., Samuelsson, P., Wramneby, A. & Rummukainen, M. 2011. A model of the coupled dynamics of climate, vegetation and terrestrial ecosystem biogeochemistry for regional applications. Tellus 63A: 87-106.

Creating Dynamically Downscaled Seasonal Climate Forecast and Climate Change Projection Information for the North American Monsoon Region Suitable for Decision Making Purposes

NASA Astrophysics Data System (ADS)

Castro, C. L.; Dominguez, F.; Chang, H.

2010-12-01

Current seasonal climate forecasts and climate change projections of the North American monsoon are based on the use of course-scale information from a general circulation model. The global models, however, have substantial difficulty in resolving the regional scale forcing mechanisms of precipitation. This is especially true during the period of the North American Monsoon in the warm season. Precipitation is driven primarily due to the diurnal cycle of convection, and this process cannot be resolve in coarse-resolution global models that have a relatively poor representation of terrain. Though statistical downscaling may offer a relatively expedient method to generate information more appropriate for the regional scale, and is already being used in the resource decision making processes in the Southwest U.S., its main drawback is that it cannot account for a non-stationary climate. Here we demonstrate the use of a regional climate model, specifically the Weather Research and Forecast (WRF) model, for dynamical downscaling of the North American Monsoon. To drive the WRF simulations, we use retrospective reforecasts from the Climate Forecast System (CFS) model, the operational model used at the U.S. National Center for Environmental Prediction, and three select “well performing” IPCC AR 4 models for the A2 emission scenario. Though relatively computationally expensive, the use of WRF as a regional climate model in this way adds substantial value in the representation of the North American Monsoon. In both cases, the regional climate model captures a fairly realistic and reasonable monsoon, where none exists in the driving global model, and captures the dominant modes of precipitation anomalies associated with ENSO and the Pacific Decadal Oscillation (PDO). Long-term precipitation variability and trends in these simulations is considered via the standardized precipitation index (SPI), a commonly used metric to characterize long-term drought. Dynamically downscaled climate projection data will be integrated into future water resource projections in the state of Arizona, through a cooperative effort involving numerous water resource stakeholders.

High-Resolution Regional Reanalysis in China: Evaluation of 1 Year Period Experiments

NASA Astrophysics Data System (ADS)

Zhang, Qi; Pan, Yinong; Wang, Shuyu; Xu, Jianjun; Tang, Jianping

2017-10-01

Globally, reanalysis data sets are widely used in assessing climate change, validating numerical models, and understanding the interactions between the components of a climate system. However, due to the relatively coarse resolution, most global reanalysis data sets are not suitable to apply at the local and regional scales directly with the inadequate descriptions of mesoscale systems and climatic extreme incidents such as mesoscale convective systems, squall lines, tropical cyclones, regional droughts, and heat waves. In this study, by using a data assimilation system of Gridpoint Statistical Interpolation, and a mesoscale atmospheric model of Weather Research and Forecast model, we build a regional reanalysis system. This is preliminary and the first experimental attempt to construct a high-resolution reanalysis for China main land. Four regional test bed data sets are generated for year 2013 via three widely used methods (classical dynamical downscaling, spectral nudging, and data assimilation) and a hybrid method with data assimilation coupled with spectral nudging. Temperature at 2 m, precipitation, and upper level atmospheric variables are evaluated by comparing against observations for one-year-long tests. It can be concluded that the regional reanalysis with assimilation and nudging methods can better produce the atmospheric variables from surface to upper levels, and regional extreme events such as heat waves, than the classical dynamical downscaling. Compared to the ERA-Interim global reanalysis, the hybrid nudging method performs slightly better in reproducing upper level temperature and low-level moisture over China, which improves regional reanalysis data quality.

Exposure to fall hazards and safety climate in the aircraft maintenance industry.

PubMed

Neitzel, Richard L; Seixas, Noah S; Harris, Michael J; Camp, Janice

2008-01-01

Falls represent a significant occupational hazard, particularly in industries with dynamic work environments. This paper describes rates of noncompliance with fall hazard prevention requirements, perceived safety climate and worker knowledge and beliefs, and the association between fall exposure and safety climate measures in commercial aircraft maintenance activities. Walkthrough observations were conducted on aircraft mechanics at two participating facilities (Sites A and B) to ascertain the degree of noncompliance. Mechanics at each site completed questionnaires concerning fall hazard knowledge, personal safety beliefs, and safety climate. Questionnaire results were summarized into safety climate and belief scores by workgroup and site. Noncompliance rates observed during walkthroughs were compared to the climate-belief scores, and were expected to be inversely associated. Important differences were seen in fall safety performance between the sites. The study provided a characterization of aircraft maintenance fall hazards, and also demonstrated the effectiveness of an objective hazard assessment methodology. Noncompliance varied by height, equipment used, location of work on the aircraft, shift, and by safety system. Although the expected relationship between safety climate and noncompliance was seen for site-average climate scores, workgroups with higher safety climate scores had greater observed noncompliance within Site A. Overall, use of engineered safety systems had a significant impact on working safely, while safety beliefs and climate also contributed, though inconsistently. The results of this study indicate that safety systems are very important in reducing noncompliance with fall protection requirements in aircraft maintenance facilities. Site-level fall safety compliance was found to be related to safety climate, although an unexpected relationship between compliance and safety climate was seen at the workgroup level within site. Finally, observed fall safety compliance was found to differ from self-reported compliance.

Inter-decadal variability of phytoplankton biomass along the coastal West Antarctic Peninsula.

PubMed

Kim, Hyewon; Ducklow, Hugh W; Abele, Doris; Ruiz Barlett, Eduardo M; Buma, Anita G J; Meredith, Michael P; Rozema, Patrick D; Schofield, Oscar M; Venables, Hugh J; Schloss, Irene R

2018-06-28

The West Antarctic Peninsula (WAP) is a climatically sensitive region where periods of strong warming have caused significant changes in the marine ecosystem and food-web processes. Tight coupling between phytoplankton and higher trophic levels implies that the coastal WAP is a bottom-up controlled system, where changes in phytoplankton dynamics may largely impact other food-web components. Here, we analysed the inter-decadal time series of year-round chlorophyll- a (Chl) collected from three stations along the coastal WAP: Carlini Station at Potter Cove (PC) on King George Island, Palmer Station on Anvers Island and Rothera Station on Adelaide Island. There were trends towards increased phytoplankton biomass at Carlini Station (PC) and Palmer Station, while phytoplankton biomass declined significantly at Rothera Station over the studied period. The impacts of two relevant climate modes to the WAP, the El Niño-Southern Oscillation and the Southern Annular Mode, on winter and spring phytoplankton biomass appear to be different among the three sampling stations, suggesting an important role of local-scale forcing than large-scale forcing on phytoplankton dynamics at each station. The inter-annual variability of seasonal bloom progression derived from considering all three stations together captured ecologically meaningful, seasonally co-occurring bloom patterns which were primarily constrained by water-column stability strength. Our findings highlight a coupled link between phytoplankton and physical and climate dynamics along the coastal WAP, which may improve our understanding of overall WAP food-web responses to climate change and variability.This article is part of the theme issue 'The marine system of the West Antarctic Peninsula: status and strategy for progress in a region of rapid change'. © 2018 The Author(s).

Effects of range-wide variation in climate and isolation on floral traits and reproductive output of Clarkia pulchella.

PubMed

Bontrager, Megan; Angert, Amy L

2016-01-01

Plant mating systems and geographic range limits are conceptually linked by shared underlying drivers, including landscape-level heterogeneity in climate and in species' abundance. Studies of how geography and climate interact to affect plant traits that influence mating system and population dynamics can lend insight to ecological and evolutionary processes shaping ranges. Here, we examined how spatiotemporal variation in climate affects reproductive output of a mixed-mating annual, Clarkia pulchella. We also tested the effects of population isolation and climate on mating-system-related floral traits across the range. We measured reproductive output and floral traits on herbarium specimens collected across the range of C. pulchella. We extracted climate data associated with specimens and derived a population isolation metric from a species distribution model. We then examined how predictors of reproductive output and floral traits vary among populations of increasing distance from the range center. Finally, we tested whether reproductive output and floral traits vary with increasing distance from the center of the range. Reproductive output decreased as summer precipitation decreased, and low precipitation may contribute to limiting the southern and western range edges of C. pulchella. High spring and summer temperatures are correlated with low herkogamy, but these climatic factors show contrasting spatial patterns in different quadrants of the range. Limiting factors differ among different parts of the range. Due to the partial decoupling of geography and environment, examining relationships between climate, reproductive output, and mating-system-related floral traits reveals spatial patterns that might be missed when focusing solely on geographic position. © 2016 Botanical Society of America.

Clouds and Water Vapor in the Climate System and Radiative Transfer in Clear Air and Cirrus Clouds in the Tropics

NASA Technical Reports Server (NTRS)

Anderson, James G.; DeSouza-Machado, Sergio; Strow, L. Larrabee

2002-01-01

Research supported under this grant was aimed at attacking unanswered scientific questions that lie at the intersection of radiation, dynamics, chemistry, and climate. Considerable emphasis was placed on scientific collaboration and the innovative development of instruments required to address these issues. Specific questions include water vapor distribution in the tropical troposphere, atmospheric radiation, thin cirrus clouds, stratosphere-troposphere exchange, and correlative science with satellite observations.

Structural and Functional Studies on the Fusion and Attachment Envelope Glycoproteins of Nipah Virus and Hendra Virus

DTIC Science & Technology

2003-01-01

epidemics, caused by Vibrio cholerae have been linked to specific seasons and biogeographical zones. In addition, the population dynamics of V. cholerae in...Climactic warming has directly affected the prevalence of RVFV by prolonging survival rates of the vector involved in disease transmission. 3 Cholera ...climate variability. The study of V. cholerae represents a model system of how climate change affects pathogens (2). Personal human behavior has

Diversity, Adaptability and Ecosystem Resilience

NASA Astrophysics Data System (ADS)

Keribin, Rozenn; Friend, Andrew

2013-04-01

Our ability to predict climate change and anticipate its impacts depends on Earth System Models (ESMs) and their ability to account for the high number of interacting components of the Earth System and to gauge both their influence on the climate and the feedbacks they induce. The land carbon cycle is a component of ESMs that is still poorly constrained. Since the 1990s dynamic global vegetation models (DGVMs) have become the main tool through which we understand the interactions between plant ecosystems and the climate. While DGVMs have made it clear the impacts of climate change on vegetation could be dramatic, predicting the dieback of rainforests and massive carbon losses from various ecosystems, they are highly variable both in their composition and their predictions. Their treatment of plant diversity and competition in particular vary widely and are based on highly-simplified relationships that do not account for the multiple levels of diversity and adaptability found in real plant ecosystems. The aim of this GREENCYCLES II project is to extend an individual-based DGVM to treat the diversity of physiologies found in plant communities and evaluate their effect if any on the ecosystem's transient dynamics and resilience. In the context of the InterSectoral Impacts Model Intercomparison Project (ISI-MIP), an initiative coordinated by a team at the Potsdam Institute for Climate Impact Research (PIK) that aims to provide fast-track global impact assessments for the IPCC's Fifth Assessment Report, we compare 6 vegetation models including 4 DGVMs under different climate change scenarios and analyse how the very different treatments of plant diversity and interactions from one model to the next affect the models' results. We then investigate a new, more mechanistic method of incorporating plant diversity into the DGVM "Hybrid" based on ecological tradeoffs mediated by plant traits and individual-based competition for light.

Climatic Evolution and Habitability of Terrestrial Planets: Perspectives from Coupled Atmosphere-Mantle Systems

NASA Astrophysics Data System (ADS)

Basu Sarkar, D.; Moore, W. B.

2016-12-01

A multitude of factors including the distance from the host star and the stage of planetary evolution affect planetary climate and habitability. The complex interactions between the atmosphere and dynamics of the deep interior of the planets along with stellar fluxes present a formidable challenge. This work employs simplified approaches to address these complex issues in a systematic way. To be specific, we are investigating the coupled evolution of atmosphere and mantle dynamics. The overarching goal here is to simulate the evolutionary history of the terrestrial planets, for example Venus, Earth and Mars. This research also aims at deciphering the history of Venus-like runaway greenhouse and thus explore the possibility of cataclysmic shifts in climate of Earth-like planets. We focus on volatile cycling within the solid planets to understand the role of carbon/water in climatic and tectonic outcomes of such planets. In doing so, we are considering the feedbacks in the coupled mantle-atmosphere system. The primary feedback between the atmosphere and mantle is the surface temperature established by the greenhouse effect, which regulates the temperature gradient that drives the mantle convection and controls the rate at which volatiles are exchanged through weathering. We start our models with different initial assumptions to determine the final climate outcomes within a reasonable parameter space. Currently, there are very few planetary examples, to sample the climate outcomes, however this will soon change as exoplanets are discovered and examined. Therefore, we will be able to work with a significant number of potential candidates to answer questions like this one: For every Earth is there one Venus? ten? a thousand?

Non-linear regime shifts in Holocene Asian monsoon variability: potential impacts on cultural change and migratory patterns

NASA Astrophysics Data System (ADS)

Donges, J. F.; Donner, R. V.; Marwan, N.; Breitenbach, S. F. M.; Rehfeld, K.; Kurths, J.

2015-05-01

The Asian monsoon system is an important tipping element in Earth's climate with a large impact on human societies in the past and present. In light of the potentially severe impacts of present and future anthropogenic climate change on Asian hydrology, it is vital to understand the forcing mechanisms of past climatic regime shifts in the Asian monsoon domain. Here we use novel recurrence network analysis techniques for detecting episodes with pronounced non-linear changes in Holocene Asian monsoon dynamics recorded in speleothems from caves distributed throughout the major branches of the Asian monsoon system. A newly developed multi-proxy methodology explicitly considers dating uncertainties with the COPRA (COnstructing Proxy Records from Age models) approach and allows for detection of continental-scale regime shifts in the complexity of monsoon dynamics. Several epochs are characterised by non-linear regime shifts in Asian monsoon variability, including the periods around 8.5-7.9, 5.7-5.0, 4.1-3.7, and 3.0-2.4 ka BP. The timing of these regime shifts is consistent with known episodes of Holocene rapid climate change (RCC) and high-latitude Bond events. Additionally, we observe a previously rarely reported non-linear regime shift around 7.3 ka BP, a timing that matches the typical 1.0-1.5 ky return intervals of Bond events. A detailed review of previously suggested links between Holocene climatic changes in the Asian monsoon domain and the archaeological record indicates that, in addition to previously considered longer-term changes in mean monsoon intensity and other climatic parameters, regime shifts in monsoon complexity might have played an important role as drivers of migration, pronounced cultural changes, and the collapse of ancient human societies.

System Dynamics based Dengue modeling environment to simulate evolution of Dengue infection under different climate scenarios

NASA Astrophysics Data System (ADS)

Anwar, R.; Khan, R.; Usmani, M.; Colwell, R. R.; Jutla, A.

2017-12-01

Vector borne infectious diseases such as Dengue, Zika and Chikungunya remain a public health threat. An estimate of the World Health Organization (WHO) suggests that about 2.5 billion people, representing ca. 40% of human population,are at increased risk of dengue; with more than 100 million infection cases every year. Vector-borne infections cannot be eradicated since disease causing pathogens survive in the environment. Over the last few decades dengue infection has been reported in more than 100 countries and is expanding geographically. Female Ae. Aegypti mosquito, the daytime active and a major vector for dengue virus, is associated with urban population density and regional climatic processes. However, mathematical quantification of relationships on abundance of vectors and climatic processes remain a challenge, particularly in regions where such data are not routinely collected. Here, using system dynamics based feedback mechanism, an algorithm integrating knowledge from entomological, meteorological and epidemiological processes is developed that has potential to provide ensemble simulations on risk of occurrence of dengue infection in human population. Using dataset from satellite remote sensing, the algorithm was calibrated and validated using actual dengue case data of Iquitos, Peru. We will show results on model capabilities in capturing initiation and peak in the observed time series. In addition, results from several simulation scenarios under different climatic conditions will be discussed.

Implications of climate change damage for agriculture: sectoral evidence from Pakistan.

PubMed

Ahmed, Adeel; Devadason, Evelyn S; Al-Amin, Abul Quasem

2016-10-01

This paper gives a projection of the possible damage of climate change on the agriculture sector of Pakistan for the period 2012-2037, based on a dynamic approach, using an environment-related applied computable general equilibrium model (CGE). Climate damage projections depict an upward trend for the period of review and are found to be higher than the global average. Further, the damage to the agricultural sector exceeds that for the overall economy. By sector, climatic damage disproportionately affects the major and minor crops, livestock and fisheries. The largest losses following climate change, relative to the other agricultural sectors, are expected for livestock. The reason for this is the orthodox system of production for livestock, with a low adaptability to negative shocks of climate change. Overall, the findings reveal the high exposure of the agriculture sector to climate damage. In this regard, policymakers in Pakistan should take seriously the effects of climate change on agriculture and consider suitable technology to mitigate those damages.

Atlas of Relations Between Climatic Parameters and Distributions of Important Trees and Shrubs in North America - Ecoregions of North America

USGS Publications Warehouse

Thompson, Robert S.; Anderson, Katherine H.; Pelltier, Richard T.; Shafer, Sarah L.; Bartlein, Patrick J.

2007-01-01

Climate is the primary factor controlling the continental-scale distribution of plant species, although the relations between climatic parameters and species' ranges are only now beginning to be quantified. This volume examines the relations between climate and the distributions of (1) Kuchler's 'potential natural vegetation' categories for the 48 contiguous States of the United States of America, (2) Bailey's ecoregions of North America, and (3) World Wildlife Fund's ecoregions of North America. For these analyses, we employed a 25-kilometer equal-area grid of modern climatic and bioclimatic parameters for North America, coupled with presence-absence data for the occurrence of each ecoregion under the three classification systems under consideration. The resulting relations between climate and ecoregion distributions are presented in graphical and tabular form. Presentation of ecoregion-climate relations here is intended to be useful for a greater understanding of ecosystem evolution, ecosystem dynamics, and potential effects of future climate change on ecoregions.

Tracking Climate Change through the Spatiotemporal Dynamics of the Teletherms, the Statistically Hottest and Coldest Days of the Year

DOE PAGES

Dodds, Peter Sheridan; Mitchell, Lewis; Reagan, Andrew J.; ...

2016-05-11

Instabilities and long term shifts in seasons, whether induced by natural drivers or human activities, pose great disruptive threats to ecological, agricultural, and social systems. Here, we propose, measure, and explore two fundamental markers of location-sensitive seasonal variations: the Summer and Winter Teletherms—the on-average annual dates of the hottest and coldest days of the year. We analyze daily temperature extremes recorded at 1218 stations across the contiguous United States from 1853–2012, and observe large regional variation with the Summer Teletherm falling up to 90 days after the Summer Solstice, and 50 days for the Winter Teletherm after the Winter Solstice.more » We show that Teletherm temporal dynamics are substantive with clear and in some cases dramatic shifts reflective of system bifurcations. We also compare recorded daily temperature extremes with output from two regional climate models finding considerable though relatively unbiased error. In conclusion, our work demonstrates that Teletherms are an intuitive, powerful, and statistically sound measure of local climate change, and that they pose detailed, stringent challenges for future theoretical and computational models.« less

Modeling soil organic carbon stocks and changes in Spain using the GEFSOC system

NASA Astrophysics Data System (ADS)

Álvaro-Fuentes, Jorge; Easter, Mark; Cantero-Martínez, Carlos; Paustian, Keith

2010-05-01

Currently, there is little information about soil organic carbon (SOC) stocks in Spain. To date the effects of land-use and soil management on SOC stocks in Spain have been evaluated in experimental fields under certain soil and climate conditions. However, these field experiments do not account for the spatial variability in management, cropping systems and soil and climate characteristics that exist in the whole territory. More realistic approaches like ecosystem-level dynamic simulation systems linked to geographic information systems (GIS) allow better assessments of SOC stocks at a regional or national level. The Global Environmental Facility Soil Organic Carbon (GEFSOC) system was recently built for this purpose (Milne et al., 2007) and it incorporates three widely used models for estimating SOC dynamics: (a) the Century ecosystem model; (b) the RothC soil C decomposition model; and (c) the Intergovernmental Panel on Climate Change (IPCC) method for assessing soil C at regional scales. We modeled 9.5 Mha in northeast Spain using the GEFSOC system to predict SOC stocks and changes comprising: pasture, forest, cereal-fallow, cereal monoculture, orchards, rice, irrigated land and grapes and olives. The spatial distribution of the different land use categories and their change over time was obtained from the European Corine database and from Spanish census data on land use from 1926 to 2007. At the same time, current and historical management information was collected from different sources in order to have a fairly well picture of changes in land use and management for this area. Soil parameters needed by the system were obtained from the European soil map (1 km x 1 km) and climate data was produced by the Meteorology State Agency (Ministry of the Environment and Rural and Marine Environs of Spain). The SOC stocks simulated were validated with SOC values from the European SOC map and from other national studies. Modeled SOC results suggested that spatial-based approaches are crucial for quantify SOC stocks and changes in Spain.

When climate change is a fact! Adaptive strategies for drinking water production in a changing natural environment.

PubMed

Meuleman, A F M; Cirkel, G; Zwolsman, G J J

2007-01-01

Climate change increases water system dynamics through temperature changes, changes in precipitation patterns, evaporation, and water quality and water storage in ice packs. Water system dependent economical stakeholders, such as drinking water companies in the Netherlands, have to cope with consequences of climate change, e.g. floods and water shortages in river systems, upcoming of brackish ground water, salt water intrusion, increasing peak demands and microbiological activity due to temperature rise. In the past decades, however, both water systems and drinking water production have become more and more inflexible; water systems have been heavily regulated aiming at maximum security and economic functions and the drinking water supply in the Netherlands has grown into an inflexible, but cheap and reliable, system. At a water catchment scale, flexibility and adaptation are solutions to overcome climate change related consequences. Flexible adaptive strategies for drinking water production comprise new sources for drinking water production, application of storage concepts in the short term, and a redesign of large centralized systems, including flexible treatment plants, in the long term. Transition to flexible concepts will take decades because investment depreciation periods of assets are long. These strategies must be based on thorough knowledge of current assets to seize opportunities for change.

Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

NASA Astrophysics Data System (ADS)

MacLeod, Dave A.; Jones, Anne; Di Giuseppe, Francesca; Caminade, Cyril; Morse, Andrew P.

2015-04-01

The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006 the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.

Enhancing climate literacy through the use of an interdisciplinary global change framework and conceptual models

NASA Astrophysics Data System (ADS)

Bean, J. R.; Zoehfeld, K.; Mitchell, K.; Levine, J.; White, L. D.

2016-12-01

Understanding climate change and how to mitigate the causes and consequences of anthropogenic activities are essential components of the Next Generations Science Standards. To comprehend climate change today and why current rates and magnitudes of change are of concern, students must understand the various factors that drive Earth system processes and also how they interrelate. The Understanding Global Change web resource in development from the UC Museum of Paleontology will provide science educators with a conceptual framework, graphical models, lessons, and assessment templates for teaching NGSS aligned, interdisciplinary, climate change curricula. To facilitate students learning about the Earth as a dynamic, interacting system of ongoing processes, the Understanding Global Change site will provide explicit conceptual links for the causes of climate change (e.g., burning of fossil fuels, deforestation), Earth system processes (e.g., Earth's energy budget, water cycle), and the changes scientists measure in the Earth system (e.g., temperature, precipitation). The conceptual links among topics will be presented in a series of storyboards that visually represent relationships and feedbacks among components of the Earth system and will provide teachers with guides for implementing NGSS-aligned climate change instruction that addresses physical science, life sciences, Earth and space science, and engineering performance expectations. These visualization and instructional methods are used by teachers during professional development programs at UC Berkeley and the Smithsonian National Museum of Natural History and are being tested in San Francisco Bay Area classrooms.

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

PubMed

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

2014-01-01

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

Future Effects of Southern Hemisphere Stratospheric Zonal Asymmetries on Climate

NASA Astrophysics Data System (ADS)

Stone, K.; Solomon, S.; Kinnison, D. E.; Fyfe, J. C.

2017-12-01

Stratospheric zonal asymmetries in the Southern Hemisphere have been shown to have significant influences on both stratospheric and tropospheric dynamics and climate. Accurate representation of stratospheric ozone in particular is important for realistic simulation of the polar vortex strength and temperature trends. This is therefore also important for stratospheric ozone change's effect on the troposphere, both through modulation of the Southern Annular Mode (SAM), and more localized climate. Here, we characterization the impact of future changes in Southern Hemisphere zonal asymmetry on tropospheric climate, including changes to future tropospheric temperature, and precipitation. The separate impacts of increasing GHGs and ozone recovery on the zonal asymmetric influence on the surface are also investigated. For this purpose, we use a variety of models, including Chemistry Climate Model Initiative simulations from the Community Earth System Model, version 1, with the Whole Atmosphere Community Climate Model (CESM1(WACCM)) and the Australian Community Climate and Earth System Simulator-Chemistry Climate Model (ACCESS-CCM). These models have interactive chemistry and can therefore more accurately represent the zonally asymmetric nature of the stratosphere. The CESM1(WACCM) and ACCESS-CCM models are also compared to simulations from the Canadian Can2ESM model and CESM-Large Ensemble Project (LENS) that have prescribed ozone to further investigate the importance of simulating stratospheric zonal asymmetry.

Venus climate stability and volcanic resurfacing rates

NASA Technical Reports Server (NTRS)

Bullock, M. A.; Grinspoon, D. H.; Pollack, J. B.

1994-01-01

The climate of Venus is to a large degree controlled by the radiative properties of its massive atmosphere. In addition, outgassing due to volcanic activity, exospheric escape processes, and surface/atmosphere interactions may all be important in moderating the abundances of atmospheric CO2 and other volatiles. We have developed an evolutionary climate model for Venus using a systems approach that emphasizes feedbacks between elements in the climate system. Modules for atmospheric radiative transfer, surface/atmosphere interactions, tropospheric chemistry, and exospheric escape processes have so far been developed. Climate feedback loops result from interconnections between modules, in the form of the environmental parameters pressure, temperature, and atmospheric mixing ratios. The radiative transfer module has been implemented by using Rosseland mean opacities in a one dimensional grey radiative-convective model. The model has been solved for the static (time independent) case to determine climate equilibrium points. The dynamics of the model have also been explored by employing reaction/diffusion kinetics for possible surface atmosphere heterogeneous reactions over geologic timescales. It was found that under current conditions, the model predicts that the climate of Venus is at or near an unstable equilibrium point. The effects of constant rate volcanism and corresponding exsolution of volatiles on the stability of the climate model were also explored.

Understanding Water-Energy-Ecology Nexus from an Integrated Earth-Human System Perspective

NASA Astrophysics Data System (ADS)

Li, H. Y.; Zhang, X.; Wan, W.; Zhuang, Y.; Hejazi, M. I.; Leung, L. R.

2017-12-01

Both Earth and human systems exert notable controls on streamflow and stream temperature that influence energy production and ecosystem health. An integrated water model representing river processes and reservoir regulations has been developed and coupled to a land surface model and an integrated assessment model of energy, land, water, and socioeconomics to investigate the energy-water-ecology nexus in the context of climate change and water management. Simulations driven by two climate change projections following the RCP 4.5 and RCP 8.5 radiative forcing scenarios, with and without water management, are analyzed to evaluate the individual and combined effects of climate change and water management on streamflow and stream temperature in the U.S. The simulations revealed important impacts of climate change and water management on hydrological droughts. The simulations also revealed the dynamics of competition between changes in water demand and water availability in the RCP 4.5 and RCP 8.5 scenarios that influence streamflow and stream temperature, with important consequences to thermoelectricity production and future survival of juvenile Salmon. The integrated water model is being implemented to the Accelerated Climate Modeling for Energy (ACME), a coupled Earth System Model, to enable future investigations of the energy-water-ecology nexus in the integrated Earth-Human system.

Teleconnection Paths via Climate Network Direct Link Detection.

PubMed

Zhou, Dong; Gozolchiani, Avi; Ashkenazy, Yosef; Havlin, Shlomo

2015-12-31

Teleconnections describe remote connections (typically thousands of kilometers) of the climate system. These are of great importance in climate dynamics as they reflect the transportation of energy and climate change on global scales (like the El Niño phenomenon). Yet, the path of influence propagation between such remote regions, and weighting associated with different paths, are only partially known. Here we propose a systematic climate network approach to find and quantify the optimal paths between remotely distant interacting locations. Specifically, we separate the correlations between two grid points into direct and indirect components, where the optimal path is found based on a minimal total cost function of the direct links. We demonstrate our method using near surface air temperature reanalysis data, on identifying cross-latitude teleconnections and their corresponding optimal paths. The proposed method may be used to quantify and improve our understanding regarding the emergence of climate patterns on global scales.

Dispersive models describing mosquitoes’ population dynamics

NASA Astrophysics Data System (ADS)

Yamashita, W. M. S.; Takahashi, L. T.; Chapiro, G.

2016-08-01

The global incidences of dengue and, more recently, zica virus have increased the interest in studying and understanding the mosquito population dynamics. Understanding this dynamics is important for public health in countries where climatic and environmental conditions are favorable for the propagation of these diseases. This work is based on the study of nonlinear mathematical models dealing with the life cycle of the dengue mosquito using partial differential equations. We investigate the existence of traveling wave solutions using semi-analytical method combining dynamical systems techniques and numerical integration. Obtained solutions are validated through numerical simulations using finite difference schemes.

Long-term dynamics of a floodplain shallow lake in the Pantanal wetland: Is it all about climate?

PubMed

Silio-Calzada, Ana; Barquín, José; Huszar, Vera L M; Mazzeo, Nestor; Méndez, Fernando; Álvarez-Martínez, Jose Manuel

2017-12-15

Hydrological variability over seasonal and multi-annual timescales strongly shapes the ecological structure and functioning of floodplain ecosystems. The current IPCC climate scenario foresees an increase in the frequency of extreme events. This, in conjunction with other anthropogenic disturbances (e.g., river regulation or land-use changes) poses a serious threat to the natural functioning of these ecosystems. In this study we aimed to i) evaluate the long-term variability of the flooded area of the third largest floodplain lake in the Brazilian Pantanal using remote sensing techniques, and ii) analyze the possible factors influencing this variability. Changes in open-water and riparian floodplain-wetland vegetation areas were mapped by applying an ad hoc-developed remote-sensing method (including a newly developed normalized water index, NWI) to 221 Landsat-Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+) images, acquired between 1984 and 2011. Added to the lake's natural swing between riparian floodplain-wetland vegetation expansion and retraction, our analyses revealed large interannual changes, grouped into three main periods within the studied time interval. Moreover, our results indicate that this floodplain-lake system is losing open-water area, paired with an increase in riparian floodplain-wetland vegetation. The system's long-term dynamics are not all climate related, but are the result of a combination of drivers. The start of the Manso dam's operation upstream of the studied system, and the subsequent river regulation because of the dam operation, coupled with climatic oscillation appear to be responsible for the observed changes. However, other factors which were not considered in this study might also be important in this process and contributing to the reduction of the system's resilience to droughts (e.g., land-use changes). This study illustrates the serious conservation risks that the Pantanal faces in the near future, given the current climate-change scenario and the accumulation of dam building projects in this region. Copyright © 2017 Elsevier B.V. All rights reserved.

Coupled Atmosphere-Surface Modeling of Lake Levels of the North American Great Lakes under Climate Change

NASA Astrophysics Data System (ADS)

Lofgren, B. M.; Xiao, C.

2016-12-01

The influence of projected climate change on the water levels of the Great Lakes is subject to considerable uncertainty, and methods that have long been used to determine this sensitivity have been discredited. A strong candidate, albeit expensive, to replace problematic methods is to use outputs that result from dynamical downscaling of future climate simulations, focused on the hydroclimate of the Great Lakes basin. We have produced initial estimates of Great Lakes water levels in the mid- and late 21st century using the Weather Research and Forecasting (WRF) model, including its lake module, driven by lateral boundary conditions from the Geophysical Fluid Dynamics Lab Climate Model version 3.0 (GFDL CM3), under RCP4.5 and 8.5 scenarios. Future lake levels are influenced by the balance between projected general increases in precipitation and increases in evapotranspiration from both land and lake in the basin, driven primarily by the surface radiative energy budget and secondarily by air temperature. The net result was drops in lake level of up to 15 cm, in contrast to the results from much-used older methods, which often projected drops exceeding 1 m. Future plans include increased detail in the simulation of water flow overland and in river channels using WRF-Hydro, and full coupling of regional atmospheric systems with 3-dimensional dynamical lake implementation of the Finite Volume Community Ocean Model (FVCOM).

From dynamic ocean management to climate-ready management: a case study using blue whales in the northeast Pacific.

NASA Astrophysics Data System (ADS)

Hazen, E. L.

2016-02-01

Highly migratory species regularly traverse human-imposed boundaries including exclusive economic zones and marine protected areas, thus are difficult to manage using traditional spatial approaches. Blue whales (Balaenoptera musculus) are seasonal visitors to the California Current System that target a single prey resource, krill (Euphausia pacifica, Thysanoessa spinifera), and migrate large distances to find and exploit ephemeral prey patches. Successful management of blue whales requires improved understanding of how fine-scale foraging ecology translates to population abundances. Specifically, sub-lethal factors such as anthropogenic noise and climate change, and lethal factors such as ship strikes may be limiting recovery and can be difficult to account for in current management strategies. Here we use an extensive dataset of fine-scale accelerometers (55) and broad-scale satellite tags (104) deployed on Northeast Pacific blue whales to examine the energetics of foraging, overlap with human risk, and projections of future habitat with climate change. We quantify the importance of dense prey patches (> 100 krill per cubic meter) for blue whale energetics and fitness. Distribution models can be used in concert with industry and regional offices to produce dynamic rules to reduce vessel interactions. We propose telemetry data are ripe for use in establishing dynamic management approaches that account for daily to seasonal management areas to minimize anthropogenic risks, and are also adaptable to long-term climate-driven changes in habitat.

From dynamic ocean management to climate-ready management: a case study using blue whales in the northeast Pacific.

NASA Astrophysics Data System (ADS)

Hazen, E. L.

2016-12-01

Highly migratory species regularly traverse human-imposed boundaries including exclusive economic zones and marine protected areas, thus are difficult to manage using traditional spatial approaches. Blue whales (Balaenoptera musculus) are seasonal visitors to the California Current System that target a single prey resource, krill (Euphausia pacifica, Thysanoessa spinifera), and migrate large distances to find and exploit ephemeral prey patches. Successful management of blue whales requires improved understanding of how fine-scale foraging ecology translates to population abundances. Specifically, sub-lethal factors such as anthropogenic noise and climate change, and lethal factors such as ship strikes may be limiting recovery and can be difficult to account for in current management strategies. Here we use an extensive dataset of fine-scale accelerometers (55) and broad-scale satellite tags (104) deployed on Northeast Pacific blue whales to examine the energetics of foraging, overlap with human risk, and projections of future habitat with climate change. We quantify the importance of dense prey patches (> 100 krill per cubic meter) for blue whale energetics and fitness. Distribution models can be used in concert with industry and regional offices to produce dynamic rules to reduce vessel interactions. We propose telemetry data are ripe for use in establishing dynamic management approaches that account for daily to seasonal management areas to minimize anthropogenic risks, and are also adaptable to long-term climate-driven changes in habitat.

Influence of dimethyl sulfide on the carbon cycle and biological production

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

Wang, Shanlin; Maltrud, Mathew; Elliott, Scott

Dimethyl sulfide (DMS) is a significant source of marine sulfate aerosol and plays an important role in modifying cloud properties. Fully coupled climate simulations using dynamic marine ecosystem and DMS calculations are conducted to estimate DMS fluxes under various climate scenarios and to examine the sign and strength of phytoplankton-DMS-climate feedbacks for the first time. Simulation results show small differences in the DMS production and emissions between pre-industrial and present climate scenarios, except for some areas in the Southern Ocean. There are clear changes in surface ocean DMS concentrations moving into the future, and they are attributable to changes inmore » phytoplankton production and competition driven by complex spatially varying mechanisms. Comparisons between parallel simulations with and without DMS fluxes into the atmosphere show significant differences in marine ecosystems and physical fields. Without DMS, the missing subsequent aerosol indirect effects on clouds and radiative forcing lead to fewer clouds, more solar radiation, and a much warmer climate. Phaeocystis, a uniquely efficient organosulfur producer with a growth advantage under cooler climate states, can benefit from producing the compound through cooling effects of DMS in the climate system. Our results show a tight coupling between the sulfur and carbon cycles. The ocean carbon uptake declines without DMS emissions to the atmosphere. The analysis indicates a weak positive phytoplankton-DMS-climate feedback at the global scale, with large spatial variations driven by individual autotrophic functional groups and complex mechanisms. The sign and strength of the feedback vary with climate states and phytoplankton groups. This highlights the importance of a dynamic marine ecosystem module and the sulfur cycle mechanism in climate projections.« less

Influence of dimethyl sulfide on the carbon cycle and biological production

DOE PAGES

Wang, Shanlin; Maltrud, Mathew; Elliott, Scott; ...

2018-02-27

Dimethyl sulfide (DMS) is a significant source of marine sulfate aerosol and plays an important role in modifying cloud properties. Fully coupled climate simulations using dynamic marine ecosystem and DMS calculations are conducted to estimate DMS fluxes under various climate scenarios and to examine the sign and strength of phytoplankton-DMS-climate feedbacks for the first time. Simulation results show small differences in the DMS production and emissions between pre-industrial and present climate scenarios, except for some areas in the Southern Ocean. There are clear changes in surface ocean DMS concentrations moving into the future, and they are attributable to changes inmore » phytoplankton production and competition driven by complex spatially varying mechanisms. Comparisons between parallel simulations with and without DMS fluxes into the atmosphere show significant differences in marine ecosystems and physical fields. Without DMS, the missing subsequent aerosol indirect effects on clouds and radiative forcing lead to fewer clouds, more solar radiation, and a much warmer climate. Phaeocystis, a uniquely efficient organosulfur producer with a growth advantage under cooler climate states, can benefit from producing the compound through cooling effects of DMS in the climate system. Our results show a tight coupling between the sulfur and carbon cycles. The ocean carbon uptake declines without DMS emissions to the atmosphere. The analysis indicates a weak positive phytoplankton-DMS-climate feedback at the global scale, with large spatial variations driven by individual autotrophic functional groups and complex mechanisms. The sign and strength of the feedback vary with climate states and phytoplankton groups. This highlights the importance of a dynamic marine ecosystem module and the sulfur cycle mechanism in climate projections.« less

Climate change impacts on food system

NASA Astrophysics Data System (ADS)

Zhang, X.; Cai, X.; Zhu, T.

2014-12-01

Food system includes biophysical factors (climate, land and water), human environments (production technologies and food consumption, distribution and marketing), as well as the dynamic interactions within them. Climate change affects agriculture and food systems in various ways. Agricultural production can be influenced directly by climatic factors such as mean temperature rising, change in rainfall patterns, and more frequent extreme events. Eventually, climate change could cause shift of arable land, alteration of water availability, abnormal fluctuation of food prices, and increase of people at risk of malnutrition. This work aims to evaluate how climate change would affect agricultural production biophysically and how these effects would propagate to social factors at the global level. In order to model the complex interactions between the natural and social components, a Global Optimization model of Agricultural Land and Water resources (GOALW) is applied to the analysis. GOALW includes various demands of human society (food, feed, other), explicit production module, and irrigation water availability constraint. The objective of GOALW is to maximize global social welfare (consumers' surplus and producers' surplus).Crop-wise irrigation water use in different regions around the world are determined by the model; marginal value of water (MVW) can be obtained from the model, which implies how much additional welfare benefit could be gained with one unit increase in local water availability. Using GOALW, we will analyze two questions in this presentation: 1) how climate change will alter irrigation requirements and how the social system would buffer that by price/demand adjustment; 2) how will the MVW be affected by climate change and what are the controlling factors. These results facilitate meaningful insights for investment and adaptation strategies in sustaining world's food security under climate change.

Understanding the major transitions in Quaternary climate dynamics

NASA Astrophysics Data System (ADS)

Willeit, Matteo; Ganopolski, Andrey

2017-04-01

Climate dynamics over the past 3 million years was characterized by strong variability associated with glacial cycles and several distinct regime changes. The Pliocene-Pleistocene Transition (PPT), which happened around 2.7 million years ago, was characterized by the appearance of the large continental ice sheets over Northern Eurasia and North America. For two million years after the PPT climate variability was dominated by relatively symmetric 40 kyr cycles. At around 1 million years ago the dominant mode of climate variability experienced a relatively rapid transition from 40 kyr to strongly asymmetric 100 kyr cycles of larger amplitude (Mid-Pleistocene Transition). Additionally, during the past 800 kyr there are clear differences between the earlier and the later glacial cycles with the last five cycles characterized by larger magnitude of variability (Mid-Brunhes Event). Here, we use the Earth system model of intermediate complexity CLIMBER-2 to explore possible mechanisms that could explain these regime shifts. CLIMBER-2 incorporates all major components of the Earth system - atmosphere, ocean, land surface, northern hemisphere ice sheets, terrestrial biota and soil carbon, marine biogeochemistry and aeolian dust. The model was optimally tuned to reproduce climate, ice volume and CO2 variability over the last 400,000 years. Using the same model version, we performed a large set of simulations covering the entire Quaternary (3 million years) starting from identical initial conditions and using a parallelization in time technique which consists of starting the model at different times (every 100,000 years) and running each simulation for 500,000 years. The Earth's orbital variations are the only prescribed radiative forcing. Several sets of the Northern Hemisphere orography and sediment thickness representing different stages of landscape evolution during the Quaternary are prescribed as boundary conditions for the ice sheet model and volcanic CO2 outgassing is used as the external forcing for the carbon cycle to allow for different background atmospheric CO2 concentrations. We show that by varying only these two model boundary conditions and volcanic forcing the model is able to reproduce the major regime changes of Quaternary long-term climate dynamics.

Sensitivity of the carbon cycle in the Arctic to climate change

USGS Publications Warehouse

McGuire, A. David; Anderson, Leif G.; Christensen, Torben R.; Dallimore, Scott; Guo, Laodong; Hayes, Daniel J.; Heimann, Martin; Lorenson, T.D.; Macdonald, Robie W.; Roulet, Nigel

2009-01-01

The recent warming in the Arctic is affecting a broad spectrum of physical, ecological, and human/cultural systems that may be irreversible on century time scales and have the potential to cause rapid changes in the earth system. The response of the carbon cycle of the Arctic to changes in climate is a major issue of global concern, yet there has not been a comprehensive review of the status of the contemporary carbon cycle of the Arctic and its response to climate change. This review is designed to clarify key uncertainties and vulnerabilities in the response of the carbon cycle of the Arctic to ongoing climatic change. While it is clear that there are substantial stocks of carbon in the Arctic, there are also significant uncertainties associated with the magnitude of organic matter stocks contained in permafrost and the storage of methane hydrates beneath both subterranean and submerged permafrost of the Arctic. In the context of the global carbon cycle, this review demonstrates that the Arctic plays an important role in the global dynamics of both CO2 and CH4. Studies suggest that the Arctic has been a sink for atmospheric CO2 of between 0 and 0.8 Pg C/yr in recent decades, which is between 0% and 25% of the global net land/ocean flux during the 1990s. The Arctic is a substantial source of CH4 to the atmosphere (between 32 and 112 Tg CH4/yr), primarily because of the large area of wetlands throughout the region. Analyses to date indicate that the sensitivity of the carbon cycle of the Arctic during the remainder of the 21st century is highly uncertain. To improve the capability to assess the sensitivity of the carbon cycle of the Arctic to projected climate change, we recommend that (1) integrated regional studies be conducted to link observations of carbon dynamics to the processes that are likely to influence those dynamics, and (2) the understanding gained from these integrated studies be incorporated into both uncoupled and fully coupled carbon–climate modeling efforts.

Increases in Growing Season Length and Changes in Precipitation at Six Different Arctic and Subarctic Ecosystems from 1906-Present

NASA Astrophysics Data System (ADS)

Culler, L. E.; Finger, R.; Plane, E.; Ayres, M.; Virginia, R. A.

2015-12-01

Ecological dynamics across the Arctic are responding to rapid changes in climate. As a whole, the Arctic has warmed at approximately twice the rate of the rest of the world, but changes in temperature and precipitation experienced at regional and local scales are most important for coupled human-natural systems. In addition, biologically-relevant climate indices are necessary for quantifying ecological responses of terrestrial and aquatic systems to varying climate. We compared climatic changes at six different Arctic and sub-Arctic locations, including two in Greenland (Kangerlussuaq, Sisimiut), one in Sweden (Abisko), and three in Alaska (Barrow, Nome, Fairbanks). We amassed weather data (daily temperature and precipitation), dating as far back as 1906, from public-access databases and used these data to calculate indices such as length of growing season, growing season degree days (GDD), and growing season precipitation. Annual GDD increased at all locations (average of 13% increase in GDD since 1980), but especially in western Greenland (16 and 37% in Kangerlussuaq and Sisimiut, respectively). Changes in growing season precipitation were more variable, with only Barrow, AK and Abisko, Sweden experiencing increased precipitation. All other sites experienced stable or slightly declining precipitation. Increasing temperatures and relatively stable precipitation translates to increased evapotranspiration potential, which influences soil moisture, lake depth, vegetation, carbon emissions, and fire susceptibility. Understanding local and regional trends in temperature and precipitation can help explain observed phenological changes and other processes at population, community, and ecosystem levels. In addition, identification of locations most susceptible to future change will allow scientists to closely monitor their ecological dynamics, anticipate changes in coupled human-natural systems, and consider adaptation plans for the most rapidly changing systems.

The role of East Asian monsoon system in shaping population divergence and dynamics of a constructive desert shrub Reaumuria soongarica

PubMed Central

Yin, Hengxia; Yan, Xia; Shi, Yong; Qian, Chaoju; Li, Zhonghu; Zhang, Wen; Wang, Lirong; Li, Yi; Li, Xiaoze; Chen, Guoxiong; Li, Xinrong; Nevo, Eviatar; Ma, Xiao-Fei

2015-01-01

Both of the uplift of Qinghai-Tibet Plateau (QTP) and the development of East Asian monsoon system (EAMS) could have comprehensively impacted the formation and evolution of Arid Central Asia (ACA). To understand how desert plants endemic to ACA responded to these two factors, we profiled the historical population dynamics and distribution range shift of a constructive desert shrub Reaumuria soongarica (Tamaricaceae) based on species wide investigation of sequence variation of chloroplast DNA and nuclear ribosomal ITS. Phylogenetic analysis uncovered a deep divergence occurring at ca. 2.96 Mya between the western and eastern lineages of R. soongarica, and ecological niche modeling analysis strongly supported that the monsoonal climate could have fragmented its habitats in both glacial and interglacial periods and impelled its intraspecific divergence. Additionally, the population from the east monsoonal zone expanded rapidly, suggesting that the local monsoonal climate significantly impacted its population dynamics. The isolation by distance tests supported strong maternal gene flow along the direction of the East Asian winter monsoon, whose intensification induced the genetic admixture along the latitudinal populations of R. soongarica. Our results presented a new case that the development of EAMS had prominently impacted the intraspecific divergence and population dynamics of this desert plant. PMID:26510579

Marc Snir | Argonne National Laboratory

Science.gov Websites

Molecular biology Proteomics Environmental science & technology Air quality Atmospheric & climate , H.S., Jr., Demonstrating the scalability of a molecular dynamics application on a Petaflop computer Transformations IGSBInstitute for Genomics and Systems Biology IMEInstitute for Molecular Engineering JCESRJoint

Introducing Subrid-scale Cloud Feedbacks to Radiation for Regional Meteorological and Cllimate Modeling

EPA Science Inventory

Convection systems and associated cloudiness directly influence regional and local radiation budgets, and dynamics and thermodynamics through feedbacks. However, most subgrid-scale convective parameterizations in regional weather and climate models do not consider cumulus cloud ...

Research Review, 1984

NASA Technical Reports Server (NTRS)

1986-01-01

A variety of topics relevant to global modeling and simulation are presented. Areas of interest include: (1) analysis and forecast studies; (2) satellite observing systems; (3) analysis and forecast model development; (4) atmospheric dynamics and diagnostic studies; (5) climate/ocean-air interactions; and notes from lectures.

Biodiversity redistribution under climate change: Impacts on ecosystems and human well-being.

PubMed

Pecl, Gretta T; Araújo, Miguel B; Bell, Johann D; Blanchard, Julia; Bonebrake, Timothy C; Chen, I-Ching; Clark, Timothy D; Colwell, Robert K; Danielsen, Finn; Evengård, Birgitta; Falconi, Lorena; Ferrier, Simon; Frusher, Stewart; Garcia, Raquel A; Griffis, Roger B; Hobday, Alistair J; Janion-Scheepers, Charlene; Jarzyna, Marta A; Jennings, Sarah; Lenoir, Jonathan; Linnetved, Hlif I; Martin, Victoria Y; McCormack, Phillipa C; McDonald, Jan; Mitchell, Nicola J; Mustonen, Tero; Pandolfi, John M; Pettorelli, Nathalie; Popova, Ekaterina; Robinson, Sharon A; Scheffers, Brett R; Shaw, Justine D; Sorte, Cascade J B; Strugnell, Jan M; Sunday, Jennifer M; Tuanmu, Mao-Ning; Vergés, Adriana; Villanueva, Cecilia; Wernberg, Thomas; Wapstra, Erik; Williams, Stephen E

2017-03-31

Distributions of Earth's species are changing at accelerating rates, increasingly driven by human-mediated climate change. Such changes are already altering the composition of ecological communities, but beyond conservation of natural systems, how and why does this matter? We review evidence that climate-driven species redistribution at regional to global scales affects ecosystem functioning, human well-being, and the dynamics of climate change itself. Production of natural resources required for food security, patterns of disease transmission, and processes of carbon sequestration are all altered by changes in species distribution. Consideration of these effects of biodiversity redistribution is critical yet lacking in most mitigation and adaptation strategies, including the United Nation's Sustainable Development Goals. Copyright © 2017, American Association for the Advancement of Science.

Definitions of climate and climate change under varying external conditions

NASA Astrophysics Data System (ADS)

Werndl, C.

2014-06-01

Commonly, definitions of climate are endorsed where the external conditions are held constant. This paper argues that these definitions risk being empirically void because in reality the external conditions vary. As a consequence, analogous definitions for varying external conditions are explored with help of the recently developed theory of non-autonomous dynamical systems, and the similarities and differences between the cases of constant and varying external conditions are discussed. It is argued that there are analogous definitions for varying external conditions which are preferable to the definitions where the external conditions are held constant. In this context, a novel definition is proposed (namely, climate as the distribution over time under a regime of varying external conditions), which is argued to be promising.

Modelling the Climate - Greenland Ice Sheet Interaction in the Coupled Ice-sheet/Climate Model EC-EARTH - PISM

NASA Astrophysics Data System (ADS)

Yang, S.; Madsen, M. S.; Rodehacke, C. B.; Svendsen, S. H.; Adalgeirsdottir, G.

2014-12-01

Recent observations show that the Greenland ice sheet (GrIS) has been losing mass with an increasing speed during the past decades. Predicting the GrIS changes and their climate consequences relies on the understanding of the interaction of the GrIS with the climate system on both global and local scales, and requires climate model systems with an explicit and physically consistent ice sheet module. A fully coupled global climate model with a dynamical ice sheet model for the GrIS has recently been developed. The model system, EC-EARTH - PISM, consists of the EC-EARTH, an atmosphere, ocean and sea ice model system, and the Parallel Ice Sheet Model (PISM). The coupling of PISM includes a modified surface physical parameterization in EC-EARTH adapted to the land ice surface over glaciated regions in Greenland. The PISM ice sheet model is forced with the surface mass balance (SMB) directly computed inside the EC-EARTH atmospheric module and accounting for the precipitation, the surface evaporation, and the melting of snow and ice over land ice. PISM returns the simulated basal melt, ice discharge and ice cover (extent and thickness) as boundary conditions to EC-EARTH. This coupled system is mass and energy conserving without being constrained by any anomaly correction or flux adjustment, and hence is suitable for investigation of ice sheet - climate feedbacks. Three multi-century experiments for warm climate scenarios under (1) the RCP85 climate forcing, (2) an abrupt 4xCO2 and (3) an idealized 1% per year CO2 increase are performed using the coupled model system. The experiments are compared with their counterparts of the standard CMIP5 simulations (without the interactive ice sheet) to evaluate the performance of the coupled system and to quantify the GrIS feedbacks. In particular, the evolution of the Greenland ice sheet under the warm climate and its impacts on the climate system are investigated. Freshwater fluxes from the Greenland ice sheet melt to the Arctic and North Atlantic basin and their influence on the ocean stratification and ocean circulation are analysed. The changes in the surface climate and the atmospheric circulation associated with the impact of the Greenland ice sheet changes are quantified. The interaction between the Greenland ice sheet and Arctic sea ice is also examined.

Combining surface reanalysis and remote sensing data for monitoring evapotranspiration

USGS Publications Warehouse

Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W.

2012-01-01

Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.

A decision support tool for sustainable planning of urban water systems: presenting the Dynamic Urban Water Simulation Model.

PubMed

Willuweit, Lars; O'Sullivan, John J

2013-12-15

Population growth, urbanisation and climate change represent significant pressures on urban water resources, requiring water managers to consider a wider array of management options that account for economic, social and environmental factors. The Dynamic Urban Water Simulation Model (DUWSiM) developed in this study links urban water balance concepts with the land use dynamics model MOLAND and the climate model LARS-WG, providing a platform for long term planning of urban water supply and water demand by analysing the effects of urbanisation scenarios and climatic changes on the urban water cycle. Based on potential urbanisation scenarios and their effects on a city's water cycle, DUWSiM provides the functionality for assessing the feasibility of centralised and decentralised water supply and water demand management options based on forecasted water demand, stormwater and wastewater generation, whole life cost and energy and potential for water recycling. DUWSiM has been tested using data from Dublin, the capital of Ireland, and it has been shown that the model is able to satisfactorily predict water demand and stormwater runoff. Copyright © 2013 Elsevier Ltd. All rights reserved.

Regional Climate Simulations over North America: Interaction of Local Processes with Improved Large-Scale Flow.

NASA Astrophysics Data System (ADS)

Miguez-Macho, Gonzalo; Stenchikov, Georgiy L.; Robock, Alan

2005-04-01

The reasons for biases in regional climate simulations were investigated in an attempt to discern whether they arise from deficiencies in the model parameterizations or are due to dynamical problems. Using the Regional Atmospheric Modeling System (RAMS) forced by the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis, the detailed climate over North America at 50-km resolution for June 2000 was simulated. First, the RAMS equations were modified to make them applicable to a large region, and its turbulence parameterization was corrected. The initial simulations showed large biases in the location of precipitation patterns and surface air temperatures. By implementing higher-resolution soil data, soil moisture and soil temperature initialization, and corrections to the Kain-Fritch convective scheme, the temperature biases and precipitation amount errors could be removed, but the precipitation location errors remained. The precipitation location biases could only be improved by implementing spectral nudging of the large-scale (wavelength of 2500 km) dynamics in RAMS. This corrected for circulation errors produced by interactions and reflection of the internal domain dynamics with the lateral boundaries where the model was forced by the reanalysis.

Use of System Thinking Software for Determining Climate Change Impacts in Water Balance for the Rio Yaqui Basin, Sonora, Mexico

NASA Astrophysics Data System (ADS)

Tapia, E. M.; Minjarez, J. I.; Espinoza, I. G.; Sosa, C. M.

2013-05-01

Climate change in Northwestern Mexico and its hydrological impact on water balance, water scarcity and flooding events, has become a matter of increasing concern over the past several decades due to the region's semiarid conditions. Changes in temperature, precipitation, and sea level will affect agriculture, farming, and aquaculture, in addition to compromising the quality of water resources for human consumption. According to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC, 2007), Global Circulation Models (GCMs) can provide reliable estimations of future climate conditions in addition to atmospheric processes that cause them, based on different input scenarios such as A2 (higher emission of greenhouse gases) and B1 (lower emission of GHG), among others. However, GCM`s resolution results to coarse in regions which have high space and time climate variability. To remediate this, several methods based on dynamical, statistical and empirical analysis have been proposed for downcaling. In this study, we evaluate possible changes in precipitation and temperature for the "Rio Yaqui Basin" in Sonora, Mexico and assess the impact of such changes on runoff, evapotranspiration and aquifer recharge for the 2010-2099 period of time. For this purpose, we analyzed the results of a Bias Corrected and Downscaled Climate Projection from the World Climate Research Programme's (WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model dataset: UKMO-HADCM3 from the Hadley Centre for Climate Prediction. Northwest Mexico is under the influence of the North American Monsoon (NAM), a system affecting the states of Sinaloa and Sonora where the precipitation regimes change drastically during the summer months of June, July and August. It is associated to the sharp variations of topography, precipitation and temperature regimes in the region, so the importance of analyzing the downscaled climate projections. The Rio Yaqui Basin is one of the most important basins in Sonora. It is located in northwestern Mexico, and covers an approximate area of 74,054 km2, providing water for one of the most prominent agricultural zones in the state. We used the System Thinking Software "Stella 9.0.2" to dynamically visualize the effects of climate change on the Rio Yaqui Basin. In this software, the main components of the water balance are simulated over the designated period of time with tools that include stocks and flow diagrams, causal loops, model equations and built in functions. Climate change projections for the Rio Yaqui Basin showed highly variable runoff behaviors, indicating the possibility of frequent droughts alternating with years of extraordinary runoff. Simulations generated through the System Thinking Software provides a reasonable basis for establishing policies for optimizing storage of water during extraordinary runoff periods that can serve as water supplies during frequent droughts.

Climate-driven unsteady denudation and sediment flux in a high-relief unglaciated catchment-fan using 26Al and 10Be: Panamint Valley, California

NASA Astrophysics Data System (ADS)

Mason, Cody C.; Romans, Brian W.

2018-06-01

Environmental changes within erosional catchments of sediment routing systems are predicted to modulate sediment transfer dynamics. However, empirical and numerical models that predict such phenomena are difficult to test in natural systems over multi-millennial timescales. Tectonic boundary conditions and climate history in the Panamint Range, California, are relatively well-constrained by existing low-temperature thermochronology and regional multi-proxy paleoclimate studies, respectively. Catchment-fan systems present there minimize sediment storage and recycling, offering an excellent natural laboratory to test models of climate-sedimentary dynamics. We used stratigraphic characterization and cosmogenic radionuclides (CRNs; 26Al and 10Be) in the Pleasant Canyon complex (PCC), a linked catchment-fan system, to examine the effects of Pleistocene high-magnitude, high-frequency climate change on CRN-derived denudation rates and sediment flux in a high-relief, unglaciated catchment-fan system. Calculated 26Al/10Be burial ages from 13 samples collected in an ∼180 m thick outcropping stratigraphic succession range from ca. 1.55 ± 0.22 Ma in basal strata, to ca. 0.36 ± 0.18-0.52 ± 0.20 Ma within the uppermost part of the succession. The mean long-term CRN-derived paleodenudation rate, 36 ± 8 mm/kyr (1σ), is higher than the modern rate of 24 ± 0.6 mm/kyr from Pleasant Canyon, and paleodenudation rates during the middle Pleistocene display some high-frequency variability in the high end (up to 54 ± 10 mm/kyr). The highest CRN-derived denudation rates are associated with stratigraphic evidence for increased precipitation during glacial-pluvial events after the middle Pleistocene transition (post ca. 0.75 Ma), suggesting 100 kyr Milankovitch periodicity could drive the observed variability. We investigated the potential for non-equilibrium sedimentary processes, i.e. increased landslides or sediment storage/recycling, to influence apparent paleodenudation rates; end-member mixing models suggest that a mixture of >50% low-CRN-concentration sediment from landslides is required to produce the largest observed increase in paleodenudation rate. The overall pattern of CRN-derived burial ages, paleodenudation rates, and stratigraphic facies suggests Milankovitch timescale climate transitions drive variability in catchment denudation rates and sediment flux, or alternatively that climate transitions affect sedimentary process regimes that result in measurable variability of CRN concentrations in unglaciated catchment-fan systems.

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

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

Dynamic response of desert wetlands to abrupt climate change

PubMed Central

Springer, Kathleen B.; Manker, Craig R.; Pigati, Jeffrey S.

2015-01-01

Desert wetlands are keystone ecosystems in arid environments and are preserved in the geologic record as groundwater discharge (GWD) deposits. GWD deposits are inherently discontinuous and stratigraphically complex, which has limited our understanding of how desert wetlands responded to past episodes of rapid climate change. Previous studies have shown that wetlands responded to climate change on glacial to interglacial timescales, but their sensitivity to short-lived climate perturbations is largely unknown. Here, we show that GWD deposits in the Las Vegas Valley (southern Nevada, United States) provide a detailed and nearly complete record of dynamic hydrologic changes during the past 35 ka (thousands of calibrated 14C years before present), including cycles of wetland expansion and contraction that correlate tightly with climatic oscillations recorded in the Greenland ice cores. Cessation of discharge associated with rapid warming events resulted in the collapse of entire wetland systems in the Las Vegas Valley at multiple times during the late Quaternary. On average, drought-like conditions, as recorded by widespread erosion and the formation of desert soils, lasted for a few centuries. This record illustrates the vulnerability of desert wetland flora and fauna to abrupt climate change. It also shows that GWD deposits can be used to reconstruct paleohydrologic conditions at millennial to submillennial timescales and informs conservation efforts aimed at protecting these fragile ecosystems in the face of anthropogenic warming. PMID:26554007

Dynamic response of desert wetlands to abrupt climate change

USGS Publications Warehouse

Springer, Kathleen; Manker, Craig; Pigati, Jeffrey S.

2015-01-01

Desert wetlands are keystone ecosystems in arid environments and are preserved in the geologic record as groundwater discharge (GWD) deposits. GWD deposits are inherently discontinuous and stratigraphically complex, which has limited our understanding of how desert wetlands responded to past episodes of rapid climate change. Previous studies have shown that wetlands responded to climate change on glacial to interglacial timescales, but their sensitivity to short-lived climate perturbations is largely unknown. Here, we show that GWD deposits in the Las Vegas Valley (southern Nevada, United States) provide a detailed and nearly complete record of dynamic hydrologic changes during the past 35 ka (thousands of calibrated 14C years before present), including cycles of wetland expansion and contraction that correlate tightly with climatic oscillations recorded in the Greenland ice cores. Cessation of discharge associated with rapid warming events resulted in the collapse of entire wetland systems in the Las Vegas Valley at multiple times during the late Quaternary. On average, drought-like conditions, as recorded by widespread erosion and the formation of desert soils, lasted for a few centuries. This record illustrates the vulnerability of desert wetland flora and fauna to abrupt climate change. It also shows that GWD deposits can be used to reconstruct paleohydrologic conditions at millennial to submillennial timescales and informs conservation efforts aimed at protecting these fragile ecosystems in the face of anthropogenic warming.

Ecosystem management can mitigate vegetation shifts induced by climate change in African savannas

NASA Astrophysics Data System (ADS)

Scheiter, Simon; Savadogo, Patrice

2017-04-01

The welfare of people in the tropics and sub-tropics strongly depends on goods and services that ecosystems supply. Flows of these ecosystem services are strongly influenced by interactions between climate change and land use. A prominent example are savannas, covering approximately 20% of the Earth's land surface. Key ecosystem services in these areas are fuel wood for cooking and heating, food production and livestock. Changes in the structure and dynamics of savanna vegetation may strongly influence local people's living conditions, as well as the climate system and biogeochemical cycles. We used a dynamic vegetation model to explore interactive effects of climate and land use on the vegetation structure, distribution and carbon cycling of African savannas under current and future conditions. More specifically, we simulate long term impacts of fire management, grazing and fuel wood harvesting. The model projects that under future climate without human land use impacts, large savanna areas would shift towards more wood dominated vegetation due to CO2 fertilization effects and changes in water use efficiency. However, land use activities can mitigate climate change impacts on vegetation to maintain desired ecosystem states that ensure fluxes of important ecosystem services. We then use optimization algorithms to identify sustainable land use strategies that maximize the utility of people managing savannas while preserving a stable vegetation state. Our results highlight that the development of land use policy for tropical and sub-tropical areas needs to account for climate change impacts on vegetation.

Sr/Ca and δ18O records of a coral from Sanya: reconstructions of temperature and precipitation in the northern South China Sea in the late Holocene

NASA Astrophysics Data System (ADS)

Wagner, S.; Xoplaki, E.; Luterbacher, J.; Zorita, E.; Fleitmann, D.; Preiser-Kapeller, J.; Toreti, A., , Dr; Sargent, A. M.; Bozkurt, D.; White, S.; Haldon, J. F.; Akçer-Ön, S.; Izdebski, A.

2016-12-01

Past civilisations were influenced by complex external and internal forces, including changes in the environment, climate, politics and economy. A geographical hotspot of the interplay between those agents is the Mediterranean, a cradle of cultural and scientific development. We analyse a novel compilation of high-quality hydroclimate proxy records and spatial reconstructions from the Mediterranean and compare them with two Earth System Model simulations (CCSM4, MPI-ESM-P) for three historical time intervals - the Crusaders, 1095-1290 CE; the Mamluk regime in Transjordan, 1260-1516 CE; and the Ottoman crisis and Celâlî Rebellion, 1580-1610 CE - when environmental and climatic stress tested the resilience of complex societies. ESMs provide important information on the dynamical mechanisms and underlying processes that led to anomalous hydroclimatic conditions of the past. We find that the multidecadal precipitation and drought variations in the Central and Eastern Mediterranean during the three periods cannot be explained by external forcings (solar variations, tropical volcanism); rather they were driven by internal climate dynamics. The integrated analysis of palaeoclimate proxies, climate reconstructions and model simulations sheds light on our understanding of past climate change and its societal impact. Finally, our research emphasises the need to further study the societal dimension of environmental and climate change in the past, in order to properly understand the role that climate has played in human history.

Integrating Climate Science, Marine Ecology, and Fisheries Economics to Predict the Effects of Climate Change on New England lobster Fisheries

NASA Astrophysics Data System (ADS)

Le Bris, A.; Pershing, A. J.; Holland, D. S.; Mills, K.; Sun, C. H. J.

2016-02-01

The Gulf of Maine and the northwest Atlantic shelf have experienced one of the fastest warming rates of the global ocean over the past decade, and concerns are growing about the long-term sustainability of the fishing industries in the region. The lucrative American lobster fishery occurs over a steep temperature gradient, providing a unique opportunity to evaluate the consequences of climate change and variability on marine socio-ecological systems. This study aims at developing an integrated climate, population dynamics, and fishery economics model to predict consequences of climate change on the American lobster fishery. In this talk, we first describe a mechanistic model that combines life-history theory and a size-spectrum approach to simulate the dynamics of the population. Results show that as temperature increases, early growth rate and predation on small individuals increases, while size-at-maturity, maximum length and predation on large individuals decreases, resulting in a lower recruitment in the southern New-England and higher recruitment in the northern Gulf of Maine. Second, we present an integrated fishery and economic module that links temperature to landings and price through its influence on catchability and abundance. Preliminary results show that temperature is positively correlated with landings and negatively correlated with price in the Gulf of Maine. Finally, we discuss how model simulations under various fishing effort, market and climate scenarios can be used to identify adaptation opportunities to improve the resilience of the fishery to climate change.

Growth response of conifers in Adirondack plantations to changing environment: Model approaches based on stem-analysis

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

Pan, Y.

1993-01-01

Based on model approaches, three conifer species, red pine, Norway spruce and Scots pine grown in plantations at Pack Demonstration Forest, in the southeastern Adirondack mountains of New York, were chosen to study growth response to different environmental changes, including silvicultural treatments and changes in climate and chemical environment. Detailed stem analysis data provided a basis for constructing tree growth models. These models were organized into three groups: morphological, dynamic and predictive. The morphological model was designed to evaluate relationship between tree attributes and interactive influences of intrinsic and extrinsic factors on the annual increments. Three types of morphological patternsmore » have been characterized: space-time patterns of whole-stem rings, intrinsic wood deposition pattern along the tree-stem, and bolewood allocation ratio patterns along the tree-stem. The dynamic model reflects the growth process as a system which responds to extrinsic signal inputs, including fertilization pulses, spacing effects and climatic disturbance, as well as intrinsic feedback. Growth signals indicative of climatic effects were used to construct growth-climate models using both multivariate analysis and Kalman filter methods. The predictive model utilized GCMs and growth-climate relationships to forecast tree growth responses in relation to future scenarios of CO[sub 2]-induced climate change. Prediction results indicate that different conifer species have individualistic growth response to future climatic change and suggest possible changes in future growth and distribution of naturally occurring conifers in this region.« less

Seasonally Varying Predation Behavior and Climate Shifts Are Predicted to Affect Predator-Prey Cycles.

PubMed

Tyson, Rebecca; Lutscher, Frithjof

2016-11-01

The functional response of some predator species changes from a pattern characteristic for a generalist to that for a specialist according to seasonally varying prey availability. Current theory does not address the dynamic consequences of this phenomenon. Since season length correlates strongly with altitude and latitude and is predicted to change under future climate scenarios, including this phenomenon in theoretical models seems essential for correct prediction of future ecosystem dynamics. We develop and analyze a two-season model for the great horned owl (Bubo virginialis) and snowshoe hare (Lepus americanus). These species form a predator-prey system in which the generalist to specialist shift in predation pattern has been documented empirically. We study the qualitative behavior of this predator-prey model community as summer season length changes. We find that relatively small changes in summer season length can have a profound impact on the system. In particular, when the predator has sufficient alternative resources available during the summer season, it can drive the prey to extinction, there can be coexisting stable states, and there can be stable large-amplitude limit cycles coexisting with a stable steady state. Our results illustrate that the impacts of global change on local ecosystems can be driven by internal system dynamics and can potentially have catastrophic consequences.

Satellite-derived attributes of cloud vortex systems and their application to climate studies

NASA Technical Reports Server (NTRS)

Carleton, Andrew M.

1987-01-01

Defense Meteorological Satellite Program (DMSP) visible and infrared mosaics are analyzed in conjunction with synoptic meteorological observations of sea level pressure (SLP) and upper-air height to derive composite patterns of cyclonic cloud vortices for the Northern Hemisphere. The patterns reveal variations in the structure and implied dynamics of cyclonic systems at different stages of development that include: (1) increasing vertical symmetry of the lower-level and upper-air circulations and (2) decreasing lower-tropospheric thicknesses and temperature advection, associated with increasing age of the vortex. Cloud vortices are more intense in winter than in summer and typically reach maximum intensity in the short-lived prespiral signature stage. There are major structural differences among frontal wave, polar air, and 'instant occlusion' cyclogenesis types. Cyclones in the dissipation stage may reintensify (deepen), as denoted by the appearance in the imagery of an asymmetric cloud band or a tightened spiral vortex. The satellite-derived statistics on cloud vortex intensity, which are seasonal- and latitude- as well as type-dependent, are applied to a preliminary examination of the synoptic manifestations of seasonal climate variability. An apparently close relationship is found, for two winter and spring seasons, between Northern Hemisphere cyclonic activity and variations in cryosphere variables, particularly the extent of Arctic sea ice. The results may indicate that increased snow and ice extent accompany a southward displacement of cyclonic activity and/or a predominance of deeper systems. However, there is also a strong regional dependence to the ice-synoptics feedback. This study demonstrates the utility of high resolution meteorological satellite imagery for studies of climate variations (climate dynamics).

Importance of vegetation distribution for future carbon balance

NASA Astrophysics Data System (ADS)

Ahlström, A.; Xia, J.; Arneth, A.; Luo, Y.; Smith, B.

2015-12-01

Projections of future terrestrial carbon uptake vary greatly between simulations. Net primary production (NPP), wild fires, vegetation dynamics (including biome shifts) and soil decomposition constitute the main processes governing the response of the terrestrial carbon cycle in a changing climate. While primary production and soil respiration are relatively well studied and implemented in all global ecosystem models used to project the future land sink of CO2, vegetation dynamics are less studied and not always represented in global models. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality and the associated turnover and proven skill in predicting vegetation distribution and succession. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the CMIP5 ensemble under RCP8.5 radiative forcing at year 2085. We exchanged carbon cycle processes between these 13 simulations and investigate the changes predicted by the emulator. This method allowed us to partition the entire ensemble carbon uptake uncertainty into individual processes. We found that NPP, vegetation dynamics (including biome shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33% respectively of uncertainties in modeled global C-uptake. Uncertainty due to vegetation dynamics was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by shifts in vegetation distribution, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Submesoscale Flows and Mixing in the Ocean Surface Layer Using the Regional Oceanic Modeling System (ROMS)

DTIC Science & Technology

2013-09-30

chemical cycles, water quality, blooms , micro-nutrients, larval dispersal, biome transitions, and coupling to higher tropic levels. We collaborate with...Kurian, 2012: Heat balance and eddies in the Peru- Chile Current System. Climate Dynamics 39, 509-529, doi:10.1007/s00382-011-1170-6. Colas, F., X

Climate change, urbanization, and optimal long-term floodplain protection

NASA Astrophysics Data System (ADS)

Zhu, Tingju; Lund, Jay R.; Jenkins, Marion W.; Marques, Guilherme F.; Ritzema, Randall S.

2007-06-01

This paper examines levee-protected floodplains and economic aspects of adaptation to increasing long-term flood risk due to urbanization and climate change. The lower American River floodplain in the Sacramento, California, metropolitan area is used as an illustration to explore the course of optimal floodplain protection decisions over long periods. A dynamic programming model is developed and suggests economically desirable adaptations for floodplain levee systems given simultaneous changes in flood climate and urban land values. Economic engineering optimization analyses of several climate change and urbanization scenarios are made. Sensitivity analyses consider assumptions about future values of floodplain land and damageable property along with the discount rate. Methodological insights and policy lessons are drawn from modeling results, reflecting the joint effects and relationships that climate, economic costs, and regional economic growth can have on floodplain levee planning decisions.

Communicating climate sciences in academia and beyond

NASA Astrophysics Data System (ADS)

Dupigny-Giroux, L. L.

2008-12-01

Climate change has catapulted climate and atmospheric sciences onto center stage in a way that eclipses the challenges of acid rain deposition in the late 1990s. However, there are subtle differences in the non- scientists' understanding of climate dynamics, processes, feedbacks etc.. Even among non-atmospheric scientists, there is sometimes an under-appreciation of the nuances of the land-atmosphere-ocean system. Many agencies are poised to play pivotal roles in helping to move this understanding forward, either due to their scientific missions or outreach components. Among these are the American Association of State Climatologists, the American Meteorological Society, American Geophysical Union, UCAR, NOAA, NASA and Association of American Geographers to name a few. This presentation will suggest directions in communicating climate science that come out a State Climatologist's perspective as well as liberal arts academic setting.

Ice sheets play important role in climate change

NASA Astrophysics Data System (ADS)

Clark, Peter U.; MacAyeal, Douglas R.; Andrews, John T.; Bartlein, Patrick J.

Ice sheets once were viewed as passive elements in the climate system enslaved to orbitally generated variations in solar radiation. Today, modeling results and new geologic records suggest that ice sheets actively participated in late-Pleistocene climate change, amplifying or driving significant variability at millennial as well as orbital timescales. Although large changes in global ice volume were ultimately caused by orbital variations (the Milankovitch hypothesis), once in existence, the former ice sheets behaved dynamically and strongly influenced regional and perhaps even global climate by altering atmospheric and oceanic circulation and temperature.Experiments with General Circulation Models (GCMs) yielded the first inklings of ice sheets' climatic significance. Manabe and Broccoli [1985], for example, found that the topographic and albedo effects of ice sheets alone explain much of the Northern Hemisphere cooling identified in paleoclimatic records of the last glacial maximum (˜21 ka).

Population-level consequences of herbivory, changing climate, and source-sink dynamics on a long-lived invasive shrub.

PubMed

van Klinken, R D; Pichancourt, J B

2015-12-01

Long-lived plant species are highly valued environmentally, economically, and socially, but can also cause substantial harm as invaders. Realistic demographic predictions can guide management decisions, and are particularly valuable for long-lived species where population response times can be long. Long-lived species are also challenging, given population dynamics can be affected by factors as diverse as herbivory, climate, and dispersal. We developed a matrix model to evaluate the effects of herbivory by a leaf-feeding biological control agent released in Australia against a long-lived invasive shrub (mesquite, Leguminoseae: Prosopis spp.). The stage-structured, density-dependent model used an annual time step and 10 climatically diverse years of field data. Mesquite population demography is sensitive to source-sink dynamics as most seeds are consumed and redistributed spatially by livestock. In addition, individual mesquite plants, because they are long lived, experience natural climate variation that cycles over decadal scales, as well as anthropogenic climate change. The model therefore explicitly considered the effects of both net dispersal and climate variation. Herbivory strongly regulated mesquite populations through reduced growth and fertility, but additional mortality of older plants will be required to reach management goals within a reasonable time frame. Growth and survival of seeds and seedlings were correlated with daily soil moisture. As a result, population dynamics were sensitive to rainfall scenario, but population response times were typically slow (20-800 years to reach equilibrium or extinction) due to adult longevity. Equilibrium population densities were expected to remain 5% higher, and be more dynamic, if historical multi-decadal climate patterns persist, the effect being dampened by herbivory suppressing seed production irrespective of preceding rainfall. Dense infestations were unlikely to form under a drier climate, and required net dispersal under the current climate. Seed input wasn't required to form dense infestations under a wetter climate. Each factor we considered (ongoing herbivory, changing climate, and source-sink dynamics) has a strong bearing on how this invasive species should be managed, highlighting the need for considering both ecological context (in this case, source-sink dynamics) and the effect of climate variability at relevant temporal scales (daily, multi-decadal, and anthropogenic) when deriving management recommendations for long-lived species.

Climate Analytics as a Service. Chapter 11

NASA Technical Reports Server (NTRS)

Schnase, John L.

2016-01-01

Exascale computing, big data, and cloud computing are driving the evolution of large-scale information systems toward a model of data-proximal analysis. In response, we are developing a concept of climate analytics as a service (CAaaS) that represents a convergence of data analytics and archive management. With this approach, high-performance compute-storage implemented as an analytic system is part of a dynamic archive comprising both static and computationally realized objects. It is a system whose capabilities are framed as behaviors over a static data collection, but where queries cause results to be created, not found and retrieved. Those results can be the product of a complex analysis, but, importantly, they also can be tailored responses to the simplest of requests. NASA's MERRA Analytic Service and associated Climate Data Services API provide a real-world example of climate analytics delivered as a service in this way. Our experiences reveal several advantages to this approach, not the least of which is orders-of-magnitude time reduction in the data assembly task common to many scientific workflows.

Dynamic Vulnerability of Karst Systems: a Concept to understand qualitative and quantitative Aspects of Karst springs due to Changes in Groundwater Recharge

NASA Astrophysics Data System (ADS)

Huggenberger, P.; Butscher, C.; Epting, J.; Auckenthaler, A.

2015-12-01

Karst groundwater resources represent valuable water resources, which may be affected by different types of pollution and changes of groundwater recharge by climate change. In many parts of Europe, it has been predicted that record-breaking heat waves, such as the one experienced in 2003 and 2015, will become more frequent. At the same time, even as summers become drier, the incidence of severe precipitation events could increase. What is the influence such changes to the quantitative and qualitative aspects of Karst groundwater systems? A factor to be considered in conjunction with groundwater quality is the vulnerability of the resource, which is defined as the sensitivity of a groundwater system to pollution. Intrinsic vulnerability refers to the sensitivity to pollution when considering only natural, geogenic conditions without the effects of human activities such as contaminant release. Intrinsic vulnerability depends on the recharge conditions, which are dependent on the surface and subsurface structure and on precipitation and evaporation patterns. The latter are highly time dependent. Therefore, our groundwater vulnerability concept also includes dynamic aspects of the system, the variations of spatial and temporal components. We present results of combined monitoring and modelling experiments of several types of Karst systems in the Tabular and the Folded Jura of NW Switzerland. The recharge, conduit flow, diffuse flow(RCD) rainfall-discharge model "RCD-seasonal" was used to simulate the discharge and substance concentration of several spring. This lumped parameter model include: the recharge system (soil and epikarst system), the conduit flow system, and the diffuse flow system. The numerically derived Dynamic Vulnerability Index (DVI) can indicate qualitative changes of spring water with sufficient accuracy to be used for drinking water management. In addition, the results obtained from the test sites indicate a decrease in short-lived contaminants in spring water as a result of climate change. The impact of persistent contaminants, however, can only be determined if future climatic conditions at the site can be estimated with sufficient accuracy, because predicted summer heat waves and severe rainfall events will have opposite effects on the groundwater vulnerability.

Impacts of land use and climate change on carbon dynamics in south-central Senegal

USGS Publications Warehouse

Liu, Shu-Guang; Kaire, M.; Wood, Eric C.; Diallo, O.; Tieszen, Larry L.

2004-01-01

Total carbon stock in vegetation and soils was reduced 37% in south-central Senegal from 1900 to 2000. The decreasing trend will continue during the 21st century unless forest clearing is stopped, selective logging dramatically reduced, and climate change, if any, relatively small. Developing a sustainable fuelwood and charcoal production system could be the most feasible and significant carbon sequestration project in the region. If future climate changes dramatically as some models have predicted, cropland productivity will drop more than 65% around 2100, posing a serious threat to food security and the efficiency of carbon sequestration projects.

Marine lake ecosystem dynamics illustrate ENSO variation in the tropical western Pacific.

PubMed

Martin, Laura E; Dawson, Michael N; Bell, Lori J; Colin, Patrick L

2006-03-22

Understanding El Niño/Southern Oscillation (ENSO) and its biological consequences is hindered by a lack of high-resolution, long-term data from the tropical western Pacific. We describe a preliminary, 6 year dataset that shows tightly coupled ENSO-related bio-physical dynamics in a seawater lake in Palau, Micronesia. The lake is more strongly stratified during La Niña than El Niño conditions, temperature anomalies in the lake co-vary strongly with the Niño 3.4 climate index, and the abundance of the dominant member of the pelagic community, an endemic subspecies of zooxanthellate jellyfish, is temperature associated. These results have broad relevance because the lake: (i) illustrates an ENSO signal that is partly obscured in surrounding semi-enclosed lagoon waters and, therefore, (ii) may provide a model system for studying the effects of climate change on community evolution and cnidarian-zooxanthellae symbioses, which (iii) should be traceable throughout the Holocene because the lake harbours a high quality sediment record; the sediment record should (iv) provide a sensitive and regionally unique record of Holocene climate relevant to predicting ENSO responses to future global climate change and, finally, (v) seawater lake ecosystems elsewhere in the Pacific may hold similar potential for past, present, and predictive measurements of climate variation and ecosystem response.

Combined effects of climate, predation, and density dependence on Greater and Lesser Scaup population dynamics

USGS Publications Warehouse

Ross, Beth E.; Hooten, Mevin B.; DeVink, Jean-Michel; Koons, David N.

2015-01-01

An understanding of species relationships is critical in the management and conservation of populations facing climate change, yet few studies address how climate alters species interactions and other population drivers. We use a long-term, broad-scale data set of relative abundance to examine the influence of climate, predators, and density dependence on the population dynamics of declining scaup (Aythya) species within the core of their breeding range. The state-space modeling approach we use applies to a wide range of wildlife species, especially populations monitored over broad spatiotemporal extents. Using this approach, we found that immediate snow cover extent in the preceding winter and spring had the strongest effects, with increases in mean snow cover extent having a positive effect on the local surveyed abundance of scaup. The direct effects of mesopredator abundance on scaup population dynamics were weaker, but the results still indicated a potential interactive process between climate and food web dynamics (mesopredators, alternative prey, and scaup). By considering climate variables and other potential effects on population dynamics, and using a rigorous estimation framework, we provide insight into complex ecological processes for guiding conservation and policy actions aimed at mitigating and reversing the decline of scaup.

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers

PubMed Central

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell’Aquila, Alessandro

2014-01-01

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests. PMID:24706833

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers.

PubMed

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell'Aquila, Alessandro

2014-04-15

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests.

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.

Introducing Enabling Computational Tools to the Climate Sciences: Multi-Resolution Climate Modeling with Adaptive Cubed-Sphere Grids

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

Jablonowski, Christiane

The research investigates and advances strategies how to bridge the scale discrepancies between local, regional and global phenomena in climate models without the prohibitive computational costs of global cloud-resolving simulations. In particular, the research explores new frontiers in computational geoscience by introducing high-order Adaptive Mesh Refinement (AMR) techniques into climate research. AMR and statically-adapted variable-resolution approaches represent an emerging trend for atmospheric models and are likely to become the new norm in future-generation weather and climate models. The research advances the understanding of multi-scale interactions in the climate system and showcases a pathway how to model these interactions effectively withmore » advanced computational tools, like the Chombo AMR library developed at the Lawrence Berkeley National Laboratory. The research is interdisciplinary and combines applied mathematics, scientific computing and the atmospheric sciences. In this research project, a hierarchy of high-order atmospheric models on cubed-sphere computational grids have been developed that serve as an algorithmic prototype for the finite-volume solution-adaptive Chombo-AMR approach. The foci of the investigations have lied on the characteristics of both static mesh adaptations and dynamically-adaptive grids that can capture flow fields of interest like tropical cyclones. Six research themes have been chosen. These are (1) the introduction of adaptive mesh refinement techniques into the climate sciences, (2) advanced algorithms for nonhydrostatic atmospheric dynamical cores, (3) an assessment of the interplay between resolved-scale dynamical motions and subgrid-scale physical parameterizations, (4) evaluation techniques for atmospheric model hierarchies, (5) the comparison of AMR refinement strategies and (6) tropical cyclone studies with a focus on multi-scale interactions and variable-resolution modeling. The results of this research project demonstrate significant advances in all six research areas. The major conclusions are that statically-adaptive variable-resolution modeling is currently becoming mature in the climate sciences, and that AMR holds outstanding promise for future-generation weather and climate models on high-performance computing architectures.« less

The impact of climate change on coastal ecosystems: chapter 6

USGS Publications Warehouse

Burkett, Virginia; Woodroffe, Colin D.; Nicholls, Robert J.; Forbes, Donald L.

2014-01-01

In this chapter we stress two important features of coasts and coastal ecosystems. First, these are dynamic systems which continually undergo adjustments, especially through erosion and re-deposition, in response to a range of processes. Many coastal ecosystems adjust naturally at a range of time scales and their potential for response is examined partly by reconstructing how such systems have coped with natural changes of climate and sea level in the geological past. Second, coasts have changed profoundly through the 20th Century due to the impacts of human development (such as urbanisation, port and industrial expansion, shore protection, and the draining and conversion of coastal wetlands), with these development-related drivers closely linked to a growing global population and economy. It remains a challenge to isolate the impacts of climate change and sea-level rise from either the natural trajectory of shoreline change, or the accelerated pathway resulting from other human-related stressors. There exists a danger of overstating the importance of climate change, or overlooking significant interactions of climate change with other drivers.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Temperature drives abundance fluctuations, but spatial dynamics is constrained by landscape configuration: Implications for climate-driven range shift in a butterfly.

PubMed

Fourcade, Yoan; Ranius, Thomas; Öckinger, Erik

2017-10-01

Prediction of species distributions in an altered climate requires knowledge on how global- and local-scale factors interact to limit their current distributions. Such knowledge can be gained through studies of spatial population dynamics at climatic range margins. Here, using a butterfly (Pyrgus armoricanus) as model species, we first predicted based on species distribution modelling that its climatically suitable habitats currently extend north of its realized range. Projecting the model into scenarios of future climate, we showed that the distribution of climatically suitable habitats may shift northward by an additional 400 km in the future. Second, we used a 13-year monitoring dataset including the majority of all habitat patches at the species northern range margin to assess the synergetic impact of temperature fluctuations and spatial distribution of habitat, microclimatic conditions and habitat quality, on abundance and colonization-extinction dynamics. The fluctuation in abundance between years was almost entirely determined by the variation in temperature during the species larval development. In contrast, colonization and extinction dynamics were better explained by patch area, between-patch connectivity and host plant density. This suggests that the response of the species to future climate change may be limited by future land use and how its host plants respond to climate change. It is, thus, probable that dispersal limitation will prevent P. armoricanus from reaching its potential future distribution. We argue that models of range dynamics should consider the factors influencing metapopulation dynamics, especially at the range edges, and not only broad-scale climate. It includes factors acting at the scale of habitat patches such as habitat quality and microclimate and landscape-scale factors such as the spatial configuration of potentially suitable patches. Knowledge of population dynamics under various environmental conditions, and the incorporation of realistic scenarios of future land use, appears essential to provide predictions useful for actions mitigating the negative effects of climate change. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Identifying legal, ecological and governance obstacles and opportunities for adapting to climate change

USGS Publications Warehouse

Cosens, Barbara; Gunderson, Lance; Allen, Craig R.; Benson, Melinda H.

2014-01-01

Current governance of regional scale water management systems in the United States has not placed them on a path toward sustainability, as conflict and gridlock characterize the social arena and ecosystem services continue to erode. Changing climate may continue this trajectory, but it also provides a catalyst for renewal of ecosystems and a window of opportunity for change in institutions. Resilience provides a bridging concept that predicts that change in ecological and social systems is often dramatic, abrupt, and surprising. Adapting to the uncertainty of climate driven change must be done in a manner perceived as legitimate by the participants in a democratic society. Adaptation must begin with the current hierarchical and fragmented social-ecological system as a baseline from which new approaches must be applied. Achieving a level of integration between ecological concepts and governance requires a dialogue across multiple disciplines, including ecologists with expertise in ecological resilience, hydrologists and climate experts, with social scientists and legal scholars. Criteria and models that link ecological dynamics with policies in complex, multi-jurisdictional water basins with adaptive management and governance frameworks may move these social-ecological systems toward greater sustainability.

GRACE storage-runoff hystereses reveal the dynamics of regional watersheds

EPA Science Inventory

Watersheds function as integrated systems where climate and geology govern the movement of water. In situ instrumentation can provide local-scale insights into the non-linear relationship between streamflow and water stored in a watershed as snow, soil moisture, and groundwater. ...

Aeolian processes and the bioshpere: Interactions and feedback loops

USDA-ARS?s Scientific Manuscript database

Aeolian processes affect landform evolution, biogeochemical cycles, regional climate, human health, and desertification. The entrainment, transport and deposition of aeolian sediments are recognized as major drivers in the dynamics of the earth system and there is a growing interest in the scientif...

A Data-Driven Assessment of the Sensitivity of Global Ecosystems to Climate Anomalies

NASA Astrophysics Data System (ADS)

Miralles, D. G.; Papagiannopoulou, C.; Demuzere, M.; Decubber, S.; Waegeman, W.; Verhoest, N.; Dorigo, W.

2017-12-01

Vegetation is a central player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and short-term disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a non-linear random forest predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. This overall dependency of ecosystems on water availability is larger than previously reported, partly owed to the ability of our machine-learning framework to disentangle the co-linearites between climatic drivers, and to quantify non-linear impacts of climate on vegetation. Our observation-based results are then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes. Our findings indicate that the sensitivity of vegetation to climatic anomalies is ill-reproduced by some widely-used ESMs.

The influence of historical climate on the population dynamics of three dominant sagebrush steppe plants.

USDA-ARS?s Scientific Manuscript database

Climate change could alter the population growth of dominant species, leading to profound effects on community structure and ecosystem dynamics. Understanding the links between historical variation in climate and population vital rates (survival, growth, recruitment) is one way to predict the impact...

Critical Watersheds: Climate Change, Tipping Points, and Energy-Water Impacts

NASA Astrophysics Data System (ADS)

Middleton, R. S.; Brown, M.; Coon, E.; Linn, R.; McDowell, N. G.; Painter, S. L.; Xu, C.

2014-12-01

Climate change, extreme climate events, and climate-induced disturbances will have a substantial and detrimental impact on terrestrial ecosystems. How ecosystems respond to these impacts will, in turn, have a significant effect on the quantity, quality, and timing of water supply for energy security, agriculture, industry, and municipal use. As a community, we lack sufficient quantitative and mechanistic understanding of the complex interplay between climate extremes (e.g., drought, floods), ecosystem dynamics (e.g., vegetation succession), and disruptive events (e.g., wildfire) to assess ecosystem vulnerabilities and to design mitigation strategies that minimize or prevent catastrophic ecosystem impacts. Through a combination of experimental and observational science and modeling, we are developing a unique multi-physics ecohydrologic framework for understanding and quantifying feedbacks between novel climate and extremes, surface and subsurface hydrology, ecosystem dynamics, and disruptive events in critical watersheds. The simulation capability integrates and advances coupled surface-subsurface hydrology from the Advanced Terrestrial Simulator (ATS), dynamic vegetation succession from the Ecosystem Demography (ED) model, and QUICFIRE, a novel wildfire behavior model developed from the FIRETEC platform. These advances are expected to make extensive contributions to the literature and to earth system modeling. The framework is designed to predict, quantify, and mitigate the impacts of climate change on vulnerable watersheds, with a focus on the US Mountain West and the energy-water nexus. This emerging capability is used to identify tipping points in watershed ecosystems, quantify impacts on downstream users, and formally evaluate mitigation efforts including forest (e.g., thinning, prescribed burns) and watershed (e.g., slope stabilization). The framework is being trained, validated, and demonstrated using field observations and remote data collections in the Valles Caldera National Preserve, including pre- and post-wildfire and infestation observations. Ultimately, the framework will be applied to the upper Colorado River basin. Here, we present an overview of the framework development strategy and latest field and modeling results.

Green roofs'retention performances in different climates

NASA Astrophysics Data System (ADS)

Viola, Francesco; Hellies, Matteo; Deidda, Roberto

2017-04-01

The ongoing process of global urbanization contributes to increasing stormwater runoff from impervious surfaces, threatening also water quality. Green roofs have been proved to be an innovative stormwater management tool to partially restore natural state, enhancing interception, infiltration and evapotranspiration fluxes. The amount of water that is retained within green roofs depends mainly on both soil properties and climate. The evaluation of the retained water is not trivial since it depends on the stochastic soil moisture dynamics. The aim of this work is to explore performances of green roofs, in terms of water retention, as a function of their depth considering different climate regimes. The role of climate in driving water retention has been mainly represented by rainfall and potential evapotranspiration dynamics, which are simulated by a simple conceptual weather generator at daily time scale. The model is able to describe seasonal (in-phase and counter-phase) and stationary behaviors of climatic forcings. Model parameters have been estimated on more than 20,000 historical time series retrieved worldwide. Exemplifying cases are discussed for five different climate scenarios, changing the amplitude and/or the phase of daily mean rainfall and evapotranspiration forcings. The first scenario represents stationary climates, in two other cases the daily mean rainfall or the potential evapotranspiration evolve sinusoidally. In the latter two cases, we simulated the in-phase or in counter-phase conditions. Stochastic forcings have been then used as an input to a simple conceptual hydrological model which simulate soil moisture dynamics, evapotranspiration fluxes, runoff and leakage from soil pack at daily time scale. For several combinations of annual rainfall and potential evapotranspiration, the analysis allowed assessing green roofs' retaining capabilities, at annual time scale. Provided abacus allows a first approximation of possible hydrological benefits deriving from the implementation of intensive or extensive green roofs in different world areas, i.e. less input to sewer systems.

Desert dust and anthropogenic aerosol interactions in the Community Climate System Model coupled-carbon-climate model

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

Mahowald, Natalie; Rothenberg, D.; Lindsay, Keith

2011-02-01

Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries) and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climatemore » feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.« less

Self-organization of the climate system: Synchronized polar and oceanic teleconnections

NASA Astrophysics Data System (ADS)

Reischmann, Elizabeth Piccard

Synchronization is a widespread phenomenon in nonlinear, physical systems. It describes the phenomena of two or more weakly interacting, nonlinear oscillators adjust their natural frequencies until they come into phase and frequency lock. This behavior has been observed in biological, chemical and electronic systems, including neurons, fireflies, and computers, but has not been widely studied in climate. This thesis presents a study of several major examples of synchronized climatic systems, starting with ice age timings seemingly caused by the global climate's gradual synchronization to the Earth's 413kyr orbital eccentricity band, which may be responsible for the shift of ice age timings and amplitudes at the Mid-Pleistocene transition. The focus of the thesis, however, is centered the second major example of stable synchronization in the climate system: the continuous, 90 degree phase relationship of the polar climate signals for the entirety of the available ice record. The existence of a relationship between polar climates has been widely observed since ice core proxies became available in both Greenland and Antarctica. However, my work focuses on refining this phase relationship, utilizing it's linear nature to apply deconvolution and establish an energy transfer function. This transfer function shows a distinctly singular frequency, suggesting that climate signal is predominately communicated north to south with a period of 1.6kyrs. This narrows down possible mechanisms of polar connection dramatically, and is further investigated via a collection of intermediate proxy datasets and a set of more contemporary, synchronized, sea surface temperature dipoles. While the former fails to show any strong indication of the nature of the polar signal due in part to the overwhelming uncertainties present on the centennial and millennial scales, the latter demonstrates a large set of synchronized climate oscillations exist, communicate in a variety of networks, and have a direct connection to larger climate patterns (in this case, precipitation anomalies). Overall, this thesis represents a clear advance in our understanding of global climate dynamics, presents a new method of climate time series analysis, evidence of 16, stable, synchronized sea surface temperature dipoles, and provides a detailed sediment core database with explanations of age model limitations for future investigation.

Between the high mountains and the deserts: reconstructing palaeoenvironments in the Arid Central Asian loess

NASA Astrophysics Data System (ADS)

Fitzsimmons, Kathryn; Sprafke, Tobias; Deom, Jean-Marc; Sala, Renato; Nigmatova, Saida

2017-04-01

Central Asia lies at the arid core of the largest and most populous continent on Earth - Eurasia - and at the intersection between the major climatic drivers of the North Atlantic westerlies, the polar front and the Asian monsoon. It furthermore represents a global "hotspot" for future desertification, facing a potent combination of sensitive climate dynamics and intensive land use. However, we know little about the role of Central Asia in global climate dynamics past and present. This is largely because we have yet to realise the full potential of the widespread loess archives which extend across the semi-arid piedmonts to the north of the Asian high mountains, at the southern margins of the Silk Road deserts. These records have been largely overlooked by scientific investigation, despite correlations between the well-studied loess archives of Europe and China. In spite of its key position in the northern hemisphere climate circulation systems, the climatic history - and trajectory - of arid Central Asia remains largely unknown. Here we reconstruct palaeoenvironmental change over the last 40 ky from three sites in the loess foothills of the northern Tien Shan. Our emerging sedimentological, palaeopedological, geochemical and geochronological datasets suggest that aeolian deposition in this semi-arid region responds in a more complex way to climate than the classical sequences of the Chinese Loess Plateau and Danube basin. In arid Central Asia, landscapes appear to have responded not only to the cooler and warmer conditions of the glacial and interglacial periods respectively, but also to the availability of moisture. Variations in precipitation patterns may have been out of phase with the ice ages, and the impact of precipitation regime change may have been intensified by an extreme continental climate. Emerging data from the Central Asian loess suggest that past climates may not only have been subject to spatial migration, expansion and contraction of the major climate subsystems, but also the compression and the blockage of system teleconnections. These hypotheses set the scene for future, targeted research based on quantitative palaeoclimate reconstruction from loess records in the heart of Eurasia.

Towards a mechanistic understanding of the linkages between PETM climate modulation and stratigraphy, as discerned from the Piceance Basin, CO, USA

NASA Astrophysics Data System (ADS)

Barefoot, E. A.; Nittrouer, J. A.; Foreman, B.; Moodie, A. J.; Dickens, G. R.

2017-12-01

The Paleocene-Eocene Thermal Maximum (PETM) was a period of rapid climatic change when global temperatures increased by 5-8˚C in as little as 5 ka. It has been hypothesized that by drastically enhancing the hydrologic cycle, this temperature change significantly perturbed landscape dynamics over the ensuing 200 ka. Much of the evidence documenting hydrological variability derives from studies of the stratigraphic record, which is interpreted to encode a system-clearing event in fluvial systems worldwide during and after the PETM. For example, in the Piceance Basin of Western Colorado, it is hypothesized that intensification of monsoons due to PETM warming caused an increase in sediment flux to the basin. The resulting stratigraphy records a modulation of the sedimentation rate, where the PETM interval is represented by a laterally extensive sheet sand positioned between units dominated by floodplain muds. The temporal interval, the sediment provenance history, as well as the tectonic history of the PETM in the Piceance Basin are all well-constrained, leaving climate as the most significant allogenic forcing in the Piceance Basin during the PETM. However, the precise nature of landscape change that link climate forcing by the PETM to modulation of the sedimentation rate in this basin remains to be demonstrated. Here, we present a simple stratigraphic numerical model coupled with a conceptual source-to-sink framework to test the impact of a suite of changing upstream boundary conditions on the fluvial system. In the model, climate-related variables force changes in flow characteristics such as sediment transport, slope, and velocity, which determine the resultant floodplain stratigraphy. The model is based on mathematical relations that link bankfull geometry and water discharge, impacting the lateral migration rate of the channel, sediment transport rate, and avulsion frequency, thereby producing a cross-section of basin stratigraphy. In this way, we simulate a raft of plausible, and mutually exclusive, climate-change scenarios for the case study of the Piceance Basin during the PETM, which may be compared to the stratigraphic record through field observation. The method described here represents a step towards connecting the impacts of global climate change to fluvial systems and sedimentation dynamics.

Zoonoses As Ecological Entities: A Case Review of Plague

PubMed Central

de Almeida, Alzira Maria Paiva; Cordeiro-Estrela, Pedro

2016-01-01

As a zoonosis, Plague is also an ecological entity, a complex system of ecological interactions between the pathogen, the hosts, and the spatiotemporal variations of its ecosystems. Five reservoir system models have been proposed: (i) assemblages of small mammals with different levels of susceptibility and roles in the maintenance and amplification of the cycle; (ii) species-specific chronic infection models; (ii) flea vectors as the true reservoirs; (iii) Telluric Plague, and (iv) a metapopulation arrangement for species with a discrete spatial organization, following a source-sink dynamic of extinction and recolonization with naïve potential hosts. The diversity of the community that harbors the reservoir system affects the transmission cycle by predation, competition, and dilution effect. Plague has notable environmental constraints, depending on altitude (500+ meters), warm and dry climates, and conditions for high productivity events for expansion of the transmission cycle. Human impacts are altering Plague dynamics by altering landscape and the faunal composition of the foci and adjacent areas, usually increasing the presence and number of human cases and outbreaks. Climatic change is also affecting the range of its occurrence. In the current transitional state of zoonosis as a whole, Plague is at risk of becoming a public health problem in poor countries where ecosystem erosion, anthropic invasion of new areas, and climate change increase the contact of the population with reservoir systems, giving new urgency for ecologic research that further details its maintenance in the wild, the spillover events, and how it links to human cases. PMID:27711205

Zoonoses As Ecological Entities: A Case Review of Plague.

PubMed

Zeppelini, Caio Graco; de Almeida, Alzira Maria Paiva; Cordeiro-Estrela, Pedro

2016-10-01

As a zoonosis, Plague is also an ecological entity, a complex system of ecological interactions between the pathogen, the hosts, and the spatiotemporal variations of its ecosystems. Five reservoir system models have been proposed: (i) assemblages of small mammals with different levels of susceptibility and roles in the maintenance and amplification of the cycle; (ii) species-specific chronic infection models; (ii) flea vectors as the true reservoirs; (iii) Telluric Plague, and (iv) a metapopulation arrangement for species with a discrete spatial organization, following a source-sink dynamic of extinction and recolonization with naïve potential hosts. The diversity of the community that harbors the reservoir system affects the transmission cycle by predation, competition, and dilution effect. Plague has notable environmental constraints, depending on altitude (500+ meters), warm and dry climates, and conditions for high productivity events for expansion of the transmission cycle. Human impacts are altering Plague dynamics by altering landscape and the faunal composition of the foci and adjacent areas, usually increasing the presence and number of human cases and outbreaks. Climatic change is also affecting the range of its occurrence. In the current transitional state of zoonosis as a whole, Plague is at risk of becoming a public health problem in poor countries where ecosystem erosion, anthropic invasion of new areas, and climate change increase the contact of the population with reservoir systems, giving new urgency for ecologic research that further details its maintenance in the wild, the spillover events, and how it links to human cases.

Climate change: effects on animal disease systems and implications for surveillance and control.

PubMed

de La Rocque, S; Rioux, J A; Slingenbergh, J

2008-08-01

Climate driven and other changes in landscape structure and texture, plus more general factors, may create favourable ecological niches for emerging diseases. Abiotic factors impact on vectors, reservoirs and pathogen bionomics and their ability to establish in new ecosystems. Changes in climatic patterns and in seasonal conditions may affect disease behaviour in terms of spread pattern, diffusion range, amplification and persistence in novel habitats. Pathogen invasion may result in the emergence of novel disease complexes, presenting major challenges for the sustainability of future animal agriculture at the global level. In this paper, some of the ecological mechanisms underlying the impact of climatic change on disease transmission and disease spread are further described. Potential effects of different climatic variables on pathogens and host population dynamics and distribution are complex to assess, and different approaches are used to describe the underlying epidemiological processes and the availability of ecological niches for pathogens and vectors. The invasion process can disrupt the long-term co-evolution of species. Pathogens adhering to an r-type strategy (e.g. RNA viruses) may be more inclined to encroach on a novel niche resulting from climate change. However, even when linkage between disease dynamics and climate change are relatively strong, there are other factors changing disease behaviour, and these should be accounted for as well. Overall vulnerability of a given ecosystem is a key variable in this regard. The impact of climate-driven changes varies in different parts of the world and in the different agro-climatic zones. Perhaps priority should go to those geographical areas where the integrity of the ecosystem is most severely affected and the adaptability, in terms of robustness and sustainability of response, relatively low.

Stress testing hydrologic models using bottom-up climate change assessment

NASA Astrophysics Data System (ADS)

Stephens, C.; Johnson, F.; Marshall, L. A.

2017-12-01

Bottom-up climate change assessment is a promising approach for understanding the vulnerability of a system to potential future changes. The technique has been utilised successfully in risk-based assessments of future flood severity and infrastructure vulnerability. We find that it is also an ideal tool for assessing hydrologic model performance in a changing climate. In this study, we applied bottom-up climate change to compare the performance of two different hydrologic models (an event-based and a continuous model) under increasingly severe climate change scenarios. This allowed us to diagnose likely sources of future prediction error in the two models. The climate change scenarios were based on projections for southern Australia, which indicate drier average conditions with increased extreme rainfall intensities. We found that the key weakness in using the event-based model to simulate drier future scenarios was the model's inability to dynamically account for changing antecedent conditions. This led to increased variability in model performance relative to the continuous model, which automatically accounts for the wetness of a catchment through dynamic simulation of water storages. When considering more intense future rainfall events, representation of antecedent conditions became less important than assumptions around (non)linearity in catchment response. The linear continuous model we applied may underestimate flood risk in a future climate with greater extreme rainfall intensity. In contrast with the recommendations of previous studies, this indicates that continuous simulation is not necessarily the key to robust flood modelling under climate change. By applying bottom-up climate change assessment, we were able to understand systematic changes in relative model performance under changing conditions and deduce likely sources of prediction error in the two models.

Review of Aerosol–Cloud Interactions: Mechanisms, Significance, and Challenges

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

Fan, Jiwen; Wang, Yuan; Rosenfeld, Daniel

2016-11-01

Over the past decade, the number of studies that investigate aerosol-cloud interactions has increased considerably. Although tremendous progress has been made to improve our understanding of basic physical mechanisms of aerosol-cloud interactions and reduce their uncertainties in climate forcing, we are still in poor understanding of (1) some of the mechanisms that interact with each other over multiple spatial and temporal scales, (2) the feedback between microphysical and dynamical processes and between local-scale processes and large-scale circulations, and (3) the significance of cloud-aerosol interactions on weather systems as well as regional and global climate. This review focuses on recent theoreticalmore » studies and important mechanisms on aerosol-cloud interactions, and discusses the significances of aerosol impacts on raditative forcing and precipitation extremes associated with different cloud systems. Despite significant understanding has been gained about aerosol impacts on the main cloud types, there are still many unknowns especially associated with various deep convective systems. Therefore, large efforts are needed to escalate our understanding. Future directions should focus on obtaining concurrent measurements of aerosol properties, cloud microphysical and dynamic properties over a range of temporal and spatial scales collected over typical climate regimes and closure studies, as well as improving understanding and parameterizations of cloud microphysics such as ice nucleation, mixed-phase properties, and hydrometeor size and fall speed« less

Toward A Science of Sustainable Water Management

NASA Astrophysics Data System (ADS)

Brown, C.

2016-12-01

Societal need for improved water management and concerns for the long-term sustainability of water resources systems are prominent around the world. The continued susceptibility of society to the harmful effects of hydrologic variability, pervasive concerns related to climate change and the emergent awareness of devastating effects of current practice on aquatic ecosystems all illustrate our limited understanding of how water ought to be managed in a dynamic world. The related challenges of resolving the competition for freshwater among competing uses (so called "nexus" issues) and adapting water resources systems to climate change are prominent examples of the of sustainable water management challenges. In addition, largely untested concepts such as "integrated water resources management" have surfaced as Sustainable Development Goals. In this presentation, we argue that for research to improve water management, and for practice to inspire better research, a new focus is required, one that bridges disciplinary barriers between the water resources research focus on infrastructure planning and management, and the role of human actors, and geophysical sciences community focus on physical processes in the absence of dynamical human response. Examples drawn from climate change adaptation for water resource systems and groundwater management policy provide evidence of initial progress towards a science of sustainable water management that links improved physical understanding of the hydrological cycle with the socioeconomic and ecological understanding of water and societal interactions.

Applying a Systems Approach to Monitoring and Assessing Climate Change Mitigation Potential in Mexico's Forest Sector

NASA Astrophysics Data System (ADS)

Olguin-Alvarez, M. I.; Wayson, C.; Fellows, M.; Birdsey, R.; Smyth, C.; Magnan, M.; Dugan, A.; Mascorro, V.; Alanís, A.; Serrano, E.; Kurz, W. A.

2017-12-01

Since 2012, the Mexican government through its National Forestry Commission, with support from the Commission for Environmental Cooperation, the Forest Services of Canada and USA, the SilvaCarbon Program and research institutes in Mexico, has made important progress towards the use of carbon dynamics models ("gain-loss" approach) for greenhouse gas (GHG) emissions monitoring and projections into the future. Here we assess the biophysical mitigation potential of policy alternatives identified by the Mexican Government (e.g. net zero deforestation rate, sustainable forest management) based on a systems approach that models carbon dynamics in forest ecosystems, harvested wood products and substitution benefits in two contrasting states of Mexico. We provide key messages and results derived from the use of the Carbon Budget Model of the Canadian Forest Sector and a harvested wood products model, parameterized with input data from Mexicós National Forest Monitoring System (e.g. forest inventories, remote sensing, disturbance data). The ultimate goal of this tri-national effort is to develop data and tools for carbon assessment in strategic landscapes in North America, emphasizing the need to include multiple sectors and types of collaborators (scientific and policy-maker communities) to design more comprehensive portfolios for climate change mitigation in accordance with the Paris Agreement of the United Nation Framework Convention on Climate Change (e.g. Mid-Century Strategy, NDC goals).

Underlying mechanisms leading to El Niño-to-La Niña transition are unchanged under global warming

NASA Astrophysics Data System (ADS)

Yun, Kyung-Sook; Yeh, Sang-Wook; Ha, Kyung-Ja

2018-05-01

El Niño's transitions play critical roles in modulating severe weather and climate events. Therefore, understanding the dynamic factors leading to El Niño's transitions and its future projection is a great challenge in predicting the diverse socioeconomic influences of El Niño over the globe. This study focuses on two dynamic factors controlling the El Niño-to-La Niña transition from the present climate and to future climate, using the observation, the historical and the RCP8.5 simulations of Coupled Model Intercomparison phase 5 climate models. The first is the inter-basin coupling between the Indian Ocean and the western North Pacific through the subtropical high variability. The second is the enhanced sensitivity between sea surface temperature and a deep tropical convection in the central tropical Pacific during the El Niño's developing phase. We show that the dynamic factors leading to El Niño-to-La Niña transition in the present climate are unchanged in spite of the increase of greenhouse gas concentrations. We argue that the two dynamic factors are strongly constrained by the climatological precipitation distribution over the central tropical Pacific and western North Pacific as little changed from the present climate to future climate. This implies that two dynamical processes leading to El Niño-to-La Niña transitions in the present climate will also play a robust role in global warming.

Climate and anthropogenic impacts on forest vegetation derived from satellite data

NASA Astrophysics Data System (ADS)

Zoran, M.; Savastru, R.; Savastru, D.; Tautan, M.; Miclos, S.; Baschir, L.

2010-09-01

Vegetation and climate interact through a series of complex feedbacks, which are not very well understood. The patterns of forest vegetation are largely determined by temperature, precipitation, solar irradiance, soil conditions and CO2 concentration. Vegetation impacts climate directly through moisture, energy, and momentum exchanges with the atmosphere and indirectly through biogeochemical processes that alter atmospheric CO2 concentration. Changes in forest vegetation land cover/use alter the surface albedo and radiation fluxes, leading to a local temperature change and eventually a vegetation response. This albedo (energy) feedback is particularly important when forests mask snow cover. Forest vegetation-climate feedback regimes are designated based on the temporal correlations between the vegetation and the surface temperature and precipitation. The different feedback regimes are linked to the relative importance of vegetation and soil moisture in determining land-atmosphere interactions. Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modeling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal forest vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images over 1989 - 2009 period for a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, from IKONOS and LANDSAT TM and ETM satellite images and meteorological data. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. For investigated test area, considerable NDVI decline was observed for drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation .

The Influential Role of Sociocultural Feedbacks on Community-Managed Irrigation System Behaviors During times of Water Stress

DOE PAGES

Gunda, Thushara; Turner, B. L.; Tidwell, Vincent C.

2018-03-14

Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responsesmore » to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.« less

The Influential Role of Sociocultural Feedbacks on Community-Managed Irrigation System Behaviors During times of Water Stress

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

Gunda, Thushara; Turner, B. L.; Tidwell, Vincent C.

Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responsesmore » to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. In conclusion, continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.« less

The Influential Role of Sociocultural Feedbacks on Community-Managed Irrigation System Behaviors During Times of Water Stress

NASA Astrophysics Data System (ADS)

Gunda, T.; Turner, B. L.; Tidwell, V. C.

2018-04-01

Sociohydrological studies use interdisciplinary approaches to explore the complex interactions between physical and social water systems and increase our understanding of emergent and paradoxical system behaviors. The dynamics of community values and social cohesion, however, have received little attention in modeling studies due to quantification challenges. Social structures associated with community-managed irrigation systems around the world, in particular, reflect these communities' experiences with a multitude of natural and social shocks. Using the Valdez acequia (a communally-managed irrigation community in northern New Mexico) as a simulation case study, we evaluate the impact of that community's social structure in governing its responses to water availability stresses posed by climate change. Specifically, a system dynamics model (developed using insights from community stakeholders and multiple disciplines that captures biophysical, socioeconomic, and sociocultural dynamics of acequia systems) was used to generate counterfactual trajectories to explore how the community would behave with streamflow conditions expected under climate change. We found that earlier peak flows, combined with adaptive measures of shifting crop selection, allowed for greater production of higher value crops and fewer people leaving the acequia. The economic benefits were lost, however, if downstream water pressures increased. Even with significant reductions in agricultural profitability, feedbacks associated with community cohesion buffered the community's population and land parcel sizes from more detrimental impacts, indicating the community's resilience under natural and social stresses. Continued exploration of social structures is warranted to better understand these systems' responses to stress and identify possible leverage points for strengthening community resilience.

Use of Participatory Systems Dynamics Modelling to Generate User-Friendly Decision Support Systems for the Design of Management Policies for Complex Human-Environmental Systems: A Case Study from the Varied Socio-environmental Landscape of Guatemala

NASA Astrophysics Data System (ADS)

Malard, J. J.; Baig, A. I.; Carrera, J.; Mellini, L.; Pineda, P.; Monterroso, O.; Melgar-Quiñonez, H.; Adamowski, J. F.; Halbe, J.; Monardes, H.; Gálvez, J.

2014-12-01

The design of effective management policies for socioenvironmental systems requires the development of comprehensive, yet sufficiently simple, decision support systems (DSS) for policy makers. Guatemala is a particularly complex case, combining an enormous diversity of climates, geographies, and agroecosystems within a very small geographical scale. Although food insecurity levels are very high, indicating a generally inadequate management of the varied agroecosystems of the country, different regions have shown vastly different trends in food insecurity over the past decade, including between regions with similar geophysical and climatic characteristics and/or governmental programmes (e.g., agricultural support). These observations suggest two important points: firstly, that not merely environmental conditions but rather socio-environmental interactions play a crucial role in the successful management of human-environmental systems, and, secondly, that differences in the geophysical and climatic environments between the diverse regions significantly impact the success or failure of policies. This research uses participatory systems dynamic modelling (SDM) to build a DSS that allows local decision-makers to (1) determine the impact of current and potential policies on agroecosystem management and food security, and (2) design sustainable and resilient policies for the future. The use of participatory SDM offers several benefits, including the active involvement of the end recipients in the development of the model, greatly increasing its acceptability; the integration of physical (e.g., precipitation, crop yield) and social components in one model; adequacy for modelling long-term trends in response to particular policy decisions; and the inclusion of local stakeholder knowledge on system structure and trends through the participatory process. Preliminary results suggest that there is a set of common variables explaining the generally high levels of food insecurity in Guatemala (e.g., agricultural productivity), while others (e.g., land dynamics and access to water resources) are restricted to certain regions and have a relatively important weight in determining the success or failure of policies in these regions.

High Resolution Global Climate Modeling with GEOS-5: Intense Precipitation, Convection and Tropical Cyclones on Seasonal Time-Scales.

NASA Technical Reports Server (NTRS)

Putnam, WilliamM.

2011-01-01

In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.

Development of Representative Rainfall Periods for Green Infrastructure Design: Connecting the Dots Between Climate, Urban Hydrology and Resilience

NASA Astrophysics Data System (ADS)

Albright, C. M.; Traver, R.; Wadzuk, B.

2017-12-01

Analysis of local-to-regional climate data is critical in understanding how changing patterns in rainfall and other atmospheric conditions can affect urban hydrology. Urbanization has caused hydrologic and ecologic modifications to our land surfaces, and altered the dynamics of urban water cycle in complex ways. Green infrastructure (GI) systems, in their simplest form, reduce runoff and flooding, prevent combined sewer overflows and improve quality of receiving waters. However, when viewed through a more holistic lens, GI systems sit at the nexus of hydrology, climate and energy, yet are rarely designed to account for the impacts of these intersections. We must assess urban hydrologic systems beyond their response to a single event or design storm, incorporating multiple temporal scales and all hydrologic processes. This is of utmost importance to design and characterization of urban GI systems because the resilience of these systems will be dictated by their ability to adapt to future behavior of extreme weather patterns and climate. In this study, we characterize long-term hydrologic conditions in Philadelphia to identify periods of record that are most representative of regional climate characteristics, including a representative rainfall year and longer representative periods. Utility of these datasets will be demonstrated by showing that GI systems are able to sustain effective performance for most expected annual precipitation events. Connections between atmospheric (precipitation and temperature) patterns, GI systems and potential removal mechanisms in the urban hydrologic cycle will be presented for Philadelphia and cities with similar climate characteristics. Establishing such connections is critically needed to not only validate what is already known about urban GI, but more importantly, to advance theory and practice by linking the hydrologic benefits of urban GI to broader concepts such as risk, mitigation of extreme events and sustainable communities.

Creation of Synthetic Surface Temperature and Precipitation Ensembles Through A Computationally Efficient, Mixed Method Approach

NASA Astrophysics Data System (ADS)

Hartin, C.; Lynch, C.; Kravitz, B.; Link, R. P.; Bond-Lamberty, B. P.

2017-12-01

Typically, uncertainty quantification of internal variability relies on large ensembles of climate model runs under multiple forcing scenarios or perturbations in a parameter space. Computationally efficient, standard pattern scaling techniques only generate one realization and do not capture the complicated dynamics of the climate system (i.e., stochastic variations with a frequency-domain structure). In this study, we generate large ensembles of climate data with spatially and temporally coherent variability across a subselection of Coupled Model Intercomparison Project Phase 5 (CMIP5) models. First, for each CMIP5 model we apply a pattern emulation approach to derive the model response to external forcing. We take all the spatial and temporal variability that isn't explained by the emulator and decompose it into non-physically based structures through use of empirical orthogonal functions (EOFs). Then, we perform a Fourier decomposition of the EOF projection coefficients to capture the input fields' temporal autocorrelation so that our new emulated patterns reproduce the proper timescales of climate response and "memory" in the climate system. Through this 3-step process, we derive computationally efficient climate projections consistent with CMIP5 model trends and modes of variability, which address a number of deficiencies inherent in the ability of pattern scaling to reproduce complex climate model behavior.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Eco-hydrological Modeling in the Framework of Climate Change

NASA Astrophysics Data System (ADS)

Fatichi, Simone; Ivanov, Valeriy Y.; Caporali, Enrica

2010-05-01

A blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the plot and small catchment scale is presented. Input hydro-meteorological variables for hydrological and eco-hydrological models for present and future climates are reproduced using a stochastic downscaling technique and a weather generator, "AWE-GEN". The generated time series of meteorological variables for the present climate and an ensemble of possible future climates serve as input to a newly developed physically-based eco-hydrological model "Tethys-Chloris". An application of the proposed methodology is realized reproducing the current (1961-2000) and multiple future (2081-2100) climates for the location of Tucson (Arizona). A general reduction of precipitation and a significant increase of air temperature are inferred. The eco-hydrological model is successively applied to detect changes in water recharge and vegetation dynamics for a desert shrub ecosystem, typical of the semi-arid climate of south Arizona. Results for the future climate account for uncertainties in the downscaling and are produced in terms of probability density functions. A comparison of control and future scenarios is discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity. An appreciable effect of climate change can be observed in metrics of vegetation performance. The negative impact on vegetation due to amplification of water stress in a warmer and dryer climate is offset by a positive effect of carbon dioxide augment. This implies a positive shift in plant capabilities to exploit water. Consequently, the plant water use efficiency and rain use efficiency are expected to increase. Interesting differences in the long-term vegetation productivity are also observed for the ensemble of future climates. The reduction of precipitation and the substantial maintenance of vegetation cover ultimately leads to the depletion of soil moisture and recharge to deeper layers. Such an outcome can affect the long-tem water availability in semi-arid systems and expose plants to more severe and frequent periods of stress.

Nonlinear dynamics of global atmospheric and Earth system processes

NASA Technical Reports Server (NTRS)

Saltzman, Barry

1993-01-01

During the past eight years, we have been engaged in a NASA-supported program of research aimed at establishing the connection between satellite signatures of the earth's environmental state and the nonlinear dynamics of the global weather and climate system. Thirty-five publications and four theses have resulted from this work, which included contributions in five main areas of study: (1) cloud and latent heat processes in finite-amplitude baroclinic waves; (2) application of satellite radiation data in global weather analysis; (3) studies of planetary waves and low-frequency weather variability; (4) GCM studies of the atmospheric response to variable boundary conditions measurable from satellites; and (5) dynamics of long-term earth system changes. Significant accomplishments from the three main lines of investigation pursued during the past year are presented and include the following: (1) planetary atmospheric waves and low frequency variability; (2) GCM studies of the atmospheric response to changed boundary conditions; and (3) dynamics of long-term changes in the global earth system.

Climate Induced Spillover and Implications for U.S. Security.

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

Tidwell, Vincent C.; Naugle, Asmeret Bier; Backus, George A.

Developing nations incur a greater risk to climate change than the developed world due to poorly managed human/natural resources, unreliable infrastructure and brittle governing/economic institutions. These vulnerabilities often give rise to a climate induced “domino effect” of reduced natural resource production-leading to economic hardship, social unrest, and humanitarian crises. Integral to this cascading set of events is increased human migration, leading to the “spillover” of impacts to adjoining areas with even broader impact on global markets and security. Given the complexity of factors influencing human migration and the resultant spill-over effect, quantitative tools are needed to aid policy analysis. Towardmore » this need, a series of migration models were developed along with a system dynamics model of the spillover effect. The migration decision models were structured according to two interacting paths, one that captured long-term “chronic” impacts related to protracted deteriorating quality of life and a second focused on short-term “acute” impacts of disaster and/or conflict. Chronic migration dynamics were modeled for two different cases; one that looked only at emigration but at a national level for the entire world; and a second that looked at both emigration and immigration but focused on a single nation. Model parameterization for each of the migration models was accomplished through regression analysis using decadal data spanning the period 1960-2010. A similar approach was taken with acute migration dynamics except regression analysis utilized annual data sets limited to a shorter time horizon (2001-2013). The system dynamics spillover model was organized around two broad modules, one simulating the decision dynamics of migration and a second module that treats the changing environmental conditions that influence the migration decision. The environmental module informs the migration decision, endogenously simulating interactions/changes in the economy, labor, population, conflict, water, and food. A regional model focused on Mali in western Africa was used as a test case to demonstrate the efficacy of the model.« less

Socio-hydrologic modeling to understand and mediate the competition for water between agriculture development and environmental health: Murrumbidgee River Basin, Australia

NASA Astrophysics Data System (ADS)

van Emmerik, T. H. M.; Li, Z.; Sivapalan, M.; Pande, S.; Kandasamy, J.; Savenije, H. H. G.; Chanan, A.; Vigneswaran, S.

2014-03-01

Competition for water between humans and ecosystems is set to become a flash point in the coming decades in many parts of the world. An entirely new and comprehensive quantitative framework is needed to establish a holistic understanding of that competition, thereby enabling the development of effective mediation strategies. This paper presents a modeling study centered on the Murrumbidgee River Basin (MRB). The MRB has witnessed a unique system dynamics over the last 100 years as a result of interactions between patterns of water management and climate driven hydrological variability. Data analysis has revealed a pendulum swing between agricultural development and restoration of environmental health and ecosystem services over different stages of basin scale water resource development. A parsimonious, stylized, quasi-distributed coupled socio-hydrologic system model that simulates the two-way coupling between human and hydrological systems of the MRB is used to mimic dominant features of the pendulum swing. The model consists of coupled nonlinear ordinary differential equations that describe the interaction between five state variables that govern the co-evolution: reservoir storage, irrigated area, human population, ecosystem health, and a measure of environmental awareness. The model simulations track the propagation of the external climatic and socio-economic drivers through this coupled, complex system to the emergence of the pendulum swing. The model results point to a competition between human "productive" and environmental "restorative" forces that underpin the pendulum swing. Both the forces are endogenous, i.e., generated by the system dynamics in response to external drivers and mediated by humans through technology change and environmental awareness, respectively. We propose this as a generalizable modeling framework for coupled human hydrological systems that is potentially transferable to systems in different climatic and socio-economic settings.

A seasonal hydrologic ensemble prediction system for water resource management

NASA Astrophysics Data System (ADS)

Luo, L.; Wood, E. F.

2006-12-01

A seasonal hydrologic ensemble prediction system, developed for the Ohio River basin, has been improved and expanded to several other regions including the Eastern U.S., Africa and East Asia. The prediction system adopts the traditional Extended Streamflow Prediction (ESP) approach, utilizing the VIC (Variable Infiltration Capacity) hydrological model as the central tool for producing ensemble prediction of soil moisture, snow and streamflow with lead times up to 6-month. VIC is forced by observed meteorology to estimate the hydrological initial condition prior to the forecast, but during the forecast period the atmospheric forcing comes from statistically downscaled, seasonal forecast from dynamic climate models. The seasonal hydrologic ensemble prediction system is currently producing realtime seasonal hydrologic forecast for these regions on a monthly basis. Using hindcasts from a 19-year period (1981-1999), during which seasonal hindcasts from NCEP Climate Forecast System (CFS) and European Union DEMETER project are available, we evaluate the performance of the forecast system over our forecast regions. The evaluation shows that the prediction system using the current forecast approach is able to produce reliable and accurate precipitation, soil moisture and streamflow predictions. The overall skill is much higher then the traditional ESP. In particular, forecasts based on multiple climate model forecast are more skillful than single model-based forecast. This emphasizes the significant need for producing seasonal climate forecast with multiple climate models for hydrologic applications. Forecast from this system is expected to provide very valuable information about future hydrologic states and associated risks for end users, including water resource management and financial sectors.

Belowground adaptation and resilience to drought conditions

NASA Astrophysics Data System (ADS)

Sivandran, G.; Gentine, P.; Bras, R. L.

2012-12-01

The most expansive drought in 50 years stretched across the Midwest in 2012. In light of predicted increases in the variability of climate, this type of event can no longer be considered extreme. Understanding the resilience of both managed and natural vegetation and how these systems may adapt to this new climate reality is critical in predicting changes to the global carbon, energy and water balance. An eco-hydrological model (tRIBS+VEGGIE) was employed to model the sensitivity of vegetation to varying drought intensities. Point scale simulations were carried out using two vertical root distribution schemes: (i) Static - a temporally invariant root distribution; and (ii) Dynamic - a temporally variable root carbon allocation scheme. A stochastic climate generator was used to create a series of synthetic climate realizations varying the drought characteristics - in particular the interstorm period. This change in the seasonal distribution of precipitation impacts the spatial (soil layers) and temporal distribution of soil moisture which directly impacts the water resource niche for vegetation. This change in resource niche is reflected in a shift in the optimal static rooting strategy further highlighting the need for the incorporation of a dynamic scheme that responds to local conditions.

Mathematical Modelling of Plankton-Oxygen Dynamics Under the Climate Change.

PubMed

Sekerci, Yadigar; Petrovskii, Sergei

2015-12-01

Ocean dynamics is known to have a strong effect on the global climate change and on the composition of the atmosphere. In particular, it is estimated that about 70% of the atmospheric oxygen is produced in the oceans due to the photosynthetic activity of phytoplankton. However, the rate of oxygen production depends on water temperature and hence can be affected by the global warming. In this paper, we address this issue theoretically by considering a model of a coupled plankton-oxygen dynamics where the rate of oxygen production slowly changes with time to account for the ocean warming. We show that a sustainable oxygen production is only possible in an intermediate range of the production rate. If, in the course of time, the oxygen production rate becomes too low or too high, the system's dynamics changes abruptly, resulting in the oxygen depletion and plankton extinction. Our results indicate that the depletion of atmospheric oxygen on global scale (which, if happens, obviously can kill most of life on Earth) is another possible catastrophic consequence of the global warming, a global ecological disaster that has been overlooked.

A Linear Dynamical Systems Approach to Streamflow Reconstruction Reveals History of Regime Shifts in Northern Thailand

NASA Astrophysics Data System (ADS)

Nguyen, Hung T. T.; Galelli, Stefano

2018-03-01

Catchment dynamics is not often modeled in streamflow reconstruction studies; yet, the streamflow generation process depends on both catchment state and climatic inputs. To explicitly account for this interaction, we contribute a linear dynamic model, in which streamflow is a function of both catchment state (i.e., wet/dry) and paleoclimatic proxies. The model is learned using a novel variant of the Expectation-Maximization algorithm, and it is used with a paleo drought record—the Monsoon Asia Drought Atlas—to reconstruct 406 years of streamflow for the Ping River (northern Thailand). Results for the instrumental period show that the dynamic model has higher accuracy than conventional linear regression; all performance scores improve by 45-497%. Furthermore, the reconstructed trajectory of the state variable provides valuable insights about the catchment history—e.g., regime-like behavior—thereby complementing the information contained in the reconstructed streamflow time series. The proposed technique can replace linear regression, since it only requires information on streamflow and climatic proxies (e.g., tree-rings, drought indices); furthermore, it is capable of readily generating stochastic streamflow replicates. With a marginal increase in computational requirements, the dynamic model brings more desirable features and value to streamflow reconstructions.

A global empirical system for probabilistic seasonal climate prediction

NASA Astrophysics Data System (ADS)

Eden, J. M.; van Oldenborgh, G. J.; Hawkins, E.; Suckling, E. B.

2015-12-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

An empirical system for probabilistic seasonal climate prediction

NASA Astrophysics Data System (ADS)

Eden, Jonathan; van Oldenborgh, Geert Jan; Hawkins, Ed; Suckling, Emma

2016-04-01

Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961-2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño-Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

Assessing the Costs and Benefits of Resilience Investments: Tennessee Valley Authority Case Study

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

Allen, Melissa R.; Wilbanks, Thomas J.; Preston, Benjamin L.

This report describes a general approach for assessing climate change vulnerabilities of an electricity system and evaluating the costs and benefits of certain investments that would increase system resilience. It uses Tennessee Valley Authority (TVA) as a case study, concentrating on the Cumberland River basin area on the northern side of the TVA region. The study focuses in particular on evaluating risks associated with extreme heat wave and drought conditions that could be expected to affect the region by mid-century. Extreme climate event scenarios were developed using a combination of dynamically downscaled output from the Community Earth System Model andmore » historical heat wave and drought conditions in 1993 and 2007, respectively.« less

Regime shifts and panarchies in regional scale social-ecological water systems

EPA Science Inventory

In this article we summarize histories of nonlinear, complex interactions among societal, legal, and ecosystem dynamics in six North American water basins, as they respond to changing climate. These case studies were chosen to explore the conditions for emergence of adaptive gove...

Sensitivity of the Tropical Ocean-Atmosphere to Seasonal and Long-Term Climate Forcing

NASA Technical Reports Server (NTRS)

Kim, K.-M.; Lau, K.-M.

1999-01-01

Since the pioneer works of Bjerknes (1966,1969) many studies have been conducted to understand the El Nino and Southern Oscillation (ENSO) phenomenon. These studies have led to a basic understanding of the dynamics of El Nino. Central to the couple dynamics of ENSO is the delayed action oscillator theory (Suarez and Schopf 1988), which successfully describes the cyclic feature of El Nino. While the oscillatory feature of El Nino is reasonably well understood, the irregularity of El Nino, the effect of monsoon on ENSO, and the response of coupled system to the global warming are still under debate. In the present study, we attempt to provide some theoretical understanding of possible impacts of seasonal cycle, monsoon, and climate changes on ENSO using intermediate coupled model.

Multiannual forecasting of seasonal influenza dynamics reveals climatic and evolutionary drivers.

PubMed

Axelsen, Jacob Bock; Yaari, Rami; Grenfell, Bryan T; Stone, Lewi

2014-07-01

Human influenza occurs annually in most temperate climatic zones of the world, with epidemics peaking in the cold winter months. Considerable debate surrounds the relative role of epidemic dynamics, viral evolution, and climatic drivers in driving year-to-year variability of outbreaks. The ultimate test of understanding is prediction; however, existing influenza models rarely forecast beyond a single year at best. Here, we use a simple epidemiological model to reveal multiannual predictability based on high-quality influenza surveillance data for Israel; the model fit is corroborated by simple metapopulation comparisons within Israel. Successful forecasts are driven by temperature, humidity, antigenic drift, and immunity loss. Essentially, influenza dynamics are a balance between large perturbations following significant antigenic jumps, interspersed with nonlinear epidemic dynamics tuned by climatic forcing.

A Dynamical Systems Explanation of the Hurst Effect and Atmospheric Low-Frequency Variability

PubMed Central

Franzke, Christian L. E.; Osprey, Scott M.; Davini, Paolo; Watkins, Nicholas W.

2015-01-01

The Hurst effect plays an important role in many areas such as physics, climate and finance. It describes the anomalous growth of range and constrains the behavior and predictability of these systems. The Hurst effect is frequently taken to be synonymous with Long-Range Dependence (LRD) and is typically assumed to be produced by a stationary stochastic process which has infinite memory. However, infinite memory appears to be at odds with the Markovian nature of most physical laws while the stationarity assumption lacks robustness. Here we use Lorenz's paradigmatic chaotic model to show that regime behavior can also cause the Hurst effect. By giving an alternative, parsimonious, explanation using nonstationary Markovian dynamics, our results question the common belief that the Hurst effect necessarily implies a stationary infinite memory process. We also demonstrate that our results can explain atmospheric variability without the infinite memory previously thought necessary and are consistent with climate model simulations. PMID:25765880

The response of soil organic carbon of a rich fen peatland in interior Alaska to projected climate change.

PubMed

Fan, Zhaosheng; David McGuire, Anthony; Turetsky, Merritt R; Harden, Jennifer W; Michael Waddington, James; Kane, Evan S

2013-02-01

It is important to understand the fate of carbon in boreal peatland soils in response to climate change because a substantial change in release of this carbon as CO2 and CH4 could influence the climate system. The goal of this research was to synthesize the results of a field water table manipulation experiment conducted in a boreal rich fen into a process-based model to understand how soil organic carbon (SOC) of the rich fen might respond to projected climate change. This model, the peatland version of the dynamic organic soil Terrestrial Ecosystem Model (peatland DOS-TEM), was calibrated with data collected during 2005-2011 from the control treatment of a boreal rich fen in the Alaska Peatland Experiment (APEX). The performance of the model was validated with the experimental data measured from the raised and lowered water-table treatments of APEX during the same period. The model was then applied to simulate future SOC dynamics of the rich fen control site under various CO2 emission scenarios. The results across these emissions scenarios suggest that the rate of SOC sequestration in the rich fen will increase between year 2012 and 2061 because the effects of warming increase heterotrophic respiration less than they increase carbon inputs via production. However, after 2061, the rate of SOC sequestration will be weakened and, as a result, the rich fen will likely become a carbon source to the atmosphere between 2062 and 2099. During this period, the effects of projected warming increase respiration so that it is greater than carbon inputs via production. Although changes in precipitation alone had relatively little effect on the dynamics of SOC, changes in precipitation did interact with warming to influence SOC dynamics for some climate scenarios. © 2012 Blackwell Publishing Ltd.

Intercomparison of Downscaling Methods on Hydrological Impact for Earth System Model of NE United States

NASA Astrophysics Data System (ADS)

Yang, P.; Fekete, B. M.; Rosenzweig, B.; Lengyel, F.; Vorosmarty, C. J.

2012-12-01

Atmospheric dynamics are essential inputs to Regional-scale Earth System Models (RESMs). Variables including surface air temperature, total precipitation, solar radiation, wind speed and humidity must be downscaled from coarse-resolution, global General Circulation Models (GCMs) to the high temporal and spatial resolution required for regional modeling. However, this downscaling procedure can be challenging due to the need to correct for bias from the GCM and to capture the spatiotemporal heterogeneity of the regional dynamics. In this study, the results obtained using several downscaling techniques and observational datasets were compared for a RESM of the Northeast Corridor of the United States. Previous efforts have enhanced GCM model outputs through bias correction using novel techniques. For example, the Climate Impact Research at Potsdam Institute developed a series of bias-corrected GCMs towards the next generation climate change scenarios (Schiermeier, 2012; Moss et al., 2010). Techniques to better represent the heterogeneity of climate variables have also been improved using statistical approaches (Maurer, 2008; Abatzoglou, 2011). For this study, four downscaling approaches to transform bias-corrected HADGEM2-ES Model output (daily at .5 x .5 degree) to the 3'*3'(longitude*latitude) daily and monthly resolution required for the Northeast RESM were compared: 1) Bilinear Interpolation, 2) Daily bias-corrected spatial downscaling (D-BCSD) with Gridded Meteorological Datasets (developed by Abazoglou 2011), 3) Monthly bias-corrected spatial disaggregation (M-BCSD) with CRU(Climate Research Unit) and 4) Dynamic Downscaling based on Weather Research and Forecast (WRF) model. Spatio-temporal analysis of the variability in precipitation was conducted over the study domain. Validation of the variables of different downscaling methods against observational datasets was carried out for assessment of the downscaled climate model outputs. The effects of using the different approaches to downscale atmospheric variables (specifically air temperature and precipitation) for use as inputs to the Water Balance Model (WBMPlus, Vorosmarty et al., 1998;Wisser et al., 2008) for simulation of daily discharge and monthly stream flow in the Northeast US for a 100-year period in the 21st century were also assessed. Statistical techniques especially monthly bias-corrected spatial disaggregation (M-BCSD) showed potential advantage among other methods for the daily discharge and monthly stream flow simulation. However, Dynamic Downscaling will provide important complements to the statistical approaches tested.

Community-level climate change vulnerability research: trends, progress, and future directions

NASA Astrophysics Data System (ADS)

McDowell, Graham; Ford, James; Jones, Julie

2016-03-01

This study systematically identifies, characterizes, and critically evaluates community-level climate change vulnerability assessments published over the last 25 years (n = 274). We find that while the field has advanced considerably in terms of conceptual framing and methodological approaches, key shortcomings remain in how vulnerability is being studied at the community-level. We argue that vulnerability research needs to more critically engage with the following: methods for evaluating future vulnerability, the relevance of vulnerability research for decision-making, interdependencies between social and ecological systems, attention to researcher / subject power dynamics, critical interpretation of key terms, and consideration of the potentially positive opportunities presented by a changing climate. Addressing these research needs is necessary for generating knowledge that supports climate-affected communities in navigating the challenges and opportunities ahead.

Online Student Learning and Earth System Processes

NASA Astrophysics Data System (ADS)

Mackay, R. M.

2002-12-01

Many students have difficulty understanding dynamical processes related to Earth's climate system. This is particularly true in Earth System Science courses designed for non-majors. It is often tempting to gloss over these conceptually difficult topics and have students spend more study time learning factual information or ideas that require rather simple linear thought processes. Even when the professor is ambitious and tackles the more difficult ideas of system dynamics in such courses, they are typically greeted with frustration and limited success. However, an understanding of generic system concepts and processes is quite arguably an essential component of any quality liberal arts education. We present online student-centered learning modules that are designed to help students explore different aspects of Earth's climate system (see http://www.cs.clark.edu/mac/physlets/GlobalPollution/maintrace.htm for a sample activity). The JAVA based learning activities are designed to: be assessable to anyone with Web access; be self-paced, engaging, and hands-on; and make use of past results from science education research. Professors can use module activities to supplement lecture, as controlled-learning-lab activities, or as stand-alone homework assignments. Acknowledgement This work was supported by NASA Office of Space Science contract NASW-98037, Atmospheric and Environmental Research Inc. of Lexington, MA., and Clark College.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors.

PubMed

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H; Gambhir, Manoj; Fu, Joshua S; Liu, Yang; Remais, Justin V

2013-09-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis , the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001-2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057-2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses-including altered phenology-of disease vectors to altered climate.

Spatially-Explicit Simulation Modeling of Ecological Response to Climate Change: Methodological Considerations in Predicting Shifting Population Dynamics of Infectious Disease Vectors

PubMed Central

Dhingra, Radhika; Jimenez, Violeta; Chang, Howard H.; Gambhir, Manoj; Fu, Joshua S.; Liu, Yang; Remais, Justin V.

2014-01-01

Poikilothermic disease vectors can respond to altered climates through spatial changes in both population size and phenology. Quantitative descriptors to characterize, analyze and visualize these dynamic responses are lacking, particularly across large spatial domains. In order to demonstrate the value of a spatially explicit, dynamic modeling approach, we assessed spatial changes in the population dynamics of Ixodes scapularis, the Lyme disease vector, using a temperature-forced population model simulated across a grid of 4 × 4 km cells covering the eastern United States, using both modeled (Weather Research and Forecasting (WRF) 3.2.1) baseline/current (2001–2004) and projected (Representative Concentration Pathway (RCP) 4.5 and RCP 8.5; 2057–2059) climate data. Ten dynamic population features (DPFs) were derived from simulated populations and analyzed spatially to characterize the regional population response to current and future climate across the domain. Each DPF under the current climate was assessed for its ability to discriminate observed Lyme disease risk and known vector presence/absence, using data from the US Centers for Disease Control and Prevention. Peak vector population and month of peak vector population were the DPFs that performed best as predictors of current Lyme disease risk. When examined under baseline and projected climate scenarios, the spatial and temporal distributions of DPFs shift and the seasonal cycle of key questing life stages is compressed under some scenarios. Our results demonstrate the utility of spatial characterization, analysis and visualization of dynamic population responses—including altered phenology—of disease vectors to altered climate. PMID:24772388

A systematic review of dynamics in climate risk and vulnerability assessments

NASA Astrophysics Data System (ADS)

Jurgilevich, Alexandra; Räsänen, Aleksi; Groundstroem, Fanny; Juhola, Sirkku

2017-01-01

Understanding climate risk is crucial for effective adaptation action, and a number of assessment methodologies have emerged. We argue that the dynamics of the individual components in climate risk and vulnerability assessments has received little attention. In order to highlight this, we systematically reviewed 42 sub-national climate risk and vulnerability assessments. We analysed the assessments using an analytical framework with which we evaluated (1) the conceptual approaches to vulnerability and exposure used, (2) if current or future risks were assessed, and (3) if and how changes over time (i.e. dynamics) were considered. Of the reviewed assessments, over half addressed future risks or vulnerability; and of these future-oriented studies, less than 1/3 considered both vulnerability and exposure dynamics. While the number of studies that include dynamics is growing, and while all studies included socio-economic aspects, often only biophysical dynamics was taken into account. We discuss the challenges of assessing socio-economic and spatial dynamics, particularly the poor availability of data and methods. We suggest that future-oriented studies assessing risk dynamics would benefit from larger stakeholder involvement, discussion of the assessment purpose, the use of multiple methods, inclusion of uncertainty/sensitivity analyses and pathway approaches.

Mineral dust transport and deposition to Antarctica: a climate model perspective

NASA Astrophysics Data System (ADS)

Albani, S.; Mahowald, N. M.; Maggi, V.; Delmonte, B.

2009-04-01

Windblown mineral dust is a useful proxy for paleoclimates. Its life cycle is determined by climate conditions in the source areas, and following the hydrological cycle, and the intensity and dynamics of the atmospheric circulation. In addition aeolian dust itself is an active component of the climate system, influencing the radiative balance of the atmosphere through its interaction with incoming solar radiation and outgoing planetary radiation. The mineral aerosols also have indirect effects on climate, and are linked to interactions with cloud microphysics and atmospheric chemistry as well as to dust's role of carrier of iron and other elements that constitute limitating nutrients for phytoplancton to remote ocean areas. We use climate model (CCSM) simulations that include a scheme for dust mobilization, transport and deposition in order to describe the evolution of dust deposition in some Antarctic ice cores sites where mineral dust records are available. Our focus is to determine the source apportionment for dust deposited to Antarctica under current and Last Glacial Maximum climate conditions, as well as to give an insight in the spatial features of transport patterns. The understanding of spatial and temporal representativeness of an ice core record is crucial to determine its value as a proxy of past climates and a necessary step in order to produce a global picture of how the dust component of the climate system has changed through time.

Design and Applications of a Climatic Chamber for in-situ Neutron Imaging Experiments

NASA Astrophysics Data System (ADS)

Mannes, David; Schmid, Florian; Wehmann, Timon; Lehmann, Eberhard

Due to the high sensitivity for hydrogen, the detection and quantification of moisture and moisture transport processes are some of the key topics in neutron imaging. Especially when dealing with hygroscopic material, such as wood and other porous media, it is crucial for quantitative analyses to know and control the ambient conditions of the sample precisely. In this work, a neutron transparent climatic chamber is presented, which was designed and built for the imaging facilities at the Paul Scherrer Institut (PSI), Villigen (CH). The air-conditioned measuring system consists of the actual sample chamber and a moisture generator providing air with adjustable temperature and relative humidity (%RH) (up to a dew point temperature of 70 °C). The two components are connected with a flexible tube, which features insulation, a heating system and temperature sensors to prevent condensation within the tube. The sample chamber itself is equipped with neutron transparent windows, insulating double walls with three feed-through openings for the rotation stage, sensors for humidity and temperature. Thermoelectric modules allow to control the chamber temperature in the range of -20 °C to 100 °C. The chamber allows to control the climatic conditions either in a static mode (stable temperature and %RH) or in dynamic mode (humidity or temperature cycles). The envisaged areas of application are neutron radiography and tomography investigations of dynamic processes in building materials (e.g. wood, concrete), food science and any other application necessitating the control of the climatic conditions.

Representations of the Stratospheric Polar Vortices in Versions 1 and 2 of the Goddard Earth Observing System Chemistry-Climate Model (GEOS CCM)

NASA Technical Reports Server (NTRS)

Pawson, S.; Stolarski, R.S.; Nielsen, J.E.; Perlwitz, J.; Oman, L.; Waugh, D.

2009-01-01

This study will document the behavior of the polar vortices in two versions of the GEOS CCM. Both versions of the model include the same stratospheric chemistry, They differ in the underlying circulation model. Version 1 of the GEOS CCM is based on the Goddard Earth Observing System, Version 4, general circulation model which includes the finite-volume (Lin-Rood) dynamical core and physical parameterizations from Community Climate Model, Version 3. GEOS CCM Version 2 is based on the GEOS-5 GCM that includes a different tropospheric physics package. Baseline simulations of both models, performed at two-degree spatial resolution, show some improvements in Version 2, but also some degradation, In the Antarctic, both models show an over-persistent stratospheric polar vortex with late breakdown, but the year-to-year variations that are overestimated in Version I are more realistic in Version 2. The implications of this for the interactions with tropospheric climate, the Southern Annular Mode, will be discussed. In the Arctic both model versions show a dominant dynamically forced variabi;ity, but Version 2 has a persistent warm bias in the low stratosphere and there are seasonal differences in the simulations. These differences will be quantified in terms of climate change and ozone loss. Impacts of model resolution, using simulations at one-degree and half-degree, and changes in physical parameterizations (especially the gravity wave drag) will be discussed.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

NASA Astrophysics Data System (ADS)

Way, M. J.; Aleinov, I.; Amundsen, David S.; Chandler, M. A.; Clune, T. L.; Del Genio, A. D.; Fujii, Y.; Kelley, M.; Kiang, N. Y.; Sohl, L.; Tsigaridis, K.

2017-07-01

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) is a three-dimensional General Circulation Model (GCM) developed at the NASA Goddard Institute for Space Studies for the modeling of atmospheres of solar system and exoplanetary terrestrial planets. Its parent model, known as ModelE2, is used to simulate modern Earth and near-term paleo-Earth climates. ROCKE-3D is an ongoing effort to expand the capabilities of ModelE2 to handle a broader range of atmospheric conditions, including higher and lower atmospheric pressures, more diverse chemistries and compositions, larger and smaller planet radii and gravity, different rotation rates (from slower to more rapid than modern Earth’s, including synchronous rotation), diverse ocean and land distributions and topographies, and potential basic biosphere functions. The first aim of ROCKE-3D is to model planetary atmospheres on terrestrial worlds within the solar system such as paleo-Earth, modern and paleo-Mars, paleo-Venus, and Saturn’s moon Titan. By validating the model for a broad range of temperatures, pressures, and atmospheric constituents, we can then further expand its capabilities to those exoplanetary rocky worlds that have been discovered in the past, as well as those to be discovered in the future. We also discuss the current and near-future capabilities of ROCKE-3D as a community model for studying planetary and exoplanetary atmospheres.

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

NASA Technical Reports Server (NTRS)

Way, M. J.; Aleinov, I.; Amundsen, David S.; Chandler, M. A.; Clune, T. L.; Del Genio, A.; Fujii, Y.; Kelley, M.; Kiang, N. Y.; Sohl, L.;

The Influence of Sea Ice on Arctic Low Cloud Properties and Radiative Effects

NASA Technical Reports Server (NTRS)

Taylor, Patrick C.

2015-01-01

The Arctic is one of the most climatically sensitive regions of the Earth. Climate models robustly project the Arctic to warm 2-3 times faster than the global mean surface temperature, termed polar warming amplification (PWA), but also display the widest range of surface temperature projections in this region. The response of the Arctic to increased CO2 modulates the response in tropical and extra-tropical regions through teleconnections in the atmospheric circulation. An increased frequency of extreme precipitation events in the northern mid-latitudes, for example, has been linked to the change in the background equator-to-pole temperature gradient implied by PWA. Understanding the Arctic climate system is therefore important for predicting global climate change. The ice albedo feedback is the primary mechanism driving PWA, however cloud and dynamical feedbacks significantly contribute. These feedback mechanisms, however, do not operate independently. How do clouds respond to variations in sea ice? This critical question is addressed by combining sea ice, cloud, and radiation observations from satellites, including CERES, CloudSAT, CALIPSO, MODIS, and microwave radiometers, to investigate sea ice-cloud interactions at the interannual timescale in the Arctic. Cloud characteristics are strongly tied to the atmospheric dynamic and thermodynamic state. Therefore, the sensitivity of Arctic cloud characteristics, vertical distribution and optical properties, to sea ice anomalies is computed within atmospheric dynamic and thermodynamic regimes. Results indicate that the cloud response to changes in sea ice concentration differs significantly between atmospheric state regimes. This suggests that (1) the atmospheric dynamic and thermodynamic characteristics and (2) the characteristics of the marginal ice zone are important for determining the seasonal forcing by cloud on sea ice variability.