Climatic change and wildland recreation: Examining the changing patterns of wilderness recreation in response to the effects of global climate change and the El Nino phenomenon

Treesearch

Vinod Sasidharan

2000-01-01

Impacts of global climate change on the biophysical components of wilderness areas have the potential to alter their recreational utility of wilderness areas. Concomitantly, the frequency and patterns of both land-based and water-based wilderness recreation activities will be affected. Despite the difficulty of responding to the unclear dimensions of global climate...

Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends

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

Mao, Jiafu; Shi, Xiaoying; Ricciuto, Daniel M.

Here, we examined natural and anthropogenic controls on terrestrial evapotranspiration (ET) changes from 1982-2010 using multiple estimates from remote sensing-based datasets and process-oriented land surface models. A significant increased trend of ET in each hemisphere was consistently revealed by observationally-constrained data and multi-model ensembles that considered historic natural and anthropogenic drivers. The climate impacts were simulated to determine the spatiotemporal variations in ET. Globally, rising CO 2 ranked second in these models after the predominant climatic influences, and yielded a decreasing trend in canopy transpiration and ET, especially for tropical forests and high-latitude shrub land. Increased nitrogen deposition slightly amplifiedmore » global ET via enhanced plant growth. Land-use-induced ET responses, albeit with substantial uncertainties across the factorial analysis, were minor globally, but pronounced locally, particularly over regions with intensive land-cover changes. Our study highlights the importance of employing multi-stream ET and ET-component estimates to quantify the strengthening anthropogenic fingerprint in the global hydrologic cycle.« less

Disentangling climatic and anthropogenic controls on global terrestrial evapotranspiration trends

DOE PAGES

Mao, Jiafu; Shi, Xiaoying; Ricciuto, Daniel M.; ...

2015-09-08

Here, we examined natural and anthropogenic controls on terrestrial evapotranspiration (ET) changes from 1982-2010 using multiple estimates from remote sensing-based datasets and process-oriented land surface models. A significant increased trend of ET in each hemisphere was consistently revealed by observationally-constrained data and multi-model ensembles that considered historic natural and anthropogenic drivers. The climate impacts were simulated to determine the spatiotemporal variations in ET. Globally, rising CO 2 ranked second in these models after the predominant climatic influences, and yielded a decreasing trend in canopy transpiration and ET, especially for tropical forests and high-latitude shrub land. Increased nitrogen deposition slightly amplifiedmore » global ET via enhanced plant growth. Land-use-induced ET responses, albeit with substantial uncertainties across the factorial analysis, were minor globally, but pronounced locally, particularly over regions with intensive land-cover changes. Our study highlights the importance of employing multi-stream ET and ET-component estimates to quantify the strengthening anthropogenic fingerprint in the global hydrologic cycle.« less

Data Management System for the National Energy-Water System (NEWS) Assessment Framework

NASA Astrophysics Data System (ADS)

Corsi, F.; Prousevitch, A.; Glidden, S.; Piasecki, M.; Celicourt, P.; Miara, A.; Fekete, B. M.; Vorosmarty, C. J.; Macknick, J.; Cohen, S. M.

2015-12-01

Aiming at providing a comprehensive assessment of the water-energy nexus, the National Energy-Water System (NEWS) project requires the integration of data to support a modeling framework that links climate, hydrological, power production, transmission, and economical models. Large amounts of Georeferenced data has to be streamed to the components of the inter-disciplinary model to explore future challenges and tradeoffs in the US power production, based on climate scenarios, power plant locations and technologies, available water resources, ecosystem sustainability, and economic demand. We used open source and in-house build software components to build a system that addresses two major data challenges: On-the-fly re-projection, re-gridding, interpolation, extrapolation, nodata patching, merging, temporal and spatial aggregation, of static and time series datasets in virtually any file formats and file structures, and any geographic extent for the models I/O, directly at run time; Comprehensive data management based on metadata cataloguing and discovery in repositories utilizing the MAGIC Table (Manipulation and Geographic Inquiry Control database). This innovative concept allows models to access data on-the-fly by data ID, irrespective of file path, file structure, file format and regardless its GIS specifications. In addition, a web-based information and computational system is being developed to control the I/O of spatially distributed Earth system, climate, and hydrological, power grid, and economical data flow within the NEWS framework. The system allows scenario building, data exploration, visualization, querying, and manipulation any loaded gridded, point, and vector polygon dataset. The system has demonstrated its potential for applications in other fields of Earth science modeling, education, and outreach. Over time, this implementation of the system will provide near real-time assessment of various current and future scenarios of the water-energy nexus.

Fisheries regulatory regimes and resilience to climate change.

PubMed

Ojea, Elena; Pearlman, Isaac; Gaines, Steven D; Lester, Sarah E

2017-05-01

Climate change is already producing ecological, social, and economic impacts on fisheries, and these effects are expected to increase in frequency and magnitude in the future. Fisheries governance and regulations can alter socio-ecological resilience to climate change impacts via harvest control rules and incentives driving fisher behavior, yet there are no syntheses or conceptual frameworks for examining how institutions and their regulatory approaches can alter fisheries resilience to climate change. We identify nine key climate resilience criteria for fisheries socio-ecological systems (SES), defining resilience as the ability of the coupled system of interacting social and ecological components (i.e., the SES) to absorb change while avoiding transformation into a different undesirable state. We then evaluate the capacity of four fisheries regulatory systems that vary in their degree of property rights, including open access, limited entry, and two types of rights-based management, to increase or inhibit resilience. Our exploratory assessment of evidence in the literature suggests that these regulatory regimes vary widely in their ability to promote resilient fisheries, with rights-based approaches appearing to offer more resilience benefits in many cases, but detailed characteristics of the regulatory instruments are fundamental.

Predicting the Impacts of Climate Change on Central American Agriculture

NASA Astrophysics Data System (ADS)

Winter, J. M.; Ruane, A. C.; Rosenzweig, C.

2011-12-01

Agriculture is a vital component of Central America's economy. Poor crop yields and harvest reliability can produce food insecurity, malnutrition, and conflict. Regional climate models (RCMs) and agricultural models have the potential to greatly enhance the efficiency of Central American agriculture and water resources management under both current and future climates. A series of numerical experiments was conducted using Regional Climate Model Version 3 (RegCM3) and the Weather Research and Forecasting Model (WRF) to evaluate the ability of RCMs to reproduce the current climate of Central America and assess changes in temperature and precipitation under multiple future climate scenarios. Control simulations were thoroughly compared to a variety of observational datasets, including local weather station data, gridded meteorological data, and high-resolution satellite-based precipitation products. Future climate simulations were analyzed for both mean shifts in climate and changes in climate variability, including extreme events (droughts, heat waves, floods). To explore the impacts of changing climate on maize, bean, and rice yields in Central America, RCM output was used to force the Decision Support System for Agrotechnology Transfer Model (DSSAT). These results were synthesized to create climate change impacts predictions for Central American agriculture that explicitly account for evolving distributions of precipitation and temperature extremes.

THE EARTH SYSTEM PREDICTION SUITE: Toward a Coordinated U.S. Modeling Capability

PubMed Central

Theurich, Gerhard; DeLuca, C.; Campbell, T.; Liu, F.; Saint, K.; Vertenstein, M.; Chen, J.; Oehmke, R.; Doyle, J.; Whitcomb, T.; Wallcraft, A.; Iredell, M.; Black, T.; da Silva, AM; Clune, T.; Ferraro, R.; Li, P.; Kelley, M.; Aleinov, I.; Balaji, V.; Zadeh, N.; Jacob, R.; Kirtman, B.; Giraldo, F.; McCarren, D.; Sandgathe, S.; Peckham, S.; Dunlap, R.

2017-01-01

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users. The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS®); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model. PMID:29568125

THE EARTH SYSTEM PREDICTION SUITE: Toward a Coordinated U.S. Modeling Capability.

PubMed

Theurich, Gerhard; DeLuca, C; Campbell, T; Liu, F; Saint, K; Vertenstein, M; Chen, J; Oehmke, R; Doyle, J; Whitcomb, T; Wallcraft, A; Iredell, M; Black, T; da Silva, A M; Clune, T; Ferraro, R; Li, P; Kelley, M; Aleinov, I; Balaji, V; Zadeh, N; Jacob, R; Kirtman, B; Giraldo, F; McCarren, D; Sandgathe, S; Peckham, S; Dunlap, R

2016-07-01

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open source terms or to credentialed users. The ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the U.S. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC) Layer, a set of ESMF-based component templates and interoperability conventions. This shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multi-agency development of coupled modeling systems, controlled experimentation and testing, and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NavGEM), HYbrid Coordinate Ocean Model (HYCOM), and Coupled Ocean Atmosphere Mesoscale Prediction System (COAMPS ® ); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and GEOS-5 atmospheric general circulation model.

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

NASA Technical Reports Server (NTRS)

Theurich, Gerhard; DeLuca, C.; Campbell, T.; Liu, F.; Saint, K.; Vertenstein, M.; Chen, J.; Oehmke, R.; Doyle, J.; Whitcomb, T.;

PAVICS: A platform for the Analysis and Visualization of Climate Science - adopting a workflow-based analysis method for dealing with a multitude of climate data sources

NASA Astrophysics Data System (ADS)

Gauvin St-Denis, B.; Landry, T.; Huard, D. B.; Byrns, D.; Chaumont, D.; Foucher, S.

2017-12-01

As the number of scientific studies and policy decisions requiring tailored climate information continues to increase, the demand for support from climate service centers to provide the latest information in the format most helpful for the end-user is also on the rise. Ouranos, being one such organization based in Montreal, has partnered with the Centre de recherche informatique de Montreal (CRIM) to develop a platform that will offer climate data products that have been identified as most useful for users through years of consultation. The platform is built as modular components that target the various requirements of climate data analysis. The data components host and catalog NetCDF data as well as geographical and political delimitations. The analysis components are made available as atomic operations through Web Processing Service (WPS) or as workflows, whereby the operations are chained through a simple JSON structure and executed on a distributed network of computing resources. The visualization components range from Web Map Service (WMS) to a complete frontend for searching the data, launching workflows and interacting with maps of the results. Each component can easily be deployed and executed as an independent service through the use of Docker technology and a proxy is available to regulate user workspaces and access permissions. PAVICS includes various components from birdhouse, a collection of WPS initially developed by the German Climate Research Center (DKRZ) and Institut Pierre Simon Laplace (IPSL) and is designed to be highly interoperable with other WPS as well as many Open Geospatial Consortium (OGC) standards. Further connectivity is made with the Earth System Grid Federation (ESGF) nodes and local results are made searchable using the same API terminology. Other projects conducted by CRIM that integrate with PAVICS include the OGC Testbed 13 Innovation Program (IP) initiative that will enhance advanced cloud capabilities, application packaging deployment processes, as well as enabling Earth Observation (EO) processes relevant to climate. As part of its experimental agenda, working implementations of scalable machine learning on big climate data with Spark and SciSpark were delivered.

The software architecture of climate models: a graphical comparison of CMIP5 and EMICAR5 configurations

NASA Astrophysics Data System (ADS)

Alexander, K.; Easterbrook, S. M.

2015-04-01

We analyze the source code of eight coupled climate models, selected from those that participated in the CMIP5 (Taylor et al., 2012) or EMICAR5 (Eby et al., 2013; Zickfeld et al., 2013) intercomparison projects. For each model, we sort the preprocessed code into components and subcomponents based on dependency structure. We then create software architecture diagrams that show the relative sizes of these components/subcomponents and the flow of data between them. The diagrams also illustrate several major classes of climate model design; the distribution of complexity between components, which depends on historical development paths as well as the conscious goals of each institution; and the sharing of components between different modeling groups. These diagrams offer insights into the similarities and differences in structure between climate models, and have the potential to be useful tools for communication between scientists, scientific institutions, and the public.

Climate and Management Controls on Forest Growth and Forest Carbon Balance in the Western United States

NASA Astrophysics Data System (ADS)

Kelsey, Katharine Cashman

Climate change is resulting in a number of rapid changes in forests worldwide. Forests comprise a critical component of the global carbon cycle, and therefore climate-induced changes in forest carbon balance have the potential to create a feedback within the global carbon cycle and affect future trajectories of climate change. In order to further understanding of climate-driven changes in forest carbon balance, I (1) develop a method to improve spatial estimates forest carbon stocks, (2) investigate the effect of climate change and forest management actions on forest recovery and carbon balance following disturbance, and (3) explore the relationship between climate and forest growth, and identify climate-driven trends in forest growth through time, within San Juan National Forest in southwest Colorado, USA. I find that forest carbon estimates based on texture analysis from LandsatTM imagery improve regional forest carbon maps, and this method is particularly useful for estimating carbon stocks in forested regions affected by disturbance. Forest recovery from disturbance is also a critical component of future forest carbon stocks, and my results indicate that both climate and forest management actions have important implications for forest recovery and carbon dynamics following disturbance. Specifically, forest treatments that use woody biomass removed from the forest for electricity production can reduce carbon emissions to the atmosphere, but climate driven changes in fire severity and forest recovery can have the opposite effect on forest carbon stocks. In addition to the effects of disturbance and recovery on forest condition, I also find that climate change is decreasing rates of forest growth in some species, likely in response to warming summer temperatures. These growth declines could result in changes of vegetation composition, or in extreme cases, a shift in vegetation type that would alter forest carbon storage. This work provides insight into both current and future changes in forest carbon balance as a consequence of climate change and forest management in the western US.

Modeling soil respiration and variations of source components using a multi-factor global climate change experiment

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

Chen, Xiongwen; Post, Wilfred M; Norby, Richard J

2011-01-01

Soil respiration is an important component of the global carbon cycle and is highly responsive to changes in soil temperature and moisture. Accurate prediction of soil respiration and its changes under future climatic conditions requires a clear understanding of the processes involved. In spite of this, most current empirical soil respiration models incorporate just few of the underlying mechanisms that may influence its response. In this study, a new partial process-based component model built on source components of soil respiration was tested using data collected from a multi-factor climate change experiment that manipulates CO2 concentrations, temperature and precipitation. These resultsmore » were then compared to results generated using several other established models. The component model we tested performed well across different treatments of global climate change. In contrast, some other models, which worked well predicting ambient environmental conditions, were unable to predict the changes under different climate change treatments. Based on the component model, the relative proportions of heterotrophic respiration (Rh) in the total soil respiration at different treatments varied from 0.33 to 0.85. There is a significant increase in the proportion of Rh under the elevated atmospheric CO2 concentration in comparison ambient conditions. The dry treatment resulted in higher proportion of Rh at elevated CO2 and ambient T than under elevated CO2 and elevated T. Also, the ratios between root growth and root maintenance respiration varied across different treatments. Neither increased temperature nor elevated atmospheric CO2 changed Q10 values significantly, while the average Q10 value at wet sites was significantly higher than it at dry sites. There was a higher possibility of increased soil respiration under drying relative to wetting conditions across all treatments based on monthly data, indicating that soil respiration may also be related to soil moisture at previous time periods. Our results reveal that the extent, time delay and contribution of different source components need to be included into mechanistic/processes-based soil respiration models at corresponding scale.« less

Extending the soil moisture record of the climate reference network with machine learning

USDA-ARS?s Scientific Manuscript database

Soil moisture estimation is crucial for agricultural decision-support and a key component of hydrological and climatic research. Unfortunately, quality-controlled soil moisture time series data are uncommon before the most recent decade. However, time series data for precipitation are accessible at ...

CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2015-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

A critical appraisal of allometric growth among alpine cirques based on multivariate statistics and spatial analysis

NASA Astrophysics Data System (ADS)

Delmas, Magali; Gunnell, Yanni; Calvet, Marc

2015-01-01

When considering the morphometric attributes of a glacial cirque, imbalances between length, width, and amplitude have been deemed relevant tools for discriminating between two possible pathways of cirque growth: downwearing by glaciers or backwearing by freeze-thaw processes. Based on a sample of 1071 cirques in the French Pyrenees, we reframe the concern for climatic variables by also granting systematic consideration to cirque lithology. Insight into the factors that control cirque shape is gained from Principal Component Analysis, where maps of eigenvalues assigned to six classes of bedrock display spatial patterns of cirque form as a function of position along the regional climatic gradient. Among crystalline rocks (granite, gneiss, migmatite), cirque form is predominantly determined by climatic controls. This is highlighted in the contrast between the elevated core of the Pleistocene icefield, where cirque isometry prevails, and the more peripheral areas (external sierras of the Atlantic precipitation zone and high sierras of the drier Mediterranean zone) where the lighter imprint of glaciation on the landscape has failed to erase (through glacial deepening) the allometric signature of pre-Pleistocene topographic features such as shallow valley heads and etch-basins. As a result, wide and shallow cirques occur in these settings. Among schist outcrops, in contrast, cirque form appears randomly distributed, suggesting that bedrock characteristics (e.g., structure) rather than climate are the key controls on cirque growth patterns. Given the importance of geological structure and preglacial topographic inheritance, cirques are complex landforms for which assumptions of allometric growth may be spurious. It follows that form is not always a reliable guide to process.

C-LAMP Subproject Description:Climate Forcing by the Terrestrial Biosphere During the Second Half of the 20th Century

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

Covey, Curt; Hoffman, Forrest

2008-10-02

This project will quantify selected components of climate forcing due to changes in the terrestrial biosphere over the period 1948-2004, as simulated by the climate / carboncycle models participating in C-LAMP (the Carbon-Land Model Intercomparison Project; see http://www.climatemodeling.org/c-lamp). Unlike other C-LAMP projects that attempt to close the carbon budget, this project will focus on the contributions of individual biomes in terms of the resulting climate forcing. Bala et al. (2007) used a similar (though more comprehensive) model-based technique to assess and compare different components of biospheric climate forcing, but their focus was on potential future deforestation rather than the historicalmore » period.« less

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

DOE PAGES

Theurich, Gerhard; DeLuca, C.; Campbell, T.; ...

2016-08-22

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open-source terms or to credentialed users. Furthermore, the ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the United States. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC)more » Layer, a set of ESMF-based component templates and interoperability conventions. Our shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multiagency development of coupled modeling systems; controlled experimentation and testing; and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NAVGEM), the Hybrid Coordinate Ocean Model (HYCOM), and the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model.« less

The Earth System Prediction Suite: Toward a Coordinated U.S. Modeling Capability

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

Theurich, Gerhard; DeLuca, C.; Campbell, T.

The Earth System Prediction Suite (ESPS) is a collection of flagship U.S. weather and climate models and model components that are being instrumented to conform to interoperability conventions, documented to follow metadata standards, and made available either under open-source terms or to credentialed users. Furthermore, the ESPS represents a culmination of efforts to create a common Earth system model architecture, and the advent of increasingly coordinated model development activities in the United States. ESPS component interfaces are based on the Earth System Modeling Framework (ESMF), community-developed software for building and coupling models, and the National Unified Operational Prediction Capability (NUOPC)more » Layer, a set of ESMF-based component templates and interoperability conventions. Our shared infrastructure simplifies the process of model coupling by guaranteeing that components conform to a set of technical and semantic behaviors. The ESPS encourages distributed, multiagency development of coupled modeling systems; controlled experimentation and testing; and exploration of novel model configurations, such as those motivated by research involving managed and interactive ensembles. ESPS codes include the Navy Global Environmental Model (NAVGEM), the Hybrid Coordinate Ocean Model (HYCOM), and the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS); the NOAA Environmental Modeling System (NEMS) and the Modular Ocean Model (MOM); the Community Earth System Model (CESM); and the NASA ModelE climate model and the Goddard Earth Observing System Model, version 5 (GEOS-5), atmospheric general circulation model.« less

A GUI Based Software for Sizing Stand Alone AC Coupled Hybrid PV-Diesel Power System under Malaysia Climate

NASA Astrophysics Data System (ADS)

Syafiqah Syahirah Mohamed, Nor; Amalina Banu Mohamat Adek, Noor; Hamid, Nurul Farhana Abd

2018-03-01

This paper presents the development of Graphical User Interface (GUI) software for sizing main component in AC coupled photovoltaic (PV) hybrid power system based on Malaysia climate. This software provides guideline for PV system integrator to design effectively the size of components and system configuration to match the system and load requirement with geographical condition. The concept of the proposed software is balancing the annual average renewable energy generation and load demand. In this study, the PV to diesel generator (DG) ratio is introduced by considering the hybrid system energy contribution. The GUI software is able to size the main components in the PV hybrid system to meet with the set target of energy contribution ratio. The rated powers of the components to be defined are PV array, grid-tie inverter, bi-directional inverter, battery storage and DG. GUI is used to perform all the system sizing procedures to make it user friendly interface as a sizing tool for AC coupled PV hybrid system. The GUI will be done by using Visual Studio 2015 based on the real data under Malaysia Climate.

Controls on winter ecosystem respiration in temperate and boreal ecosystems

Treesearch

T. Wang; P. Ciais; S.L. Piao; C. Ottle; P. Brender; F. Maignan; A. Arain; A. Cescatti; D. Gianelle; C. Gough; L Gu; P. Lafleur; T. Laurila; B. Marcolla; H. Margolis; L. Montagnani; E. Moors; N. Saigusa; T. Vesala; G. Wohlfahrt; C. Koven; A. Black; E. Dellwik; A. Don; D. Hollinger; A. Knohl; R. Monson; J. Munger; A. Suyker; A. Varlagin; S. Verma

2011-01-01

Winter CO2 fluxes represent an important component of the annual carbon budget in northern ecosystems. Understanding winter respiration processes and their responses to climate change is also central to our ability to assess terrestrial carbon cycle and climate feedbacks in the future. However, the factors influencing the spatial and temporal...

Fostering High-Quality Teaching with an Enriched Curriculum and Professional Development Support: The Head Start REDI Program

PubMed Central

Domitrovich, Celene E.; Gest, Scott D.; Gill, Sukhdeep; Bierman, Karen L.; Welsh, Janet; Jones, Damon

2017-01-01

This randomized controlled trial tested whether teaching quality in Head Start classrooms could be improved with the addition of evidence-based curriculum components targeting emergent language/literacy and social-emotional development and the provision of associated professional development support. Participants were lead and assistant teachers in 44 Head Start classrooms. Teachers received 4 days of workshop training along with weekly in-class support from a mentor teacher. End-of-year observations indicated that, compared to the control group, intervention teachers talked with children more frequently and in more cognitively complex ways, established a more positive classroom climate, and used more preventive behavior management strategies. Results supported the conclusion that enriched curriculum components and professional development support can produce improvements in multiple domains of teaching quality. PMID:29081534

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

AgMIP Climate Data and Scenarios for Integrated Assessment. Chapter 3

NASA Technical Reports Server (NTRS)

Ruane, Alexander C.; Winter, Jonathan M.; McDermid, Sonali P.; Hudson, Nicholas I.

2015-01-01

Climate change presents a great challenge to the agricultural sector as changes in precipitation, temperature, humidity, and circulation patterns alter the climatic conditions upon which many agricultural systems rely. Projections of future climate conditions are inherently uncertain owing to a lack of clarity on how society will develop, policies that may be implemented to reduce greenhouse-gas (GHG) emissions, and complexities in modeling the atmosphere, ocean, land, cryosphere, and biosphere components of the climate system. Global climate models (GCMs) are based on well-established physics of each climate component that enable the models to project climate responses to changing GHG concentration scenarios (Stocker et al., 2013).The most recent iteration of the Coupled Model Intercomparison Project (CMIP5; Taylor et al., 2012) utilized representative concentration pathways (RCPs) to cover the range of plausible GHG concentrations out past the year 2100, with RCP8.5 representing an extreme scenario and RCP4.5 representing a lower concentrations scenario (Moss et al., 2010).

Climate Risk Management and Decision Support Tools for the Agriculture Sector in Lao PDR, Bangladesh, and Indonesia

NASA Astrophysics Data System (ADS)

Allis, E. C.; Greene, A. M.; Cousin, R.

2014-12-01

We describe a comprehensive project for developing climate information and decision support / climate risk management tools in Lao PDR, Bangladesh and Indonesia. Mechanisms are developed for bringing the benefits of these tools to both policy makers and poor rural farmers, with the goal of enabling better management, at the farm level, of the risks associated with climate variability and change. The project comprises several interwoven threads, differentially applied in the different study regions. These include data management and quality control, development of seasonal forecast capabilities, use of dynamic cropping calendars and climate advisories, the development of longer-term climate information for both past and future and a weather index insurance component. Stakeholder engagement and capacity building served as reinforcing and complementary elements to all components. In this talk we will provide a project overview, show how the various components fit together and describe some lessons learned in this attempt to promote the uptake of actionable climate information from farmer to policy level. The applied research project was led by the International Research Institute for Climate and Society (IRI) at Columbia University with funding from the International Fund for Agriculture Development (IFAD) and in close collaboration with our regional partners at the Centre for Climate Risk and Opportunity Management in Southeast Asia Pacific (at Bogor Agricultural University in Indonesia), Indonesia's National Agency for Meteorology, Climatology and Geophysics (BMKG), Lao PDR's National Agriculture and Forestry Research Institute (NAFRI), Laotian Department of Meteorology and Hydrology (DMH), WorldFish Center, Bangladesh Meteorology Department (BMD), and CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS).

ICLUS v1.3 Population Projections

EPA Pesticide Factsheets

Climate and land-use change are major components of global environmental change with feedbacks between these components. The consequences of these interactions show that land use may exacerbate or alleviate climate change effects. Based on these findings it is important to use land-use scenarios that are consistent with the specific assumptions underlying climate-change scenarios. The Integrated Climate and Land-Use Scenarios (ICLUS) project developed land-use outputs that are based on a downscaled version of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines. ICLUS outputs are derived from a pair of models. A demographic model generates county-level population estimates that are distributed by a spatial allocation model (SERGoM v3) as housing density across the landscape. Land-use outputs were developed for the four main SRES storylines and a baseline (base case). The model is run for the conterminous USA and output is available for each scenario by decade to 2100. In addition to housing density at a 1 hectare spatial resolution, this project also generated estimates of impervious surface at a resolution of 1 square kilometer. This shapefile holds population data for all counties of the conterminous USA for all decades (2010-2100) and SRES population growth scenarios (A1, A2, B1, B2), as well as a 'base case' (BC) scenario, for use in the Integrated Climate and Land Use

The software architecture of climate models: a graphical comparison of CMIP5 and EMICAR5 configurations

NASA Astrophysics Data System (ADS)

Alexander, K.; Easterbrook, S. M.

2015-01-01

We analyse the source code of eight coupled climate models, selected from those that participated in the CMIP5 (Taylor et al., 2012) or EMICAR5 (Eby et al., 2013; Zickfeld et al., 2013) intercomparison projects. For each model, we sort the preprocessed code into components and subcomponents based on dependency structure. We then create software architecture diagrams which show the relative sizes of these components/subcomponents and the flow of data between them. The diagrams also illustrate several major classes of climate model design; the distribution of complexity between components, which depends on historical development paths as well as the conscious goals of each institution; and the sharing of components between different modelling groups. These diagrams offer insights into the similarities and differences between models, and have the potential to be useful tools for communication between scientists, scientific institutions, and the public.

Climate change and future wildfire in the western USA: what model projections do and don't tell us

NASA Astrophysics Data System (ADS)

Littell, J. S.; McKenzie, D.; Cushman, S. A.; Wan, H. Y.

2017-12-01

We developed statistical climate-fire models describing area burned for 70 ecosections in the western U.S. Historically, these ecosections collectively represent a gradient of climate-fire relationships from purely fuel limited (characterized by antecedent positive water balance anomalies and/or negative energy balance anomalies) to purely flammability limited (characterized by antecedent negative water balance anomalies and/or positive energy balance anomalies). Sixty-eight ecosection linear models included significant climate predictors, and 56 ecosections satisfied regression diagnostics, yielding acceptable climate-fire models. There is considerable diversity in seasonality, dominant variables, and prevalence of lagged climatic terms in the climate-fire regression models, indicating variation in mechanisms of climate-fire linkages across ecosystems. This diversity, however, is not random - there is a clear pattern in the fuzzy set membership of the relative dominance of regression predictor variables. This pattern defines a fuel-flammability gradient of limitations, with a tendency toward warm season drought on the flammability end and a tendency toward antecedent moisture on the fuel end. Projected area burned under a multi-model composite future climate scenarios varies, with increasing area burned in 41 ecosections in the West by 2030-2059 (median 132% among 10 purely flammability limited ecosections, median 240% among 25 flammability limited systems with a fuel limitation component, and median 43% among 6 systems with equal control) but decreasing (median -119% among 13 fuel limited systems with a flammability component). For the period 2070-2099, the projected area burned increases much more in the flammability (769%) and flammability-fuel hybrid (442%) systems than those with joint control (139%), and continues to decrease (-178%) in fuel-flammability hybrid systems. Filtering the projected results with fire rotation limits projections biased high by the static assumptions of the statistical models. Exceedence probabilities for 95th%ile fire years increases for the 2040s and 2080s and are largest in exclusively flammability limited ecosections compared with other fuel controls.

Climate and Human Pressure Constraints Co-Explain Regional Plant Invasion at Different Spatial Scales

PubMed Central

García-Baquero, Gonzalo; Caño, Lidia; Biurrun, Idoia; García-Mijangos, Itziar; Loidi, Javier; Herrera, Mercedes

2016-01-01

Alien species invasion represents a global threat to biodiversity and ecosystems. Explaining invasion patterns in terms of environmental constraints will help us to assess invasion risks and plan control strategies. We aim to identify plant invasion patterns in the Basque Country (Spain), and to determine the effects of climate and human pressure on that pattern. We modeled the regional distribution of 89 invasive plant species using two approaches. First, distance-based Moran’s eigenvector maps were used to partition variation in the invasive species richness, S, into spatial components at broad and fine scales; redundancy analysis was then used to explain those components on the basis of climate and human pressure descriptors. Second, we used generalized additive mixed modeling to fit species-specific responses to the same descriptors. Climate and human pressure descriptors have different effects on S at different spatial scales. Broad-scale spatially structured temperature and precipitation, and fine-scale spatially structured human population density and percentage of natural and semi-natural areas, explained altogether 38.7% of the total variance. The distribution of 84% of the individually tested species was related to either temperature, precipitation or both, and 68% was related to either population density or natural and semi-natural areas, displaying similar responses. The spatial pattern of the invasive species richness is strongly environmentally forced, mainly by climate factors. Since individual species responses were proved to be both similarly constrained in shape and explained variance by the same environmental factors, we conclude that the pattern of invasive species richness results from individual species’ environmental preferences. PMID:27741276

A Modified Formula of the First-order Approximation for Assessing the Contribution of Climate Change to Runoff Based on the Budyko Hypothesis

NASA Astrophysics Data System (ADS)

Liu, W.; Ning, T.; Han, X.

2015-12-01

The climate elasticity based on the Budyko curves has been widely used to evaluate the hydrological responses to climate change. The Mezentsev-Choudhury-Yang formula is one of the representative analytical equations for Budyko curves. Previous researches mostly used the variation of runoff (R) caused by the changes of annual precipitation (P) and potential evapotranspiration (ET0) as the hydrological response to climate change and evaluated it by a first-order approximation in a form of total differential, the major components of which include the partial derivatives of R to P and ET0, as well as climate elasticity on this basis. Based on analytic derivation and the characteristics of Budyko curves, this study proposed a modified formula of the first-order approximation to reduce the errors from the approximation. In the calculation of partial derivatives and climate elasticity, the values of P and ET0 were taken to the sum of their base values and half increments, respectively. The calculation was applied in 33 catchments of the Hai River basin in China and the results showed that the mean absolute value of relative error of approximated runoff change decreased from 8.4% to 0.4% and the maximum value, from 23.4% to 1.3%. Given the variation values of P, ET0 and the controlling parameter (n), the modified formula can exactly quantify the contributions of climate fluctuation and underlying surface change to runoff. Taking the Murray-Darling basin in Australia as an example of the contribution calculated by the modified formula, the reductions of mean annual runoff caused by changes of P, ET0 and n from 1895-1996 to 1997-2006 were 2.6, 0.6 and 2.9 mm, respectively, and the sum of them was 6.1 mm, which was completely consistent with the observed runoff. The modified formula of the first-order approximation proposed in this study can be not only used to assess the contributions of climate change to the runoff, but also widely used to analyze the effects of similar issues based on a certain functional relationship in hydrological and climate changes.

Climate change risk analysis framework (CCRAF) a probabilistic tool for analyzing climate change uncertainties

NASA Astrophysics Data System (ADS)

Legget, J.; Pepper, W.; Sankovski, A.; Smith, J.; Tol, R.; Wigley, T.

2003-04-01

Potential risks of human-induced climate change are subject to a three-fold uncertainty associated with: the extent of future anthropogenic and natural GHG emissions; global and regional climatic responses to emissions; and impacts of climatic changes on economies and the biosphere. Long-term analyses are also subject to uncertainty regarding how humans will respond to actual or perceived changes, through adaptation or mitigation efforts. Explicitly addressing these uncertainties is a high priority in the scientific and policy communities Probabilistic modeling is gaining momentum as a technique to quantify uncertainties explicitly and use decision analysis techniques that take advantage of improved risk information. The Climate Change Risk Assessment Framework (CCRAF) presented here a new integrative tool that combines the probabilistic approaches developed in population, energy and economic sciences with empirical data and probabilistic results of climate and impact models. The main CCRAF objective is to assess global climate change as a risk management challenge and to provide insights regarding robust policies that address the risks, by mitigating greenhouse gas emissions and by adapting to climate change consequences. The CCRAF endogenously simulates to 2100 or beyond annual region-specific changes in population; GDP; primary (by fuel) and final energy (by type) use; a wide set of associated GHG emissions; GHG concentrations; global temperature change and sea level rise; economic, health, and biospheric impacts; costs of mitigation and adaptation measures and residual costs or benefits of climate change. Atmospheric and climate components of CCRAF are formulated based on the latest version of Wigley's and Raper's MAGICC model and impacts are simulated based on a modified version of Tol's FUND model. The CCRAF is based on series of log-linear equations with deterministic and random components and is implemented using a Monte-Carlo method with up to 5000 variants per set of fixed input parameters. The shape and coefficients of CCRAF equations are derived from regression analyses of historic data and expert assessments. There are two types of random components in CCRAF - one reflects a year-to-year fluctuations around the expected value of a given variable (e.g., standard error of the annual GDP growth) and another is fixed within each CCRAF variant and represents some essential constants within a "world" represented by that variant (e.g., the value of climate sensitivity). Both types of random components are drawn from pre-defined probability distributions functions developed based on historic data or expert assessments. Preliminary CCRAF results emphasize the relative importance of uncertainties associated with the conversion of GHG and particulate emissions into radiative forcing and quantifying climate change effects at the regional level. A separates analysis involves an "adaptive decision-making", which optimizes the expected future policy effects given the estimated probabilistic uncertainties. As uncertainty for some variables evolve over the time steps, the decisions also adapt. This modeling approach is feasible only with explicit modeling of uncertainties.

Deciphering the History of Martian Volatiles: A Multi-Component Space Exploration Program

NASA Astrophysics Data System (ADS)

Chassefiere, E.

2000-07-01

To characterize Mars climate evolution requires to trace back the history of volatile species, including water. Indeed, atmospheric gases control, through UV-visible absorption and IR radiative transfer, the thermal structure of the atmosphere, the surface temperature, and ultimately the global hydrological system, which is a major component of the present Earth climate system. The composition and mass of the atmosphere is controlled by physical/chemical processes acting as sources (outgassing) or sinks (atmospheric escape, surface weathering, physical trapping in the subsurface). The history of volatiles is influenced by inner planet processes, like core convection which may give rise to a planetary-scale magnetic field able to withhold the atmosphere from the solar wind, inhibiting escape, or mantle convection, through outgassing and recycling of gas by geochemical cycles. Conversely, atmosphere may possibly retroact on the inner planet dynamical regime, for example if large amounts of liquid water are maintained at the surface by greenhouse effect, which could favour specific tectonism styles (like plate tectonism). The history of volatiles may therefore be related, not only to climate, but also to the thermal history of the inner planet, through a complicated chain of causes and effects. It is an essential link for reconstructing the global evolution of the Mars system. Focusing on climate, it appears that, provided the present climate system is understood and modelled, it must be possible to extrapolate to the past, provided the way the atmosphere evolved is known, as well as solar emission fluxes controlling thermal structure and escape.

Stakeholder-based evaluation categories for regional climate services - a case study at the German Baltic Sea coast

NASA Astrophysics Data System (ADS)

Meinke, Insa

2017-08-01

In this study, categories, dimensions, and criteria for evaluating regional climate services are derived by a participatory approach with potential service users at the German Baltic Sea coast. The development is carried out within nine face-to-face interviews conducted with decision makers, working in climate sensitive sectors at the German Baltic Sea coast. Three main groups of categories were localized which seem to matter most to the considered stakeholders and which seem to be crucial evaluation categories for regional climate services: (1) credibility, (2) relevance, and (3) appropriateness. For each of these evaluation categories several dimensions emerged, indicating certain perspectives of stakeholder demands. When summarizing these evaluation categories and their dimensions, 13 evaluation criteria for regional climate services can be derived (see Table 1). The results show that stakeholders do mainly address components other than those found in the literature (e.g. inputs, process, outputs, outcomes, and impacts). This might indicate that an evaluation, following solely literature-based (non-participative) components, is not sufficient to localize deficiencies or efficiencies within a regional climate service, since it might lead to results which are not relevant for potential users.

Rivers and Floodplains as Key Components of Global Terrestrial Water Storage Variability

NASA Astrophysics Data System (ADS)

Getirana, Augusto; Kumar, Sujay; Girotto, Manuela; Rodell, Matthew

2017-10-01

This study quantifies the contribution of rivers and floodplains to terrestrial water storage (TWS) variability. We use state-of-the-art models to simulate land surface processes and river dynamics and to separate TWS into its main components. Based on a proposed impact index, we show that surface water storage (SWS) contributes 8% of TWS variability globally, but that contribution differs widely among climate zones. Changes in SWS are a principal component of TWS variability in the tropics, where major rivers flow over arid regions and at high latitudes. SWS accounts for 22-27% of TWS variability in both the Amazon and Nile Basins. Changes in SWS are negligible in the Western U.S., Northern Africa, Middle East, and central Asia. Based on comparisons with Gravity Recovery and Climate Experiment-based TWS, we conclude that accounting for SWS improves simulated TWS in most of South America, Africa, and Southern Asia, confirming that SWS is a key component of TWS variability.

Drivers of lignin composition in boreal forest organic soils across a climate gradient

NASA Astrophysics Data System (ADS)

Myers-Pigg, A.; Kaiser, K.; Benner, R. H.; Ziegler, S. E.

2017-12-01

Lignin diagenesis in soils, including the cumulative effects of degradation and leaching, increases with experimental warming, signifying a potentially important change relevant to soil organic matter accumulation and fate. However, decadal to centennial climatic effects including changes in precipitation, litterfall inputs, and understory sources, on lignin composition are poorly constrained. We examined the lignin content and composition, via cupric oxide oxidation (CuO), within the organic layers of podzolic soils under similar balsam fir forests across a latitudinal climate gradient in Atlantic Canada. By exploring variation in lignin by both soil depth and climate region, this study informs on the climate drivers of lignin stability within boreal forest soil. A two-way analysis of variance (ANOVA) revealed significant variations in common signatures of CuO by-products with depth and/or site, indicating source and/or diagenetic controllers. Importantly, none of these signatures, with the exception of p-hydroxyphenols, exhibited a site by depth interaction indicating a similar degree of diagenetic alternation with depth across climates. The site by depth interaction for p-hydroxyphenols is a result of greater moss input in the northernmost site. To better elucidate this climate-induced source variation on our interpretation of lignin diagenesis, a principle component (PCA) model was built using signatures varying by site (p<0.01). These signatures loaded uniquely with the percentage of wood, needles, and mosses within the L layer in each region. Site differences in this loading indicate that shifts in understory input is a major climate effect controlling lignin composition in these forest soils. A lignin diagenesis PCA model was built using (1) all non-moss related signatures identified in the first PCA model, and (2) scores for additional sites within each region, calculated from modeled lignin composition based on 13C-NMR spectra. The combined results indicate that the lignin diagenetic states among soils is similar, despite the large increase in soil C turnover with climate warming across this transect. Thus our results indicate that shifts in moss contribution, and not increased diagenesis, controls CuO by-products with climate change in these moist boreal forests.

Spatial patterns of simulated transpiration response to climate variability in a snow dominated mountain ecosystem

USGS Publications Warehouse

Christensen, L.; Tague, C.L.; Baron, Jill S.

2008-01-01

Transpiration is an important component of soil water storage and stream-flow and is linked with ecosystem productivity, species distribution, and ecosystem health. In mountain environments, complex topography creates heterogeneity in key controls on transpiration as well as logistical challenges for collecting representative measurements. In these settings, ecosystem models can be used to account for variation in space and time of the dominant controls on transpiration and provide estimates of transpiration patterns and their sensitivity to climate variability and change. The Regional Hydro-Ecological Simulation System (RHESSys) model was used to assess elevational differences in sensitivity of transpiration rates to the spatiotemporal variability of climate variables across the Upper Merced River watershed, Yosemite Valley, California, USA. At the basin scale, predicted annual transpiration was lowest in driest and wettest years, and greatest in moderate precipitation years (R2 = 0.32 and 0.29, based on polynomial regression of maximum snow depth and annual precipitation, respectively). At finer spatial scales, responsiveness of transpiration rates to climate differed along an elevational gradient. Low elevations (1200-1800 m) showed little interannual variation in transpiration due to topographically controlled high soil moistures along the river corridor. Annual conifer stand transpiration at intermediate elevations (1800-2150 m) responded more strongly to precipitation, resulting in a unimodal relationship between transpiration and precipitation where highest transpiration occurred during moderate precipitation levels, regardless of annual air temperatures. Higher elevations (2150-2600 m) maintained this trend, but air temperature sensitivities were greater. At these elevations, snowfall provides enough moisture for growth, and increased temperatures influenced transpiration. Transpiration at the highest elevations (2600-4000 m) showed strong sensitivity to air temperature, little sensitivity to precipitation. Model results suggest elevational differences in vegetation water use and sensitivity to climate were significant and will likely play a key role in controlling responses and vulnerability of Sierra Nevada ecosystems to climate change. Copyright ?? 2008 John Wiley & Sons, Ltd.

Temporal trend and climate factors of hemorrhagic fever with renal syndrome epidemic in Shenyang City, China

PubMed Central

2011-01-01

Background Hemorrhagic fever with renal syndrome (HFRS) is an important infectious disease caused by different species of hantaviruses. As a rodent-borne disease with a seasonal distribution, external environmental factors including climate factors may play a significant role in its transmission. The city of Shenyang is one of the most seriously endemic areas for HFRS. Here, we characterized the dynamic temporal trend of HFRS, and identified climate-related risk factors and their roles in HFRS transmission in Shenyang, China. Methods The annual and monthly cumulative numbers of HFRS cases from 2004 to 2009 were calculated and plotted to show the annual and seasonal fluctuation in Shenyang. Cross-correlation and autocorrelation analyses were performed to detect the lagged effect of climate factors on HFRS transmission and the autocorrelation of monthly HFRS cases. Principal component analysis was constructed by using climate data from 2004 to 2009 to extract principal components of climate factors to reduce co-linearity. The extracted principal components and autocorrelation terms of monthly HFRS cases were added into a multiple regression model called principal components regression model (PCR) to quantify the relationship between climate factors, autocorrelation terms and transmission of HFRS. The PCR model was compared to a general multiple regression model conducted only with climate factors as independent variables. Results A distinctly declining temporal trend of annual HFRS incidence was identified. HFRS cases were reported every month, and the two peak periods occurred in spring (March to May) and winter (November to January), during which, nearly 75% of the HFRS cases were reported. Three principal components were extracted with a cumulative contribution rate of 86.06%. Component 1 represented MinRH0, MT1, RH1, and MWV1; component 2 represented RH2, MaxT3, and MAP3; and component 3 represented MaxT2, MAP2, and MWV2. The PCR model was composed of three principal components and two autocorrelation terms. The association between HFRS epidemics and climate factors was better explained in the PCR model (F = 446.452, P < 0.001, adjusted R2 = 0.75) than in the general multiple regression model (F = 223.670, P < 0.000, adjusted R2 = 0.51). Conclusion The temporal distribution of HFRS in Shenyang varied in different years with a distinctly declining trend. The monthly trends of HFRS were significantly associated with local temperature, relative humidity, precipitation, air pressure, and wind velocity of the different previous months. The model conducted in this study will make HFRS surveillance simpler and the control of HFRS more targeted in Shenyang. PMID:22133347

Future Sulfur Dioxide Emissions

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

Smith, Steven J.; Pitcher, Hugh M.; Wigley, Tom M.

2005-12-01

The importance of sulfur dioxide emissions for climate change is now established, although substantial uncertainties remain. This paper presents projections for future sulfur dioxide emissions using the MiniCAM integrated assessment model. A new income-based parameterization for future sulfur dioxide emissions controls is developed based on purchasing power parity (PPP) income estimates and historical trends related to the implementation of sulfur emissions limitations. This parameterization is then used to produce sulfur dioxide emissions trajectories for the set of scenarios developed for the Special Report on Emission Scenarios (SRES). We use the SRES methodology to produce harmonized SRES scenarios using the latestmore » version of the MiniCAM model. The implications, and requirements, for IA modeling of sulfur dioxide emissions are discussed. We find that sulfur emissions eventually decline over the next century under a wide set of assumptions. These emission reductions result from a combination of emission controls, the adoption of advanced electric technologies, and a shift away from the direct end use of coal with increasing income levels. Only under a scenario where incomes in developing regions increase slowly do global emission levels remain at close to present levels over the next century. Under a climate policy that limits emissions of carbon dioxide, sulfur dioxide emissions fall in a relatively narrow range. In all cases, the relative climatic effect of sulfur dioxide emissions decreases dramatically to a point where sulfur dioxide is only a minor component of climate forcing by the end of the century. Ecological effects of sulfur dioxide, however, could be significant in some developing regions for many decades to come.« less

Climate change impact assessment on hydrology of a small watershed using semi-distributed model

NASA Astrophysics Data System (ADS)

Pandey, Brij Kishor; Gosain, A. K.; Paul, George; Khare, Deepak

2017-07-01

This study is an attempt to quantify the impact of climate change on the hydrology of Armur watershed in Godavari river basin, India. A GIS-based semi-distributed hydrological model, soil and water assessment tool (SWAT) has been employed to estimate the water balance components on the basis of unique combinations of slope, soil and land cover classes for the base line (1961-1990) and future climate scenarios (2071-2100). Sensitivity analysis of the model has been performed to identify the most critical parameters of the watershed. Average monthly calibration (1987-1994) and validation (1995-2000) have been performed using the observed discharge data. Coefficient of determination (R2), Nash-Sutcliffe efficiency (ENS) and root mean square error (RMSE) were used to evaluate the model performance. Calibrated SWAT setup has been used to evaluate the changes in water balance components of future projection over the study area. HadRM3, a regional climatic data, have been used as input of the hydrological model for climate change impact studies. In results, it was found that changes in average annual temperature (+3.25 °C), average annual rainfall (+28 %), evapotranspiration (28 %) and water yield (49 %) increased for GHG scenarios with respect to the base line scenario.

Design and control strategy for a hybrid green energy system for mobile telecommunication sites

NASA Astrophysics Data System (ADS)

Okundamiya, Michael S.; Emagbetere, Joy O.; Ogujor, Emmanuel A.

2014-07-01

The rising energy costs and carbon footprint of operating mobile telecommunication sites in the emerging world have increased research interests in green technology. The intermittent nature of most green energy sources creates the problem of designing the optimum configuration for a given location. This study presents the design analysis and control strategy for a cost effective and reliable operation of the hybrid green energy system (HGES) for GSM base transceiver station (BTS) sites in isolated regions. The design constrains the generation and distribution of power to reliably satisfy the energy demand while ensuring safe operation of the system. The overall process control applies the genetic algorithm-based technique for optimal techno-economic sizing of system's components. The process simulation utilized meteorological data for 3 locations (Abuja, Benin City and Sokoto) with varying climatic conditions in Nigeria. Simulation results presented for green GSM BTS sites are discussed and compared with existing approaches.

Synthesizing long-term sea level rise projections - the MAGICC sea level model v2.0

NASA Astrophysics Data System (ADS)

Nauels, Alexander; Meinshausen, Malte; Mengel, Matthias; Lorbacher, Katja; Wigley, Tom M. L.

2017-06-01

Sea level rise (SLR) is one of the major impacts of global warming; it will threaten coastal populations, infrastructure, and ecosystems around the globe in coming centuries. Well-constrained sea level projections are needed to estimate future losses from SLR and benefits of climate protection and adaptation. Process-based models that are designed to resolve the underlying physics of individual sea level drivers form the basis for state-of-the-art sea level projections. However, associated computational costs allow for only a small number of simulations based on selected scenarios that often vary for different sea level components. This approach does not sufficiently support sea level impact science and climate policy analysis, which require a sea level projection methodology that is flexible with regard to the climate scenario yet comprehensive and bound by the physical constraints provided by process-based models. To fill this gap, we present a sea level model that emulates global-mean long-term process-based model projections for all major sea level components. Thermal expansion estimates are calculated with the hemispheric upwelling-diffusion ocean component of the simple carbon-cycle climate model MAGICC, which has been updated and calibrated against CMIP5 ocean temperature profiles and thermal expansion data. Global glacier contributions are estimated based on a parameterization constrained by transient and equilibrium process-based projections. Sea level contribution estimates for Greenland and Antarctic ice sheets are derived from surface mass balance and solid ice discharge parameterizations reproducing current output from ice-sheet models. The land water storage component replicates recent hydrological modeling results. For 2100, we project 0.35 to 0.56 m (66 % range) total SLR based on the RCP2.6 scenario, 0.45 to 0.67 m for RCP4.5, 0.46 to 0.71 m for RCP6.0, and 0.65 to 0.97 m for RCP8.5. These projections lie within the range of the latest IPCC SLR estimates. SLR projections for 2300 yield median responses of 1.02 m for RCP2.6, 1.76 m for RCP4.5, 2.38 m for RCP6.0, and 4.73 m for RCP8.5. The MAGICC sea level model provides a flexible and efficient platform for the analysis of major scenario, model, and climate uncertainties underlying long-term SLR projections. It can be used as a tool to directly investigate the SLR implications of different mitigation pathways and may also serve as input for regional SLR assessments via component-wise sea level pattern scaling.

Rapid Characterization of Components in Bolbostemma paniculatum by UPLC/LTQ-Orbitrap MSn Analysis and Multivariate Statistical Analysis for Herb Discrimination.

PubMed

Zeng, Yanling; Lu, Yang; Chen, Zhao; Tan, Jiawei; Bai, Jie; Li, Pengyue; Wang, Zhixin; Du, Shouying

2018-05-11

Bolbostemma paniculatum is a traditional Chinese medicine (TCM) showed various therapeutic effects. Owing to its complex chemical composition, few investigations have acquired a comprehensive cognition for the chemical profiles of this herb and explicated the differences between samples collected from different places. In this study, a strategy based on UPLC tandem LTQ-Orbitrap MS n was established for characterizing chemical components of B. paniculatum . Through a systematic identification strategy, a total of 60 components in B. paniculatum were rapidly separated in 30 min and identified. Then based on peak intensities of all the characterized components, principle component analysis (PCA) and hierarchical cluster analysis (HCA) were employed to classify 18 batches of B. paniculatum into four groups, which were highly consistent with the four climate types of their original places. And five compounds were finally screened out as chemical markers to discriminate the internal quality of B. paniculatum . As the first study to systematically characterize the chemical components of B. paniculatum by UPLC-MS n , the above results could offer essential data for its pharmacological research. And the current strategy could provide useful reference for future investigations on discovery of important chemical constituents in TCM, as well as establishment of quality control and evaluation method.

Summarizing components of U.S. Department of the Interior vulnerability assessments to focus climate adaptation planning

USGS Publications Warehouse

Thompson, Laura M.; Staudinger, Michelle D.; Carter, Shawn L.

2015-09-29

A secretarial order identified climate adaptation as a critical performance objective for future management of U.S. Department of the Interior (DOI) lands and resources in response to global change. Vulnerability assessments can inform climate adaptation planning by providing insight into what natural resources are most at risk and why. Three components of vulnerability—exposure, sensitivity, and adaptive capacity—were defined by the Intergovernmental Panel on Climate Change (IPCC) as necessary for identifying climate adaptation strategies and actions. In 2011, the DOI requested all internal bureaus report ongoing or completed vulnerability assessments about a defined range of assessment targets or climate-related threats. Assessment targets were defined as freshwater resources, landscapes and wildlife habitat, native and cultural resources, and ocean health. Climate-related threats were defined as invasive species, wildfire risk, sea-level rise, and melting ice and permafrost. Four hundred and three projects were reported, but the original DOI survey did not specify that information be provided on exposure, sensitivity, and adaptive capacity collectively as part of the request, and it was unclear which projects adhered to the framework recommended by the IPCC. Therefore, the U.S. Geological Survey National Climate Change and Wildlife Science Center conducted a supplemental survey to determine how frequently each of the three vulnerability components was assessed. Information was categorized for 124 of the 403 reported projects (30.8 percent) based on the three vulnerability components, and it was discovered that exposure was the most common component assessed (87.9 percent), followed by sensitivity (68.5 percent) and adaptive capacity (33.1 percent). The majority of projects did not fully assess vulnerability; projects focused on landscapes/wildlife habitats and sea-level rise were among the minority that simultaneously addressed all three vulnerability components. To maintain consistency with the IPCC definition of vulnerability, DOI may want to focus initial climate adaptation planning only on the outcomes of studies that comprehensively address vulnerability as inclusive of exposure, sensitivity, and adaptive capacity. Although the present study results are preliminary and used an unstructured survey design, they illustrate the importance of a comprehensive and consistent vulnerability definition and of using information on vulnerability components in DOI surveys to ensure relevant data are used to identify adaptation options.

The Software Architecture of Global Climate Models

NASA Astrophysics Data System (ADS)

Alexander, K. A.; Easterbrook, S. M.

2011-12-01

It has become common to compare and contrast the output of multiple global climate models (GCMs), such as in the Climate Model Intercomparison Project Phase 5 (CMIP5). However, intercomparisons of the software architecture of GCMs are almost nonexistent. In this qualitative study of seven GCMs from Canada, the United States, and Europe, we attempt to fill this gap in research. We describe the various representations of the climate system as computer programs, and account for architectural differences between models. Most GCMs now practice component-based software engineering, where Earth system components (such as the atmosphere or land surface) are present as highly encapsulated sub-models. This architecture facilitates a mix-and-match approach to climate modelling that allows for convenient sharing of model components between institutions, but it also leads to difficulty when choosing where to draw the lines between systems that are not encapsulated in the real world, such as sea ice. We also examine different styles of couplers in GCMs, which manage interaction and data flow between components. Finally, we pay particular attention to the varying levels of complexity in GCMs, both between and within models. Many GCMs have some components that are significantly more complex than others, a phenomenon which can be explained by the respective institution's research goals as well as the origin of the model components. In conclusion, although some features of software architecture have been adopted by every GCM we examined, other features show a wide range of different design choices and strategies. These architectural differences may provide new insights into variability and spread between models.

10Be in late deglacial climate simulated by ECHAM5-HAM - Part 2: Isolating the solar signal from 10Be deposition

NASA Astrophysics Data System (ADS)

Heikkilä, U.; Shi, X.; Phipps, S. J.; Smith, A. M.

2013-10-01

This study investigates the effect of deglacial climate on the deposition of the solar proxy 10Be globally, and at two specific locations, the GRIP site at Summit, Central Greenland, and the Law Dome site in coastal Antarctica. The deglacial climate is represented by three 30 yr time slice simulations of 10 000 BP (years before present = 1950 CE), 11 000 BP and 12 000 BP, compared with a preindustrial control simulation. The model used is the ECHAM5-HAM atmospheric aerosol-climate model, driven with sea surface temperatures and sea ice cover simulated using the CSIRO Mk3L coupled climate system model. The focus is on isolating the 10Be production signal, driven by solar variability, from the weather or climate driven noise in the 10Be deposition flux during different stages of climate. The production signal varies on lower frequencies, dominated by the 11yr solar cycle within the 30 yr time scale of these experiments. The climatic noise is of higher frequencies. We first apply empirical orthogonal functions (EOF) analysis to global 10Be deposition on the annual scale and find that the first principal component, consisting of the spatial pattern of mean 10Be deposition and the temporally varying solar signal, explains 64% of the variability. The following principal components are closely related to those of precipitation. Then, we apply ensemble empirical decomposition (EEMD) analysis on the time series of 10Be deposition at GRIP and at Law Dome, which is an effective method for adaptively decomposing the time series into different frequency components. The low frequency components and the long term trend represent production and have reduced noise compared to the entire frequency spectrum of the deposition. The high frequency components represent climate driven noise related to the seasonal cycle of e.g. precipitation and are closely connected to high frequencies of precipitation. These results firstly show that the 10Be atmospheric production signal is preserved in the deposition flux to surface even during climates very different from today's both in global data and at two specific locations. Secondly, noise can be effectively reduced from 10Be deposition data by simply applying the EOF analysis in the case of a reasonably large number of available data sets, or by decomposing the individual data sets to filter out high-frequency fluctuations.

Evidence for Holocene centennial variability in sea ice cover based on IP25 biomarker reconstruction in the southern Kara Sea (Arctic Ocean)

NASA Astrophysics Data System (ADS)

Hörner, Tanja; Stein, Rüdiger; Fahl, Kirsten

2017-10-01

The Holocene is characterized by the late Holocene cooling trend as well as by internal short-term centennial fluctuations. Because Arctic sea ice acts as a significant component (amplifier) within the climate system, investigating its past long- and short-term variability and controlling processes is beneficial for future climate predictions. This study presents the first biomarker-based (IP25 and PIP25) sea ice reconstruction from the Kara Sea (core BP00-07/7), covering the last 8 ka. These biomarker proxies reflect conspicuous short-term sea ice variability during the last 6.5 ka that is identified unprecedentedly in the source region of Arctic sea ice by means of a direct sea ice indicator. Prominent peaks of extensive sea ice cover occurred at 3, 2, 1.3 and 0.3 ka. Spectral analysis of the IP25 record revealed 400- and 950-year cycles. These periodicities may be related to the Arctic/North Atlantic Oscillation, but probably also to internal climate system fluctuations. This demonstrates that sea ice belongs to a complex system that more likely depends on multiple internal forcing.

Evaluating social and ecological vulnerability of coral reef fisheries to climate change.

PubMed

Cinner, Joshua E; Huchery, Cindy; Darling, Emily S; Humphries, Austin T; Graham, Nicholas A J; Hicks, Christina C; Marshall, Nadine; McClanahan, Tim R

2013-01-01

There is an increasing need to evaluate the links between the social and ecological dimensions of human vulnerability to climate change. We use an empirical case study of 12 coastal communities and associated coral reefs in Kenya to assess and compare five key ecological and social components of the vulnerability of coastal social-ecological systems to temperature induced coral mortality [specifically: 1) environmental exposure; 2) ecological sensitivity; 3) ecological recovery potential; 4) social sensitivity; and 5) social adaptive capacity]. We examined whether ecological components of vulnerability varied between government operated no-take marine reserves, community-based reserves, and openly fished areas. Overall, fished sites were marginally more vulnerable than community-based and government marine reserves. Social sensitivity was indicated by the occupational composition of each community, including the importance of fishing relative to other occupations, as well as the susceptibility of different fishing gears to the effects of coral bleaching on target fish species. Key components of social adaptive capacity varied considerably between the communities. Together, these results show that different communities have relative strengths and weaknesses in terms of social-ecological vulnerability to climate change.

Targeting Classrooms' Emotional Climate and Preschoolers' Socioemotional Adjustment: Implementation of the Chicago School Readiness Project

PubMed Central

Li-Grining, Christine P.; Raver, C. Cybele; Jones-Lewis, Darlene; Madison-Boyd, Sybil; Lennon, Jaclyn

2015-01-01

Children living in low-income families are more likely to experience less self-regulation, greater behavior problems, and lower academic achievement than higher income children. To help prevent children's later socioemotional and academic difficulties, the Chicago School Readiness Project (CSRP) team implemented a clustered, randomized controlled trial (RCT) in early childhood programs with Head Start funding. Head Start sites were randomly assigned to receive CSRP services, which were offered as part of a multi-component, classroom-based mental health intervention. Here, we provide an overview of the CSRP model, its components, and a descriptive portrait of its implementation. In so doing, we address various aspects of the implementation of three of its components: 1) the training of teachers, 2) MHCs' coaching of teachers, and 3) teachers' behavior management of children. We conclude with a discussion of factors potentially related to the implementation of CSRP and directions for future research. PMID:25321641

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

NASA Astrophysics Data System (ADS)

Radhakrishnan, A.; Gupta, J.

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Decadal-timescale changes of the Atlantic overturning circulation and climate in a coupled climate model with a hybrid-coordinate ocean component

NASA Astrophysics Data System (ADS)

Persechino, A.; Marsh, R.; Sinha, B.; Megann, A. P.; Blaker, A. T.; New, A. L.

2012-08-01

A wide range of statistical tools is used to investigate the decadal variability of the Atlantic Meridional Overturning Circulation (AMOC) and associated key variables in a climate model (CHIME, Coupled Hadley-Isopycnic Model Experiment), which features a novel ocean component. CHIME is as similar as possible to the 3rd Hadley Centre Coupled Model (HadCM3) with the important exception that its ocean component is based on a hybrid vertical coordinate. Power spectral analysis reveals enhanced AMOC variability for periods in the range 15-30 years. Strong AMOC conditions are associated with: (1) a Sea Surface Temperature (SST) anomaly pattern reminiscent of the Atlantic Multi-decadal Oscillation (AMO) response, but associated with variations in a northern tropical-subtropical gradient; (2) a Surface Air Temperature anomaly pattern closely linked to SST; (3) a positive North Atlantic Oscillation (NAO)-like pattern; (4) a northward shift of the Intertropical Convergence Zone. The primary mode of AMOC variability is associated with decadal changes in the Labrador Sea and the Greenland Iceland Norwegian (GIN) Seas, in both cases linked to the tropical activity about 15 years earlier. These decadal changes are controlled by the low-frequency NAO that may be associated with a rapid atmospheric teleconnection from the tropics to the extratropics. Poleward advection of salinity anomalies in the mixed layer also leads to AMOC changes that are linked to processes in the Labrador Sea. A secondary mode of AMOC variability is associated with interannual changes in the Labrador and GIN Seas, through the impact of the NAO on local surface density.

Building Quantitative Hydrologic Storylines from Process-based Models for Managing Water Resources in the U.S. Under Climate-changed Futures

NASA Astrophysics Data System (ADS)

Arnold, J.; Gutmann, E. D.; Clark, M. P.; Nijssen, B.; Vano, J. A.; Addor, N.; Wood, A.; Newman, A. J.; Mizukami, N.; Brekke, L. D.; Rasmussen, R.; Mendoza, P. A.

2016-12-01

Climate change narratives for water-resource applications must represent the change signals contextualized by hydroclimatic process variability and uncertainty at multiple scales. Building narratives of plausible change includes assessing uncertainties across GCM structure, internal climate variability, climate downscaling methods, and hydrologic models. Work with this linked modeling chain has dealt mostly with GCM sampling directed separately to either model fidelity (does the model correctly reproduce the physical processes in the world?) or sensitivity (of different model responses to CO2 forcings) or diversity (of model type, structure, and complexity). This leaves unaddressed any interactions among those measures and with other components in the modeling chain used to identify water-resource vulnerabilities to specific climate threats. However, time-sensitive, real-world vulnerability studies typically cannot accommodate a full uncertainty ensemble across the whole modeling chain, so a gap has opened between current scientific knowledge and most routine applications for climate-changed hydrology. To close that gap, the US Army Corps of Engineers, the Bureau of Reclamation, and the National Center for Atmospheric Research are working on techniques to subsample uncertainties objectively across modeling chain components and to integrate results into quantitative hydrologic storylines of climate-changed futures. Importantly, these quantitative storylines are not drawn from a small sample of models or components. Rather, they stem from the more comprehensive characterization of the full uncertainty space for each component. Equally important from the perspective of water-resource practitioners, these quantitative hydrologic storylines are anchored in actual design and operations decisions potentially affected by climate change. This talk will describe part of our work characterizing variability and uncertainty across modeling chain components and their interactions using newly developed observational data, models and model outputs, and post-processing tools for making the resulting quantitative storylines most useful in practical hydrology applications.

Fire and ecosystem change in the Arctic across the Paleocene-Eocene Thermal Maximum

NASA Astrophysics Data System (ADS)

Denis, E. H.; Pedentchouk, N.; Schouten, S.; Pagani, M.; Freeman, K. H.

2016-12-01

Fire, an important component of ecosystems at a range of spatial and temporal scales, affects vegetation distribution, the carbon cycle, and climate. In turn, climate influences fuel composition (e.g., amount and type of vegetation), fuel availability (e.g., vegetation that can burn based on precipitation and temperature), and ignition sources (e.g., lightning). Climate studies predict increased wildfire activity in future decades, but mechanisms that control the relationship between climate and fire are complex. Reconstructing environmental conditions during past warming events (e.g., the Paleocene-Eocene Thermal Maximum (PETM)) will help elucidate climate-vegetation-fire relationships that are expressed over long durations (1,000 - 10,000 yrs). The abrupt global warming during the PETM dramatically altered vegetation and hydrologic patterns, and, possibly, fire occurrence. To investigate coincident changes in climate, vegetation, and fire occurrence, we studied biomarkers, including polycyclic aromatic hydrocarbons (PAHs), terpenoids, and alkanes from the PETM interval at IODP site 302 (the Lomonosov Ridge) in the Arctic Ocean. Both pollen and biomarker records indicate angiosperms abundance increased during the PETM relative to gymnosperms, reflecting a significant ecological shift to angiosperm-dominated vegetation. PAH abundances increased relative to plant biomarkers throughout the PETM, which suggests PAH production increased relative to plant productivity. Increased PAH production associated with the angiosperm vegetation shift indicates a greater prevalence of more fire-prone species. A time lag between increased moisture transport (based on published δD of n-alkanes data) to the Arctic and increased angiosperms and PAH production suggests wetter conditions, followed by increased air temperatures, favored angiosperms and combined to enhance fire occurrence.

Multi-timescale data assimilation for atmosphere–ocean state estimates

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

Steiger, Nathan; Hakim, Gregory

2016-06-24

Paleoclimate proxy data span seasonal to millennial timescales, and Earth's climate system has both high- and low-frequency components. Yet it is currently unclear how best to incorporate multiple timescales of proxy data into a single reconstruction framework and to also capture both high- and low-frequency components of reconstructed variables. Here we present a data assimilation approach that can explicitly incorporate proxy data at arbitrary timescales. The principal advantage of using such an approach is that it allows much more proxy data to inform a climate reconstruction, though there can be additional benefits. Through a series of offline data-assimilation-based pseudoproxy experiments,more » we find that atmosphere–ocean states are most skillfully reconstructed by incorporating proxies across multiple timescales compared to using proxies at short (annual) or long (~ decadal) timescales alone. Additionally, reconstructions that incorporate long-timescale pseudoproxies improve the low-frequency components of the reconstructions relative to using only high-resolution pseudoproxies. We argue that this is because time averaging high-resolution observations improves their covariance relationship with the slowly varying components of the coupled-climate system, which the data assimilation algorithm can exploit. These results are consistent across the climate models considered, despite the model variables having very different spectral characteristics. Furthermore, our results also suggest that it may be possible to reconstruct features of the oceanic meridional overturning circulation based on atmospheric surface temperature proxies, though here we find such reconstructions lack spectral power over a broad range of frequencies.« less

Storylines of socio-economic and climatic drivers for land use and their hydrological impacts in alpine catchments - the STELLA project example

NASA Astrophysics Data System (ADS)

Strasser, Ulrich; Formayer, Herbert; Förster, Kristian; Marke, Thomas; Meißl, Gertraud; Schermer, Markus; Stotten, Friederike; Themessl, Matthias

2016-04-01

Future land use in Alpine catchments is controlled by the evolution of socio-economy and climate. Estimates of their coupled development should hence fulfill the principles of plausibility (be convincing) and consistency (be unambiguous). In the project STELLA, coupled future climate and land use scenarios are used as input in a hydrological modelling exercise with the physically-based, distributed water balance model WaSiM. The aim of the project is to quantify the effects of these two framing components on the future water cycle. The test site for the simulations is the catchment of the Brixentaler Ache in Tyrol/Austria (47.5°N, 322 km2). The so-called „storylines" of future coupled climate and forest/land use management, policy, social cooperation, tourism and economy have jointly been developed in an inter- and transdisciplinary assessment with local actors. The climate background is given by simulations for the A1B (temperature conditions like today in Merano/Italy, 46.7°N) and RCP 8.5 (temperature conditions like today in Bologna/Italy, 44.5°N) emission scenarios. These two climate scenarios were combined with three potential socio-economic developments („local"/„glocal"/ „superglobal"), each in a positive and in a negative specification. From these twelve storylines of coupled climate/land use future, a set of four storylines was selected to be used in transient hydrological modelling experiments. Historical simulations of the water balance for the test site reveal the pattern of land use being the most prominent factor for the spatial distribution of its components. A new prototype for a snow-canopy interaction simulation module provides explicit rates of intercepted and sublimated snow from the trees and stems of the different forest stands in the catchment. This new canopy module will be used to model the coupled climate/land use future storylines for the Brixental. The aim is to quantify the effects of climate change and land use on the water balance and streamflow, both separately and in their respective combination.

Development of fine-leaved Festuca grass for forage and wildfire control in the Great Basin

USDA-ARS?s Scientific Manuscript database

Drought and heat tolerant fine-leaved fescue (Festuca ssp.) grasses have potential as components in rangeland greenstrips for wildfire control in semi-arid climates, although such grasses have not been evaluated under rangeland conditions. Therefore, 64 geographically diverse Festuca accessions of ...

PRMS-IV, the precipitation-runoff modeling system, version 4

USGS Publications Warehouse

Markstrom, Steven L.; Regan, R. Steve; Hay, Lauren E.; Viger, Roland J.; Webb, Richard M.; Payn, Robert A.; LaFontaine, Jacob H.

2015-01-01

Computer models that simulate the hydrologic cycle at a watershed scale facilitate assessment of variability in climate, biota, geology, and human activities on water availability and flow. This report describes an updated version of the Precipitation-Runoff Modeling System. The Precipitation-Runoff Modeling System is a deterministic, distributed-parameter, physical-process-based modeling system developed to evaluate the response of various combinations of climate and land use on streamflow and general watershed hydrology. Several new model components were developed, and all existing components were updated, to enhance performance and supportability. This report describes the history, application, concepts, organization, and mathematical formulation of the Precipitation-Runoff Modeling System and its model components. This updated version provides improvements in (1) system flexibility for integrated science, (2) verification of conservation of water during simulation, (3) methods for spatial distribution of climate boundary conditions, and (4) methods for simulation of soil-water flow and storage.

The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model

NASA Astrophysics Data System (ADS)

Baehr, J.; Fröhlich, K.; Botzet, M.; Domeisen, D. I. V.; Kornblueh, L.; Notz, D.; Piontek, R.; Pohlmann, H.; Tietsche, S.; Müller, W. A.

2015-05-01

A seasonal forecast system is presented, based on the global coupled climate model MPI-ESM as used for CMIP5 simulations. We describe the initialisation of the system and analyse its predictive skill for surface temperature. The presented system is initialised in the atmospheric, oceanic, and sea ice component of the model from reanalysis/observations with full field nudging in all three components. For the initialisation of the ensemble, bred vectors with a vertically varying norm are implemented in the ocean component to generate initial perturbations. In a set of ensemble hindcast simulations, starting each May and November between 1982 and 2010, we analyse the predictive skill. Bias-corrected ensemble forecasts for each start date reproduce the observed surface temperature anomalies at 2-4 months lead time, particularly in the tropics. Niño3.4 sea surface temperature anomalies show a small root-mean-square error and predictive skill up to 6 months. Away from the tropics, predictive skill is mostly limited to the ocean, and to regions which are strongly influenced by ENSO teleconnections. In summary, the presented seasonal prediction system based on a coupled climate model shows predictive skill for surface temperature at seasonal time scales comparable to other seasonal prediction systems using different underlying models and initialisation strategies. As the same model underlying our seasonal prediction system—with a different initialisation—is presently also used for decadal predictions, this is an important step towards seamless seasonal-to-decadal climate predictions.

Energy performance and savings potentials with skylights

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

Arasteh, D.; Johnson, R.; Selkowitz, S.

1984-12-01

This study systematically explores the energy effects of skylight systems in a prototypical office building module and examines the savings from daylighting. For specific climates, roof/skylight characteristics are identified that minimize total energy or peak electrical demand. Simplified techniques for energy performance calculation are also presented based on a multiple regression analysis of our data base so that one may easily evaluate daylighting's effects on total and component energy loads and electrical peaks. This provides additional insights into the influence of skylight parameters on energy consumption and electrical peaks. We use the DOE-2.1B energy analysis program with newly incorporated daylightingmore » algorithms to determine hourly, monthly, and annual impacts of daylighting strategies on electrical lighting consumption, cooling, heating, fan power, peak electrical demands, and total energy use. A data base of more than 2000 parametric simulations for 14 US climates has been generated. Parameters varied include skylight-to-roof ratio, shading coefficient, visible transmittance, skylight well light loss, electric lighting power density, roof heat transfer coefficient, and electric lighting control type. 14 references, 13 figures, 4 tables.« less

A missing piece of the puzzle in climate change hotspots: Near-surface turbulent interactions controlling ET-soil moisture coupling in semiarid areas

NASA Astrophysics Data System (ADS)

Haghighi, Erfan; Gianotti, Daniel J.; Rigden, Angela J.; Salvucci, Guido D.; Kirchner, James W.; Entekhabi, Dara

2017-04-01

Being located in the transitional zone between dry and wet climate areas, semiarid ecosystems (and their associated ecohydrological processes) play a critical role in controlling climate change and global warming. Land evapotranspiration (ET), which is a central process in the climate system and a nexus of the water, energy and carbon cycles, typically accounts for up to 95% of the water budget in semiarid areas. Thus, the manner in which ET is partitioned into soil evaporation and plant transpiration in these settings is of practical importance for water and carbon cycling and their feedbacks to the climate system. ET (and its partitioning) in these regions is primarily controlled by surface soil moisture which varies episodically under stochastic precipitation inputs. Important as the ET-soil moisture relationship is, it remains empirical, and physical mechanisms governing its nature and dynamics are underexplored. Thus, the objective of this study is twofold: (1) to provide observational evidence for the influence of surface cover conditions on ET-soil moisture coupling in semiarid regions using soil moisture data from NASA's SMAP satellite mission combined with independent observationally based ET estimates, and (2) to develop a relatively simple mechanistic modeling platform improving our physical understanding of interactions between micro and macroscale processes controlling ET and its partitioning in partially vegetated areas. To this end, we invoked concepts from recent progress in mechanistic modeling of turbulent energy flux exchange in bluff-rough regions, and developed a physically based ET model that explicitly accounts for how vegetation-induced turbulence in the near-surface region influences soil drying and thus ET rates and dynamics. Model predictions revealed nonlinearities in the strength of the ET-soil moisture relationship (i.e., ∂ET/∂θ) as vegetation cover fraction increases, accounted for by the nonlinearity of surface-cover-dependent turbulent interactions. We identified a (predictable) critical vegetation cover fraction (as a function of vegetation stature and environmental conditions) that yields the strongest ET-soil moisture relationship under prescribed atmospheric conditions. Overall, the results suggest that ∂ET/ ∂θ varies more widely in regions with tall-stature woody vegetation that experience higher rates of change in turbulence intensity as the cover fraction increases. Our results facilitate a mathematically tractable description of ∂ET/ ∂θ, which is a core component of models that seek to predict hydrology-climate feedback processes in a changing climate.

The Nevada NSF EPSCoR infrastructure for climate change science, education, and outreach project: highlights and progress on investigations of ecological change and water resources along elevational gradients

NASA Astrophysics Data System (ADS)

Saito, L.; Biondi, F.; Fenstermaker, L. F.; Arnone, J.; Devitt, D.; Riddle, B.; Young, M.

2010-12-01

In 2008, the Nevada System of Higher Education received a 5-year, $15 million grant from the National Science Foundation’s (NSF) Experimental Program to Stimulate Competitive Research (EPSCoR). The mission of the project is to create a statewide interdisciplinary program to stimulate transformative research, education, and outreach about the effects of regional climate change on ecosystem services (especially water resources), and support use of this knowledge by policy makers and stakeholders. The overarching question that this effort will address is: how will climate change affect water resources, disturbance regimes and linked ecosystem and human services? While the overall project includes cyberinfrastructure, policy, education and climate modeling, this presentation will focus on the ecological change and water resources components. The goals of these two components are: 1) improving understanding of processes controlling local- and basin-wide impacts of climate on species dynamics, disturbance regimes, and water recharge rates; 2) evaluating interactions between landscape-level processes and biophysical indicators; 3) evaluating interactions between surface and groundwater systems; 4) predicting changes in wildfire regime, primary productivity, and biodiversity (including invasive species); and 5) assessing how interactions between water and ecology will differ under climate change and/or climate variability scenarios. To achieve these goals, the two components will quantify present-day climate variability at multiple temporal and spatial scales, including at multiple elevations within Nevada’s Basin and Range ecosystem continuum. This presentation will discuss key elements for achieving these goals, including the establishment of instrumented transects spanning a range of elevations and vegetation zones in eastern and southern Nevada.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2015-06-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition, and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverages of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverages of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2016-01-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

A likelihood-based time series modeling approach for application in dendrochronology to examine the growth-climate relations and forest disturbance history

EPA Science Inventory

A time series intervention analysis (TSIA) of dendrochronological data to infer the tree growth-climate-disturbance relations and forest disturbance history is described. Maximum likelihood is used to estimate the parameters of a structural time series model with components for ...

Family climates: family factors specific to disturbed eating and bulimia nervosa.

PubMed

Laliberté, M; Boland, F J; Leichner, P

1999-09-01

More than a decade of research has characterized the families of individuals with bulimia and bulimia anorexia (Anorexia Nervosa, Binge/Purging Type) as less expressive, less cohesive, and experiencing more conflicts than normal control families. This two-part study investigated variables believed more directly related to disturbed eating and bulimia as contributing to a "family climate for eating disorders." In Study 1. a nonclinical sample of 324 women who had just left home for college and a sample of 121 mothers evaluated their families. Principal-components analyses revealed the same factor structure for both students and mothers, with Family Body Satisfaction, Family Social Appearance Orientation, and Family Achievement Emphasis loading together, representing the hypothesized family climate for eating disorders: the remaining variables loaded with the more traditional family process variables (conflict, cohesion, expressiveness), representing a more general family dysfunction. As predicted, the family climate for eating disorders factor score was a more powerful predictor of disturbed eating. Study 2 extended these findings into a clin ical population, examining whether the family climate for eating disorders variables would distinguish individuals with bulimia from both depressed and healthy controls. Groups of eating-disordered patients (n = 40) and depressed (n = 17) and healthy (n = 27) controls completed family measures. The eating-disordered group scored significantly higher on family climate variables than control groups. Family process variables distinguished clinical groups (depressed and eating disordered) from healthy controls, but not from one another. Controlling for depression removed group differences on family process variables, but family climate variables continued to distinguish the eating-disordered group from both control groups. Indications for further research are discussed.

Assessment of the impact of climate shifts on malaria transmission in the Sahel.

PubMed

Bomblies, Arne; Eltahir, Elfatih A B

2009-09-01

Climate affects malaria transmission through a complex network of causative pathways. We seek to evaluate the impact of hypothetical climate change scenarios on malaria transmission in the Sahel by using a novel mechanistic, high spatial- and temporal-resolution coupled hydrology and agent-based entomology model. The hydrology model component resolves individual precipitation events and individual breeding pools. The impact of future potential climate shifts on the representative Sahel village of Banizoumbou, Niger, is estimated by forcing the model of Banizoumbou environment with meteorological data from two locations along the north-south climatological gradient observed in the Sahel--both for warmer, drier scenarios from the north and cooler, wetter scenarios from the south. These shifts in climate represent hypothetical but historically realistic climate change scenarios. For Banizoumbou climatic conditions (latitude 13.54 N), a shift toward cooler, wetter conditions may dramatically increase mosquito abundance; however, our modeling results indicate that the increased malaria transmissibility is not simply proportional to the precipitation increase. The cooler, wetter conditions increase the length of the sporogonic cycle, dampening a large vectorial capacity increase otherwise brought about by increased mosquito survival and greater overall abundance. Furthermore, simulations varying rainfall event frequency demonstrate the importance of precipitation patterns, rather than simply average or time-integrated precipitation, as a controlling factor of these dynamics. Modeling results suggest that in addition to changes in temperature and total precipitation, changes in rainfall patterns are very important to predict changes in disease susceptibility resulting from climate shifts. The combined effect of these climate-shift-induced perturbations can be represented with the aid of a detailed mechanistic model.

Relative Linkages of Chlorophyll-a with the Hydroclimatic and Biogeochemical Variables across the Continental U.S. (CONUS)

NASA Astrophysics Data System (ADS)

Ahmed, M. H.; Abdul-Aziz, O. I.

2017-12-01

Chlorophyll-a (Chl-a) is a key indicator for stream water quality and ecological health. The characterization of interplay between Chl-a and its numerous hydroclimatic and biogeochemical drivers is complex, and often involves multicollinear datasets. A systematic data analytics methodology was employed to determine the relative linkages of stream Chl-a with its dynamic environmental drivers at 50 stream water quality monitoring stations across the continental U.S. Multivariate statistical techniques of principal component analysis (PCA) and factor analysis (FA), in concert with Pearson correlation analysis, were applied to evaluate interrelationships among hydroclimatic, biogeochemical, and biological variables. Power-law based partial least square regression (PLSR) models were developed with a bootstrap Monte Carlo procedure (1000 iterations) to reliably estimate the comparative linkages of Chl-a by resolving multicollinearity in the data matrices (Nash-Sutcliff efficiency = 0.50-87). The data analytics suggested four environmental regimes of stream Chl-a, as dominated by nutrient, climate, redox, and hydro-atmospheric contributions, respectively. Total phosphorous (TP) was the most dominant driver of stream Chl-a in the nutrient controlled regime. Water temperature demonstrated the strongest control of Chl-a in the climate-dominated regime. Furthermore, pH and stream flow were found to be the most important drivers of Chl-a in the redox and hydro-atmospheric component dominated regimes, respectively. The research led to a significant reduction of dimensionality in the large data matrices, providing quantitative and qualitative insights on the dynamics of stream Chl-a. The findings would be useful to manage stream water quality and ecosystem health in the continental U.S. and around the world under a changing climate and environment.

Projecting climate-driven increases in North American fire activity

NASA Astrophysics Data System (ADS)

Wang, D.; Morton, D. C.; Collatz, G. J.

2013-12-01

Climate regulates fire activity through controls on vegetation productivity (fuels), lightning ignitions, and conditions governing fire spread. In many regions of the world, human management also influences the timing, duration, and extent of fire activity. These coupled interactions between human and natural systems make fire a complex component of the Earth system. Satellite data provide valuable information on the spatial and temporal dynamics of recent fire activity, as active fires, burned area, and land cover information can be combined to separate wildfires from intentional burning for agriculture and forestry. Here, we combined satellite-derived burned area data with land cover and climate data to assess fire-climate relationships in North America between 2000-2012. We used the latest versions of the Global Fire Emissions Database (GFED) burned area product and Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate data to develop regional relationships between burned area and potential evaporation (PE), an integrated dryness metric. Logistic regression models were developed to link burned area with PE and individual climate variables during and preceding the fire season, and optimal models were selected based on Akaike Information Criterion (AIC). Overall, our model explained 85% of the variance in burned area since 2000 across North America. Fire-climate relationships from the era of satellite observations provide a blueprint for potential changes in fire activity under scenarios of climate change. We used that blueprint to evaluate potential changes in fire activity over the next 50 years based on twenty models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). All models suggest an increase of PE under low and high emissions scenarios (Representative Concentration Pathways (RCP) 4.5 and 8.5, respectively), with largest increases in projected burned area across the western US and central Canada. Overall, near-term climate projections point to pronounced changes in fire season length, total burned area, and the frequency of extreme events across North America by 2050.

Probabilistic Integrated Assessment of ``Dangerous'' Climate Change

NASA Astrophysics Data System (ADS)

Mastrandrea, Michael D.; Schneider, Stephen H.

2004-04-01

Climate policy decisions are being made despite layers of uncertainty. Such decisions directly influence the potential for ``dangerous anthropogenic interference with the climate system.'' We mapped a metric for this concept, based on Intergovernmental Panel on Climate Change assessment of climate impacts, onto probability distributions of future climate change produced from uncertainty in key parameters of the coupled social-natural system-climate sensitivity, climate damages, and discount rate. Analyses with a simple integrated assessment model found that, under midrange assumptions, endogenously calculated, optimal climate policy controls can reduce the probability of dangerous anthropogenic interference from ~45% under minimal controls to near zero.

A comprehensive data acquisition and management system for an ecosystem-scale peatland warming and elevated CO2 experiment

NASA Astrophysics Data System (ADS)

Krassovski, M. B.; Riggs, J. S.; Hook, L. A.; Nettles, W. R.; Hanson, P. J.; Boden, T. A.

2015-07-01

Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE Project (Spruce and Peatland Responses Under Climatic and Environmental Change, http://mnspruce.ornl.gov) is such an experiment funded by the Department of Energy's (DOE), Office of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, the cycling and release of CO2 and CH4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. To successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are: 1. Data acquisition and control system - set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components. 2. Data collection system - set of hardware and software to deliver data to a central depository for storage and further processing. 3. Data management plan - set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an efficient data system for managing high volume sources of in-situ observations in a remote, harsh environmental location. The approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data.

A comprehensive data acquisition and management system for an ecosystem-scale peatland warming and elevated CO2 experiment

NASA Astrophysics Data System (ADS)

Krassovski, M. B.; Riggs, J. S.; Hook, L. A.; Nettles, W. R.; Hanson, P. J.; Boden, T. A.

2015-11-01

Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE project (Spruce and Peatland Responses Under Climatic and Environmental Change, http://mnspruce.ornl.gov) is such an experiment funded by the Department of Energy's (DOE), Office of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, and the cycling and release of CO2 and CH4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. To successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are the following: 1. data acquisition and control system - set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components; 2. data collection system - set of hardware and software to deliver data to a central depository for storage and further processing; 3. data management plan - set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an efficient data system for managing high volume sources of in situ observations in a remote, harsh environmental location. The approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data.

ClimateSpark: An in-memory distributed computing framework for big climate data analytics

NASA Astrophysics Data System (ADS)

Hu, Fei; Yang, Chaowei; Schnase, John L.; Duffy, Daniel Q.; Xu, Mengchao; Bowen, Michael K.; Lee, Tsengdar; Song, Weiwei

2018-06-01

The unprecedented growth of climate data creates new opportunities for climate studies, and yet big climate data pose a grand challenge to climatologists to efficiently manage and analyze big data. The complexity of climate data content and analytical algorithms increases the difficulty of implementing algorithms on high performance computing systems. This paper proposes an in-memory, distributed computing framework, ClimateSpark, to facilitate complex big data analytics and time-consuming computational tasks. Chunking data structure improves parallel I/O efficiency, while a spatiotemporal index is built for the chunks to avoid unnecessary data reading and preprocessing. An integrated, multi-dimensional, array-based data model (ClimateRDD) and ETL operations are developed to address big climate data variety by integrating the processing components of the climate data lifecycle. ClimateSpark utilizes Spark SQL and Apache Zeppelin to develop a web portal to facilitate the interaction among climatologists, climate data, analytic operations and computing resources (e.g., using SQL query and Scala/Python notebook). Experimental results show that ClimateSpark conducts different spatiotemporal data queries/analytics with high efficiency and data locality. ClimateSpark is easily adaptable to other big multiple-dimensional, array-based datasets in various geoscience domains.

The Moving Target of Climate Mitigation: Examples from the Energy Sector in California

NASA Astrophysics Data System (ADS)

Tarroja, B.; AghaKouchak, A.; Forrest, K.; Chiang, F.; Samuelsen, S.

2016-12-01

In response to the concerns of climate change-induced impacts on human health, environmental integrity, and the secure operation of resource supply infrastructures, strategies to reduce greenhouse gas (GHG) emissions of major societal sectors have been in development. In the energy sector, these strategies are based in low carbon primary energy deployment, increased energy efficiency, and implementing complementary technologies for operational resilience. While these strategies are aimed at climate mitigation, a degree of climate change-induced impacts will occur by the time of their deployment, and many of these impacts can compromise the effectiveness of these climate mitigation strategies. In order to develop climate mitigation strategies that will achieve their GHG reduction and other goals, the impact that climate change-induced conditions can have on different components of climate mitigation strategies must be understood. This presentation will highlight three examples of how climate change-induced conditions affect components of climate mitigation strategies in California: through impacts on 1) hydropower generation, 2) renewable potential for geothermal and solar thermal resources to form part of the renewable resource portfolio, and 3) the magnitudes and shapes of the electric load demand that must be met sustainably. These studies are part of a larger, overarching project to understand how climate change impacts the energy system and how to develop a sustainable energy infrastructure that is resilient against these impacts.

Mechanical Description of the Mars Climate Sounder Instrument

NASA Technical Reports Server (NTRS)

Jau, Bruno M.

2008-01-01

This paper introduces the Mars Climate Sounder (MCS) Instrument of the Mars Reconnaissance Orbiter (MRO) spacecraft. The instrument scans the Martian atmosphere almost continuously to systematically acquire weather and climate observations over time. Its primary components are an optical bench that houses dual telescopes with a total of nine channels for visible and infrared sensing, and a two axis gimbal that provides pointing capabilities. Both rotating joints consist of an integrated actuator with a hybrid planetary/harmonic transmission and a twist cap section that enables the electrical wiring to pass through the rotating joint. Micro stepping is used to reduce spacecraft disturbance torques to acceptable levels while driving the stepper motors. To ensure survivability over its four year life span, suitable mechanical components, lubrication, and an active temperature control system were incorporated. Some life test results and lessons learned are provided to serve as design guidelines for actuator parts and flex cables.

Climate, Water and Renewable Energy in the Nordic Countries

NASA Astrophysics Data System (ADS)

Snorrason, A.; Jonsdottir, J. F.

2004-05-01

Climate and Energy (CE) is a new Nordic research project with funding from Nordic Energy Research (NEFP) and the Nordic energy sector. The project has the objective of a comprehensive assessment of the impact of climate variability and change on Nordic renewable energy resources including hydropower, wind power, bio-fuels and solar energy. This will include assessment of the power production of the hydropower dominated Nordic energy system and its sensitivity and vulnerability to climate change on both temporal and spatial scales; assessment of the impacts of extremes including floods, droughts, storms, seasonal patterns and variability. Within the CE project several thematic groups work on specific issues of climatic change and their impacts on renewable energy. A primary aim of the CE climate group is to supply a standard set of common scenarios of climate change in northern Europe and Greenland, based on recent global and regional climate change experiments. The snow and ice group has chosen glaciers from Greenland, Iceland, Norway and Sweden for an analysis of the response of glaciers to climate changes. Mass balance and dynamical changes, corresponding to the common scenario for climate changes, will be modelled and effects on glacier hydrology will be estimated. Preliminary work with dynamic modelling and climate scenarios shows a dramatic response of glacial runoff to increased temperature and precipitation. The statistical analysis group has reported on the status of time series analysis in the Nordic countries. The group has selected and quality controlled time series of stream flow to be included in the Nordic component of the database FRIEND. Also the group will collect information on time series for other variables and these series will be systematically analysed with respect to trend and other long-term changes. Preliminary work using multivariate analysis on stream flow and climate variables shows strong linkages with the long term atmospheric circulation in the North Atlantic. The hydrological modelling group has already reported on "Climate change impacts on water resources in the Nordic countries - State of the art and discussion of principles". The group will compare different approaches of transferring the climate change signal into hydrological models and discuss uncertainties in models and climate scenarios. Furthermore, comprehensive assessment and mapping of impact of climate change will be produced for the whole Nordic region based on the scenarios from the CE-climate group.

Relative Linkages of Stream Dissolved Oxygen with the Climatic, Hydrological, and Biogeochemical Drivers across the East Coast of U.S.A.

NASA Astrophysics Data System (ADS)

Abdul-Aziz, O. I.; Ahmed, S.

2017-12-01

Dissolved oxygen (DO) is a key indicator of stream water quality and ecosystem health. However, the temporal dynamics of stream DO is controlled by a multitude of interacting environmental drivers. The relative linkages of stream DO with the relevant environmental drivers were determined in this study across the U.S. East Coast by employing a systematic data analytics approach. The study analyzed temporal data for 51 water quality monitoring stations from USGS NWIS and EPA STORET databases. Principal component analysis and factor analysis, along with Pearson's correlation analysis, were applied to identify the interrelationships and unravel latent patterns among DO and the environmental drivers. Power law based partial least squares regression models with a bootstarp Monte-Carlo procedure (1000 iterations) were developed to reliably estimate the environmental linkages of DO by resolving multicollinearity. Based on the similarity of dominant drivers, the streams were categorized into three distinct environmental regimes. Stream DO in the northern part of temperate zone (e.g., northeast coast) had the strongest linkage with water temperature; suggesting an environmental regime with dominant climatic control. However, stream DO in the tropical zones (e.g., southeast Florida) was mostly driven by pH; indicating an environmental regime likely controlled by redox chemistry. Further, a transitional regime was found between the temperate and tropical zones, where stream DO was controlled by both water temperature and pH. The results suggested a strong effect of the climatic gradient (temperate to tropical) on stream DO along the East Coast. The identified environmental regimes and the regime-specific relative linkages provided new information on the dominant controls of coastal stream water quality dynamics. The findings would guide the planning and management of coastal stream water quality and ecosystem health across the U.S. East Coast and around the world.

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

Planning for climate change: the need for mechanistic systems-based approaches to study climate change impacts on diarrheal diseases

PubMed Central

Levy, Karen; Zimmerman, Julie; Elliott, Mark; Bartram, Jamie; Carlton, Elizabeth; Clasen, Thomas; Dillingham, Rebecca; Eisenberg, Joseph; Guerrant, Richard; Lantagne, Daniele; Mihelcic, James; Nelson, Kara

2016-01-01

Increased precipitation and temperature variability as well as extreme events related to climate change are predicted to affect the availability and quality of water globally. Already heavily burdened with diarrheal diseases due to poor access to water, sanitation and hygiene facilities, communities throughout the developing world lack the adaptive capacity to sufficiently respond to the additional adversity caused by climate change. Studies suggest that diarrhea rates are positively correlated with increased temperature, and show a complex relationship with precipitation. Although climate change will likely increase rates of diarrheal diseases on average, there is a poor mechanistic understanding of the underlying disease transmission processes and substantial uncertainty surrounding current estimates. This makes it difficult to recommend appropriate adaptation strategies. We review the relevant climate-related mechanisms behind transmission of diarrheal disease pathogens and argue that systems-based mechanistic approaches incorporating human, engineered and environmental components are urgently needed. We then review successful systems-based approaches used in other environmental health fields and detail one modeling framework to predict climate change impacts on diarrheal diseases and design adaptation strategies. PMID:26799810

An experimental detrending approach to attributing change of pan evaporation in comparison with the traditional partial differential method

NASA Astrophysics Data System (ADS)

Wang, Tingting; Sun, Fubao; Xia, Jun; Liu, Wenbin; Sang, Yanfang

2017-04-01

In predicting how droughts and hydrological cycles would change in a warming climate, change of atmospheric evaporative demand measured by pan evaporation (Epan) is one crucial element to be understood. Over the last decade, the derived partial differential (PD) form of the PenPan equation is a prevailing attribution approach to attributing changes to Epan worldwide. However, the independency among climatic variables required by the PD approach cannot be met using long term observations. Here we designed a series of numerical experiments to attribute changes of Epan over China by detrending each climatic variable, i.e., an experimental detrending approach, to address the inter-correlation among climate variables, and made comparison with the traditional PD method. The results show that the detrending approach is superior not only to a complicate system with multi-variables and mixing algorithm like aerodynamic component (Ep,A) and Epan, but also to a simple case like radiative component (Ep,R), when compared with traditional PD method. The major reason for this is the strong and significant inter-correlation of input meteorological forcing. Very similar and fine attributing results have been achieved based on detrending approach and PD method after eliminating the inter-correlation of input through a randomize approach. The contribution of Rh and Ta in net radiation and thus Ep,R, which has been overlooked based on the PD method but successfully detected by detrending approach, provides some explanation to the comparing results. We adopted the control run from the detrending approach and applied it to made adjustment of PD method. Much improvement has been made and thus proven this adjustment an effective way in attributing changes to Epan. Hence, the detrending approach and the adjusted PD method are well recommended in attributing changes in hydrological models to better understand and predict water and energy cycle.

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

PubMed

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

2017-01-01

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

An approach toward incorporation of global warming effects into Intensity-Duration-Frequency values

NASA Astrophysics Data System (ADS)

Kunkel, K.; Easterling, D. R.

2017-12-01

Rising global temperatures from increasing greenhouse gas concentrations will increase overall atmospheric water vapor concentrations. There is a high level of scientific confidence that this will increase the future intensity and frequency of extreme precipitation events, even in regions where overall precipitation may decrease. For control of runoff from extreme rainfall, infrastructure engineering utilizes design values of rainfall known as Intensity-Duration-Frequency (IDF) values. Use of the existing IDF values, which are based solely on historical climate records, is likely to lead to under-design of runoff control structures, and associated increased flood damages. However, future changes in IDF values are uncertain and probably regionally variable. Our paradigm is that changes in IDF values will result from changes in atmospheric capacity (water vapor concentrations) and opportunity (the number and intensity of heavy precipitation-producing storm systems). Relevant storm systems being investigated include extratropical cyclones and their associated fronts, tropical cyclones, and the North American Monsoon system. The overall approach involves developing IDF adjustment factors for changes in these components of the climate system. The adjustment factors have associated uncertainties, primarily from (1) uncertainties in the future pathway of greenhouse gas emissions and (2) variations among climate models in the sensitivity of the climate system to greenhouse gas concentration changes. In addition to meteorological considerations, the lifetime of projects designed using IDF values is an essential consideration because the IDF values may change substantially during that time. The initial results of this project will be discussed.

The cumulative effects of forest disturbance and climate variability on streamflow components in a large forest-dominated watershed

NASA Astrophysics Data System (ADS)

Li, Qiang; Wei, Xiaohua; Zhang, Mingfang; Liu, Wenfei; Giles-Hansen, Krysta; Wang, Yi

2018-02-01

Assessing how forest disturbance and climate variability affect streamflow components is critical for watershed management, ecosystem protection, and engineering design. Previous studies have mainly evaluated the effects of forest disturbance on total streamflow, rarely with attention given to its components (e.g., base flow and surface runoff), particularly in large watersheds (>1000 km2). In this study, the Upper Similkameen River watershed (1810 km2), an international watershed situated between Canada and the USA, was selected to examine how forest disturbance and climate variability interactively affect total streamflow, baseflow, and surface runoff. Baseflow was separated using a combination of the recursive digital filter method and conductivity mass balance method. Time series analysis and modified double mass curves were then employed to quantitatively separate the relative contributions of forest disturbance and climate variability to each streamflow component. Our results showed that average annual baseflow and baseflow index (baseflow/streamflow) were 113.3 ± 35.6 mm year-1 and 0.27 for 1954-2013, respectively. Forest disturbance increased annual streamflow, baseflow, and surface runoff of 27.7 ± 13.7 mm, 7.4 ± 3.6 mm, and 18.4 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 27.0 ± 23.0%, 29.2 ± 23.1%, and 25.7 ± 23.4%, respectively. In contrast, climate variability decreased them by 74.9 ± 13.7 mm, 17.9 ± 3.6 mm, and 53.3 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 73.0 ± 23.0%, 70.8 ± 23.1% and 73.1 ± 23.4%, respectively. Despite working in opposite ways, the impacts of climate variability on annual streamflow, baseflow, and surface runoff were of a much greater magnitude than forest disturbance impacts. This study has important implications for the protection of aquatic habitat, engineering design, and watershed planning in the context of future forest disturbance and climate change.

10Be in late deglacial climate simulated by ECHAM5-HAM - Part 2: Isolating the solar signal from 10Be deposition

NASA Astrophysics Data System (ADS)

Heikkilä, U.; Shi, X.; Phipps, S. J.; Smith, A. M.

2014-04-01

This study investigates the effect of deglacial climate on the deposition of the solar proxy 10Be globally, and at two specific locations, the GRIP site at Summit, Central Greenland, and the Law Dome site in coastal Antarctica. The deglacial climate is represented by three 30 year time slice simulations of 10 000 BP (years before present = 1950 CE), 11 000 and 12 000 BP, compared with a preindustrial control simulation. The model used is the ECHAM5-HAM atmospheric aerosol-climate model, driven with sea-surface temperatures and sea ice cover simulated using the CSIRO Mk3L coupled climate system model. The focus is on isolating the 10Be production signal, driven by solar variability, from the weather- or climate-driven noise in the 10Be deposition flux during different stages of climate. The production signal varies at lower frequencies, dominated by the 11 year solar cycle within the 30 year timescale of these experiments. The climatic noise is of higher frequencies than 11 years during the 30 year period studied. We first apply empirical orthogonal function (EOF) analysis to global 10Be deposition on the annual scale and find that the first principal component, consisting of the spatial pattern of mean 10Be deposition and the temporally varying solar signal, explains 64% of the variability. The following principal components are closely related to those of precipitation. Then, we apply ensemble empirical decomposition (EEMD) analysis to the time series of 10Be deposition at GRIP and at Law Dome, which is an effective method for adaptively decomposing the time series into different frequency components. The low-frequency components and the long-term trend represent production and have reduced noise compared to the entire frequency spectrum of the deposition. The high-frequency components represent climate-driven noise related to the seasonal cycle of e.g. precipitation and are closely connected to high frequencies of precipitation. These results firstly show that the 10Be atmospheric production signal is preserved in the deposition flux to surface even during climates very different from today's both in global data and at two specific locations. Secondly, noise can be effectively reduced from 10Be deposition data by simply applying the EOF analysis in the case of a reasonably large number of available data sets, or by decomposing the individual data sets to filter out high-frequency fluctuations.

Evaluating Social and Ecological Vulnerability of Coral Reef Fisheries to Climate Change

PubMed Central

Cinner, Joshua E.; Huchery, Cindy; Darling, Emily S.; Humphries, Austin T.; Graham, Nicholas A. J.; Hicks, Christina C.; Marshall, Nadine; McClanahan, Tim R.

2013-01-01

There is an increasing need to evaluate the links between the social and ecological dimensions of human vulnerability to climate change. We use an empirical case study of 12 coastal communities and associated coral reefs in Kenya to assess and compare five key ecological and social components of the vulnerability of coastal social-ecological systems to temperature induced coral mortality [specifically: 1) environmental exposure; 2) ecological sensitivity; 3) ecological recovery potential; 4) social sensitivity; and 5) social adaptive capacity]. We examined whether ecological components of vulnerability varied between government operated no-take marine reserves, community-based reserves, and openly fished areas. Overall, fished sites were marginally more vulnerable than community-based and government marine reserves. Social sensitivity was indicated by the occupational composition of each community, including the importance of fishing relative to other occupations, as well as the susceptibility of different fishing gears to the effects of coral bleaching on target fish species. Key components of social adaptive capacity varied considerably between the communities. Together, these results show that different communities have relative strengths and weaknesses in terms of social-ecological vulnerability to climate change. PMID:24040228

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.

Safety climate in the US federal wildland fire management community: influences of organizational, environmental, group, and individual characteristics

Treesearch

Anne E. Black; Brooke Baldauf McBride

2013-01-01

This study examined the effects of organisational, environmental, group and individual characteristics on five components of safety climate (High Reliability Organising Practices, Leadership, Group Culture, Learning Orientation and Mission Clarity) in the US federal wildland fire management community. Of particular interest were differences between perceptions based on...

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

USGS Publications Warehouse

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

2007-01-01

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

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

PubMed

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

2016-01-01

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

Bias and robustness of uncertainty components estimates in transient climate projections

NASA Astrophysics Data System (ADS)

Hingray, Benoit; Blanchet, Juliette; Jean-Philippe, Vidal

2016-04-01

A critical issue in climate change studies is the estimation of uncertainties in projections along with the contribution of the different uncertainty sources, including scenario uncertainty, the different components of model uncertainty and internal variability. Quantifying the different uncertainty sources faces actually different problems. For instance and for the sake of simplicity, an estimate of model uncertainty is classically obtained from the empirical variance of the climate responses obtained for the different modeling chains. These estimates are however biased. Another difficulty arises from the limited number of members that are classically available for most modeling chains. In this case, the climate response of one given chain and the effect of its internal variability may be actually difficult if not impossible to separate. The estimate of scenario uncertainty, model uncertainty and internal variability components are thus likely to be not really robust. We explore the importance of the bias and the robustness of the estimates for two classical Analysis of Variance (ANOVA) approaches: a Single Time approach (STANOVA), based on the only data available for the considered projection lead time and a time series based approach (QEANOVA), which assumes quasi-ergodicity of climate outputs over the whole available climate simulation period (Hingray and Saïd, 2014). We explore both issues for a simple but classical configuration where uncertainties in projections are composed of two single sources: model uncertainty and internal climate variability. The bias in model uncertainty estimates is explored from theoretical expressions of unbiased estimators developed for both ANOVA approaches. The robustness of uncertainty estimates is explored for multiple synthetic ensembles of time series projections generated with MonteCarlo simulations. For both ANOVA approaches, when the empirical variance of climate responses is used to estimate model uncertainty, the bias is always positive. It can be especially high with STANOVA. In the most critical configurations, when the number of members available for each modeling chain is small (< 3) and when internal variability explains most of total uncertainty variance (75% or more), the overestimation is higher than 100% of the true model uncertainty variance. The bias can be considerably reduced with a time series ANOVA approach, owing to the multiple time steps accounted for. The longer the transient time period used for the analysis, the larger the reduction. When a quasi-ergodic ANOVA approach is applied to decadal data for the whole 1980-2100 period, the bias is reduced by a factor 2.5 to 20 depending on the projection lead time. In all cases, the bias is likely to be not negligible for a large number of climate impact studies resulting in a likely large overestimation of the contribution of model uncertainty to total variance. For both approaches, the robustness of all uncertainty estimates is higher when more members are available, when internal variability is smaller and/or the response-to-uncertainty ratio is higher. QEANOVA estimates are much more robust than STANOVA ones: QEANOVA simulated confidence intervals are roughly 3 to 5 times smaller than STANOVA ones. Excepted for STANOVA when less than 3 members is available, the robustness is rather high for total uncertainty and moderate for internal variability estimates. For model uncertainty or response-to-uncertainty ratio estimates, the robustness is conversely low for QEANOVA to very low for STANOVA. In the most critical configurations (small number of member, large internal variability), large over- or underestimation of uncertainty components is very thus likely. To propose relevant uncertainty analyses and avoid misleading interpretations, estimates of uncertainty components should be therefore bias corrected and ideally come with estimates of their robustness. This work is part of the COMPLEX Project (European Collaborative Project FP7-ENV-2012 number: 308601; http://www.complex.ac.uk/). Hingray, B., Saïd, M., 2014. Partitioning internal variability and model uncertainty components in a multimodel multireplicate ensemble of climate projections. J.Climate. doi:10.1175/JCLI-D-13-00629.1 Hingray, B., Blanchet, J. (revision) Unbiased estimators for uncertainty components in transient climate projections. J. Climate Hingray, B., Blanchet, J., Vidal, J.P. (revision) Robustness of uncertainty components estimates in climate projections. J.Climate

Millennial-scale climate variability during the Last Glacial period in the tropical Andes

NASA Astrophysics Data System (ADS)

Fritz, S. C.; Baker, P. A.; Ekdahl, E.; Seltzer, G. O.; Stevens, L. R.

2010-04-01

Millennial-scale climate variation during the Last Glacial period is evident in many locations worldwide, but it is unclear if such variation occurred in the interior of tropical South America, and, if so, how the low-latitude variation was related to its high-latitude counterpart. A high-resolution record, derived from the deep drilling of sediments on the floor of Lake Titicaca in the southern tropical Andes, is presented that shows clear evidence of millennial-scale climate variation between ˜60 and 20 ka BP. This variation is manifested by alternations of two interbedded sedimentary units. The two units have distinctive sedimentary, geochemical, and paleobiotic properties that are controlled by the relative abundance of terrigenous or nearshore components versus pelagic components. The sediments of more terrigenous or nearshore nature likely were deposited during regionally wetter climates when river transport of water and sediment was higher, whereas the sediments of more pelagic character were deposited during somewhat drier climates regionally. The majority of the wet periods inferred from the Lake Titicaca sediment record are correlated with the cold events in the Greenland ice cores and North Atlantic sediment cores, indicating that increased intensity of the South American summer monsoon was part of near-global scale climate excursions.

Linking models of human behaviour and climate alters projected climate change

DOE PAGES

Beckage, Brian; Gross, Louis J.; Lacasse, Katherine; ...

2018-01-01

Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4–6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with themore » largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Lastly, our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.« less

Linking models of human behaviour and climate alters projected climate change

NASA Astrophysics Data System (ADS)

Beckage, Brian; Gross, Louis J.; Lacasse, Katherine; Carr, Eric; Metcalf, Sara S.; Winter, Jonathan M.; Howe, Peter D.; Fefferman, Nina; Franck, Travis; Zia, Asim; Kinzig, Ann; Hoffman, Forrest M.

2018-01-01

Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4-6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with the largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.

Linking models of human behaviour and climate alters projected climate change

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

Beckage, Brian; Gross, Louis J.; Lacasse, Katherine

Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4–6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with themore » largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Lastly, our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.« less

Regional climates in the GISS general circulation model: Surface air temperature

NASA Technical Reports Server (NTRS)

Hewitson, Bruce

1994-01-01

One of the more viable research techniques into global climate change for the purpose of understanding the consequent environmental impacts is based on the use of general circulation models (GCMs). However, GCMs are currently unable to reliably predict the regional climate change resulting from global warming, and it is at the regional scale that predictions are required for understanding human and environmental responses. Regional climates in the extratropics are in large part governed by the synoptic-scale circulation and the feasibility of using this interscale relationship is explored to provide a way of moving to grid cell and sub-grid cell scales in the model. The relationships between the daily circulation systems and surface air temperature for points across the continental United States are first developed in a quantitative form using a multivariate index based on principal components analysis (PCA) of the surface circulation. These relationships are then validated by predicting daily temperature using observed circulation and comparing the predicted values with the observed temperatures. The relationships predict surface temperature accurately over the major portion of the country in winter, and for half the country in summer. These relationships are then applied to the surface synoptic circulation of the Goddard Institute for Space Studies (GISS) GCM control run, and a set of surface grid cell temperatures are generated. These temperatures, based on the larger-scale validated circulation, may now be used with greater confidence at the regional scale. The generated temperatures are compared to those of the model and show that the model has regional errors of up to 10 C in individual grid cells.

The changing strength and nature of fire-climate relationships in the northern Rocky Mountains, U.S.A., 1902-2008

USGS Publications Warehouse

Littell, Jeremy

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008

PubMed Central

Higuera, Philip E.; Abatzoglou, John T.; Littell, Jeremy S.; Morgan, Penelope

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity. PMID:26114580

The Changing Strength and Nature of Fire-Climate Relationships in the Northern Rocky Mountains, U.S.A., 1902-2008.

PubMed

Higuera, Philip E; Abatzoglou, John T; Littell, Jeremy S; Morgan, Penelope

2015-01-01

Time-varying fire-climate relationships may represent an important component of fire-regime variability, relevant for understanding the controls of fire and projecting fire activity under global-change scenarios. We used time-varying statistical models to evaluate if and how fire-climate relationships varied from 1902-2008, in one of the most flammable forested regions of the western U.S.A. Fire-danger and water-balance metrics yielded the best combination of calibration accuracy and predictive skill in modeling annual area burned. The strength of fire-climate relationships varied markedly at multi-decadal scales, with models explaining < 40% to 88% of the variation in annual area burned. The early 20th century (1902-1942) and the most recent two decades (1985-2008) exhibited strong fire-climate relationships, with weaker relationships for much of the mid 20th century (1943-1984), coincident with diminished burning, less fire-conducive climate, and the initiation of modern fire fighting. Area burned and the strength of fire-climate relationships increased sharply in the mid 1980s, associated with increased temperatures and longer potential fire seasons. Unlike decades with high burning in the early 20th century, models developed using fire-climate relationships from recent decades overpredicted area burned when applied to earlier periods. This amplified response of fire to climate is a signature of altered fire-climate-relationships, and it implicates non-climatic factors in this recent shift. Changes in fuel structure and availability following 40+ yr of unusually low fire activity, and possibly land use, may have resulted in increased fire vulnerability beyond expectations from climatic factors alone. Our results highlight the potential for non-climatic factors to alter fire-climate relationships, and the need to account for such dynamics, through adaptable statistical or processes-based models, for accurately predicting future fire activity.

Climate Variability and Wildfires: Insights from Global Earth System Models

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

[Effects of soil, climate, and their interaction on some neutral volatile aroma components in flue-cured tobacco leaves from high quality tobacco planting regions of Hunan Province].

PubMed

Deng, Xiao-Hua; Xie, Peng-Fei; Peng, Xin-Hui; Yi, Jian-Hua; Zhou, Ji-Heng; Zhou, Qing-Ming; Pu, Wen-Xuan; Dai, Yuan-Gang

2010-08-01

A pot experiment with the soils from Yongzhou, Liuyang, and Sangzhi, the high-quality tobacco planting regions of Hunan Province, was conducted to study the effects of climate, soil, and their interaction on some neutral volatile aroma components in flue-cured tobacco leaves. The contents of test neutral volatile aroma components in the flue-cured tobacco leaves were of medium variation, and the variation intensity was decreased in the order of dihydroactinolide, damascenone, furfural, total megastigmatrienone, and beta-ionone. Climate, soil, and their interaction affected the neutral volatile aroma components in different degrees. The furfural content was most affected by climate, the damascenone content was most affected by climate and by soil, the total megastigmatrienone and beta-ionone contents were most affected by the interaction of soil and climate, while the dihydroactinolide content was less affected by soil, climate, and their interaction. The contribution of climate, soil, and their interaction to the contents of the five aroma components was 40.82%, 20.67%, and 38.51%, respectively. During different growth periods of tobacco, different climate factors had different effects on the neutral volatile aroma components. The rainfall, cloudiness, and mean air temperature at rooting stage, the diurnal temperature amplitude, sunshine time, and evaporation at vigorous growth stage, and the rainfall, evaporation, and mean air temperature at maturing stage were the top three climate factors affecting the contents of the neutral volatile aroma components in flue-tobacco leaves. For the soil factors, the available potassium, available phosphorus, and pH were the top three factors affecting the contents of the five components.

Climate Change Concepts and POGIL: Using climate change to teach general chemistry

NASA Astrophysics Data System (ADS)

King, D. B.; Lewis, J. E.; Anderson, K.; Latch, D.; Sutheimer, S.; Webster, G.; Middlecamp, C.; Moog, R.

2013-12-01

Climate change is a topic that can be used to engage students in a variety of courses and disciplines. Through an NSF-funded project, we have written a set of in-class POGIL (Process Oriented Guided Inquiry Learning) activities that use climate change topics to teach general chemistry concepts. POGIL is a pedagogical approach that uses group activities to teach content and process skills. In these group activities an initial model and a series of critical thinking questions are used to guide students through the introduction to or application of course content. Students complete the activities on their own, with the faculty member as a facilitator of learning, rather than a provider of information. Through assigned group roles and intentionally designed activity structure, process skills, such as teamwork, communication, and information processing, are developed during completion of the activity. While POGIL activities were initially developed for chemistry courses, this approach has now been used to create materials for use in other fields, such as biology, math, engineering and computer science. An additional component of this project is the incorporation of questions that relate to socio-scientific issues, e.g., the economic and social effects of climate change policies. The goal is for students to use evidence-based arguments in situations where opinion-based arguments are common. Key components (i.e., models and the corresponding critical thinking questions) of one activity will be presented. We will also report preliminary feedback based on initial classroom testing of several of the activities.

Comparison of the timings between abrupt climate changes in Greenland, Antarctica, China and Japan based on robust correlation using Lake Suigetsu as a template.

NASA Astrophysics Data System (ADS)

Nakagawa, T.

2014-12-01

High-resolution pollen-derived climate records from Lake Suigetsu varved sediment core were compared with climate archives from other regions and revealed a particular spatio-temporal structure of the monsoon climate change during so-called D-O events. Leads and lags of the climate change between different regions hold the key to understand the climate system. However, robust assessment of the relative timing of the climate change is often very challenging because correlation of the climatic archives from different regions often has inevitable uncertainties. Greenland and Cariaco basin, for example, provide two of the most frequently sited palaeoclimatic proxy data representative of the high- and low-latitudinal Atlantic regions. However, robust correlation of the records from those regions is difficult because of the uncertainties in layer countings, lack of the radiocarbon age control from ice cores, marine reservoir age of the Cariaco sediments, and the absence of the tephra layers shared by both cites. Similarly, Speleothem and ice core records are not robustly correlated to each other, either for the dead carbon fraction in the speleothems and lack of reliable correlation markers. The generally accepted hypothesis of synchronous climate change between China and the Greenland is, therefore, essentially hypothetical. Lake Suigetsu provides solution to this problem. The lake Suigetsu chronology is supposed to be coherent to the speleothems' U-Th age scale. Suigetsu's semi-continuous radiocarbon dataset, which constitutes major component of the IntCal13 radiocarbon calibration model, also provides opportunity to correlate lake Suigetsu and the Greenland and Antarctic ice cores using cosmogenic isotopes as the correlation key. Results of the correlation and timing comparison, which cast new lights to the mechanism of the monsoon change, will be presented.

Climate fails to predict wood decomposition at regional scales

NASA Astrophysics Data System (ADS)

Bradford, Mark A.; Warren, Robert J., II; Baldrian, Petr; Crowther, Thomas W.; Maynard, Daniel S.; Oldfield, Emily E.; Wieder, William R.; Wood, Stephen A.; King, Joshua R.

2014-07-01

Decomposition of organic matter strongly influences ecosystem carbon storage. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on mean responses can be irrelevant and misleading. We test whether climate controls on the decomposition rate of dead wood--a carbon stock estimated to represent 73 +/- 6 Pg carbon globally--are sensitive to the spatial scale from which they are inferred. We show that the common assumption that climate is a predominant control on decomposition is supported only when local-scale variation is aggregated into mean values. Disaggregated data instead reveal that local-scale factors explain 73% of the variation in wood decomposition, and climate only 28%. Further, the temperature sensitivity of decomposition estimated from local versus mean analyses is 1.3-times greater. Fundamental issues with mean correlations were highlighted decades ago, yet mean climate-decomposition relationships are used to generate simulations that inform management and adaptation under environmental change. Our results suggest that to predict accurately how decomposition will respond to climate change, models must account for local-scale factors that control regional dynamics.

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

PubMed

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

2013-01-01

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

Phylogenetic patterns of climatic, habitat and trophic niches in a European avian assemblage

PubMed Central

Pearman, Peter B; Lavergne, Sébastien; Roquet, Cristina; Wüest, Rafael; Zimmermann, Niklaus E; Thuiller, Wilfried

2014-01-01

Aim The origins of ecological diversity in continental species assemblages have long intrigued biogeographers. We apply phylogenetic comparative analyses to disentangle the evolutionary patterns of ecological niches in an assemblage of European birds. We compare phylogenetic patterns in trophic, habitat and climatic niche components. Location Europe. Methods From polygon range maps and handbook data we inferred the realized climatic, habitat and trophic niches of 405 species of breeding birds in Europe. We fitted Pagel's lambda and kappa statistics, and conducted analyses of disparity through time to compare temporal patterns of ecological diversification on all niche axes together. All observed patterns were compared with expectations based on neutral (Brownian) models of niche divergence. Results In this assemblage, patterns of phylogenetic signal (lambda) suggest that related species resemble each other less in regard to their climatic and habitat niches than they do in their trophic niche. Kappa estimates show that ecological divergence does not gradually increase with divergence time, and that this punctualism is stronger in climatic niches than in habitat and trophic niches. Observed niche disparity markedly exceeds levels expected from a Brownian model of ecological diversification, thus providing no evidence for past phylogenetic niche conservatism in these multivariate niches. Levels of multivariate disparity are greatest for the climatic niche, followed by disparity of the habitat and the trophic niches. Main conclusions Phylogenetic patterns in the three niche components differ within this avian assemblage. Variation in evolutionary rates (degree of gradualism, constancy through the tree) and/or non-random macroecological sampling probably lead here to differences in the phylogenetic structure of niche components. Testing hypotheses on the origin of these patterns requires more complete phylogenetic trees of the birds, and extended ecological data on different niche components for all bird species. PMID:24790525

Seasonal fire danger forecasts for the USA

Treesearch

J. Roads; F. Fujioka; S. Chen; R. Burgan

2005-01-01

The Scripps Experimental Climate Prediction Center has been making experimental, near-real-time, weekly to seasonal fire danger forecasts for the past 5 years. US fire danger forecasts and validations are based on standard indices from the National Fire Danger Rating System (DFDRS), which include the ignition component (IC), energy release component (ER), burning...

A new multicriteria risk mapping approach based on a multiattribute frontier concept

Treesearch

Denys Yemshanov; Frank H. Koch; Yakov Ben-Haim; Marla Downing; Frank Sapio; Marty Siltanen

2013-01-01

Invasive species risk maps provide broad guidance on where to allocate resources for pest monitoring and regulation, but they often present individual risk components (such as climatic suitability, host abundance, or introduction potential) as independent entities. These independent risk components are integrated using various multicriteria analysis techniques that...

An Assessment of Vulnerability and Trade-offs of Dairy Farmers of India to Climate Variability and Change

NASA Astrophysics Data System (ADS)

Radhakrishnan, Aparna; Gupta, Jancy; Ravindran, Dileepkumar

2017-04-01

The study aims at assessing the vulnerability and tradeoffs of dairy based livelihoods to Climate Variability and Change (CVC) in the Western Ghats ecosystem, India. For this purpose; data were aggregated to an overall Livelihood Vulnerability Index (LVI) to CVC underlying the principles of IPCC, using 40 indicators under 7 LVI components. Fussel framework was used for the nomenclature of vulnerable situation and trade-off between vulnerability components and milk production was calculated. Data were collected through participatory rural appraisal and personal interviews from 360 randomly selected dairy farmers of nine blocks from three states of Western Ghat region, complemented by thirty years of gridded weather data and livestock data. The LVI score of dairy based livelihoods of six taluks were negative. The data were normalized and then combined into three indices of sensitivity, exposure and adaptive capacity, which were then averaged with weights given using principal component analysis, to obtain the overall vulnerability index. Mann Whitney U test was used to find the significant difference between the taluks in terms of LVI and cumulative square root frequency method was used to categorise the farmers. Even though the taluks are geographically closer, there is significant difference in the LVI values of the regions. Results indicated that the Lanja taluks of Maharashtra is the most vulnerable having an overall LVI value -4.17 with 48% farmers falling in highly vulnerable category. Panel regression analysis reveals that there is significant synergy between average milk production and livestock, social network component and trade-off between natural disasters climate variability component of LVI. Policies for incentivizing the 'climate risk adaptation' costs for small and marginal farmers and livelihood infrastructure for mitigating risks and promoting grass root level innovations are necessary to sustain dairy farming of the region. Thus the research will provide an important basis for policy makers to develop appropriate adaptation strategies for alarming situation and decision making for farmers to minimize the risk of dairy sector to climate variability.

Green roof impact on the hydrological cycle components

NASA Astrophysics Data System (ADS)

Lamera, Carlotta; Rulli, Maria Cristina; Becciu, Gianfranco; Rosso, Renzo

2013-04-01

In the last decades the importance of storm water management in urban areas has increased considerably, due to both urbanization extension and to a greater concern for environment pollution. Traditional storm water control practices, based on the "all to the sewer" attitude, rely on conveyance to route storm water runoff from urban impervious surfaces towards the nearby natural water bodies. In recent years, infiltration facilities are receiving an increasing attention, due to their particular efficiency in restoring a balance in hydrological cycle quite equal to quite pre-urbanization condition. In particular, such techniques are designed to capture, temporarily retain and infiltrate storm water, promote evapotranspiration and harvest water at the source, encouraging in general evaporation, evapotranspiration, groundwater recharge and the re-use of storm water. Green roofs are emerging as an increasingly popular Sustainable Urban Drainage Systems (SUDS) technique for urban storm water management. Indeed, they are able to operate hydrologic control over storm water runoff: they allow a significant reduction of peak flows and runoff volumes collected by drainage system, with a consequent reduction of flooding events and pollution masses discharges by CSO. Furthermore green roofs have a positive influence on the microclimate in urban areas by helping in lower urban air temperatures and mitigate the heat island effect. Last but not least, they have the advantage of improving the thermal insulation of buildings, with significant energy savings. A detailed analysis of the hydrological dynamics, connected both with the characteristics of the climatic context and with the green roof technical design, is essential in order to obtain a full characterization of the hydrologic behavior of a green roof system and its effects on the urban water cycle components. The purpose of this paper is to analysis the hydrological effects and urban benefits of the vegetation cover of a building by installing green roofs and, thus, providing a conversion of rooftops in pervious areas; the objective is modeling hydrological fluxes (interception, evapotranspiration, soil water fluxes in the surface and hypodermic components) in relation to climate forcing, basic technology components and geometric characteristics of green roof systems (thickness of the stratigraphy, soil layers and materials, vegetation typology and density). The sensitivity analysis of hydrological processes at different hydrological, climatic and geometric parameters has allowed to draw some general guidelines useful in the design and construction of this type of drainage systems.

Addressing Spatial Dependence Bias in Climate Model Simulations—An Independent Component Analysis Approach

NASA Astrophysics Data System (ADS)

Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish

2018-02-01

Conventional bias correction is usually applied on a grid-by-grid basis, meaning that the resulting corrections cannot address biases in the spatial distribution of climate variables. To solve this problem, a two-step bias correction method is proposed here to correct time series at multiple locations conjointly. The first step transforms the data to a set of statistically independent univariate time series, using a technique known as independent component analysis (ICA). The mutually independent signals can then be bias corrected as univariate time series and back-transformed to improve the representation of spatial dependence in the data. The spatially corrected data are then bias corrected at the grid scale in the second step. The method has been applied to two CMIP5 General Circulation Model simulations for six different climate regions of Australia for two climate variables—temperature and precipitation. The results demonstrate that the ICA-based technique leads to considerable improvements in temperature simulations with more modest improvements in precipitation. Overall, the method results in current climate simulations that have greater equivalency in space and time with observational data.

Earth system sensitivity inferred from Pliocene modelling and data

USGS Publications Warehouse

Lunt, D.J.; Haywood, A.M.; Schmidt, G.A.; Salzmann, U.; Valdes, P.J.; Dowsett, H.J.

2010-01-01

Quantifying the equilibrium response of global temperatures to an increase in atmospheric carbon dioxide concentrations is one of the cornerstones of climate research. Components of the Earths climate system that vary over long timescales, such as ice sheets and vegetation, could have an important effect on this temperature sensitivity, but have often been neglected. Here we use a coupled atmosphere-ocean general circulation model to simulate the climate of the mid-Pliocene warm period (about three million years ago), and analyse the forcings and feedbacks that contributed to the relatively warm temperatures. Furthermore, we compare our simulation with proxy records of mid-Pliocene sea surface temperature. Taking these lines of evidence together, we estimate that the response of the Earth system to elevated atmospheric carbon dioxide concentrations is 30-50% greater than the response based on those fast-adjusting components of the climate system that are used traditionally to estimate climate sensitivity. We conclude that targets for the long-term stabilization of atmospheric greenhouse-gas concentrations aimed at preventing a dangerous human interference with the climate system should take into account this higher sensitivity of the Earth system. ?? 2010 Macmillan Publishers Limited. All rights reserved.

Development of fine-leaved Festuca grass populations identified genetic resources having potential for improved forage production and wildfire control in the western United States

USDA-ARS?s Scientific Manuscript database

Drought and heat tolerant fine-leaved fescue (Festuca ssp.) grasses have potential as components in rangeland greenstrips for wildfire control in semi-arid climates. However, such fine-leaved grasses have been difficult to identify because of specific adaptations, lack of late maturity, and often p...

Planning for climate change: The need for mechanistic systems-based approaches to study climate change impacts on diarrheal diseases.

PubMed

Mellor, Jonathan E; Levy, Karen; Zimmerman, Julie; Elliott, Mark; Bartram, Jamie; Carlton, Elizabeth; Clasen, Thomas; Dillingham, Rebecca; Eisenberg, Joseph; Guerrant, Richard; Lantagne, Daniele; Mihelcic, James; Nelson, Kara

2016-04-01

Increased precipitation and temperature variability as well as extreme events related to climate change are predicted to affect the availability and quality of water globally. Already heavily burdened with diarrheal diseases due to poor access to water, sanitation and hygiene facilities, communities throughout the developing world lack the adaptive capacity to sufficiently respond to the additional adversity caused by climate change. Studies suggest that diarrhea rates are positively correlated with increased temperature, and show a complex relationship with precipitation. Although climate change will likely increase rates of diarrheal diseases on average, there is a poor mechanistic understanding of the underlying disease transmission processes and substantial uncertainty surrounding current estimates. This makes it difficult to recommend appropriate adaptation strategies. We review the relevant climate-related mechanisms behind transmission of diarrheal disease pathogens and argue that systems-based mechanistic approaches incorporating human, engineered and environmental components are urgently needed. We then review successful systems-based approaches used in other environmental health fields and detail one modeling framework to predict climate change impacts on diarrheal diseases and design adaptation strategies. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Quantifying the impacts of climatic trend and fluctuation on crop yields in northern China.

PubMed

Qiao, Jianmin; Yu, Deyong; Liu, Yupeng

2017-10-01

Climate change plays a critical role in crop yield variations, which has attracted a great deal of concern worldwide. However, the mechanisms of how climatic trend and fluctuations affect crop yields are not well understood and need to be further investigated. Thus, using the GIS-based Environmental Policy Integrated Climate (EPIC) model, we simulated the yields of major crops (i.e., wheat, maize, and rice) and evaluated the impacts of climatic factors on crop yields in the Agro-Pastoral Transitional Zone (APTZ) of northern China between 1980 and 2010. The partial least squares regression model was used to assess the contribution rates of climatic factors (i.e., precipitation, photosynthetically active radiation (PAR), minimum temperature (T min ), maximum temperature (T max )) to the variation of crop yields. The Breaks for Additive Season and Trend (BFAST) model was adopted to decompose the climate factors into trend and fluctuation components, and the relative contributions of climate trend and fluctuation were then evaluated. The results indicated that the contributions of climatic factors to yield variations of wheat, maize, and rice were 31.7, 37.7, and 23.1%, respectively. That is, climate change had larger impacts on maize than wheat and rice. More cultivated areas were significantly and positively correlated with precipitation than with other climatic factors due to the limited precipitation in the APTZ. Also, climatic trend component had positive impacts on crop yields in the whole region, whereas the climate fluctuation was associated mainly with the areas where the crop yields decreased. This study helps improve our understanding of the mechanisms of climate change impacts on crop yields, and provides useful scientific information for designing regional-scale strategies of adaptation to climate change.

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.

Adjustment of the thermal component of two tourism climatological assessment tools using thermal perception and preference surveys from Hungary

NASA Astrophysics Data System (ADS)

Kovács, Attila; Unger, János; Gál, Csilla V.; Kántor, Noémi

2016-07-01

This study introduces new methodological concepts for integrating seasonal subjective thermal assessment patterns of people into the thermal components of two tourism climatological evaluation tools: the Tourism Climatic Index (TCI) and the Climate-Tourism/Transfer-Information-Scheme (CTIS). In the case of the TCI, we replaced the air temperature and relative humidity as the basis of the initial rating system with the physiologically equivalent temperature (PET)—a complex human biometeorological index. This modification improves the TCI's potential to evaluate the thermal aspects of climate. The major accomplishments of this study are (a) the development of a new, PET-based rating system and its integration into the thermal sub-indices of the TCI and (b) the regionalization of the thermal components of CTIS to reflect both the thermal sensation and preference patterns of people. A 2-year-long (2011-2012) thermal comfort survey conducted in Szeged, Hungary, from spring to autumn was utilized to demonstrate the implementation of the introduced concepts. We found considerable differences between the thermal perception and preference patterns of Hungarians, with additional variations across the evaluated seasons. This paper describes the proposed methodology for the integration of the new seasonal, perception-based, and preference-based PET rating systems into the TCI, and presents the incorporation of new PET thresholds into the CTIS. In order to demonstrate the utility of the modified evaluation tools, we performed case study climate analyses for three Hungarian tourist destinations. The additional adjustments introduced during the course of those analyses include the reduction of TCI's temporal resolution to 10-day intervals and the exclusion of nocturnal and winter periods from the investigation.

Monitoring the performance of the next Climate Forecast System version 3, throughout its development stage at EMC/NCEP

NASA Astrophysics Data System (ADS)

Peña, M.; Saha, S.; Wu, X.; Wang, J.; Tripp, P.; Moorthi, S.; Bhattacharjee, P.

2016-12-01

The next version of the operational Climate Forecast System (version 3, CFSv3) will be a fully coupled six-components system with diverse applications to earth system modeling, including weather and climate predictions. This system will couple the earth's atmosphere, land, ocean, sea-ice, waves and aerosols for both data assimilation and modeling. It will also use the NOAA Environmental Modeling System (NEMS) software super structure to couple these components. The CFSv3 is part of the next Unified Global Coupled System (UGCS), which will unify the global prediction systems that are now operational at NCEP. The UGCS is being developed through the efforts of dedicated research and engineering teams and through coordination across many CPO/MAPP and NGGPS groups. During this development phase, the UGCS is being tested for seasonal purposes and undergoes frequent revisions. Each new revision is evaluated to quickly discover, isolate and solve problems that negatively impact its performance. In the UGCS-seasonal model, components (e.g., ocean, sea-ice, atmosphere, etc.) are coupled through a NEMS-based "mediator". In this numerical infrastructure, model diagnostics and forecast validation are carried out, both component by component, and as a whole. The next stage, model optimization, will require enhanced performance diagnostics tools to help prioritize areas of numerical improvements. After the technical development of the UGCS-seasonal is completed, it will become the first realization of the CFSv3. All future development of this system will be carried out by the climate team at NCEP, in scientific collaboration with the groups that developed the individual components, as well as the climate community. A unique challenge to evaluate this unified weather-climate system is the large number of variables, which evolve over a wide range of temporal and spatial scales. A small set of performance measures and scorecard displays are been created, and collaboration and software contributions from research and operational centers are being incorporated. A status of the CFSv3/UGCS-seasonal development and examples of its performance and measuring tools will be presented.

Coal and Coal/Biomass-Based Power Generation

EPA Science Inventory

For Frank Princiotta's book, Global Climate Change--The Technology Challenge Coal is a key, growing component in power generation globally. It generates 50% of U.S. electricity, and criteria emissions from coal-based power generation are being reduced. However, CO2 emissions m...

Secular trends and climate drift in coupled ocean-atmosphere general circulation models

NASA Astrophysics Data System (ADS)

Covey, Curt; Gleckler, Peter J.; Phillips, Thomas J.; Bader, David C.

2006-02-01

Coupled ocean-atmosphere general circulation models (coupled GCMs) with interactive sea ice are the primary tool for investigating possible future global warming and numerous other issues in climate science. A long-standing problem with such models is that when different components of the physical climate system are linked together, the simulated climate can drift away from observation unless constrained by ad hoc adjustments to interface fluxes. However, 11 modern coupled GCMs, including three that do not employ flux adjustments, behave much better in this respect than the older generation of models. Surface temperature trends in control run simulations (with external climate forcing such as solar brightness and atmospheric carbon dioxide held constant) are small compared with observed trends, which include 20th century climate change due to both anthropogenic and natural factors. Sea ice changes in the models are dominated by interannual variations. Deep ocean temperature and salinity trends are small enough for model control runs to extend over 1000 simulated years or more, but trends in some regions, most notably the Arctic, differ substantially among the models and may be problematic. Methods used to initialize coupled GCMs can mitigate climate drift but cannot eliminate it. Lengthy "spin-ups" of models, made possible by increasing computer power, are one reason for the improvements this paper documents.

Probabilistic Evaluation of Competing Climate Models

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Chatterjee, S.; Heyman, M.; Cressie, N.

2017-12-01

A standard paradigm for assessing the quality of climate model simulations is to compare what these models produce for past and present time periods, to observations of the past and present. Many of these comparisons are based on simple summary statistics called metrics. Here, we propose an alternative: evaluation of competing climate models through probabilities derived from tests of the hypothesis that climate-model-simulated and observed time sequences share common climate-scale signals. The probabilities are based on the behavior of summary statistics of climate model output and observational data, over ensembles of pseudo-realizations. These are obtained by partitioning the original time sequences into signal and noise components, and using a parametric bootstrap to create pseudo-realizations of the noise sequences. The statistics we choose come from working in the space of decorrelated and dimension-reduced wavelet coefficients. We compare monthly sequences of CMIP5 model output of average global near-surface temperature anomalies to similar sequences obtained from the well-known HadCRUT4 data set, as an illustration.

Analyses of historical and projected climates to support climate adaptation in the northern Rocky Mountains: Chapter 4

USGS Publications Warehouse

Gross, John E.; Tercek, Michael; Guay, Kevin; Chang, Tony; Talbert, Marian; Rodman, Ann; Thoma, David; Jantz, Patrick; Morisette, Jeffrey T.

2016-01-01

Most of the western United States is experiencing the effects of rapid and directional climate change (Garfin et al. 2013). These effects, along with forecasts of profound changes in the future, provide strong motivation for resource managers to learn about and prepare for future changes. Climate adaptation plans are based on an understanding of historic climate variation and their effects on ecosystems and on forecasts of future climate trends. Frameworks for climate adaptation thus universally identify the importance of a summary of historical, current, and projected climates (Glick, Stein, and Edelson 2011; Cross et al. 2013; Stein et al. 2014). Trends in physical climate variables are usually the basis for evaluating the exposure component in vulnerability assessments. Thus, this chapter focuses on step 2 of the Climate-Smart Conservation framework (chap. 2): vulnerability assessment. We present analyses of historical and current observations of temperature, precipitation, and other key climate measurements to provide context and a baseline for interpreting the ecological impacts of projected climate changes.

A comprehensive data acquisition and management system for an ecosystem-scale peatland warming and elevated CO 2 experiment

DOE PAGES

Krassovski, M. B.; Riggs, J. S.; Hook, L. A.; ...

2015-11-09

Ecosystem-scale manipulation experiments represent large science investments that require well-designed data acquisition and management systems to provide reliable, accurate information to project participants and third party users. The SPRUCE project (Spruce and Peatland Responses Under Climatic and Environmental Change, http://mnspruce.ornl.gov) is such an experiment funded by the Department of Energy's (DOE), Office of Science, Terrestrial Ecosystem Science (TES) Program. The SPRUCE experimental mission is to assess ecosystem-level biological responses of vulnerable, high carbon terrestrial ecosystems to a range of climate warming manipulations and an elevated CO 2 atmosphere. SPRUCE provides a platform for testing mechanisms controlling the vulnerability of organisms,more » biogeochemical processes, and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, and the cycling and release of CO 2 and CH 4 to the atmosphere). The SPRUCE experiment will generate a wide range of continuous and discrete measurements. In order to successfully manage SPRUCE data collection, achieve SPRUCE science objectives, and support broader climate change research, the research staff has designed a flexible data system using proven network technologies and software components. The primary SPRUCE data system components are the following; 1. data acquisition and control system – set of hardware and software to retrieve biological and engineering data from sensors, collect sensor status information, and distribute feedback to control components; 2. data collection system – set of hardware and software to deliver data to a central depository for storage and further processing; and 3. data management plan – set of plans, policies, and practices to control consistency, protect data integrity, and deliver data. This publication presents our approach to meeting the challenges of designing and constructing an efficient data system for managing high volume sources of in situ observations in a remote, harsh environmental location. Finally, the approach covers data flow starting from the sensors and ending at the archival/distribution points, discusses types of hardware and software used, examines design considerations that were used to choose them, and describes the data management practices chosen to control and enhance the value of the data.« less

Variations in Modeled Dengue Transmission over Puerto Rico Using a Climate Driven Dynamic Model

NASA Technical Reports Server (NTRS)

Morin, Cory; Monaghan, Andrew; Crosson, William; Quattrochi, Dale; Luvall, Jeffrey

2014-01-01

Dengue fever is a mosquito-borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Because of variations in topography, ocean influences and atmospheric processes, temperature and rainfall patterns vary across Puerto Rico and so do dengue virus transmission rates. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input, ground-based observations for temperature input, and laboratory confirmed dengue cases reported by the Centers for Disease Control and Prevention for parameter calibration, we modeled dengue transmission at the county level across Puerto Rico from 2010-2013 using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations for each county in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. The top 1% of model simulations that best reproduced the reported dengue case data were then analyzed to determine the most important parameters for dengue virus transmission in each county, as well as the relative influence of climate variability on transmission. These results can be used by public health workers to implement dengue control methods that are targeted for specific locations and climate conditions.

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

NASA Astrophysics Data System (ADS)

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

1990-10-01

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

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.

Creating the Climate for Humanistic Change in the Elementary School with Principal as Change Agent

ERIC Educational Resources Information Center

Heichberger, Robert L.

1975-01-01

It is suggested that three necessary components prerequisite to educational change are: dynamic leadership, a philosophical base, and a positive environment. The purpose of this paper is to discuss these components and indicate why and how they can be made available in a given elementary school situation. (Editor/RK)

Adaptation of Land-Use Demands to the Impact of Climate Change on the Hydrological Processes of an Urbanized Watershed

PubMed Central

Lin, Yu-Pin; Hong, Nien-Ming; Chiang, Li-Chi; Liu, Yen-Lan; Chu, Hone-Jay

2012-01-01

The adaptation of land-use patterns is an essential aspect of minimizing the inevitable impact of climate change at regional and local scales; for example, adapting watershed land-use patterns to mitigate the impact of climate change on a region’s hydrology. The objective of this study is to simulate and assess a region’s ability to adapt to hydrological changes by modifying land-use patterns in the Wu-Du watershed in northern Taiwan. A hydrological GWLF (Generalized Watershed Loading Functions) model is used to simulate three hydrological components, namely, runoff, groundwater and streamflow, based on various land-use scenarios under six global climate models. The land-use allocations are simulated by the CLUE-s model for the various development scenarios. The simulation results show that runoff and streamflow are strongly related to the precipitation levels predicted by different global climate models for the wet and dry seasons, but groundwater cycles are more related to land-use. The effects of climate change on groundwater and runoff can be mitigated by modifying current land-use patterns; and slowing the rate of urbanization would also reduce the impact of climate change on hydrological components. Thus, land-use adaptation on a local/regional scale provides an alternative way to reduce the impacts of global climate change on local hydrology. PMID:23202833

Safety climate and mindful safety practices in the oil and gas industry.

PubMed

Dahl, Øyvind; Kongsvik, Trond

2018-02-01

The existence of a positive association between safety climate and the safety behavior of sharp-end workers in high-risk organizations is supported by a considerable body of research. Previous research has primarily analyzed two components of safety behavior, namely safety compliance and safety participation. The present study extends previous research by looking into the relationship between safety climate and another component of safety behavior, namely mindful safety practices. Mindful safety practices are defined as the ability to be aware of critical factors in the environment and to act appropriately when dangers arise. Regression analysis was used to examine whether mindful safety practices are, like compliance and participation, promoted by a positive safety climate, in a questionnaire-based study of 5712 sharp-end workers in the oil and gas industry. The analysis revealed that a positive safety climate promotes mindful safety practices. The regression model accounted for roughly 31% of the variance in mindful safety practices. The most important safety climate factor was safety leadership. The findings clearly demonstrate that mindful safety practices are highly context-dependent, hence, manageable and susceptible to change. In order to improve safety climate in a direction which is favorable for mindful safety practices, the results demonstrate that it is important to give the fundamental features of safety climate high priority and in particular that of safety leadership. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

Climate responses to anthropogenic emissions of short-lived climate pollutants

NASA Astrophysics Data System (ADS)

Baker, L. H.; Collins, W. J.; Olivié, D. J. L.; Cherian, R.; Hodnebrog, Ø.; Myhre, G.; Quaas, J.

2015-07-01

Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealized, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere-ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all models showing an increase in surface temperature focussed in the Northern Hemisphere mid and (especially) high latitudes, and showing a corresponding increase in global mean precipitation. Changes in precipitation patterns are driven mostly by a northward shift in the ITCZ (Intertropical Convergence Zone), consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker response, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are free-running means that the BC and OC mitigation measures do not necessarily lead to a discernible climate response.

Climate responses to anthropogenic emissions of short-lived climate pollutants

NASA Astrophysics Data System (ADS)

Baker, L. H.; Collins, W. J.; Olivié, D. J. L.; Cherian, R.; Hodnebrog, Ø.; Myhre, G.; Quaas, J.; Samset, B. H.

2015-02-01

Policies to control air quality focus on mitigating emissions of aerosols and their precursors, and other short-lived climate pollutants (SLCPs). On a local scale, these policies will have beneficial impacts on health and crop yields, by reducing particulate matter (PM) and surface ozone concentrations; however, the climate impacts of reducing emissions of SLCPs are less straightforward to predict. In this paper we consider a set of idealised, extreme mitigation strategies, in which the total anthropogenic emissions of individual SLCP emissions species are removed. This provides an upper bound on the potential climate impacts of such air quality strategies. We focus on evaluating the climate responses to changes in anthropogenic emissions of aerosol precursor species: black carbon (BC), organic carbon (OC) and sulphur dioxide (SO2). We perform climate integrations with four fully coupled atmosphere-ocean global climate models (AOGCMs), and examine the effects on global and regional climate of removing the total land-based anthropogenic emissions of each of the three aerosol precursor species. We find that the SO2 emissions reductions lead to the strongest response, with all three models showing an increase in surface temperature focussed in the northern hemisphere high latitudes, and a corresponding increase in global mean precipitation and run-off. Changes in precipitation and run-off patterns are driven mostly by a northward shift in the ITCZ, consistent with the hemispherically asymmetric warming pattern driven by the emissions changes. The BC and OC emissions reductions give a much weaker forcing signal, and there is some disagreement between models in the sign of the climate responses to these perturbations. These differences between models are due largely to natural variability in sea-ice extent, circulation patterns and cloud changes. This large natural variability component to the signal when the ocean circulation and sea-ice are free-running means that the BC and OC mitigation measures do not necessarily lead to a discernible climate response.

Forecasting sagebrush ecosystem components and greater sage-grouse habitat for 2050: learning from past climate patterns and Landsat imagery to predict the future

USGS Publications Warehouse

Homer, Collin G.; Xian, George Z.; Aldridge, Cameron L.; Meyer, Debra K.; Loveland, Thomas R.; O'Donnell, Michael S.

2015-01-01

Sagebrush (Artemisia spp.) ecosystems constitute the largest single North American shrub ecosystem and provide vital ecological, hydrological, biological, agricultural, and recreational ecosystem services. Disturbances have altered and reduced this ecosystem historically, but climate change may ultimately represent the greatest future risk. Improved ways to quantify, monitor, and predict climate-driven gradual change in this ecosystem is vital to its future management. We examined the annual change of Daymet precipitation (daily gridded climate data) and five remote sensing ecosystem sagebrush vegetation and soil components (bare ground, herbaceous, litter, sagebrush, and shrub) from 1984 to 2011 in southwestern Wyoming. Bare ground displayed an increasing trend in abundance over time, and herbaceous, litter, shrub, and sagebrush showed a decreasing trend. Total precipitation amounts show a downward trend during the same period. We established statistically significant correlations between each sagebrush component and historical precipitation records using a simple least squares linear regression. Using the historical relationship between sagebrush component abundance and precipitation in a linear model, we forecasted the abundance of the sagebrush components in 2050 using Intergovernmental Panel on Climate Change (IPCC) precipitation scenarios A1B and A2. Bare ground was the only component that increased under both future scenarios, with a net increase of 48.98 km2 (1.1%) across the study area under the A1B scenario and 41.15 km2 (0.9%) under the A2 scenario. The remaining components decreased under both future scenarios: litter had the highest net reductions with 49.82 km2 (4.1%) under A1B and 50.8 km2 (4.2%) under A2, and herbaceous had the smallest net reductions with 39.95 km2 (3.8%) under A1B and 40.59 km2 (3.3%) under A2. We applied the 2050 forecast sagebrush component values to contemporary (circa 2006) greater sage-grouse (Centrocercus urophasianus) habitat models to evaluate the effects of potential climate-induced habitat change. Under the 2050 IPCC A1B scenario, 11.6% of currently identified nesting habitat was lost, and 0.002% of new potential habitat was gained, with 4% of summer habitat lost and 0.039% gained. Our results demonstrate the successful ability of remote sensing based sagebrush components, when coupled with precipitation, to forecast future component response using IPCC precipitation scenarios. Our approach also enables future quantification of greater sage-grouse habitat under different precipitation scenarios, and provides additional capability to identify regional precipitation influence on sagebrush component response.

A likelihood-based time series modeling approach for application in dendrochronology to examine the growth-climate relations and forest disturbance history.

PubMed

Lee, E Henry; Wickham, Charlotte; Beedlow, Peter A; Waschmann, Ronald S; Tingey, David T

2017-10-01

A time series intervention analysis (TSIA) of dendrochronological data to infer the tree growth-climate-disturbance relations and forest disturbance history is described. Maximum likelihood is used to estimate the parameters of a structural time series model with components for climate and forest disturbances (i.e., pests, diseases, fire). The statistical method is illustrated with a tree-ring width time series for a mature closed-canopy Douglas-fir stand on the west slopes of the Cascade Mountains of Oregon, USA that is impacted by Swiss needle cast disease caused by the foliar fungus, Phaecryptopus gaeumannii (Rhode) Petrak. The likelihood-based TSIA method is proposed for the field of dendrochronology to understand the interaction of temperature, water, and forest disturbances that are important in forest ecology and climate change studies.

Developing Vulnerability Analysis Method for Climate Change Adaptation on Agropolitan Region in Malang District

NASA Astrophysics Data System (ADS)

Sugiarto, Y.; Perdinan; Atmaja, T.; Wibowo, A.

2017-03-01

Agriculture plays a strategic role in strengthening sustainable development. Based on agropolitan concept, the village becomes the center of economic activities by combining agriculture, agro-industry, agribusiness and tourism that able to create high value-added economy. The impact of climate change on agriculture and water resources may increase the pressure on agropolitan development. The assessment method is required to measure the vulnerability of area-based communities in the agropolitan to climate change impact. An analysis of agropolitan vulnerability was conducted in Malang district based on four aspects and considering the availability and distribution of water as the problem. The indicators used to measure was vulnerability component which consisted of sensitivity and adaptive capacity and exposure component. The studies earned 21 indicators derived from the 115 village-based data. The results of vulnerability assessments showed that most of the villages were categorised at a moderate level. Around 20% of 388 villages were categorized at high to very high level of vulnerability due to low level of agricultural economic. In agropolitan region within the sub-district of Poncokusumo, the vulnerability of the villages varies between very low to very high. The most villages were vulnerable due to lower adaptive capacity, eventhough the level of sensitivity and exposure of all villages were relatively similar. The existence of water resources was the biggest contributor to the high exposure of the villages in Malang district, while the reception of credit facilities and source of family income were among the indicators that lead to high sensitivity component.

Adaptive governance and institutional strategies for climate-induced community relocations in Alaska.

PubMed

Bronen, Robin; Chapin, F Stuart

2013-06-04

This article presents governance and institutional strategies for climate-induced community relocations. In Alaska, repeated extreme weather events coupled with climate change-induced coastal erosion impact the habitability of entire communities. Community residents and government agencies concur that relocation is the only adaptation strategy that can protect lives and infrastructure. Community relocation stretches the financial and institutional capacity of existing governance institutions. Based on a comparative analysis of three Alaskan communities, Kivalina, Newtok, and Shishmaref, which have chosen to relocate, we examine the institutional constraints to relocation in the United States. We identify policy changes and components of a toolkit that can facilitate community-based adaptation when environmental events threaten people's lives and protection in place is not possible. Policy changes include amendment of the Stafford Act to include gradual geophysical processes, such as erosion, in the statutory definition of disaster and the creation of an adaptive governance framework to allow communities a continuum of responses from protection in place to community relocation. Key components of the toolkit are local leadership and integration of social and ecological well-being into adaptation planning.

Communicating for Climate Change Adaptation: Lessons from a Case Study with Nature-Based Tour Operators

NASA Astrophysics Data System (ADS)

Timm, K.; Sparrow, E. B.; Pettit, E. C.; Trainor, S. F.; Taylor, K.

2014-12-01

Increasing temperatures are projected to have a positive effect on the length of Alaska's tourism season, but the natural attractions that tourism relies on, such as glaciers, wildlife, fish, or other natural resources, may change. In order to continue to derive benefits from these resources, nature-based tour operators may have to adapt to these changes, and communication is an essential, but poorly understood, component of the climate change adaptation process. The goal of this study was to determine how to provide useful climate change information to nature-based tour operators by answering the following questions: 1. What environmental changes do nature-based tour operators perceive? 2. How are nature-based tour operators responding to climate and environmental change? 3. What climate change information do nature-based tour operators need? To answer these questions, twenty-four nature-based tour operators representing 20 different small and medium sized businesses in Juneau, Alaska were interviewed. The results show that many of Juneau's nature-based tour operators are observing, responding to, and in some cases, actively planning for further changes in the environment. The types of responses tended to vary depending on the participants' certainty in climate change and the perceived risks to their organization. Using these two factors, this study proposes a framework to classify climate change responses for the purpose of generating meaningful information and communication processes that promote adaptation and build adaptive capacity. During the course of the study, several other valuable lessons were learned about communicating about adaptation. The results of this study demonstrate that science communication research has an important place in the practice of promoting and fostering climate change adaptation. While the focus of this study was tour operators, the lessons learned may be valuable to other organizations striving to engage unique groups in climate change adaptation planning efforts and to social scientists trying to understanding of the role of communication in climate change adaptation.

Radiative Forcing in the ACCMIP Historical and Future Climate Simulations

NASA Technical Reports Server (NTRS)

Shindell, Drew Todd; Lamarque, J.-F.; Schulz, M.; Flanner, M.; Jiao, C.; Chin, M.; Young, P. J.; Lee, Y. H.; Rotstayn, L.; Mahowald, N.;

Statistical attribution of mid-term droughts in central Europe

NASA Astrophysics Data System (ADS)

Mikšovský, Jiří; Trnka, Miroslav; Brázdil, Rudolf

2017-04-01

Occurrence and intensity of meteorological droughts are determined by a number of factors, both anthropogenic and natural. Besides the trend-like components, often attributable to local or global man-induced changes to the climate system, manifestations of internal climate oscillatory modes are also of great importance in establishing the hydrological regime. In this presentation, we focus on identification and quantification of factors responsible for central European drought variability at seasonal time scales. Using multivariable regression analysis applied to predictands reflecting various definitions of meteorological droughts (based on Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index and Palmer's Z-index, over the 1883-2010 period), components attributable to external and internal climate-forming agents are extracted and evaluated with regard to their statistical significance. Our results confirm presence of strong links of central European droughts to the anthropogenic radiative forcing and to the phase of the North Atlantic Oscillation, but also existence of connections to the climate oscillations originating from the Pacific area. In this context, we demonstrate that prominence of components related to the phase of the Pacific Decadal Oscillation generally surpasses that of El Niño - Southern Oscillation, although the related transfer mechanisms still remain unclear. Finally, it is shown that noteworthy deviations from linearity exist in some of the drought responses, particularly for the effects of the North Atlantic Oscillation.

Model confirmation in climate economics

PubMed Central

Millner, Antony; McDermott, Thomas K. J.

2016-01-01

Benefit–cost integrated assessment models (BC-IAMs) inform climate policy debates by quantifying the trade-offs between alternative greenhouse gas abatement options. They achieve this by coupling simplified models of the climate system to models of the global economy and the costs and benefits of climate policy. Although these models have provided valuable qualitative insights into the sensitivity of policy trade-offs to different ethical and empirical assumptions, they are increasingly being used to inform the selection of policies in the real world. To the extent that BC-IAMs are used as inputs to policy selection, our confidence in their quantitative outputs must depend on the empirical validity of their modeling assumptions. We have a degree of confidence in climate models both because they have been tested on historical data in hindcasting experiments and because the physical principles they are based on have been empirically confirmed in closely related applications. By contrast, the economic components of BC-IAMs often rely on untestable scenarios, or on structural models that are comparatively untested on relevant time scales. Where possible, an approach to model confirmation similar to that used in climate science could help to build confidence in the economic components of BC-IAMs, or focus attention on which components might need refinement for policy applications. We illustrate the potential benefits of model confirmation exercises by performing a long-run hindcasting experiment with one of the leading BC-IAMs. We show that its model of long-run economic growth—one of its most important economic components—had questionable predictive power over the 20th century. PMID:27432964

Methods of Si based ceramic components volatilization control in a gas turbine engine

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

Garcia-Crespo, Andres Jose; Delvaux, John; Dion Ouellet, Noemie

A method of controlling volatilization of silicon based components in a gas turbine engine includes measuring, estimating and/or predicting a variable related to operation of the gas turbine engine; correlating the variable to determine an amount of silicon to control volatilization of the silicon based components in the gas turbine engine; and injecting silicon into the gas turbine engine to control volatilization of the silicon based components. A gas turbine with a compressor, combustion system, turbine section and silicon injection system may be controlled by a controller that implements the control method.

Combined influence of multiple climatic factors on the incidence of bacterial foodborne diseases.

PubMed

Park, Myoung Su; Park, Ki Hwan; Bahk, Gyung Jin

2018-01-01

Information regarding the relationship between the incidence of foodborne diseases (FBD) and climatic factors is useful in designing preventive strategies for FBD based on anticipated future climate change. To better predict the effect of climate change on foodborne pathogens, the present study investigated the combined influence of multiple climatic factors on bacterial FBD incidence in South Korea. During 2011-2015, the relationships between 8 climatic factors and the incidences of 13 bacterial FBD, were determined based on inpatient stays, on a monthly basis using the Pearson correlation analyses, multicollinearity tests, principal component analysis (PCA), and the seasonal autoregressive integrated moving average (SARIMA) modeling. Of the 8 climatic variables, the combination of temperature, relative humidity, precipitation, insolation, and cloudiness was significantly associated with salmonellosis (P<0.01), vibriosis (P<0.05), and enterohemorrhagic Escherichia coli O157:H7 infection (P<0.01). The combined effects of snowfall, wind speed, duration of sunshine, and cloudiness were not significant for these 3 FBD. Other FBD, including campylobacteriosis, were not significantly associated with any combination of climatic factors. These findings indicate that the relationships between multiple climatic factors and bacterial FBD incidence can be valuable for the development of prediction models for future patterns of diseases in response to changes in climate. Copyright © 2017 Elsevier B.V. All rights reserved.

Enhancing the Extreme Climate Index (ECI) to monitor climate extremes for an index-based insurance scheme across Africa

NASA Astrophysics Data System (ADS)

Helmschrot, J.; Malherbe, J.; Chamunorwa, M.; Muthige, M.; Petitta, M.; Calmanti, S.; Cucchi, M.; Syroka, J.; Iyahen, E.; Engelbrecht, F.

2017-12-01

Climate services are a key component of National Adaptation Plan (NAP) processes, which require the analysis of current climate conditions, future climate change scenarios and the identification of adaptation strategies, including the capacity to finance and implement effective adaptation options. The Extreme Climate Facility (XCF) proposed by the African Risk Capacity (ARC) developed a climate index insurance scheme, which is based on the Extreme Climate Index (ECI): an objective, multi-hazard index capable of tracking changes in the frequency or magnitude of extreme weather events, thus indicating possible shifts to a new climate regime in various regions. The main hazards covered by ECI are extreme dry, wet and heat events, with the possibility of adding other region-specific risk events. The ECI is standardized across broad geographical regions, so that extreme events occurring under different climatic regimes in Africa can be compared. Initially developed by an Italian company specialized in Climate Services, research is now conducted at the CSIR and SASSCAL, to verify and further develop the ECI for application in southern African countries, through a project initiated by the World Food Programme (WFP) and ARC. The paper will present findings on the most appropriate definitions of extremely wet and dry conditions in Africa, in terms of their impact across a multitude of sub-regional climates of the African continent. Findings of a verification analysis of the ECI, as determined through vegetation monitoring data and the SASSCAL weather station network will be discussed. Changes in the ECI under climate change will subsequently be projected, using detailed regional projections generated by the CSIR and through the Coordinated Regional Downscaling Experiment (CORDEX). This work will be concluded by the development of a web-based climate service informing African Stakeholders on climate extremes.

Unmanned Aerial Systems as Part of a Multi-Component Assessment Strategy to Address Climate Change and Atmospheric Processes

NASA Astrophysics Data System (ADS)

Lange, Manfred; Vrekoussis, Mihalis; Sciare, Jean; Argyrides, Marios; Ioannou, Stelios; Keleshis, Christos

2015-04-01

Unmanned Aerial Systems (UAS) have been established as versatile tools for different applications, providing data and observations for atmospheric and Earth-Systems research. They offer an urgently needed link between in-situ ground based measurements and satellite remote sensing observations and are distinguished by significant versatility, flexibility and moderate operational costs. UAS have the proven potential to contribute to a multi-component assessment strategy that combines remote-sensing, numerical modelling and surface measurements in order to elucidate important atmospheric processes. This includes physical and chemical transformations related to ongoing climate change as well as issues linked to aerosol-cloud interactions and air quality. The distinct advantages offered by UAS comprise, to name but a few: (i) their ability to operate from altitudes of a few meters to up to a few kilometers; (ii) their capability to perform autonomously controlled missions, which provides for repeat-measurements to be carried out at precisely defined locations; (iii) their relative ease of operation, which enables flexible employment at short-term notice and (iv) the employment of more than one platform in stacked formation, which allows for unique, quasi-3D-observations of atmospheric properties and processes. These advantages are brought to bear in combining in-situ ground based observations and numerical modeling with UAS-based remote sensing in elucidating specific research questions that require both horizontally and vertically resolved measurements at high spatial and temporal resolutions. Employing numerical atmospheric modelling, UAS can provide survey information over spatially and temporally localized, focused areas of evolving atmospheric phenomena, as they become identified by the numerical models. Conversely, UAS observations offer urgently needed data for model verification and provide boundary conditions for numerical models. In this presentation, we will briefly describe the current elements of our observational capabilities that enable the aforementioned multi-component assessment strategy by the Unmanned Systems Research Laboratory of the Cyprus Institute. This strategy is applied and utilized in the context of the EU-funded BACCHUS project, aside from other tasks. The ongoing and planned observations are particularly relevant as they are carried out in the Eastern Mediterranean and the Middle East, a region characterized by increasing anthropogenic pressures and ongoing and anticipated severe climatic changes and their impacts.

Vertical separation of the atmospheric aerosol components by using poliphon retrieval in polarized micro pulse lidar (P-MPL) measurements: case studies of specific climate-relevant aerosol types

NASA Astrophysics Data System (ADS)

Córdoba-Jabonero, Carmen; Sicard, Michaël; Ansmann, Albert; Águila, Ana del; Baars, Holger

2018-04-01

POLIPHON (POlarization-LIdar PHOtometer Networking) retrieval consists in the vertical separation of two/three particle components in aerosol mixtures, highlighting their relative contributions in terms of the optical properties and mass concentrations. This method is based on the specific particle linear depolarization ratio given for different types of aerosols, and is applied to the new polarized Micro-Pulse Lidar (P-MPL). Case studies of specific climate-relevant aerosols (dust particles, fire smoke, and pollen aerosols, including a clean case as reference) observed over Barcelona (Spain) are presented in order to evaluate firstly the potential of P-MPLs measurements in combination with POLIPHON for retrieving the vertical separation of those particle components forming aerosol mixtures and their properties.

Regional climate change predictions from the Goddard Institute for Space Studies high resolution GCM

NASA Technical Reports Server (NTRS)

Crane, Robert G.; Hewitson, Bruce

1990-01-01

Model simulations of global climate change are seen as an essential component of any program aimed at understanding human impact on the global environment. A major weakness of current general circulation models (GCMs), however, is their inability to predict reliably the regional consequences of a global scale change, and it is these regional scale predictions that are necessary for studies of human/environmental response. This research is directed toward the development of a methodology for the validation of the synoptic scale climatology of GCMs. This is developed with regard to the Goddard Institute for Space Studies (GISS) GCM Model 2, with the specific objective of using the synoptic circulation form a doubles CO2 simulation to estimate regional climate change over North America, south of Hudson Bay. This progress report is specifically concerned with validating the synoptic climatology of the GISS GCM, and developing the transfer function to derive grid-point temperatures from the synoptic circulation. Principal Components Analysis is used to characterize the primary modes of the spatial and temporal variability in the observed and simulated climate, and the model validation is based on correlations between component loadings, and power spectral analysis of the component scores. The results show that the high resolution GISS model does an excellent job of simulating the synoptic circulation over the U.S., and that grid-point temperatures can be predicted with reasonable accuracy from the circulation patterns.

Dynamic analysis of pan evaporation variations in the Huai River Basin, a climate transition zone in eastern China.

PubMed

Li, Meng; Chu, Ronghao; Shen, Shuanghe; Islam, Abu Reza Md Towfiqul

2018-06-01

Pan evaporation (E pan ), which we examine in this study to better understand atmospheric evaporation demand, represents a pivotal indicator of the terrestrial ecosystem and hydrological cycle, particularly in the Huai River Basin (HRB) in eastern China, where high potential risks of drought and flooding are commonly observed. In this study, we examine the spatiotemporal trend patterns of climatic factors and E pan by using the Mann-Kendall test and the Theil-Sen estimator based on a daily meteorological dataset from 89 weather stations during 1965-2013 in the HRB. Furthermore, the PenPan model is employed to estimate E pan at a monthly time scale, and a differential equation method is applied to quantify contributions from four meteorological variables to E pan trends. The results show that E pan significantly decreased (P<0.001) at an average rate of -8.119mm·a -2 at annual time scale in the whole HRB, with approximately 90% of stations occupied. Meanwhile, the generally higher E pan values were detected in the northern HRB. The values of the aerodynamic components in the PenPan model were much greater than those of the radiative components, which were responsible for the variations in the E pan trend. The significantly decreasing wind speed (u 2 ) was the most dominant factor that controlled the decreasing E pan trend at each time scale, followed by the notable decreasing net radiation (R n ) at the annual time scale also in growing season and summer. However, the second dominant factor shifted to the mean temperature (T a ) during the spring and winter and the vapor pressure deficit (vpd) during the autumn. These phenomena demonstrated a positive link between the significance of climate variables and their control over the E pan trend. Copyright © 2017 Elsevier B.V. All rights reserved.

Climate fails to predict wood decomposition at regional scales

Treesearch

Mark A. Bradford; Robert J. Warren; Petr Baldrian; Thomas W. Crowther; Daniel S. Maynard; Emily E. Oldfield; William R. Wieder; Stephen A. Wood; Joshua R. King

2014-01-01

Decomposition of organic matter strongly influences ecosystem carbon storage1. In Earth-system models, climate is a predominant control on the decomposition rates of organic matter2, 3, 4, 5. This assumption is based on the mean response of decomposition to climate, yet there is a growing appreciation in other areas of global change science that projections based on...

Sea level fall during glaciation stabilized atmospheric CO2 by enhanced volcanic degassing

PubMed Central

Hasenclever, Jörg; Knorr, Gregor; Rüpke, Lars H.; Köhler, Peter; Morgan, Jason; Garofalo, Kristin; Barker, Stephen; Lohmann, Gerrit; Hall, Ian R.

2017-01-01

Paleo-climate records and geodynamic modelling indicate the existence of complex interactions between glacial sea level changes, volcanic degassing and atmospheric CO2, which may have modulated the climate system’s descent into the last ice age. Between ∼85 and 70 kyr ago, during an interval of decreasing axial tilt, the orbital component in global temperature records gradually declined, while atmospheric CO2, instead of continuing its long-term correlation with Antarctic temperature, remained relatively stable. Here, based on novel global geodynamic models and the joint interpretation of paleo-proxy data as well as biogeochemical simulations, we show that a sea level fall in this interval caused enhanced pressure-release melting in the uppermost mantle, which may have induced a surge in magma and CO2 fluxes from mid-ocean ridges and oceanic hotspot volcanoes. Our results reveal a hitherto unrecognized negative feedback between glaciation and atmospheric CO2 predominantly controlled by marine volcanism on multi-millennial timescales of ∼5,000–15,000 years. PMID:28681844

Regression-based season-ahead drought prediction for southern Peru conditioned on large-scale climate variables

NASA Astrophysics Data System (ADS)

Mortensen, Eric; Wu, Shu; Notaro, Michael; Vavrus, Stephen; Montgomery, Rob; De Piérola, José; Sánchez, Carlos; Block, Paul

2018-01-01

Located at a complex topographic, climatic, and hydrologic crossroads, southern Peru is a semiarid region that exhibits high spatiotemporal variability in precipitation. The economic viability of the region hinges on this water, yet southern Peru is prone to water scarcity caused by seasonal meteorological drought. Meteorological droughts in this region are often triggered during El Niño episodes; however, other large-scale climate mechanisms also play a noteworthy role in controlling the region's hydrologic cycle. An extensive season-ahead precipitation prediction model is developed to help bolster the existing capacity of stakeholders to plan for and mitigate deleterious impacts of drought. In addition to existing climate indices, large-scale climatic variables, such as sea surface temperature, are investigated to identify potential drought predictors. A principal component regression framework is applied to 11 potential predictors to produce an ensemble forecast of regional January-March precipitation totals. Model hindcasts of 51 years, compared to climatology and another model conditioned solely on an El Niño-Southern Oscillation index, achieve notable skill and perform better for several metrics, including ranked probability skill score and a hit-miss statistic. The information provided by the developed model and ancillary modeling efforts, such as extending the lead time of and spatially disaggregating precipitation predictions to the local level as well as forecasting the number of wet-dry days per rainy season, may further assist regional stakeholders and policymakers in preparing for drought.

Tales from the Jungle: The Evolving Climate Services Ecosystem

NASA Astrophysics Data System (ADS)

Redmond, K. T.

2015-12-01

In 2001 the NRC Report "A Climate Services Vision: First Steps Toward the Future" examined the state and trends of climate services. That report included a definition of this term that has lost no relevance: "The timely production and delivery of useful climate data, information, and knowledge to decision makers." The original entities delivering such services, at the state level, are represented by the American Association of State Climatologists (AASC). In 1986 the NOAA Regional Climate Center program was initiated, followed in 1994 by the NOAA Regional Climate Sciences and Assessments. Since 2010 we have seen the establishment of the USDI Climate Science Centers and the Landscape Conservation Cooperatives, the NOAA Regional Climate Service Directors, and the USDA Regional Climate Hubs. The recent expansion of formal programs has essentially filled out the agency "niche space." Other non-governmental and private entities are also expanding into this space. The present profusion runs a risk of creating a perception of excessive duplication in some quarters, including those funding these enterprises. Collectively these activities form what can be thought of as an ecosystem of climate services. A certain amount of replication is desirable, healthy, and necessary, but beyond some point can be excessive unless the total capacity remains insufficient. Each component has come into existence for a different set of reasons. Since these components were invented by human beings, their subsequent evolution can in theory be guided by humans. The history and purpose of each component needs to be borne in mind, with capsule descriptions suitable for rapid delivery to the decision-makers who approve the support for the various components. Good communication among the components is therefore essential for a healthy and functional overall system. This in turn calls for the ability to adequately represent the role of each of those components, a purpose best informed through actual participation in multiple components, to obtain the necessary familiarity.

Climate reconstruction analysis using coexistence likelihood estimation (CRACLE): a method for the estimation of climate using vegetation.

PubMed

Harbert, Robert S; Nixon, Kevin C

2015-08-01

• Plant distributions have long been understood to be correlated with the environmental conditions to which species are adapted. Climate is one of the major components driving species distributions. Therefore, it is expected that the plants coexisting in a community are reflective of the local environment, particularly climate.• Presented here is a method for the estimation of climate from local plant species coexistence data. The method, Climate Reconstruction Analysis using Coexistence Likelihood Estimation (CRACLE), is a likelihood-based method that employs specimen collection data at a global scale for the inference of species climate tolerance. CRACLE calculates the maximum joint likelihood of coexistence given individual species climate tolerance characterization to estimate the expected climate.• Plant distribution data for more than 4000 species were used to show that this method accurately infers expected climate profiles for 165 sites with diverse climatic conditions. Estimates differ from the WorldClim global climate model by less than 1.5°C on average for mean annual temperature and less than ∼250 mm for mean annual precipitation. This is a significant improvement upon other plant-based climate-proxy methods.• CRACLE validates long hypothesized interactions between climate and local associations of plant species. Furthermore, CRACLE successfully estimates climate that is consistent with the widely used WorldClim model and therefore may be applied to the quantitative estimation of paleoclimate in future studies. © 2015 Botanical Society of America, Inc.

Seasonal forecasts in the Sahel region: the use of rainfall-based predictive variables

NASA Astrophysics Data System (ADS)

Lodoun, Tiganadaba; Sanon, Moussa; Giannini, Alessandra; Traoré, Pierre Sibiry; Somé, Léopold; Rasolodimby, Jeanne Millogo

2014-08-01

In the Sahel region, seasonal predictions are crucial to alleviate the impacts of climate variability on populations' livelihoods. Agricultural planning (e.g., decisions about sowing date, fertilizer application date, and choice of crop or cultivar) is based on empirical predictive indices whose accuracy to date has not been scientifically proven. This paper attempts to statistically test whether the pattern of rainfall distribution over the May-July period contributes to predicting the real onset date and the nature (wet or dry) of the rainy season, as farmers believe. To that end, we considered historical records of daily rainfall from 51 stations spanning the period 1920-2008 and the different agro-climatic zones in Burkina Faso. We performed (1) principal component analysis to identify climatic zones, based on the patterns of intra-seasonal rainfall, (2) and linear discriminant analysis to find the best rainfall-based variables to distinguish between real and false onset dates of the rainy season, and between wet and dry seasons in each climatic zone. A total of nine climatic zones were identified in each of which, based on rainfall records from May to July, we derived linear discriminant functions to correctly predict the nature of a potential onset date of the rainy season (real or false) and that of the rainy season (dry or wet) in at least three cases out of five. These functions should contribute to alleviating the negative impacts of climate variability in the different climatic zones of Burkina Faso.

Global Carbon Project: the Global Carbon Budget 2015 (V.1.0., issued Nov. 2015 and V.1.1, issued Dec. 2015)

DOE Data Explorer

Le Quere, C. [University of East Anglia, Norwich UK; Moriarty, R. [University of East Anglia, Norwich UK; Andrew, R. M. [Univ. of Oslo (Norway); Canadell, J. G. [Commonwealth Scientific and Industrial Research Organization (CSIRO) Oceans and Atmosphere, Canberra ACT (Australia); Sitch, S. [University of Exeter, Exter UK; Boden, T. A. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States) Carbon Dioxide Information Analysis Center (CDIAC); al., et

2015-01-01

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates as well as consistency within and among components, alongside methodology and data limitations.

Mid-21st-century climate changes increase predicted fire occurrence and fire season length, Northern Rocky Mountains, United States

USGS Publications Warehouse

Riley, Karin L.; Loehman, Rachel A.

2016-01-01

Climate changes are expected to increase fire frequency, fire season length, and cumulative area burned in the western United States. We focus on the potential impact of mid-21st-century climate changes on annual burn probability, fire season length, and large fire characteristics including number and size for a study area in the Northern Rocky Mountains. Although large fires are rare they account for most of the area burned in western North America, burn under extreme weather conditions, and exhibit behaviors that preclude methods of direct control. Allocation of resources, development of management plans, and assessment of fire effects on ecosystems all require an understanding of when and where fires are likely to burn, particularly under altered climate regimes that may increase large fire occurrence. We used the large fire simulation model FSim to model ignition, growth, and containment of wildfires under two climate scenarios: contemporary (based on instrumental weather) and mid-century (based on an ensemble average of global climate models driven by the A1B SRES emissions scenario). Modeled changes in fire patterns include increased annual burn probability, particularly in areas of the study region with relatively short contemporary fire return intervals; increased individual fire size and annual area burned; and fewer years without large fires. High fire danger days, represented by threshold values of Energy Release Component (ERC), are projected to increase in number, especially in spring and fall, lengthening the climatic fire season. For fire managers, ERC is an indicator of fire intensity potential and fire economics, with higher ERC thresholds often associated with larger, more expensive fires. Longer periods of elevated ERC may significantly increase the cost and complexity of fire management activities, requiring new strategies to maintain desired ecological conditions and limit fire risk. Increased fire activity (within the historical range of frequency and severity, and depending on the extent to which ecosystems are adapted) may maintain or restore ecosystem functionality; however, in areas that are highly departed from historical fire regimes or where there is disequilibrium between climate and vegetation, ecosystems may be rapidly and persistently altered by wildfires, especially those that burn under extreme conditions.

Fire activity and severity in the western US vary along proxy gradients representing fuel amount and fuel moisture.

PubMed

Parks, Sean A; Parisien, Marc-André; Miller, Carol; Dobrowski, Solomon Z

2014-01-01

Numerous theoretical and empirical studies have shown that wildfire activity (e.g., area burned) at regional to global scales may be limited at the extremes of environmental gradients such as productivity or moisture. Fire activity, however, represents only one component of the fire regime, and no studies to date have characterized fire severity along such gradients. Given the importance of fire severity in dictating ecological response to fire, this is a considerable knowledge gap. For the western US, we quantify relationships between climate and the fire regime by empirically describing both fire activity and severity along two climatic water balance gradients, actual evapotranspiration (AET) and water deficit (WD), that can be considered proxies for fuel amount and fuel moisture, respectively. We also concurrently summarize fire activity and severity among ecoregions, providing an empirically based description of the geographic distribution of fire regimes. Our results show that fire activity in the western US increases with fuel amount (represented by AET) but has a unimodal (i.e., humped) relationship with fuel moisture (represented by WD); fire severity increases with fuel amount and fuel moisture. The explicit links between fire regime components and physical environmental gradients suggest that multivariable statistical models can be generated to produce an empirically based fire regime map for the western US. Such models will potentially enable researchers to anticipate climate-mediated changes in fire recurrence and its impacts based on gridded spatial data representing future climate scenarios.

Fire Activity and Severity in the Western US Vary along Proxy Gradients Representing Fuel Amount and Fuel Moisture

PubMed Central

Parks, Sean A.; Parisien, Marc-André; Miller, Carol; Dobrowski, Solomon Z.

2014-01-01

Numerous theoretical and empirical studies have shown that wildfire activity (e.g., area burned) at regional to global scales may be limited at the extremes of environmental gradients such as productivity or moisture. Fire activity, however, represents only one component of the fire regime, and no studies to date have characterized fire severity along such gradients. Given the importance of fire severity in dictating ecological response to fire, this is a considerable knowledge gap. For the western US, we quantify relationships between climate and the fire regime by empirically describing both fire activity and severity along two climatic water balance gradients, actual evapotranspiration (AET) and water deficit (WD), that can be considered proxies for fuel amount and fuel moisture, respectively. We also concurrently summarize fire activity and severity among ecoregions, providing an empirically based description of the geographic distribution of fire regimes. Our results show that fire activity in the western US increases with fuel amount (represented by AET) but has a unimodal (i.e., humped) relationship with fuel moisture (represented by WD); fire severity increases with fuel amount and fuel moisture. The explicit links between fire regime components and physical environmental gradients suggest that multivariable statistical models can be generated to produce an empirically based fire regime map for the western US. Such models will potentially enable researchers to anticipate climate-mediated changes in fire recurrence and its impacts based on gridded spatial data representing future climate scenarios. PMID:24941290

Quantifying the Global Fresh Water Budget: Capabilities from Current and Future Satellite Sensors

NASA Technical Reports Server (NTRS)

Hildebrand, Peter; Zaitchik, Benjamin

2007-01-01

The global water cycle is complex and its components are difficult to measure, particularly at the global scales and with the precision needed for assessing climate impacts. Recent advances in satellite observational capabilities, however, are greatly improving our knowledge of the key terms in the fresh water flux budget. Many components of the of the global water budget, e.g. precipitation, atmospheric moisture profiles, soil moisture, snow cover, sea ice are now routinely measured globally using instruments on satellites such as TRMM, AQUA, TERRA, GRACE, and ICESat, as well as on operational satellites. New techniques, many using data assimilation approaches, are providing pathways toward measuring snow water equivalent, evapotranspiration, ground water, ice mass, as well as improving the measurement quality for other components of the global water budget. This paper evaluates these current and developing satellite capabilities to observe the global fresh water budget, then looks forward to evaluate the potential for improvements that may result from future space missions as detailed by the US Decadal Survey, and operational plans. Based on these analyses, and on the goal of improved knowledge of the global fresh water budget under the effects of climate change, we suggest some priorities for the future, based on new approaches that may provide the improved measurements and the analyses needed to understand and observe the potential speed-up of the global water cycle under the effects of climate change.

Quantification of Magnetic Components in Sediments with Applications in Paleoenvironmental Studies

NASA Astrophysics Data System (ADS)

Lascu, Ioan

The present dissertation is a collection of papers investigating the magnetic properties of sediments. The main aim of the work presented here is to study the magnetic characteristics of sedimentary deposits by using a methodology that efficiently quantifies the contributions of various ferrimagnetic components in sediments, and to exemplify how this model can be used to make inferences about past climatic and environmental variability. Magnetic minerals in sediments have long been used as indicators of variability in the factors controlling sediment deposition, and sediment-magnetic properties can be interpreted in terms of the processes controlling the fluxes of various magnetic components. Ferrimagnetic minerals, such as magnetite, are strong magnetically, and tend to dominate the signal from bulk measurements. Two sedimentary ferrimagnetic components that play a major role in shaping the magnetic record with time: a detrital component and a biogenic component. The detrital component of magnetic assemblages probably accounts for the greater proportion of the magnetic signal in many records, and therefore has been the focus of most environmental magnetism studies. The processes that control detrital records are mostly tied to local hydrology, climate, and vegetation cover. However, there is strong evidence that many magnetic assemblages are dominated by autochthonous magnetic particles, which in most cases are produced as a result of direct biologic control. Knowing the contribution of each of these components to the total mass of ferrimagnetic material becomes important when making inferences about past climatic or environmental conditions. The theoretical mixing model devised here using the characteristics of detrital and biogenic end members was tested on lake sediments from Minnesota. The analysis incorporates both spatial and temporal effects on magnetic record. We have investigated the history of sediment flux to Deming Lake, Minnesota, for the past 1000 years. Our results reveal several episodes of reduced precipitation, during which less sediment is mobilized from the catchment by overland flow and runoff. The most prominent episode occurred at the end of the Little Ice Age, indicating that this time period was not only cold but might have been drier than previously thought. The spatial control on sediment-magnetic properties was established via a survey of the magnetic properties of surface sediments from several Minnesota lakes. The magnetic properties are controlled by the competing fluxes of detrital and biogenic particles, according to location in the basin, while the position of the oxic-anoxic interface controls whether biogenic magnetite is formed in the sediment or in the water column, with implications in the preservation of intact versus collapsed bacterial chains. The thesis concludes with an incursion into the magnetic properties of chemical sediments from caves, or speleothems. The magnetic recordings preserved in calcite speleothems hold enormous potential for paleomagnetic and paleoenvironmental reconstructions. Speleothems lock in magnetization instantly, are not affected by post-depositional effects, and can be dated with high precision. The natural remanence in speleothems is carried mainly by magnetite, and the main remanence acquisition mechanism is depositional, through physical alignment of detrital magnetic grains parallel to the Earth's magnetic field. Future speleothem magnetism studies should benefit from increasingly sensitive magnetometers, operating at high spatial resolution, that are able to resolve short-term geomagnetic variability, and characterize events such as geomagnetic excursions at an unprecedented scale.

DEVELOPMENT OF COLD CLIMATE HEAT PUMP USING TWO-STAGE COMPRESSION

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

Shen, Bo; Rice, C Keith; Abdelaziz, Omar

2015-01-01

This paper uses a well-regarded, hardware based heat pump system model to investigate a two-stage economizing cycle for cold climate heat pump applications. The two-stage compression cycle has two variable-speed compressors. The high stage compressor was modelled using a compressor map, and the low stage compressor was experimentally studied using calorimeter testing. A single-stage heat pump system was modelled as the baseline. The system performance predictions are compared between the two-stage and single-stage systems. Special considerations for designing a cold climate heat pump are addressed at both the system and component levels.

Spatiotemporal Patterns of Evapotranspiration in Response to Multiple Environmental Factors Simulated by the Community Land Model

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

Shi, Xiaoying; Mao, Jiafu; Thornton, P.

Spatiotemporal patterns of evapotranspiration (ET) over the period from 1982 to 2008 are investigated and attributed to multiple environmental factors using the Community Land Model version 4 (CLM4). Our results show that CLM4 captures the spatial distribution and interannual variability of ET well when compared to observation-based estimates. We find that climate dominates the predicted variability in ET. Elevated atmospheric CO2 concentration also plays an important role in modulating the trend of predicted ET over most land areas, and replaces climate to function as the dominant factor controlling ET changes over the North America, South America and Asia regions. Comparedmore » to the effect of climate and CO2 concentration, the roles of other factors such as nitrogen deposition, land use change and aerosol deposition are less pronounced and regionally dependent. The aerosol deposition contribution is the third most important factor for trends of ET over Europe, while it has the smallest impact over other regions. As ET is a dominant component of the terrestrial water cycle, our results suggest that environmental factors like elevated CO2, nitrogen and aerosol depositions, and land use change, in addition to climate, could have significant impact on future projections of water resources and water cycle dynamics at global and regional scales.« less

Application of multi-scale wavelet entropy and multi-resolution Volterra models for climatic downscaling

NASA Astrophysics Data System (ADS)

Sehgal, V.; Lakhanpal, A.; Maheswaran, R.; Khosa, R.; Sridhar, Venkataramana

2018-01-01

This study proposes a wavelet-based multi-resolution modeling approach for statistical downscaling of GCM variables to mean monthly precipitation for five locations at Krishna Basin, India. Climatic dataset from NCEP is used for training the proposed models (Jan.'69 to Dec.'94) and are applied to corresponding CanCM4 GCM variables to simulate precipitation for the validation (Jan.'95-Dec.'05) and forecast (Jan.'06-Dec.'35) periods. The observed precipitation data is obtained from the India Meteorological Department (IMD) gridded precipitation product at 0.25 degree spatial resolution. This paper proposes a novel Multi-Scale Wavelet Entropy (MWE) based approach for clustering climatic variables into suitable clusters using k-means methodology. Principal Component Analysis (PCA) is used to obtain the representative Principal Components (PC) explaining 90-95% variance for each cluster. A multi-resolution non-linear approach combining Discrete Wavelet Transform (DWT) and Second Order Volterra (SoV) is used to model the representative PCs to obtain the downscaled precipitation for each downscaling location (W-P-SoV model). The results establish that wavelet-based multi-resolution SoV models perform significantly better compared to the traditional Multiple Linear Regression (MLR) and Artificial Neural Networks (ANN) based frameworks. It is observed that the proposed MWE-based clustering and subsequent PCA, helps reduce the dimensionality of the input climatic variables, while capturing more variability compared to stand-alone k-means (no MWE). The proposed models perform better in estimating the number of precipitation events during the non-monsoon periods whereas the models with clustering without MWE over-estimate the rainfall during the dry season.

Robust high-performance control for robotic manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1991-01-01

Model-based and performance-based control techniques are combined for an electrical robotic control system. Thus, two distinct and separate design philosophies have been merged into a single control system having a control law formulation including two distinct and separate components, each of which yields a respective signal component that is combined into a total command signal for the system. Those two separate system components include a feedforward controller and a feedback controller. The feedforward controller is model-based and contains any known part of the manipulator dynamics that can be used for on-line control to produce a nominal feedforward component of the system's control signal. The feedback controller is performance-based and consists of a simple adaptive PID controller which generates an adaptive control signal to complement the nominal feedforward signal.

Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming

DOE PAGES

Feng, Wenting; Liang, Junyi; Hale, Lauren E.; ...

2017-06-09

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon–climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long-term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming.more » Taking advantage of a 12-year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO 2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C-degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long-term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change.« less

Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming

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

Feng, Wenting; Liang, Junyi; Hale, Lauren E.

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon–climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long-term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming.more » Taking advantage of a 12-year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO 2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C-degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long-term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change.« less

Enhanced decomposition of stable soil organic carbon and microbial catabolic potentials by long-term field warming.

PubMed

Feng, Wenting; Liang, Junyi; Hale, Lauren E; Jung, Chang Gyo; Chen, Ji; Zhou, Jizhong; Xu, Minggang; Yuan, Mengting; Wu, Liyou; Bracho, Rosvel; Pegoraro, Elaine; Schuur, Edward A G; Luo, Yiqi

2017-11-01

Quantifying soil organic carbon (SOC) decomposition under warming is critical to predict carbon-climate feedbacks. According to the substrate regulating principle, SOC decomposition would decrease as labile SOC declines under field warming, but observations of SOC decomposition under warming do not always support this prediction. This discrepancy could result from varying changes in SOC components and soil microbial communities under warming. This study aimed to determine the decomposition of SOC components with different turnover times after subjected to long-term field warming and/or root exclusion to limit C input, and to test whether SOC decomposition is driven by substrate lability under warming. Taking advantage of a 12-year field warming experiment in a prairie, we assessed the decomposition of SOC components by incubating soils from control and warmed plots, with and without root exclusion for 3 years. We assayed SOC decomposition from these incubations by combining inverse modeling and microbial functional genes during decomposition with a metagenomic technique (GeoChip). The decomposition of SOC components with turnover times of years and decades, which contributed to 95% of total cumulative CO 2 respiration, was greater in soils from warmed plots. But the decomposition of labile SOC was similar in warmed plots compared to the control. The diversity of C-degradation microbial genes generally declined with time during the incubation in all treatments, suggesting shifts of microbial functional groups as substrate composition was changing. Compared to the control, soils from warmed plots showed significant increase in the signal intensities of microbial genes involved in degrading complex organic compounds, implying enhanced potential abilities of microbial catabolism. These are likely responsible for accelerated decomposition of SOC components with slow turnover rates. Overall, the shifted microbial community induced by long-term warming accelerates the decomposition of SOC components with slow turnover rates and thus amplify the positive feedback to climate change. © 2017 John Wiley & Sons Ltd.

The Effects of El Niño on Precipitation in Southern California Climate Divisions: Year 2016 Precipitation Forecast.

NASA Astrophysics Data System (ADS)

Perez Cruz, L.; Idris, N.; El-Askary, H. M.

2015-12-01

Recently, it has been reported by the National Oceanic and Atmospheric Administration (NOAA) that there is very high chance not only for El Niño to continue through Northern Hemisphere winter 2015-16, but also a remarkable chance for El Niño to last into early spring 2016. This research aims at: 1) investigating the impact of El Niño on precipitation in the Southern California Climate Divisions: Climate Division 6 South Coast Drainage, and Division 7 South Coast Desert Basin. 2) Analyzing the precipitation of Southern California region using the Empirical Mode Decomposition Method (EMD). 3) Looking at the SOI components and compare it with the precipitation components of Southern California Climate Divisions. 4) Comparing precipitation data with Niño indices: Niño 1+2, Niño 3, Nino 3.4, and Niño 4. As results, we found a significant cross correlation of 0.7 between SOI component 10 and precipitation component 10 in Climate Division 6. Furthermore, among all the Niño indices, Niño 3 region displayed the best correlation. When we compared precipitation division 7 component 9 with Niño 3 component 10, a 0.95 cross correlation value was obtained. The lowest cross correlation value of (0.33) was obtained from Climate Division 6, precipitation component 7 with Niño 4 component 7.

Climate change impact on the annual water balance in the northwest Florida coastal

NASA Astrophysics Data System (ADS)

Alizad, K.; Wang, D.; Alimohammadi, N.; Hagen, S. C.

2012-12-01

As the largest tributary to the Apalachicola River, the Chipola River originates in southern Alabama, flows through Florida Panhandle and ended to Gulf of Mexico. The Chipola watershed is located in an intermediate climate environment with aridity index around one. Watershed provides habitat for a number of threatened and endangered animal and plant species. However, climate change affects hydrologic cycle of Chipola River watershed at various temporal and spatial scales. Studying the effects of climate variations is of great importance for water and environmental management purposes in this catchment. This research is mainly focuses on assessing climate change impact on the partitioning pattern of rainfall from mean annual to inter-annual and to seasonal scales. At the mean annual scale, rainfall is partitioned into runoff and evaporation assuming negligible water storage changes. Mean annual runoff is controlled by both mean annual precipitation and potential evaporation. Changes in long term mean runoff caused by variations of long term mean precipitation and potential evaporation will be evaluated based on Budyko hypothesis. At the annual scale, rainfall is partitioned into runoff, evaporation, and storage change. Inter-annual variability of runoff and evaporation are mainly affected by the changes of mean annual climate variables as well as their inter-annual variability. In order to model and evaluate each component of water balance at the annual scale, parsimonious but reliable models, are developed. Budyko hypothesis on the existing balance between available water and energy supply is reconsidered and redefined for the sub-annual time scale and reconstructed accordingly in order to accurately model seasonal hydrologic balance of the catchment. Models are built in the seasonal time frame with a focus on the role of storage change in water cycle. Then for Chipola catchment, models are parameterized based on a sufficient time span of historical data and the their coefficients are quantified. For necessary future predictions, data obtained from climate regional models starting 2040 to 2069 will be utilized. To accommodate the inherent uncertainty of climate projections, an ensemble of regional climate models will be used to assess changes of rainfall and potential evaporation. Then, the climate change impact on seasonal and annual runoff, evaporation, and water storage changes will be projected.

Impact of Land Model Depth on Long Term Climate Variability and Change.

NASA Astrophysics Data System (ADS)

Gonzalez-Rouco, J. F.; García-Bustamante, E.; Hagemann, S.; Lorentz, S.; Jungclaus, J.; de Vrese, P.; Melo, C.; Navarro, J.; Steinert, N.

2017-12-01

The available evidence indicates that the simulation of subsurface thermodynamics in current General Circulation Models (GCMs) is not accurate enough due to the land-surface model imposing a zero heat flux boundary condition that is too close to the surface. Shallow land model components distort the amplitude and phase of the heat propagation in the subsurface with implications for energy storage and land-air interactions. Off line land surface model experiments forced with GCM climate change simulations and comparison with borehole temperature profiles indicate there is a large reduction of the energy storage of the soil using the typical shallow land models included in most GCMs. However, the impact of increasing the depth of the soil model in `on-line' GCM simulations of climate variability or climate change has not yet been systematically explored. The JSBACH land surface model has been used in stand alone mode, driven by outputs of the MPIESM to assess the impacts of progressively increasing the depth of the soil model. In a first stage, preindustrial control simulations are developed increasing the lower depth of the zero flux bottom boundary condition placed for temperature at the base of the fifth model layer (9.83 m) down to 294.6 m (layer 9), thus allowing for the bottom layers to reach equilibrium. Starting from piControl conditions, historical and scenario simulations have been performed since 1850 yr. The impact of increasing depths on the subsurface layer temperatures is analysed as well as the amounts of energy involved. This is done also considering permafrost processes (freezing and thawing). An evaluation on the influence of deepening the bottom boundary on the simulation of low frequency variability and temperature trends is provided.

Vegetation controls on the biophysical surface properties at global scale

NASA Astrophysics Data System (ADS)

Forzieri, Giovanni; Cescatti, Alessandro

2016-04-01

Leaf area index (LAI) plays an important role in determining resistances to heat, moisture and momentum exchanges between the land surface and atmosphere. Exploring how variations in LAI may induce changes in the surface energy balance is a key to understanding vegetation-climate interactions and for predicting biophysical climate impacts associated to changes in land cover. To this end, we analyzed remote sensing-observed dynamics in LAI, surface energy fluxes and climate drivers at global scale. We investigated the link between interannual variability of LAI and the components of the surface energy budget under diverse climate gradients. Results show that a 25% increase in annual LAI may induce up to 2% increase in available surface energy, as consequence of higher short wave absorption due to reduced albedos, up to 20% increase and 10% decrease in latent and sensible heat, respectively, leading to a decrease of the Bowen ratio in densely vegetated canopies. Opposite patterns are found for a reduction in LAI of similar magnitude. Such changes are strongly modulated by concurrent year-to-year variations and climatological means of air temperature, precipitation and snow cover as well as by land cover-specific physiological processes. Boreal and semi-arid regions appear to be mostly exposed to large changes in biophysical surface processes induced by interannual fluctuations in LAI. The combination of the emergent patters translates into variations in the long-wave outgoing radiation that reflect the surface warming/cooling associated to LAI changes. These findings provide a deeper understanding of the vegetation control on biophysical surface properties and define a set of observational-based diagnostics of LAI-dependent land surface-atmosphere interactions.

A commentary on the Atlantic meridional overturning circulation stability in climate models

NASA Astrophysics Data System (ADS)

Gent, Peter R.

2018-02-01

The stability of the Atlantic meridional overturning circulation (AMOC) in ocean models depends quite strongly on the model formulation, especially the vertical mixing, and whether it is coupled to an atmosphere model. A hysteresis loop in AMOC strength with respect to freshwater forcing has been found in several intermediate complexity climate models and in one fully coupled climate model that has very coarse resolution. Over 40% of modern climate models are in a bistable AMOC state according to the very frequently used simple stability criterion which is based solely on the sign of the AMOC freshwater transport across 33° S. In a recent freshwater hosing experiment in a climate model with an eddy-permitting ocean component, the change in the gyre freshwater transport across 33° S is larger than the AMOC freshwater transport change. This casts very strong doubt on the usefulness of this simple AMOC stability criterion. If a climate model uses large surface flux adjustments, then these adjustments can interfere with the atmosphere-ocean feedbacks, and strongly change the AMOC stability properties. AMOC can be shut off for many hundreds of years in modern fully coupled climate models if the hosing or carbon dioxide forcing is strong enough. However, in one climate model the AMOC recovers after between 1000 and 1400 years. Recent 1% increasing carbon dioxide runs and RCP8.5 future scenario runs have shown that the AMOC reduction is smaller using an eddy-resolving ocean component than in the comparable standard 1° ocean climate models.

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.

Tropical Ocean Surface Energy Balance Variability: Linking Weather to Climate Scales

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Clayson, Carol Anne

2013-01-01

Radiative and turbulent surface exchanges of heat and moisture across the atmosphere-ocean interface are fundamental components of the Earth s energy and water balance. Characterizing the spatiotemporal variability of these exchanges of heat and moisture is critical to understanding the global water and energy cycle variations, quantifying atmosphere-ocean feedbacks, and improving model predictability. These fluxes are integral components to tropical ocean-atmosphere variability; they can drive ocean mixed layer variations and modify the atmospheric boundary layer properties including moist static stability, thereby influencing larger-scale tropical dynamics. Non-parametric cluster-based classification of atmospheric and ocean surface properties has shown an ability to identify coherent weather regimes, each typically associated with similar properties and processes. Using satellite-based observational radiative and turbulent energy flux products, this study investigates the relationship between these weather states and surface energy processes within the context of tropical climate variability. Investigations of surface energy variations accompanying intraseasonal and interannual tropical variability often use composite-based analyses of the mean quantities of interest. Here, a similar compositing technique is employed, but the focus is on the distribution of the heat and moisture fluxes within their weather regimes. Are the observed changes in surface energy components dominated by changes in the frequency of the weather regimes or through changes in the associated fluxes within those regimes? It is this question that the presented work intends to address. The distribution of the surface heat and moisture fluxes is evaluated for both normal and non-normal states. By examining both phases of the climatic oscillations, the symmetry of energy and water cycle responses are considered.

Bioclimatic Classification of Northeast Asia for climate change response

NASA Astrophysics Data System (ADS)

Choi, Y.; Jeon, S. W.; Lim, C. H.

2016-12-01

As climate change has been getting worse, we should monitor the change of biodiversity, and distribution of species to handle the crisis and take advantage of climate change. The development of bioclimatic map which classifies land into homogenous zones by similar environment properties is the first step to establish a strategy. Statistically derived classifications of land provide useful spatial frameworks to support ecosystem research, monitoring and policy decisions. Many countries are trying to make this kind of map and actively utilize it to ecosystem conservation and management. However, the Northeast Asia including North Korea doesn't have detailed environmental information, and has not built environmental classification map. Therefore, this study presents a bioclimatic map of Northeast Asia based on statistical clustering of bioclimate data. Bioclim data ver1.4 which provided by WorldClim were considered for inclusion in a model. Eight of the most relevant climate variables were selected by correlation analysis, based on previous studies. Principal Components Analysis (PCA) was used to explain 86% of the variation into three independent dimensions, which were subsequently clustered using an ISODATA clustering. The bioclimatic zone of Northeast Asia could consist of 29, 35, and 50 zones. This bioclimatic map has a 30' resolution. To assess the accuracy, the correlation coefficient was calculated between the first principal component values of the classification variables and the vegetation index, Gross Primary Production (GPP). It shows about 0.5 Pearson correlation coefficient. This study constructed Northeast Asia bioclimatic map by statistical method with high resolution, but in order to better reflect the realities, the variety of climate variables should be considered. Also, further studies should do more quantitative and qualitative validation in various ways. Then, this could be used more effectively to support decision making on climate change adaptation.

Spectral Kernel Approach to Study Radiative Response of Climate Variables and Interannual Variability of Reflected Solar Spectrum

NASA Technical Reports Server (NTRS)

Jin, Zhonghai; Wielicki, Bruce A.; Loukachine, Constantin; Charlock, Thomas P.; Young, David; Noeel, Stefan

2011-01-01

The radiative kernel approach provides a simple way to separate the radiative response to different climate parameters and to decompose the feedback into radiative and climate response components. Using CERES/MODIS/Geostationary data, we calculated and analyzed the solar spectral reflectance kernels for various climate parameters on zonal, regional, and global spatial scales. The kernel linearity is tested. Errors in the kernel due to nonlinearity can vary strongly depending on climate parameter, wavelength, surface, and solar elevation; they are large in some absorption bands for some parameters but are negligible in most conditions. The spectral kernels are used to calculate the radiative responses to different climate parameter changes in different latitudes. The results show that the radiative response in high latitudes is sensitive to the coverage of snow and sea ice. The radiative response in low latitudes is contributed mainly by cloud property changes, especially cloud fraction and optical depth. The large cloud height effect is confined to absorption bands, while the cloud particle size effect is found mainly in the near infrared. The kernel approach, which is based on calculations using CERES retrievals, is then tested by direct comparison with spectral measurements from Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) (a different instrument on a different spacecraft). The monthly mean interannual variability of spectral reflectance based on the kernel technique is consistent with satellite observations over the ocean, but not over land, where both model and data have large uncertainty. RMS errors in kernel ]derived monthly global mean reflectance over the ocean compared to observations are about 0.001, and the sampling error is likely a major component.

Simulating streamflow in ungauged basins under a changing climate: The importance of landscape characteristics

NASA Astrophysics Data System (ADS)

Teutschbein, Claudia; Grabs, Thomas; Laudon, Hjalmar; Karlsen, Reinert H.; Bishop, Kevin

2018-06-01

In this paper we explored how landscape characteristics such as topography, geology, soils and land cover influence the way catchments respond to changing climate conditions. Based on an ensemble of 15 regional climate models bias-corrected with a distribution-mapping approach, present and future streamflow in 14 neighboring and rather similar catchments in Northern Sweden was simulated with the HBV model. We established functional relationships between a range of landscape characteristics and projected changes in streamflow signatures. These were then used to analyze hydrological consequences of physical perturbations in a hypothetically ungauged basin in a climate change context. Our analysis showed a strong connection between the forest cover extent and the sensitivity of different components of a catchment's hydrological regime to changing climate conditions. This emphasizes the need to redefine forestry goals and practices in advance of climate change-related risks and uncertainties.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Wavelet-based time series bootstrap model for multidecadal streamflow simulation using climate indicators

NASA Astrophysics Data System (ADS)

Erkyihun, Solomon Tassew; Rajagopalan, Balaji; Zagona, Edith; Lall, Upmanu; Nowak, Kenneth

2016-05-01

A model to generate stochastic streamflow projections conditioned on quasi-oscillatory climate indices such as Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO) is presented. Recognizing that each climate index has underlying band-limited components that contribute most of the energy of the signals, we first pursue a wavelet decomposition of the signals to identify and reconstruct these features from annually resolved historical data and proxy based paleoreconstructions of each climate index covering the period from 1650 to 2012. A K-Nearest Neighbor block bootstrap approach is then developed to simulate the total signal of each of these climate index series while preserving its time-frequency structure and marginal distributions. Finally, given the simulated climate signal time series, a K-Nearest Neighbor bootstrap is used to simulate annual streamflow series conditional on the joint state space defined by the simulated climate index for each year. We demonstrate this method by applying it to simulation of streamflow at Lees Ferry gauge on the Colorado River using indices of two large scale climate forcings: Pacific Decadal Oscillation (PDO) and Atlantic Multi-decadal Oscillation (AMO), which are known to modulate the Colorado River Basin (CRB) hydrology at multidecadal time scales. Skill in stochastic simulation of multidecadal projections of flow using this approach is demonstrated.

Northward shift of the agricultural climate zone under 21st-century global climate change.

PubMed

King, Myron; Altdorff, Daniel; Li, Pengfei; Galagedara, Lakshman; Holden, Joseph; Unc, Adrian

2018-05-21

As agricultural regions are threatened by climate change, warming of high latitude regions and increasing food demands may lead to northward expansion of global agriculture. While socio-economic demands and edaphic conditions may govern the expansion, climate is a key limiting factor. Extant literature on future crop projections considers established agricultural regions and is mainly temperature based. We employed growing degree days (GDD), as the physiological link between temperature and crop growth, to assess the global northward shift of agricultural climate zones under 21 st -century climate change. Using ClimGen scenarios for seven global climate models (GCMs), based on greenhouse gas (GHG) emissions and transient GHGs, we delineated the future extent of GDD areas, feasible for small cereals, and assessed the projected changes in rainfall and potential evapotranspiration. By 2099, roughly 76% (55% to 89%) of the boreal region might reach crop feasible GDD conditions, compared to the current 32%. The leading edge of the feasible GDD will shift northwards up to 1200 km by 2099 while the altitudinal shift remains marginal. However, most of the newly gained areas are associated with highly seasonal and monthly variations in climatic water balances, a critical component of any future land-use and management decisions.

Holistic uncertainty analysis in river basin modeling for climate vulnerability assessment

NASA Astrophysics Data System (ADS)

Taner, M. U.; Wi, S.; Brown, C.

2017-12-01

The challenges posed by uncertain future climate are a prominent concern for water resources managers. A number of frameworks exist for assessing the impacts of climate-related uncertainty, including internal climate variability and anthropogenic climate change, such as scenario-based approaches and vulnerability-based approaches. While in many cases climate uncertainty may be dominant, other factors such as future evolution of the river basin, hydrologic response and reservoir operations are potentially significant sources of uncertainty. While uncertainty associated with modeling hydrologic response has received attention, very little attention has focused on the range of uncertainty and possible effects of the water resources infrastructure and management. This work presents a holistic framework that allows analysis of climate, hydrologic and water management uncertainty in water resources systems analysis with the aid of a water system model designed to integrate component models for hydrology processes and water management activities. The uncertainties explored include those associated with climate variability and change, hydrologic model parameters, and water system operation rules. A Bayesian framework is used to quantify and model the uncertainties at each modeling steps in integrated fashion, including prior and the likelihood information about model parameters. The framework is demonstrated in a case study for the St. Croix Basin located at border of United States and Canada.

High-resolution IP25-based reconstruction of sea-ice variability in the western North Pacific and Bering Sea during the past 18,000 years

NASA Astrophysics Data System (ADS)

Méheust, Marie; Stein, Ruediger; Fahl, Kirsten; Max, Lars; Riethdorf, Jan-Rainer

2016-04-01

Due to its strong influence on heat and moisture exchange between the ocean and the atmosphere, sea ice is an essential component of the global climate system. In the context of its alarming decrease in terms of concentration, thickness and duration, understanding the processes controlling sea-ice variability and reconstructing paleo-sea-ice extent in polar regions have become of great interest for the scientific community. In this study, for the first time, IP25, a recently developed biomarker sea-ice proxy, was used for a high-resolution reconstruction of the sea-ice extent and its variability in the western North Pacific and western Bering Sea during the past 18,000 years. To identify mechanisms controlling the sea-ice variability, IP25 data were associated with published sea-surface temperature as well as diatom and biogenic opal data. The results indicate that a seasonal sea-ice cover existed during cold periods (Heinrich Stadial 1 and Younger Dryas), whereas during warmer intervals (Bølling-Allerød and Holocene) reduced sea ice or ice-free conditions prevailed in the study area. The variability in sea-ice extent seems to be linked to climate anomalies and sea-level changes controlling the oceanographic circulation between the subarctic Pacific and the Bering Sea, especially the Alaskan Stream injection though the Aleutian passes.

Fires: Pushing the Reset Button or a Flash in the Pan?

NASA Astrophysics Data System (ADS)

MacDonald, L. H.; Wagenbrenner, J. W.; Robichaud, P. R.; Nelson, P. A.; Kampf, S. K.; Brogan, D. J.

2016-12-01

High and moderate severity wildfires can reduce infiltration rates to less than 10 mm/hr, and the resulting surface runoff can increase small-scale peak flows by one or more orders of magnitude. Fires can increase hillslope erosion rates by several orders of magnitude, but this increase is less linear with rainfall intensity because it also depends on sediment supply and detachment processes as well as transport capacity. These localized and shorter-term effects have been relatively well documented, but there is much more uncertainty in how these fire-induced changes can lead to larger-scale and/or longer-term effects. The goal of this presentation is to provide a process-based analysis of how, where, and when wildfires can cause either longer-term or larger-scale changes, effectively resetting the system as opposed to a more transient "flash in the pan". An understanding of vegetation, climatic, and geomorphic dynamics are are critical for predicting larger-scale and longer-term effects. First is the potential for the vegetation to return to pre-fire conditions, and this depends on vegetation type, spatial extent of the fire, and if the pre-fire vegetation is marginalized by climate change, land use, or other factors. The trajectory of post-fire regrowth controls the duration of increased runoff and erosion as well as the size and severity of future fires, which then sets the scene for longer-term hydrologic and geomorphic change. Climate defines the dominant storm type and how they match up with the spatial extent of a fire. Historic data help estimate the extent and magnitude of post-fire rainfall, but there is a strong stochastic component and the more extreme events are of greatest concern. Geomorphic controls on larger-scale effects include the valley and drainage network characteristics that help govern the storage and delivery of water and sediment. Assessing each component involves multiple site factors, but the biggest problem is understanding their complex interactions to predict resource impacts, landscape change over different temporal and spatial scales, and the potential to ameliorate adverse impacts. Data from multiple field studies are used to illustrate the range of post-fire effects, selected interactions of the different components, and identify key research needs.

Analysis and Experimental Investigation of Optimum Design of Thermoelectric Cooling/Heating System for Car Seat Climate Control (CSCC)

NASA Astrophysics Data System (ADS)

Elarusi, Abdulmunaem; Attar, Alaa; Lee, HoSung

2018-02-01

The optimum design of a thermoelectric system for application in car seat climate control has been modeled and its performance evaluated experimentally. The optimum design of the thermoelectric device combining two heat exchangers was obtained by using a newly developed optimization method based on the dimensional technique. Based on the analytical optimum design results, commercial thermoelectric cooler and heat sinks were selected to design and construct the climate control heat pump. This work focuses on testing the system performance in both cooling and heating modes to ensure accurate analytical modeling. Although the analytical performance was calculated using the simple ideal thermoelectric equations with effective thermoelectric material properties, it showed very good agreement with experiment for most operating conditions.

CICE, The Los Alamos Sea Ice Model

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

Hunke, Elizabeth; Lipscomb, William; Jones, Philip

The Los Alamos sea ice model (CICE) is the result of an effort to develop a computationally efficient sea ice component for a fully coupled atmosphere–land–ocean–ice global climate model. It was originally designed to be compatible with the Parallel Ocean Program (POP), an ocean circulation model developed at Los Alamos National Laboratory for use on massively parallel computers. CICE has several interacting components: a vertical thermodynamic model that computes local growth rates of snow and ice due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of ice dynamics, which predicts the velocity field of themore » ice pack based on a model of the material strength of the ice; an incremental remapping transport model that describes horizontal advection of the areal concentration, ice and snow volume and other state variables; and a ridging parameterization that transfers ice among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the ice ecosystem. The CICE sea ice model is used for climate research as one component of complex global earth system models that include atmosphere, land, ocean and biogeochemistry components. It is also used for operational sea ice forecasting in the polar regions and in numerical weather prediction models.« less

Development of an integrated model for the Campaspe catchment: a tool to help improve understanding of the interaction between society, policy, farming decision, ecology, hydrology and climate

NASA Astrophysics Data System (ADS)

Iwanaga, Takuya; Zare, Fateme; Croke, Barry; Fu, Baihua; Merritt, Wendy; Partington, Daniel; Ticehurst, Jenifer; Jakeman, Anthony

2018-06-01

Management of water resources requires understanding of the hydrology and hydrogeology, as well as the policy and human drivers and their impacts. This understanding requires relevant inputs from a wide range of disciplines, which will vary depending on the specific case study. One approach to gain understanding of the impact of climate and society on water resources is through the use of an integrated modelling process that engages stakeholders and experts in specifics of problem framing, co-design of the underpinning conceptual model, and discussion of the ensuing results. In this study, we have developed such an integrated modelling process for the Campaspe basin in northern Victoria, Australia. The numerical model built has a number of components:

• - Node/link based surface water hydrology module based on the IHACRES rainfall-streamflow model
• - Distributed groundwater model for the lower catchment (MODFLOW)
• - Farm decision optimisation module (to determine irrigation requirements)
• - Policy module (setting conditions on availability of water based on existing rules)
• - Ecology module (determining the impacts of available streamflow on platypus, fish and river red gum trees)

An Investigation of the Relationship between the Components of School Climate and Leadership Behaviors on Student Achievement: Urban School Districts in the Mid-Atlantic Region

ERIC Educational Resources Information Center

Collins, Karmen J.

2015-01-01

The purpose of this research study was to investigate the relationship between the components of school climate and leadership behaviors on student achievement in an urban school district in the mid-atlantic region. School climate and leadership behaviors for the participating school districts was determined by the School Climate Survey (Corner…

A review on vegetation models and applicability to climate simulations at regional scale

NASA Astrophysics Data System (ADS)

Myoung, Boksoon; Choi, Yong-Sang; Park, Seon Ki

2011-11-01

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson's rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.

Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances

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

Holm, Jennifer A.; Van Bloem, Skip J.; Larocque, Guy R.

Caribbean tropical forests are subject to hurricane disturbances of great variability. In addition to natural storm incongruity, climate change can alter storm formation, duration, frequency, and intensity. This model -based investigation assessed the impacts of multiple storms of different intensities and occurrence frequencies on the long-term dynamics of subtropical dry forests in Puerto Rico. Using the previously validated individual-based gap model ZELIG-TROP, we developed a new hurricane damage routine and parameterized it with site- and species-specific hurricane effects. A baseline case with the reconstructed historical hurricane regime represented the control condition. Ten treatment cases, reflecting plausible shifts in hurricane regimes,more » manipulated both hurricane return time (i.e. frequency) and hurricane intensity. The treatment-related change in carbon storage and fluxes were reported as changes in aboveground forest biomass (AGB), net primary productivity (NPP), and in the aboveground carbon partitioning components, or annual carbon accumulation (ACA). Increasing the frequency of hurricanes decreased aboveground biomass by between 5% and 39%, and increased NPP between 32% and 50%. Decadal-scale biomass fluctuations were damped relative to the control. In contrast, increasing hurricane intensity did not create a large shift in the long-term average forest structure, NPP, or ACA from that of historical hurricane regimes, but produced large fluctuations in biomass. Decreasing both the hurricane intensity and frequency by 50% produced the highest values of biomass and NPP. For the control scenario and with increased hurricane intensity, ACA was negative, which indicated that the aboveground forest components acted as a carbon source. However, with an increase in the frequency of storms or decreased storms, the total ACA was positive due to shifts in leaf production, annual litterfall, and coarse woody debris inputs, indicating a carbon sink into the forest over the long-term. The carbon loss from each hurricane event, in all scenarios, always recovered over sufficient time. Our results suggest that subtropical dry forests will remain resilient to hurricane disturbance. However carbon stocks will decrease if future climates increase hurricane frequency by 50% or more.« less

Understanding the Impact of Ground Water Treatment and Evapotranspiration Parameterizations in the NCEP Climate Forecast System (CFS) on Warm Season Predictions

NASA Astrophysics Data System (ADS)

Ek, M. B.; Yang, R.

2016-12-01

Skillful short-term weather forecasts, which rely heavily on quality atmospheric initial conditions, have a fundamental limit of about two weeks owing to the chaotic nature of the atmosphere. Useful forecasts at sub-seasonal to seasonal time scales, on the other hand, require well-simulated large-scale atmospheric response to slowly varying lower boundary forcings from both the ocean and land surface. The critical importance of ocean has been recognized, where the ocean indices have been used in a variety of climate applications. In contrast, the impact of land surface anomalies, especially soil moisture and associated evaporation, has been proven notably difficult to demonstrate. The Noah Land Surface Model (LSM) is the land component of NCEP CFS version 2 (CFSv2) used for seasonal predictions. The Noah LSM originates from the Oregon State University (OSU) LSM. The evaporation control in the Noah LSM is based on the Penman-Monteith equation, which takes into account the solar radiation, relative humidity, air temperature, and soil moisture effects. The Noah LSM is configured with four soil layers with a fixed depth of 2 meters and free drainage at the bottom soil layer. This treatment assumes that the soil water table depth is well within the specified range, and also potentially misrepresents the soil moisture memory effects at seasonal time scales. To overcome the limitation, an unconfined aquifer is attached to the bottom of the soil to allow the water table to move freely up and down. In addition, in conjunction with the water table, an alternative Ball-Berry photosynthesis-based evaporation parameterization is examined to evaluate the impact from using a different evaporation control methodology. Focusing on the 2011 and 2012 intense summer droughts in the central US, seasonal ensemble forecast experiments with early May initial conditions are carried out for the two years using an enhanced version of CFSv2, where the atmospheric component of the CFSv2 is coupled to the Noah Multiple-Parameterization (Noah-MP) land model. The Noah-MP has different options for ground water and evaporation control parameterizations. The differences will be presented and results will be discussed.

Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances

NASA Astrophysics Data System (ADS)

Holm, Jennifer A.; Van Bloem, Skip J.; Larocque, Guy R.; Shugart, Herman H.

2017-02-01

Caribbean tropical forests are subject to hurricane disturbances of great variability. In addition to natural storm incongruity, climate change can alter storm formation, duration, frequency, and intensity. This model-based investigation assessed the impacts of multiple storms of different intensities and occurrence frequencies on the long-term dynamics of subtropical dry forests in Puerto Rico. Using the previously validated individual-based gap model ZELIG-TROP, we developed a new hurricane damage routine and parameterized it with site- and species-specific hurricane effects. A baseline case with the reconstructed historical hurricane regime represented the control condition. Ten treatment cases, reflecting plausible shifts in hurricane regimes, manipulated both hurricane return time (i.e. frequency) and hurricane intensity. The treatment-related change in carbon storage and fluxes were reported as changes in aboveground forest biomass (AGB), net primary productivity (NPP), and in the aboveground carbon partitioning components, or annual carbon accumulation (ACA). Increasing the frequency of hurricanes decreased aboveground biomass by between 5% and 39%, and increased NPP between 32% and 50%. Decadal-scale biomass fluctuations were damped relative to the control. In contrast, increasing hurricane intensity did not create a large shift in the long-term average forest structure, NPP, or ACA from that of historical hurricane regimes, but produced large fluctuations in biomass. Decreasing both the hurricane intensity and frequency by 50% produced the highest values of biomass and NPP. For the control scenario and with increased hurricane intensity, ACA was negative, which indicated that the aboveground forest components acted as a carbon source. However, with an increase in the frequency of storms or decreased storms, the total ACA was positive due to shifts in leaf production, annual litterfall, and coarse woody debris inputs, indicating a carbon sink into the forest over the long-term. The carbon loss from each hurricane event, in all scenarios, always recovered over sufficient time. Our results suggest that subtropical dry forests will remain resilient to hurricane disturbance. However carbon stocks will decrease if future climates increase hurricane frequency by 50% or more.

Shifts in biomass and productivity for a subtropical dry forest in response to simulated elevated hurricane disturbances

DOE PAGES

Holm, Jennifer A.; Van Bloem, Skip J.; Larocque, Guy R.; ...

2017-02-07

Caribbean tropical forests are subject to hurricane disturbances of great variability. In addition to natural storm incongruity, climate change can alter storm formation, duration, frequency, and intensity. This model -based investigation assessed the impacts of multiple storms of different intensities and occurrence frequencies on the long-term dynamics of subtropical dry forests in Puerto Rico. Using the previously validated individual-based gap model ZELIG-TROP, we developed a new hurricane damage routine and parameterized it with site- and species-specific hurricane effects. A baseline case with the reconstructed historical hurricane regime represented the control condition. Ten treatment cases, reflecting plausible shifts in hurricane regimes,more » manipulated both hurricane return time (i.e. frequency) and hurricane intensity. The treatment-related change in carbon storage and fluxes were reported as changes in aboveground forest biomass (AGB), net primary productivity (NPP), and in the aboveground carbon partitioning components, or annual carbon accumulation (ACA). Increasing the frequency of hurricanes decreased aboveground biomass by between 5% and 39%, and increased NPP between 32% and 50%. Decadal-scale biomass fluctuations were damped relative to the control. In contrast, increasing hurricane intensity did not create a large shift in the long-term average forest structure, NPP, or ACA from that of historical hurricane regimes, but produced large fluctuations in biomass. Decreasing both the hurricane intensity and frequency by 50% produced the highest values of biomass and NPP. For the control scenario and with increased hurricane intensity, ACA was negative, which indicated that the aboveground forest components acted as a carbon source. However, with an increase in the frequency of storms or decreased storms, the total ACA was positive due to shifts in leaf production, annual litterfall, and coarse woody debris inputs, indicating a carbon sink into the forest over the long-term. The carbon loss from each hurricane event, in all scenarios, always recovered over sufficient time. Our results suggest that subtropical dry forests will remain resilient to hurricane disturbance. However carbon stocks will decrease if future climates increase hurricane frequency by 50% or more.« less

Climate, Water and Energy in the Nordic Countries

NASA Astrophysics Data System (ADS)

Snorrason, A.; Jonsdottir, J. F.

2003-04-01

In light of the recent IPCC Climate Change Assessment and recent progress made in meteorological and hydrological modelling, the directors of the Nordic hydrological institutes (CHIN) initiated a research project "Climate, Water and Energy" (CWE) with funding from the Nordic Energy Research and the Nordic Council of Ministers focusing on climatic impact assessment in the energy sector. Climatic variability and change affect the hydrological systems, which in turn affect the energy sector, this will increase the risk associated with the development and use of water resources in the Nordic countries. Within the CWE project four thematic groups work on this issue of climatic change and how changes in precipitation and temperature will have direct influences on runoff. A primary aim of the CWE climate group is to derive a common scenario or a "best-guess" estimate of climate change in northern Europe and Greenland, based on recent regional climate change experiments and representing the change from 1990 to 2050 under the IPCC SRES B2 emission scenario. A data set, along with the most important information for using the scenario is available at the project web site. The glacier group has chosen 8 glaciers from Greenland, Iceland, Norway and Sweden for an analysis of the response of glaciers to climate changes. Mass balance and dynamical changes, corresponding to the common scenario for climate changes, will be modelled and effects on glacier hydrology will be estimated. The long time series group has reported on the status of time series analysis in the Nordic countries. The group will select and quality control time series of stream flow to be included in the Nordic component of the database FRIEND. Also the group will collect information on time series for other variables and these series will be systematically analysed with respect to trend and other long-term changes. The hydrological modelling group has reported on "Climate change impacts on water resources in the Nordic countries - State of the art and discussion of principles". The group will compare different hydrological models and discuss uncertainties in models and climate scenarios, while production of new results based on the composite scenario from the CWE-climate group depends on other projects. The product of the project will be an in-depth analysis of the present status of research and know-how in the sphere of climatic and hydrological research in the Nordic countries. It will be a synthesis and integration of present research with focus on the needs of the energy sector. It will also identify and prioritise key future research areas that are of benefit to the energy sector.

Development of climate data storage and processing model

NASA Astrophysics Data System (ADS)

Okladnikov, I. G.; Gordov, E. P.; Titov, A. G.

2016-11-01

We present a storage and processing model for climate datasets elaborated in the framework of a virtual research environment (VRE) for climate and environmental monitoring and analysis of the impact of climate change on the socio-economic processes on local and regional scales. The model is based on a «shared nothings» distributed computing architecture and assumes using a computing network where each computing node is independent and selfsufficient. Each node holds a dedicated software for the processing and visualization of geospatial data providing programming interfaces to communicate with the other nodes. The nodes are interconnected by a local network or the Internet and exchange data and control instructions via SSH connections and web services. Geospatial data is represented by collections of netCDF files stored in a hierarchy of directories in the framework of a file system. To speed up data reading and processing, three approaches are proposed: a precalculation of intermediate products, a distribution of data across multiple storage systems (with or without redundancy), and caching and reuse of the previously obtained products. For a fast search and retrieval of the required data, according to the data storage and processing model, a metadata database is developed. It contains descriptions of the space-time features of the datasets available for processing, their locations, as well as descriptions and run options of the software components for data analysis and visualization. The model and the metadata database together will provide a reliable technological basis for development of a high- performance virtual research environment for climatic and environmental monitoring.

Nevada Infrastructure for Climate Change Science, Education, and Outreach

NASA Astrophysics Data System (ADS)

Dana, G. L.; Lancaster, N.; Mensing, S. A.; Piechota, T.

2008-12-01

The Great Basin is characterized by complex basin and range topography, arid to semiarid climate, and a history of sensitivity to climate change. Mountain areas comprise about 10% of the landscape, yet are the areas of highest precipitation and generate 85% of groundwater recharge and most surface runoff. These characteristics provide an ideal natural laboratory to study the effects of climate change. The Nevada system of Higher Education, including the University of Nevada, Las Vegas, the University of Nevada, Reno, the Desert Research Institute, and Nevada State College have begun a five year research and infrastructure building program, funded by the National Science Foundation Experimental Program to Stimulate Competitive Research (NSF EPSCoR) with the vision "to create a statewide interdisciplinary program and virtual climate change center that will stimulate transformative research, education, and outreach on the effects of regional climate change on ecosystem resources (especially water) and support use of this knowledge by policy makers and stakeholders." Six major strategies are proposed to develop infrastructure needs and attain our vision: 1) Develop a capability to model climate change at a regional and sub-regional scale(Climate Modeling Component) 2) Analyze effects on ecosystems and disturbance regimes (Ecological Change Component) 3) Quantify and model changes in water balance and resources under climate change (Water Resources Component) 4) Assess effects on human systems and enhance policy making and outreach to communities and stakeholders (Policy, Decision-Making, and Outreach Component) 5) Develop a data portal and software to support interdisciplinary research via integration of data from observational networks and modeling (Cyberinfrastructure Component) and 6) Train teachers and students at all levels and provide public outreach in climate change issues (Education Component). Two new climate observational transects will be established across Great Basin Ranges, one anticipated on a mountain range in southern Nevada and the second to be located in north-central Nevada. Climatic, hydrologic and ecological data from these transects will be downloaded into high capacity data storage units and made available to researchers through creation of the Nevada climate change portal. Our research will aim to answer two interdisciplinary science questions key to understanding the effects of future climate change on Great Basin mountain ecosystems and the potential management strategies for responding to these changes: 1) How will climate change affect water resources and linked ecosystem resources and human systems? And 2) How will climate change affect disturbance regimes (e.g., wildland fires, invasive species, insect outbreaks, droughts) and linked systems? Infrastructure developed through this project will provide new interdisciplinary capability to detect, analyze, and model effects of regional climate change in mountainous regions of the west and provide a major contribution to existing climate change research and monitoring networks.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Sensitivity of river fishes to climate change: The role of hydrological stressors on habitat range shifts.

PubMed

Segurado, Pedro; Branco, Paulo; Jauch, Eduardo; Neves, Ramiro; Ferreira, M Teresa

2016-08-15

Climate change will predictably change hydrological patterns and processes at the catchment scale, with impacts on habitat conditions for fish. The main goal of this study is to assess how shifts in fish habitat favourability under climate change scenarios are affected by hydrological stressors. The interplay between climate and hydrological stressors has important implications in river management under climate change because management actions to control hydrological parameters are more feasible than controlling climate. This study was carried out in the Tamega catchment of the Douro basin. A set of hydrological stressor variables were generated through a process-based modelling based on current climate data (2008-2014) and also considering a high-end future climate change scenario. The resulting parameters, along with climatic and site-descriptor variables were used as explanatory variables in empirical habitat models for nine fish species using boosted regression trees. Models were calibrated for the whole Douro basin using 254 fish sampling sites and predictions under future climate change scenarios were made for the Tamega catchment. Results show that models using climatic variables but not hydrological stressors produce more stringent predictions of future favourability, predicting more distribution contractions or stronger range shifts. The use of hydrological stressors strongly influences projections of habitat favourability shifts; the integration of these stressors in the models thinned shifts in range due to climate change. Hydrological stressors were retained in the models for most species and had a high importance, demonstrating that it is important to integrate hydrology in studies of impacts of climate change on freshwater fishes. This is a relevant result because it means that management actions to control hydrological parameters in rivers will have an impact on the effects of climate change and may potentially be helpful to mitigate its negative effects on fish populations and assemblages. Copyright © 2016 Elsevier B.V. All rights reserved.

Representing Northern Peatland Hydrology and Biogeochemistry with ALM Land Surface Model

NASA Astrophysics Data System (ADS)

Shi, X.; Ricciuto, D. M.; Thornton, P. E.; Hanson, P. J.; Xu, X.; Mao, J.; Warren, J.; Yuan, F.; Norby, R. J.; Sebestyen, S.; Griffiths, N.; Weston, D. J.; Walker, A.

2017-12-01

Northern peatlands are likely to be important in future carbon cycle-climate feedbacks due to their large carbon pool and vulnerability to hydrological change. Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. Firstly, we introduce a new configuration of the land model (ALM) of Accelerated Climate model for Energy (ACME), which includes a fully prognostic water table calculation for a vegetated peatland. Secondly, we couple our new hydrology treatment with vertically structured soil organic matter pool, and the addition of components from methane biogeochemistry. Thirdly, we introduce a new PFT for mosses and implement the water content dynamics and physiology of mosses. We inform and test our model based on SPRUCE experiment to get the reasonable results for the seasonal dynamics water table depths, water content dynamics and physiology of mosses, and correct soil carbon profiles. Then, we use our new model structure to test the how the water table depth and CH4 emission will respond to elevated CO2 and different warming scenarios.

A climate sensitive model of carbon transfer through atmosphere, vegetation and soil in managed forest ecosystems

NASA Astrophysics Data System (ADS)

Loustau, D.; Moreaux, V.; Bosc, A.; Trichet, P.; Kumari, J.; Rabemanantsoa, T.; Balesdent, J.; Jolivet, C.; Medlyn, B. E.; Cavaignac, S.; Nguyen-The, N.

2012-12-01

For predicting the future of the forest carbon cycle in forest ecosystems, it is necessary to account for both the climate and management impacts. Climate effects are significant not only at a short time scale but also at the temporal horizon of a forest life cycle e.g. through shift in atmospheric CO2 concentration, temperature and precipitation regimes induced by the enhanced greenhouse effect. Intensification of forest management concerns an increasing fraction of temperate and tropical forests and untouched forests represents only one third of the present forest area. Predicting tools are therefore needed to project climate and management impacts over the forest life cycle and understand the consequence of management on the forest ecosystem carbon cycle. This communication summarizes the structure, main components and properties of a carbon transfer model that describes the processes controlling the carbon cycle of managed forest ecosystems. The model, GO+, links three main components, (i) a module describing the vegetation-atmosphere mass and energy exchanges in 3D, (ii) a plant growth module and a (iii) soil carbon dynamics module in a consistent carbon scheme of transfer from atmosphere back into the atmosphere. It was calibrated and evaluated using observed data collected on coniferous and broadleaved forest stands. The model predicts the soil, water and energy balance of entire rotations of managed stands from the plantation to the final cut and according to a range of management alternatives. It accounts for the main soil and vegetation management operations such as soil preparation, understorey removal, thinnings and clearcutting. Including the available knowledge on the climatic sensitivity of biophysical and biogeochemical processes involved in atmospheric exchanges and carbon cycle of forest ecosystems, GO+ can produce long-term backward or forward simulations of forest carbon and water cycles under a range of climate and management scenarios. This model applications to the prediction and analysis of climate scenarios impacts on southwestern European forests underlines the role of management alternatives, precipitation regime, CO2 concentration and atmospheric humidity .Frequency of soil preparation operations and understorey management play a major role in controlling the net carbon flux into the atmosphere at the juvenile stage ( 0 to 10 y-old) whereas climate and rotation duration control the functioning of adult phase. The model predicts that a drier and warmer climate will reduce the forest productivity and deplete soil and carbon stocks in managed forest from Southwestern Europe within decades, such effects being amplified for most intensive management alternatives. This work was part of the European research project GHG-Europe (EU contract No. 244122) and the French national project FAST co-funded by the Ecology, Agriculture and Forestry Ministries and the Region Aquitaine.

Global ice-sheet system interlocked by sea level

NASA Astrophysics Data System (ADS)

Denton, George H.; Hughes, Terence J.; Karlén, Wibjörn

1986-07-01

Denton and Hughes (1983, Quaternary Research20, 125-144) postulated that sea level linked a global ice-sheet system with both terrestrial and grounded marine components during late Quaternary ice ages. Summer temperature changes near Northern Hemisphere melting margins initiated sea-level fluctuations that controlled marine components in both polar hemispheres. It was further proposed that variations of this ice-sheet system amplified and transmitted Milankovitch summer half-year insolation changes between 45 and 75°N into global climatic changes. New tests of this hypothesis implicate sea level as a major control of the areal extent of grounded portions of the Antarctic Ice Sheet, thus fitting the concept of a globally interlocked ice-sheet system. But recent atmospheric modeling results ( Manabe and Broccoli, 1985, Journal of Geophysical Research90, 2167-2190) suggest that factors other than areal changes of the grounded Antarctic Ice Sheet strongly influenced Southern Hemisphere climate and terminated the last ice age simultaneously in both polar hemispheres. Atmospheric carbon dioxide linked to high-latitude oceans is the most likely candidate ( Shackleton and Pisias, 1985, Atmospheric carbon dioxide, orbital forcing, and climate. In "The Carbon Cycle and Atmospheric CO 2: Natural Variations Archean to Present" (E. T. Sundquest and W. S. Broecker, Eds.), pp. 303-318. Geophysical Monograph 32, American Geophysical Union, Washington, D.C.), but another potential influence was high-frequency climatic oscillations (2500 yr). It is postulated that variations in atmospheric carbon dioxide acted through an Antarctic ice shelf linked to the grounded ice sheet to produce and terminate Southern Hemisphere ice-age climate. It is further postulated that Milankovitch summer insolation combined with a warm high-frequency oscillation caused marked recession of Northern Hemisphere ice-sheet melting margins and the North Atlantic polar front about 14,000 14C yr B.P. This permitted renewed formation of North Atlantic Deep Water, which could well have controlled atmospheric carbon dioxide ( W. S. Broecker, D. M. Peteet, and D. Rind, 1985, Nature ( London) 315, 21-26). Combined melting and consequent sea-level rise from the three warming factors initiated irreversible collapse of the interlocked global ice-sheet system, which was at its largest but most vulnerable configuration.

Land Use, climate change and BIOdiversity in cultural landscapes (LUBIO): Assessing feedbacks and promoting land-use strategies towards a viable future

NASA Astrophysics Data System (ADS)

Dullinger, Iwona; Bohner, Andreas; Dullinger, Stefan; Essl, Franz; Gaube, Veronika; Haberl, Helmut; Mayer, Andreas; Plutzar, Christoph; Remesch, Alexander

2016-04-01

Land-use and climate change are important, pervasive drivers of global environmental change and pose major threats to global biodiversity. Research to date has mostly focused either on land-use change or on climate change, but rarely on the interactions between both drivers, even though it is expected that systemic feedbacks between changes in climate and land use will have important effects on biodiversity. In particular, climate change will not only alter the pool of plant and animal species capable of thriving in a specific area, it will also force land owners to reconsider their land use decisions. Such changes in land-use practices may have major additional effects on local and regional species composition and abundance. In LUBIO, we will explore the anticipated systemic feedbacks between (1) climate change, (2) land owner's decisions on land use, (3) land-use change, and (4) changes in biodiversity patterns during the coming decades in a regional context which integrates a broad range of land use practices and intensity gradients. To achieve this goal, an integrated socioecological model will be designed and implemented, consisting of three principal components: (1) an agent based model (ABM) that simulates decisions of important actors, (2) a spatially explicit GIS model that translates these decisions into changes in land cover and land use patterns, and (3) a species distribution model (SDM) that calculates changes in biodiversity patterns following from both changes in climate and the land use decisions as simulated in the ABM. Upon integration of these three components, the coupled socioecological model will be used to generate scenarios of future land-use decisions of landowners under climate change and, eventually, the combined effects of climate and land use changes on biodiversity. Model development of the ABM will be supported by a participatory process intended to collect regional and expert knowledge through a series of expert interviews, a series of transdisciplinary participatory modelling workshops, and a questionnaire-based survey targeted at regional farmers. Beside the integrated socioecological model a catalogue of recommended actions will be developed in order to distribute the insights of the research to the most relevant regional stakeholder groups.

Hydrologic sensitivity of headwater catchments to climate and landscape variability

NASA Astrophysics Data System (ADS)

Kelleher, Christa; Wagener, Thorsten; McGlynn, Brian; Nippgen, Fabian; Jencso, Kelsey

2013-04-01

Headwater streams cumulatively represent an extensive portion of the United States stream network, yet remain largely unmonitored and unmapped. As such, we have limited understanding of how these systems will respond to change, knowledge that is important for preserving these unique ecosystems, the services they provide, and the biodiversity they support. We compare responses across five adjacent headwater catchments located in Tenderfoot Creek Experimental Forest in Montana, USA, to understand how local differences may affect the sensitivity of headwaters to change. We utilize global, variance-based sensitivity analysis to understand which aspects of the physical system (e.g., vegetation, topography, geology) control the variability in hydrologic behavior across these basins, and how this varies as a function of time (and therefore climate). Basin fluxes and storages, including evapotranspiration, snow water equivalent and melt, soil moisture and streamflow, are simulated using the Distributed Hydrology-Vegetation-Soil Model (DHSVM). Sensitivity analysis is applied to quantify the importance of different physical parameters to the spatial and temporal variability of different water balance components, allowing us to map similarities and differences in these controls through space and time. Our results show how catchment influences on fluxes vary across seasons (thus providing insight into transferability of knowledge in time), and how they vary across catchments with different physical characteristics (providing insight into transferability in space).

The role of psychosocial working conditions on burnout and its core component emotional exhaustion – a systematic review

PubMed Central

2014-01-01

Aims To analyze the association between psychosocial working conditions and burnout and its core component emotional exhaustion, a systematic literature review was undertaken including cohort studies, case–control studies, and randomized controlled trials. Methods The literature search in Medline and PsycInfo was based on a defined search string and strict exclusion and inclusion criteria. Evaluation of the 5,599 initially identified search hits by two independent reviewers and a detailed quality assessment resulted in six methodologically adequate cohort studies considering the relationship between psychosocial working conditions and burnout (one study) as well as the burnout core component emotional exhaustion (five studies). Results The results of our systematic review point to a relationship between psychosocial working conditions and the development of emotional exhaustion/burnout. Particularly high job demands seem to play a role in the development of emotional exhaustion. However, strong intercorrelations between workplace factors, as a matter of principle, make the identification of a single psychosocial workplace factor (being associated with an especially high or low risk of burnout) difficult. Conclusions Multidimensional approaches including reduction of work demands, enhancement of decision latitude and improving the social climate might be promising for preventing burnout and emotional exhaustion. However, methodologically adequate intervention studies are urgently needed to prove the effectiveness of workplace interventions. PMID:24628839

Soil Moisture-Atmosphere Feedbacks on Atmospheric Tracers: The Effects of Soil Moisture on Precipitation and Near-Surface Chemistry

NASA Astrophysics Data System (ADS)

Tawfik, Ahmed B.

The atmospheric component is described by rapid fluctuations in typical state variables, such as temperature and water vapor, on timescales of hours to days and the land component evolves on daily to yearly timescales. This dissertation examines the connection between soil moisture and atmospheric tracers under varying degrees of soil moisture-atmosphere coupling. Land-atmosphere coupling is defined over the United States using a regional climate model. A newly examined soil moisture-precipitation feedback is identified for winter months extending the previous summer feedback to colder temperature climates. This feedback is driven by the freezing and thawing of soil moisture, leading to coupled land-atmosphere conditions near the freezing line. Soil moisture can also affect the composition of the troposphere through modifying biogenic emissions of isoprene (C5H8). A novel first-order Taylor series decomposition indicates that isoprene emissions are jointly driven by temperature and soil moisture in models. These compounds are important precursors for ozone formation, an air pollutant and a short-lived forcing agent for climate. A mechanistic description of commonly observed relationships between ground-level ozone and meteorology is presented using the concept of soil moisture-temperature coupling regimes. The extent of surface drying was found to be a better predictor of ozone concentrations than temperature or humidity for the Eastern U.S. This relationship is evaluated in a coupled regional chemistry-climate model under several land-atmosphere coupling and isoprene emissions cases. The coupled chemistry-climate model can reproduce the observed soil moisture-temperature coupling pattern, yet modeled ozone is insensitive to changes in meteorology due to the balance between isoprene and the primary atmospheric oxidant, the hydroxyl radical (OH). Overall, this work highlights the importance of soil moisture-atmosphere coupling for previously neglected cold climate regimes, controlling isoprene emissions variability, and providing a processed-based description of observed ozone-meteorology relationships. From the perspective of ozone air quality, the lack of sensitivity of ozone to meteorology suggests a systematic deficiency in chemistry models in high isoprene emission regions. This shortcoming must be addressed to better estimate tropospheric ozone radiative forcing and to understanding how ozone air quality may respond to future warming.

Assessing the effects of climate change on aquatic invasive species.

PubMed

Rahel, Frank J; Olden, Julian D

2008-06-01

Different components of global environmental change are typically studied and managed independently, although there is a growing recognition that multiple drivers often interact in complex and nonadditive ways. We present a conceptual framework and empirical review of the interactive effects of climate change and invasive species in freshwater ecosystems. Climate change is expected to result in warmer water temperatures, shorter duration of ice cover, altered streamflow patterns, increased salinization, and increased demand for water storage and conveyance structures. These changes will alter the pathways by which non-native species enter aquatic systems by expanding fish-culture facilities and water gardens to new areas and by facilitating the spread of species during floods. Climate change will influence the likelihood of new species becoming established by eliminating cold temperatures or winter hypoxia that currently prevent survival and by increasing the construction of reservoirs that serve as hotspots for invasive species. Climate change will modify the ecological impacts of invasive species by enhancing their competitive and predatory effects on native species and by increasing the virulence of some diseases. As a result of climate change, new prevention and control strategies such as barrier construction or removal efforts may be needed to control invasive species that currently have only moderate effects or that are limited by seasonally unfavorable conditions. Although most researchers focus on how climate change will increase the number and severity of invasions, some invasive coldwater species may be unable to persist under the new climate conditions. Our findings highlight the complex interactions between climate change and invasive species that will influence how aquatic ecosystems and their biota will respond to novel environmental conditions.

The influence of competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, Joe; Arora, Vivek

2015-04-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the earth system modelling framework of the Canadian Centre for Climate Modelling and Analysis (CCCma). In its current framework, CTEM uses prescribed fractional coverage of plant functional types (PFTs) in each grid cell. In reality, vegetation cover is continually adjusting to changes in climate, atmospheric composition, and anthropogenic forcing, for example, through human-caused fires and CO2 fertilization. These changes in vegetation spatial patterns occur over timescales of years to centuries as tree migration is a slow process and vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM that includes a representation of competition between PFTs through a modified version of the Lotka-Volterra (L-V) predator-prey equations. The simulated areal extents of CTEM's seven non-crop PFTs are compared with available observation-based estimates, and simulations using unmodified L-V equations (similar to other models like TRIFFID), to demonstrate that the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. Differences remain, however, since representing the multitude of plant species with just seven non-crop PFTs only allows the large scale climatic controls on the distributions of PFTs to be captured. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model and the corresponding driving climate or the limited number of PFTs used to model the terrestrial ecosystem processes. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably with each other and observation-based estimates. These results illustrate that the parametrization of competition between PFTs in CTEM behaves in a reasonably realistic manner while the use of unmodified L-V equations results in unrealistic plant distributions.

Climate changes impact the surface albedo of a forest ecosystem based on MODIS satellite data

NASA Astrophysics Data System (ADS)

Zoran, M. A.; Nemuc, A. V.

2007-10-01

Surface albedo is one of the most important biophysical parameter responsible for energy balance control and the surface temperature and boundary-layer structure of the atmosphere. Forest land surface albedo is also highly variable temporally showing both diurnal as well as seasonal variations. In forest systems, albedo controls the microclimate conditions which affects ecosystem physical, physiological, and biogeochemical processes such as energy balance, evapotranspiration, photosynthesis. Due to anthropogenic and natural factors, land cover and land use changes result is the land surfaces albedo change. The main aim of this paper is to investigate the albedo patterns due to the impact of atmospheric pollution and climate variations of a forest ecosystem Branesti-Cernica, placed to the North-East of Bucharest city, Romania based on satellite Landsat ETM+, IKONOS and MODIS data and climate station observations. Our study focuses on 3 years of data (2003-2005), each of which had a different climatic regime. As the physical climate system is very sensitive to surface albedo, forest ecosystems could significantly feedback to the projected climate change modeling scenarios through albedo changes. The results of this research have a number of applications in weather forecasting, climate change, and forest ecosystem studies.

Assessment of spatiotemporal variations in the fluvial wash-load component in the 21st century with regard to GCM climate change scenarios.

PubMed

Mouri, Goro

2015-11-15

For stream water, in which a relationship exists between wash-load concentration and discharge, an estimate of fine-sediment delivery may be obtained from a traditional fluvial wash-load rating curve. Here, we demonstrate that the remaining wash-load material load can be estimated from a traditional empirical principle on a nationwide scale. The traditional technique was applied to stream water for the whole of Japan. Four typical GCMs were selected from the Coupled Model Intercomparison Project Phase 5 (CMIP5) ensemble to provide the driving fields for the following regional climate models to assess the wash-load component based on rating curves: the Model for Interdisciplinary Research on Climate (MIROC), the Meteorological Research Institute Atmospheric General Circulation Model (MRI-GCM), the Hadley Centre Global Environment Model (HadGEM) and the Geophysical Fluid Dynamics Laboratory (GFDL) climate model. The simulations consisted of an ensemble, including multiple physics configurations and different Representative Concentration Pathways (RCP2.6, RCP4.5 and RCP8.5), which was used to produce monthly datasets for the whole country of Japan. The impacts of future climate changes on fluvial wash load in Japanese stream water were based on the balance of changes in hydrological factors. The annual and seasonal variations of the fluvial wash load were assessed from the result of the ensemble analysis in consideration of the Greenhouse Gas (GHG) emission scenarios. The determined results for the amount of wash load increase range from approximately 20 to 110% in the 2040s, especially along part of the Pacific Ocean and the Sea of Japan regions. In the 2090s, the amount of wash load is projected to increase by more than 50% over the whole of Japan. The assessment indicates that seasonal variation is particularly important because the rainy and typhoon seasons, which include extreme events, are the dominant seasons. Because fluvial wash-load-component turbidity appears to vary exponentially, this phenomenon has an impact on the management of social capital, such as drinking water services. Prediction of the impacts of future climate change on fluvial wash-load sediment is crucial for effective environmental planning and the management of social capital to adapt to the next century. We demonstrate that simulations comprise an ensemble of factors, including multiple physical configurations, associated with the wash-load component for the whole of Japan. Copyright © 2015 Elsevier B.V. All rights reserved.

Performance-based maintenance of gas turbines for reliable control of degraded power systems

NASA Astrophysics Data System (ADS)

Mo, Huadong; Sansavini, Giovanni; Xie, Min

2018-03-01

Maintenance actions are necessary for ensuring proper operations of control systems under component degradation. However, current condition-based maintenance (CBM) models based on component health indices are not suitable for degraded control systems. Indeed, failures of control systems are only determined by the controller outputs, and the feedback mechanism compensates the control performance loss caused by the component deterioration. Thus, control systems may still operate normally even if the component health indices exceed failure thresholds. This work investigates the CBM model of control systems and employs the reduced control performance as a direct degradation measure for deciding maintenance activities. The reduced control performance depends on the underlying component degradation modelled as a Wiener process and the feedback mechanism. To this aim, the controller features are quantified by developing a dynamic and stochastic control block diagram-based simulation model, consisting of the degraded components and the control mechanism. At each inspection, the system receives a maintenance action if the control performance deterioration exceeds its preventive-maintenance or failure thresholds. Inspired by realistic cases, the component degradation model considers random start time and unit-to-unit variability. The cost analysis of maintenance model is conducted via Monte Carlo simulation. Optimal maintenance strategies are investigated to minimize the expected maintenance costs, which is a direct consequence of the control performance. The proposed framework is able to design preventive maintenance actions on a gas power plant, to ensuring required load frequency control performance against a sudden load increase. The optimization results identify the trade-off between system downtime and maintenance costs as a function of preventive maintenance thresholds and inspection frequency. Finally, the control performance-based maintenance model can reduce maintenance costs as compared to CBM and pre-scheduled maintenance.

The Aqua-Planet Experiment (APE): CONTROL SST Simulation

NASA Technical Reports Server (NTRS)

Blackburn, Michael; Williamson, David L.; Nakajima, Kensuke; Ohfuchi, Wataru; Takahashi, Yoshiyuki O.; Hayashi, Yoshi-Yuki; Nakamura, Hisashi; Ishiwatari, Masaki; Mcgregor, John L.; Borth, Hartmut;

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.

The Global Climate Dashboard: a Software Interface to Stream Comprehensive Climate Data

NASA Astrophysics Data System (ADS)

Gardiner, N.; Phillips, M.; NOAA Climate Portal Dashboard

2011-12-01

The Global Climate Dashboard is an integral component of NOAA's web portal to climate data, services, and value-added content for decision-makers, teachers, and the science-attentive public (www.clmate.gov). The dashboard provides a rapid view of observational data that demonstrate climate change and variability, as well as outputs from the Climate Model Intercomparison Project version 3, which was built to support the Intergovernmental Panel on Climate Change fourth assessment. The data shown in the dashboard therefore span a range of climate science disciplines with applications that serve audiences with diverse needs. The dashboard is designed with reusable software components that allow it to be implemented incrementally on a wide range of platforms including desktops, tablet devices, and mobile phones. The underlying software components support live streaming of data and provide a way of encapsulating graph sytles and other presentation details into a device-independent standard format that results in a common visual look and feel across all platforms. Here we describe the pedagogical objectives, technical implementation, and the deployment of the dashboard through climate.gov and partner web sites and describe plans to develop a mobile application using the same framework.

Climate data induced uncertainty in model-based estimations of terrestrial primary productivity

NASA Astrophysics Data System (ADS)

Wu, Zhendong; Ahlström, Anders; Smith, Benjamin; Ardö, Jonas; Eklundh, Lars; Fensholt, Rasmus; Lehsten, Veiko

2017-06-01

Model-based estimations of historical fluxes and pools of the terrestrial biosphere differ substantially. These differences arise not only from differences between models but also from differences in the environmental and climatic data used as input to the models. Here we investigate the role of uncertainties in historical climate data by performing simulations of terrestrial gross primary productivity (GPP) using a process-based dynamic vegetation model (LPJ-GUESS) forced by six different climate datasets. We find that the climate induced uncertainty, defined as the range among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 11 Pg C yr-1 globally (9% of mean GPP). We also assessed a hypothetical maximum climate data induced uncertainty by combining climate variables from different datasets, which resulted in significantly larger uncertainties of 41 Pg C yr-1 globally or 32% of mean GPP. The uncertainty is partitioned into components associated to the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (climate data range) and the apparent sensitivity of the modeled GPP to the driver (apparent model sensitivity). We find that LPJ-GUESS overestimates GPP compared to empirically based GPP data product in all land cover classes except for tropical forests. Tropical forests emerge as a disproportionate source of uncertainty in GPP estimation both in the simulations and empirical data products. The tropical forest uncertainty is most strongly associated with shortwave radiation and precipitation forcing, of which climate data range contributes higher to overall uncertainty than apparent model sensitivity to forcing. Globally, precipitation dominates the climate induced uncertainty over nearly half of the vegetated land area, which is mainly due to climate data range and less so due to the apparent model sensitivity. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than apparent model sensitivity to forcing. Our study highlights the need to better constrain tropical climate, and demonstrates that uncertainty caused by climatic forcing data must be considered when comparing and evaluating carbon cycle model results and empirical datasets.

Field-quantified responses of tropical rainforest aboveground productivity to increasing CO2 and climatic stress, 1997-2009

NASA Astrophysics Data System (ADS)

Clark, Deborah A.; Clark, David B.; Oberbauer, Steven F.

2013-06-01

A directional change in tropical-forest productivity, a large component in the global carbon budget, would affect the rate of increase in atmospheric carbon dioxide ([CO2]). One current hypothesis is that "CO2 fertilization" has been increasing tropical forest productivity. Some lines of evidence instead suggest climate-driven productivity declines. Relevant direct field observations remain extremely limited for this biome. Using a unique long-term record of annual field measurements, we assessed annual aboveground net primary productivity (ANPP) and its relation to climatic factors and [CO2] in a neotropical rainforest through 1997-2009. Over this 12 year period, annual productivity did not increase, as would be expected with a dominant CO2 fertilization effect. Instead, the negative responses of ANPP components to climatic stress far exceeded the small positive responses associated with increasing [CO2]. Annual aboveground biomass production was well explained (73%) by the independent negative effects of increasing minimum temperatures and greater dry-season water stress. The long-term records enable a first field-based estimate of the [CO2] response of tropical forest ANPP: 5.24 g m-2 yr-1 yr-1 (the summed [CO2]-associated increases in two of the four production components; the largest component, leaf litterfall, showed no [CO2] association). If confirmed by longer data series, such a small response from a fertile tropical rainforest would indicate that current global models overestimate the benefits from CO2 fertilization for this biome, where most forests' poorer nutrient status more strongly constrains productivity responses to increasing [CO2]. Given the rapidly intensifying warming across tropical regions, tropical forest productivity could sharply decline through coming decades.

Mini-UAV based sensory system for measuring environmental variables in greenhouses.

PubMed

Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

2015-02-02

This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor.

Mini-UAV Based Sensory System for Measuring Environmental Variables in Greenhouses

PubMed Central

Roldán, Juan Jesús; Joossen, Guillaume; Sanz, David; del Cerro, Jaime; Barrientos, Antonio

2015-01-01

This paper describes the design, construction and validation of a mobile sensory platform for greenhouse monitoring. The complete system consists of a sensory system on board a small quadrotor (i.e., a four rotor mini-UAV). The goals of this system include taking measures of temperature, humidity, luminosity and CO2 concentration and plotting maps of these variables. These features could potentially allow for climate control, crop monitoring or failure detection (e.g., a break in a plastic cover). The sensors have been selected by considering the climate and plant growth models and the requirements for their integration onboard the quadrotor. The sensors layout and placement have been determined through a study of quadrotor aerodynamics and the influence of the airflows from its rotors. All components of the system have been developed, integrated and tested through a set of field experiments in a real greenhouse. The primary contributions of this paper are the validation of the quadrotor as a platform for measuring environmental variables and the determination of the optimal location of sensors on a quadrotor. PMID:25648713

Effectiveness-weighted control of cooling system components

DOEpatents

Campbell, Levi A.; Chu, Richard C.; David, Milnes P.; Ellsworth Jr., Michael J.; Iyengar, Madhusudan K.; Schmidt, Roger R.; Simmons, Robert E.

2015-12-22

Energy efficient control of cooling system cooling of an electronic system is provided based, in part, on weighted cooling effectiveness of the components. The control includes automatically determining speed control settings for multiple adjustable cooling components of the cooling system. The automatically determining is based, at least in part, on weighted cooling effectiveness of the components of the cooling system, and the determining operates to limit power consumption of at least the cooling system, while ensuring that a target temperature associated with at least one of the cooling system or the electronic system is within a desired range by provisioning, based on the weighted cooling effectiveness, a desired target temperature change among the multiple adjustable cooling components of the cooling system. The provisioning includes provisioning applied power to the multiple adjustable cooling components via, at least in part, the determined control settings.

Hydrodynamic Influences on Multiproxy-based Paleoclimate Reconstructions from Marine Sediments

NASA Astrophysics Data System (ADS)

Ausin Gonzalez, B.; Magill, C.; Wenk, P.; Haugh, G.; McIntyre, C.; Haghipour, N.; Hodell, D. A.; Eglinton, T. I.

2017-12-01

Multiproxy approaches, including those based on the abundance and composition of sedimentary organic matter at both the bulk (total organic carbon; TOC) and molecular (e.g., alkenone-derived Uk'37) level, are increasingly applied in investigations of past climate variability. Constraining of short-term and abrupt climate changes requires the establishment of accurate chronostratigraphies. For the last glacial to the present, a single age-depth model is typically constructed from radiocarbon ages of planktonic foraminifera and then applied to all proxy records derived from the same sediment core. Here, we develop independent, high-resolution 14C chronologies for planktonic foraminifera, TOC, and alkenones for a sediment core retrieved from the so-called "Shackleton sites" in the Northeast Atlantic Ocean. We observe 14C age offsets between these sedimentary components of up to several thousand years within the same sediment layer, with TOC and alkenones exhibiting older ages than corresponding foraminiferal carbonate. This asynchroneity suggests that application of planktic foraminifera-based chronostratigraphies to other proxy carriers (e.g., TOC and alkenones) may lead to spurious interpretation of sedimentary records. In order to further explore the influence of lateral transport processes on organic matter signatures and ages, we performed down-core, grain size-specific OC 14C analyses on selected sediment horizons. Results indicate strong interdependence between 14C age of OC and sediment grain size, underlying strong hydrodynamic controls on OC age. Furthermore, the magnitude of these temporal offsets varies over time in concert with changes in the strength of the Mediterranean Outflow Water (MOW), implying that OC [proxy] signatures are influenced by non-local inputs. Such influences co-vary with ocean and climate changes, such as Heinrinch Event 1, the Younger Dryas, and those corresponding to deposition of Sapropel 1 in the Mediterranean Sea (ca. 8 ka BP). Our findings suggest an interplay between past climate and ocean change, hydrodynamic forcing, and the (a)synchroneity of multiproxy records, and highlight the importance of developing independent, proxy-specific chronostratigraphies to accurately decipher past millennial- and centennial-scale climate variability.

Research on Climate and Dengue in Malaysia: A Systematic Review.

PubMed

Hii, Yien Ling; Zaki, Rafdzah Ahmad; Aghamohammadi, Nasrin; Rocklöv, Joacim

2016-03-01

Dengue is a climate-sensitive infectious disease. Climate-based dengue early warning may be a simple, low-cost, and effective tool for enhancing surveillance and control. Scientific studies on climate and dengue in local context form the basis for advancing the development of a climate-based early warning system. This study aims to review the current status of scientific studies in climate and dengue and the prospect or challenges of such research on a climate-based dengue early warning system in a dengue-endemic country, taking Malaysia as a case study. We reviewed the relationship between climate and dengue derived from statistical modeling, laboratory tests, and field studies. We searched electronic databases including PubMed, Scopus, EBSCO (MEDLINE), Web of Science, and the World Health Organization publications, and assessed climate factors and their influence on dengue cases, mosquitoes, and virus and recent development in the field of climate and dengue. Few studies in Malaysia have emphasized the relationship between climate and dengue. Climatic factors such as temperature, rainfall, and humidity are associated with dengue; however, these relationships were not consistent. Climate change projections for Malaysia show a mounting risk for dengue in the future. Scientific studies on climate and dengue enhance dengue surveillance in the long run. It is essential for institutions in Malaysia to promote research on climate and vector-borne diseases to advance the development of climate-based early warning systems. Together, effective strategies that improve existing research capacity, maximize the use of limited resources, and promote local-international partnership are crucial for sustaining research on climate and health.

A Flexible Component based Access Control Architecture for OPeNDAP Services

NASA Astrophysics Data System (ADS)

Kershaw, Philip; Ananthakrishnan, Rachana; Cinquini, Luca; Lawrence, Bryan; Pascoe, Stephen; Siebenlist, Frank

2010-05-01

Network data access services such as OPeNDAP enable widespread access to data across user communities. However, without ready means to restrict access to data for such services, data providers and data owners are constrained from making their data more widely available. Even with such capability, the range of different security technologies available can make interoperability between services and user client tools a challenge. OPeNDAP is a key data access service in the infrastructure under development to support the CMIP5 (Couple Model Intercomparison Project Phase 5). The work is being carried out as part of an international collaboration including the US Earth System Grid and Curator projects and the EU funded IS-ENES and Metafor projects. This infrastructure will bring together Petabytes of climate model data and associated metadata from over twenty modelling centres around the world in a federation with a core archive mirrored at three data centres. A security system is needed to meet the requirements of organisations responsible for model data including the ability to restrict data access to registered users, keep them up to date with changes to data and services, audit access and protect finite computing resources. Individual organisations have existing tools and services such as OPeNDAP with which users in the climate research community are already familiar. The security system should overlay access control in a way which maintains the usability and ease of access to these services. The BADC (British Atmospheric Data Centre) has been working in collaboration with the Earth System Grid development team and partner organisations to develop the security architecture. OpenID and MyProxy were selected at an early stage in the ESG project to provide single sign-on capability across the federation of participating organisations. Building on the existing OPeNDAP specification an architecture based on pluggable server side components has been developed at the BADC. These components filter requests to the service they protect and apply the required authentication and authorisation schemes. Filters have been developed for OpenID and SSL client based authentication. The latter enabling access with MyProxy issued credentials. By preserving a clear separation between the security and application functionality, multiple authentication technologies may be supported without the need for modification to the underlying OPeNDAP application. The software has been developed in the Python programming language securing the Python based OPeNDAP implementation, PyDAP. This utilises the Python WSGI (Web Server Gateway Interface) specification to create distinct security filter components. Work is also currently underway to develop a parallel Java based filter implementation to secure the THREDDS Data Server. Whilst the ability to apply this flexible approach to the server side security layer is important, the development of compatible client software is vital to the take up of these services across a wide user base. To date PyDAP and wget based clients have been tested and work is planned to integrate the required security interface into the netCDF API. This forms part of ongoing collaboration with the OPeNDAP user and development community to ensure interoperability.

Climate change and freshwater ecosystems: impacts across multiple levels of organization

PubMed Central

Woodward, Guy; Perkins, Daniel M.; Brown, Lee E.

2010-01-01

Fresh waters are particularly vulnerable to climate change because (i) many species within these fragmented habitats have limited abilities to disperse as the environment changes; (ii) water temperature and availability are climate-dependent; and (iii) many systems are already exposed to numerous anthropogenic stressors. Most climate change studies to date have focused on individuals or species populations, rather than the higher levels of organization (i.e. communities, food webs, ecosystems). We propose that an understanding of the connections between these different levels, which are all ultimately based on individuals, can help to develop a more coherent theoretical framework based on metabolic scaling, foraging theory and ecological stoichiometry, to predict the ecological consequences of climate change. For instance, individual basal metabolic rate scales with body size (which also constrains food web structure and dynamics) and temperature (which determines many ecosystem processes and key aspects of foraging behaviour). In addition, increasing atmospheric CO2 is predicted to alter molar CNP ratios of detrital inputs, which could lead to profound shifts in the stoichiometry of elemental fluxes between consumers and resources at the base of the food web. The different components of climate change (e.g. temperature, hydrology and atmospheric composition) not only affect multiple levels of biological organization, but they may also interact with the many other stressors to which fresh waters are exposed, and future research needs to address these potentially important synergies. PMID:20513717

Software Framework for Development of Web-GIS Systems for Analysis of Georeferenced Geophysical Data

NASA Astrophysics Data System (ADS)

Okladnikov, I.; Gordov, E. P.; Titov, A. G.

2011-12-01

Georeferenced datasets (meteorological databases, modeling and reanalysis results, remote sensing products, etc.) are currently actively used in numerous applications including modeling, interpretation and forecast of climatic and ecosystem changes for various spatial and temporal scales. Due to inherent heterogeneity of environmental datasets as well as their size which might constitute up to tens terabytes for a single dataset at present studies in the area of climate and environmental change require a special software support. A dedicated software framework for rapid development of providing such support information-computational systems based on Web-GIS technologies has been created. The software framework consists of 3 basic parts: computational kernel developed using ITTVIS Interactive Data Language (IDL), a set of PHP-controllers run within specialized web portal, and JavaScript class library for development of typical components of web mapping application graphical user interface (GUI) based on AJAX technology. Computational kernel comprise of number of modules for datasets access, mathematical and statistical data analysis and visualization of results. Specialized web-portal consists of web-server Apache, complying OGC standards Geoserver software which is used as a base for presenting cartographical information over the Web, and a set of PHP-controllers implementing web-mapping application logic and governing computational kernel. JavaScript library aiming at graphical user interface development is based on GeoExt library combining ExtJS Framework and OpenLayers software. Based on the software framework an information-computational system for complex analysis of large georeferenced data archives was developed. Structured environmental datasets available for processing now include two editions of NCEP/NCAR Reanalysis, JMA/CRIEPI JRA-25 Reanalysis, ECMWF ERA-40 Reanalysis, ECMWF ERA Interim Reanalysis, MRI/JMA APHRODITE's Water Resources Project Reanalysis, meteorological observational data for the territory of the former USSR for the 20th century, and others. Current version of the system is already involved into a scientific research process. Particularly, recently the system was successfully used for analysis of Siberia climate changes and its impact in the region. The software framework presented allows rapid development of Web-GIS systems for geophysical data analysis thus providing specialists involved into multidisciplinary research projects with reliable and practical instruments for complex analysis of climate and ecosystems changes on global and regional scales. This work is partially supported by RFBR grants #10-07-00547, #11-05-01190, and SB RAS projects 4.31.1.5, 4.31.2.7, 4, 8, 9, 50 and 66.

A Model-Based Study of Ecohydrological Controls in the Mojave Desert

NASA Astrophysics Data System (ADS)

Ng, G. C.; Bedford, D.; Miller, D. M.

2010-12-01

Desert ecosystems represent extreme conditions near the limits of viability for vegetation. Their dependence on scarce resources make them vulnerable to climate and land use change. Understanding how ecohydrological conditions impact plants in such regions is critical for ecological sustainability. Various relationships have been observed in the field between vegetation growth and meteorology, terrain, and plant physiology. Quantifying the complex interactions of those influences on vegetation dynamics can be facilitated with a physically-based ecohydrological model. To assess ecohydrological controls in the Mojave Desert, we employ the CLM4.0 land-surface model with the Carbon-Nitrogen model component to simulate vegetation dynamics [Olesen et al., 2010]. Using an ecohydrological model with fully prognostic vegetation variables is essential for representing the coupled dynamics between plants and soil moisture. We apply the CLM4.0-CN model to a study basin in the Mojave National Preserve that covers a variety of conditions. Soils range from coarse-textured wash sediments to low-permeability desert pavements. Higher elevations in the basin experience cooler and moister conditions than the lower wash areas. The dominant vegetation types in the basin include the evergreen shrub Larrea tridentata (creosote) and the drought-deciduous shrub Ambrosia dumosa. Simulations are conducted over a 50 year period to investigate both seasonal and interannual dynamics. Sensitivity tests indicate that high temporal resolution rainfall inputs (at least hourly) are important for properly resolving ecohydrological dynamics at the study site. As expected, preliminary results show that both coarser soils and milder climate facilitate vegetation growth in this moisture-limited region. However, results indicate that effects of soil texture variations become subordinate with milder climate. The model also reveals how drought-deciduous and evergreen shrub types respond differently to various conditions. Due to its quick response to sporadic wet episodes, the drought-deciduous Ambrosia thrives under harsher (hotter and drier) climates in simulations. The evergreen Larrea shrub becomes more competitive with more consistent moisture of the relatively milder climates in the basin. Multi-decadal simulations indicate that anomalously wet years can yield a sustained boost in vegetation in following years, especially for Larrea. These model results coincide with many observed vegetation patterns in the field, and they serve to elucidate and quantify the contributing factors that impact desert vegetation.

Delineation, Validation and Application of EPA’s Level III and IV Ecoregions in New England

EPA Science Inventory

EPA’s ecoregions are defined as areas of similarity based on patterns and composition of aquatic and terrestrial ecosystem components of the abiotic (non-living), biotic (living), and cultural (human) environment, including geology, physiography, vegetation, climate, soils, hydro...

Climate change amplifies the interactions between wind and bark beetle disturbances in forest landscapes.

PubMed

Seidl, Rupert; Rammer, Werner

2017-07-01

Growing evidence suggests that climate change could substantially alter forest disturbances. Interactions between individual disturbance agents are a major component of disturbance regimes, yet how interactions contribute to their climate sensitivity remains largely unknown. Here, our aim was to assess the climate sensitivity of disturbance interactions, focusing on wind and bark beetle disturbances. We developed a process-based model of bark beetle disturbance, integrated into the dynamic forest landscape model iLand (already including a detailed model of wind disturbance). We evaluated the integrated model against observations from three wind events and a subsequent bark beetle outbreak, affecting 530.2 ha (3.8 %) of a mountain forest landscape in Austria between 2007 and 2014. Subsequently, we conducted a factorial experiment determining the effect of changes in climate variables on the area disturbed by wind and bark beetles separately and in combination. iLand was well able to reproduce observations with regard to area, temporal sequence, and spatial pattern of disturbance. The observed disturbance dynamics was strongly driven by interactions, with 64.3 % of the area disturbed attributed to interaction effects. A +4 °C warming increased the disturbed area by +264.7 % and the area-weighted mean patch size by +1794.3 %. Interactions were found to have a ten times higher sensitivity to temperature changes than main effects, considerably amplifying the climate sensitivity of the disturbance regime. Disturbance interactions are a key component of the forest disturbance regime. Neglecting interaction effects can lead to a substantial underestimation of the climate change sensitivity of disturbance regimes.

Integrated numerical modeling of a landslide early warning system in a context of adaptation to future climatic pressures

NASA Astrophysics Data System (ADS)

Khabarov, Nikolay; Huggel, Christian; Obersteiner, Michael; Ramírez, Juan Manuel

2010-05-01

Mountain regions are typically characterized by rugged terrain which is susceptible to different types of landslides during high-intensity precipitation. Landslides account for billions of dollars of damage and many casualties, and are expected to increase in frequency in the future due to a projected increase of precipitation intensity. Early warning systems (EWS) are thought to be a primary tool for related disaster risk reduction and climate change adaptation to extreme climatic events and hydro-meteorological hazards, including landslides. An EWS for hazards such as landslides consist of different components, including environmental monitoring instruments (e.g. rainfall or flow sensors), physical or empirical process models to support decision-making (warnings, evacuation), data and voice communication, organization and logistics-related procedures, and population response. Considering this broad range, EWS are highly complex systems, and it is therefore difficult to understand the effect of the different components and changing conditions on the overall performance, ultimately being expressed as human lives saved or structural damage reduced. In this contribution we present a further development of our approach to assess a landslide EWS in an integral way, both at the system and component level. We utilize a numerical model using 6 hour rainfall data as basic input. A threshold function based on a rainfall-intensity/duration relation was applied as a decision criterion for evacuation. Damage to infrastructure and human lives was defined as a linear function of landslide magnitude, with the magnitude modelled using a power function of landslide frequency. Correct evacuation was assessed with a ‘true' reference rainfall dataset versus a dataset of artificially reduced quality imitating the observation system component. Performance of the EWS using these rainfall datasets was expressed in monetary terms (i.e. damage related to false and correct evacuation). We applied this model to a landslide EWS in Colombia that is currently being implemented within a disaster prevention project. We evaluated the EWS against rainfall data with artificially introduced error and computed with multiple model runs the probabilistic damage functions depending on rainfall error. Then we modified the original precipitation pattern to reflect possible climatic changes e.g. change in annual precipitation as well as change in precipitation intensity with annual values remaining constant. We let the EWS model adapt for changed conditions to function optimally. Our results show that for the same errors in rainfall measurements the system's performance degrades with expected changing climatic conditions. The obtained results suggest that EWS cannot internally adapt to climate change and require exogenous adaptive measures to avoid increase in overall damage. The model represents a first attempt to integrally simulate and evaluate EWS under future possible climatic pressures. Future work will concentrate on refining model components and spatially explicit climate scenarios.

Molecular composition and paleobotanical origin of Eocene resin from northeast India

NASA Astrophysics Data System (ADS)

Rudra, Arka; Dutta, Suryendu; Raju, Srinivasan V.

2014-06-01

The molecular composition of fossil resins from early to middle Eocene coal from northeast India, has been analyzed for the first time to infer their paleobotanical source. The soluble component of fossil resin was analyzed using gas chromatography-mass spectrometry (GC-MS). The resin extracts are composed of cadalene-based C15 sesquiterpenoids and diagenetically altered triterpenoids. The macromolecular composition was investigated using pyrolysis gas chromatography-mass spectrometry (Py-GC-MS) and Fourier transform infrared (FTIR) spectroscopy. The major pyrolysis products are C15 bicyclic sesquiterpenoids, alkylated naphthalenes, benzenes and a series of C17-C34 n-alkene- n-alkane pairs. Spectroscopic analysis revealed the dominance of aliphatic components. The presence of cadalene-based sequiterpenoids confirms the resin to be Class II or dammar resin, derived from angiosperms of Dipterocarpaceae family. These sesquiterpenoids are often detected in many SE Asian fluvio-deltaic oils. Dipterocarpaceae are characteristic of warm tropical climate suggesting the prevalence of such climate during early Eocene in northeast India.

Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: the example of a small Mediterranean agro-watershed.

PubMed

Kourgialas, Nektarios N; Dokou, Zoi; Karatzas, George P

2015-05-01

The purpose of this study was to create a modeling management tool for the simulation of extreme flow events under current and future climatic conditions. This tool is a combination of different components and can be applied in complex hydrogeological river basins, where frequent flood and drought phenomena occur. The first component is the statistical analysis of the available hydro-meteorological data. Specifically, principal components analysis was performed in order to quantify the importance of the hydro-meteorological parameters that affect the generation of extreme events. The second component is a prediction-forecasting artificial neural network (ANN) model that simulates, accurately and efficiently, river flow on an hourly basis. This model is based on a methodology that attempts to resolve a very difficult problem related to the accurate estimation of extreme flows. For this purpose, the available measurements (5 years of hourly data) were divided in two subsets: one for the dry and one for the wet periods of the hydrological year. This way, two ANNs were created, trained, tested and validated for a complex Mediterranean river basin in Crete, Greece. As part of the second management component a statistical downscaling tool was used for the creation of meteorological data according to the higher and lower emission climate change scenarios A2 and B1. These data are used as input in the ANN for the forecasting of river flow for the next two decades. The final component is the application of a meteorological index on the measured and forecasted precipitation and flow data, in order to assess the severity and duration of extreme events. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

Meehl, G A; Covey, C; McAvaney, B

The Coupled Model Intercomparison Project (CMIP) is designed to allow study and intercomparison of multi-model simulations of present-day and future climate. The latter are represented by idealized forcing of compounded 1% per year CO2 increase to the time of CO2 doubling near year 70 in simulations with global coupled models that contain, typically, components representing atmosphere, ocean, sea ice and land surface. Results from CMIP diagnostic subprojects were presented at the Second CMIP Workshop held at the Max Planck Institute for Meteorology in Hamburg, Germany, in September, 2003. Significant progress in diagnosing and understanding results from global coupled models hasmore » been made since the First CMIP Workshop in Melbourne, Australia in 1998. For example, the issue of flux adjustment is slowly fading as more and more models obtain stable multi-century surface climates without them. El Nino variability, usually about half the observed amplitude in the previous generation of coupled models, is now more accurately simulated in the present generation of global coupled models, though there are still biases in simulating the patterns of maximum variability. Typical resolutions of atmospheric component models contained in coupled models is now usually around 2.5 degrees latitude-longitude, with the ocean components often having about twice the atmospheric model resolution, with even higher resolution in the equatorial tropics. Some new-generation coupled models have atmospheric model resolutions of around 1.5 degrees latitude-longitude. Modeling groups now routinely run the CMIP control and 1% CO2 simulations in addition to 20th and 21st century climate simulations with a variety of forcings (e.g. volcanoes, solar variability, anthropogenic sulfate aerosols, ozone, and greenhouse gases (GHGs), with the anthropogenic forcings for future climate as well). However, persistent systematic errors noted in previous generations of global coupled models still are present in the present generation (e.g. over-extensive equatorial Pacific cold tongue, double ITCZ). This points to the next challenge for the global coupled climate modeling community. Planning and imminent commencement of the IPCC Fourth Assessment Report (AR4) has prompted rapid coupled model development, which will lead to an expanded CMIP-like activity to collect and analyze results for the control, 1% CO2, 20th, 21st and 22nd century simulations performed for the AR4. The international climate community is encouraged to become involved in this analysis effort, and details are provided below in how to do so.« less

Robust high-performance control for robotic manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1989-01-01

Model-based and performance-based control techniques are combined for an electrical robotic control system. Thus, two distinct and separate design philosophies were merged into a single control system having a control law formulation including two distinct and separate components, each of which yields a respective signal componet that is combined into a total command signal for the system. Those two separate system components include a feedforward controller and feedback controller. The feedforward controller is model-based and contains any known part of the manipulator dynamics that can be used for on-line control to produce a nominal feedforward component of the system's control signal. The feedback controller is performance-based and consists of a simple adaptive PID controller which generates an adaptive control signal to complement the nomical feedforward signal.

Evaluating international development investments based on ecosystem services impact

NASA Astrophysics Data System (ADS)

Fremier, A. K.; Brauman, K. A.; Mulligan, M.; Chaplin-Kramer, R.; Gordon, L.; Luedeling, E.; Jones, S. K.; DeClerck, F.

2016-12-01

Engineered water-control structures to supply water for agriculture are frequently funded by international development to an effort to improve human wellbeing. Dams, reservoirs, and other forms of water control frequently have negative impacts on other water users; however, their sustainability in the face of climate change and evolving watershed processes have been called into question. Increasingly, planning for and evaluation of investments in water control require integration of these larger scale impacts and dependencies. Ecosystem service approaches can use local to regional scale knowledge to integrate a broader scope of project impacts by quantifying trade-offs in multiple services across proposed development interventions and future scenarios (economic, climate, demographic). Here, we illustrate the role an ecosystem service approach can play in investment decision making to evaluate the impact of small reservoirs on human wellbeing in the Upper Volta Basin of West Africa. Our project has four components: (1) design of a spatially explicit regional-level social-ecological characterization; (2) construction of future scenario analyses for rainfed and irrigated production system interventions; (3) co-design and co-development of benefit sharing mechanisms at the reservoir catchment level and enhancing institutional capacity to implement these mechanisms through training, professional development and targeting tools; and (4) intervention decision analysis to identify benefits, costs and risks associated with decision options. We illustrate how this approach highlights different outcomes than standard cost-benefit analysis focused narrowly on the single project. Anticipated outcomes are development of ecosystem services-based methods for more equitably and sustainably evaluating development interventions and identifying management approaches to water-impoundment structures that promote a range of ecosystem services to provide food security to a broader population.

A systematic review of the safety climate intervention literature: Past trends and future directions.

PubMed

Lee, Jin; Huang, Yueng-Hsiang; Cheung, Janelle H; Chen, Zhuo; Shaw, William S

2018-04-26

Safety climate represents the meaningfulness of safety and how safety is valued in an organization. The contributions of safety climate to organizational safety have been well documented. There is a dearth of empirical research, however, on specific safety climate interventions and their effectiveness. The present study aims at examining the trend of safety climate interventions and offering compiled information for designing and implementing evidence-based safety climate interventions. Our literature search yielded 384 titles that were inspected by three examiners. Using a stepwise process that allowed for assessment of interobserver agreement, 19 full articles were selected and reviewed. Results showed that 10 out of the 19 articles (52.6%) were based on a quasi-experimental pre- and postintervention design, whereas 42.1% (n = 8) studies were based on a mixed-design approach (including both between- and within-subject design). All interventions in these 19 studies involved either safety-/health-related communication or education/training. Improvement of safety leadership was also a common component of safety climate interventions. According to the socio-technical systems classification of intervention strategies, all studies were categorized as interventions focusing on improving organizational and managerial structure as well as the personnel subsystem; four of them also aimed at improving technological aspects of work, and five of them aimed at improving the physical work subsystem. In general, a vast majority of the studies (89.5%, n = 17) showed a statistically significant improvement in safety climate across their organizations postintervention. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Water resources in the twenty-first century; a study of the implications of climate uncertainty

USGS Publications Warehouse

Moss, Marshall E.; Lins, Harry F.

1989-01-01

The interactions of the water resources on and within the surface of the Earth with the atmosphere that surrounds it are exceedingly complex. Increased uncertainty can be attached to the availability of water of usable quality in the 21st century, therefore, because of potential anthropogenic changes in the global climate system. For the U.S. Geological Survey to continue to fulfill its mission with respect to assessing the Nation's water resources, an expanded program to study the hydrologic implications of climate uncertainty will be required. The goal for this program is to develop knowledge and information concerning the potential water-resources implications for the United States of uncertainties in climate that may result from both anthropogenic and natural changes of the Earth's atmosphere. Like most past and current water-resources programs of the Geological Survey, the climate-uncertainty program should be composed of three elements: (1) research, (2) data collection, and (3) interpretive studies. However, unlike most other programs, the climate-uncertainty program necessarily will be dominated by its research component during its early years. Critical new concerns to be addressed by the research component are (1) areal estimates of evapotranspiration, (2) hydrologic resolution within atmospheric (climatic) models at the global scale and at mesoscales, (3) linkages between hydrology and climatology, and (4) methodology for the design of data networks that will help to track the impacts of climate change on water resources. Other ongoing activities in U.S. Geological Survey research programs will be enhanced to make them more compatible with climate-uncertainty research needs. The existing hydrologic data base of the Geological Survey serves as a key element in assessing hydrologic and climatologic change. However, this data base has evolved in response to other needs for hydrologic information and probably is not as sensitive to climate change as is desirable. Therefore, as measurement and network-design methodologies are improved to account for climate-change potential, new data-collection activities will be added to the existing programs. One particular area of data-collection concern pertains to the phenomenon of evapotranspiration. Interpretive studies of the hydrologic implications of climate uncertainty will be initiated by establishing several studies at the river-basin scale in diverse hydroclimatic and demographic settings. These studies will serve as tests of the existing methodologies for studying the impacts of climate change and also will help to define subsequent research priorities. A prototype for these studies was initiated in early 1988 in the Delaware River basin.

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

PubMed Central

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; Lovell, John T.; Moyers, Brook T.; Baraoidan, Marietta; Naredo, Maria Elizabeth B.; McNally, Kenneth L.; Poland, Jesse; Bush, Daniel R.; Leung, Hei; Leach, Jan E.; McKay, John K.

2017-01-01

To ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. Here we demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor-intensive measures of flowering time, height, biomass, grain yield, and harvest index. Genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution. PMID:28220807

School Climate: Applied to Integration and Access of Special Education Children in Full Learning Environments. A Ho'okoho Module.

ERIC Educational Resources Information Center

Levy, Irena; Yoneshige, Dora

The module is intended to help educators understand the components of school climate and its influence on the integration of students with handicaps. Three competencies are addressed: (1) to develop an understanding of the concept of school climate, identify its components and analyze its relationship to educational goals; (2) to develop an…

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.

Diagnosis of abnormal patterns in multivariate microclimate monitoring: a case study of an open-air archaeological site in Pompeii (Italy).

PubMed

Merello, Paloma; García-Diego, Fernando-Juan; Zarzo, Manuel

2014-08-01

Chemometrics has been applied successfully since the 1990s for the multivariate statistical control of industrial processes. A new area of interest for these tools is the microclimatic monitoring of cultural heritage. Sensors record climatic parameters over time and statistical data analysis is performed to obtain valuable information for preventive conservation. A case study of an open-air archaeological site is presented here. A set of 26 temperature and relative humidity data-loggers was installed in four rooms of Ariadne's house (Pompeii). If climatic values are recorded versus time at different positions, the resulting data structure is equivalent to records of physical parameters registered at several points of a continuous chemical process. However, there is an important difference in this case: continuous processes are controlled to reach a steady state, whilst open-air sites undergo tremendous fluctuations. Although data from continuous processes are usually column-centred prior to applying principal components analysis, it turned out that another pre-treatment (row-centred data) was more convenient for the interpretation of components and to identify abnormal patterns. The detection of typical trajectories was more straightforward by dividing the whole monitored period into several sub-periods, because the marked climatic fluctuations throughout the year affect the correlation structures. The proposed statistical methodology is of interest for the microclimatic monitoring of cultural heritage, particularly in the case of open-air or semi-confined archaeological sites. Copyright © 2014 Elsevier B.V. All rights reserved.

Correcting speleothem oxygen isotopic variations for growth-rate controlled kinetic fractionation effects

NASA Astrophysics Data System (ADS)

Stoll, Heather; Moreno, Ana; Cacho, Isabel; Mendez Vicence, Ana; Gonzalez Lemos, Saul; Pirla Casasayas, Gemma; Cheng, Hai; Wang, Xianfeng; Edwards, R. Lawrence

2015-04-01

The oxygen isotopic signature may be the most widely used climate indicator in stalagmites, but recent experimental and theoretical studies indicate the potential for kinetic fractionation effects which may be significant, especially in situations where the primary signal from rainfall isotopic composition and cave temperature is limited to a few permil. Here we use a natural set of stalagmites to illustrate the magnitude of such effects and the potential for deconvolving kinetic signals from the primary temperature and rainfall signals. We compare isotopic records from 6 coeval stalagmites covering the interval 140 to 70 ka, from two proximal caves in NW Spain which experienced the same primary variations in temperature and rainfall d18O, but exhibit a large range in growth rates and temporal trends in growth rate. Stalagmites growing at faster rates near 50 microns/year have oxygen isotopic ratios more than 1 permil more negative than coeval stalagmites with very slow (5 micron/year) growth rates. Because growth rate variations also occur over time within any given stalagmite, the measured oxygen isotopic time series for a given stalagmite includes both climatic and kinetic components. Removal of the kinetic component of variation in each stalagmite, based on the dependence of the kinetic component on growth rate, is effective at distilling a common temporal evolution among the oxygen isotopic records of the multiple stalagmites. However, this approach is limited by the quality of the age model. For time periods characterized by very slow growth and long durations between dates, the presence of crypto-hiatus may result in average growth rates which underestimate the instantaneous speleothem deposition rates and which therefore underestimate the magnitude of kinetic effects. We compare the composite corrected oxygen isotopic record with other records of the timing of glacial inception in the North Atlantic realm.

The role of organizational trust in safety climate's influence on organizational outcomes.

PubMed

Kath, Lisa M; Magley, Vicki J; Marmet, Matthew

2010-09-01

Based on elements of social exchange theory and other conceptualizations of trust, a model was developed situating organizational trust as a central component to the relationship that safety climate has with organizational outcomes. Specifically, the model specified that two facets of safety climate--upward safety communication and management attitudes toward safety--would be positively related to organizational trust. Increased levels of trust would then predict increased motivation to engage in safe job-related behaviors, increased job satisfaction, and decreased turnover intentions. Another hypothesis investigated whether job safety relevance would moderate the relationship between safety climate and trust. Online survey research was conducted with 599 employees from 97 work groups across a New England grocery store chain. Hierarchical linear modeling indicated support for trust mediating the relationship between safety climate and organizational outcomes; further, the relationship between safety climate and trust was stronger within work groups where safety was more relevant. 2009 Elsevier Ltd. All rights reserved.

Nevada Infrastructure for Climate Change Science, Education, and Outreach

NASA Astrophysics Data System (ADS)

Dana, G. L.; Piechota, T. C.; Lancaster, N.; Mensing, S. A.

2009-12-01

The Nevada system of Higher Education, including the University of Nevada, Las Vegas, the University of Nevada, Reno, the Desert Research Institute, and Nevada State College have begun a five year research and infrastructure building program, funded by the National Science Foundation Experimental Program to Stimulate Competitive Research (NSF EPSCoR) with the vision “to create a statewide interdisciplinary program and virtual climate change center that will stimulate transformative research, education, and outreach on the effects of regional climate change on ecosystem resources (especially water) and support use of this knowledge by policy makers and stakeholders.” Six major strategies are proposed: 1) Develop a capability to model climate change and its effects at a regional and sub-regional scales to evaluate different future scenarios and strategies (Climate Modeling Component) 2) Develop data collection, modeling, and visualization infrastructure to determine and analyze effects on ecosystems and disturbance regimes (Ecological Change Component) 3) Develop data collection, modeling, and visualization infrastructure to better quantify and model changes in water balance and resources under climate change (Water Resources Component) 4) Develop data collection and modeling infrastructure to assess effects on human systems, responses to institutional and societal aspects, and enhance policy making and outreach to communities and stakeholders (Policy, Decision-Making, and Outreach Component) 5) Develop a data portal and software to support interdisciplinary research via integration of data from observational networks and modeling (Cyberinfrastructure Component) and 6) Develop educational infrastructure to train students at all levels and provide public outreach in climate change issues (Education Component). As part of the new infrastructure, two observational transects will be established across Great Basin Ranges, one in southern Nevada in the Spring Mountains, and the second to be located in the Snake Range of eastern Nevada which will reach bristlecone pine stands. Climatic, hydrologic and ecological data from these transects will be downloaded into high capacity data storage units and made available to researchers through creation of the Nevada climate change portal. Our research will aim to answer two interdisciplinary science questions: 1) How will climate change affect water resources and linked ecosystem resources and human systems? And 2) How will climate change affect disturbance regimes (e.g., wildland fires, invasive species, insect outbreaks, droughts) and linked systems?

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.

Functional approach to exploring climatic and landscape controls of runoff generation: 1. Behavioral constraints on runoff volume

NASA Astrophysics Data System (ADS)

Li, Hong-Yi; Sivapalan, Murugesu; Tian, Fuqiang; Harman, Ciaran

2014-12-01

Inspired by the Dunne diagram, the climatic and landscape controls on the partitioning of annual runoff into its various components (Hortonian and Dunne overland flow and subsurface stormflow) are assessed quantitatively, from a purely theoretical perspective. A simple distributed hydrologic model has been built sufficient to simulate the effects of different combinations of climate, soil, and topography on the runoff generation processes. The model is driven by a sequence of simple hypothetical precipitation events, for a large combination of climate and landscape properties, and hydrologic responses at the catchment scale are obtained through aggregation of grid-scale responses. It is found, first, that the water balance responses, including relative contributions of different runoff generation mechanisms, could be related to a small set of dimensionless similarity parameters. These capture the competition between the wetting, drying, storage, and drainage functions underlying the catchment responses, and in this way, provide a quantitative approximation of the conceptual Dunne diagram. Second, only a subset of all hypothetical catchment/climate combinations is found to be "behavioral," in terms of falling sufficiently close to the Budyko curve, describing mean annual runoff as a function of climate aridity. Furthermore, these behavioral combinations are mostly consistent with the qualitative picture presented in the Dunne diagram, indicating clearly the commonality between the Budyko curve and the Dunne diagram. These analyses also suggest clear interrelationships amongst the "behavioral" climate, soil, and topography parameter combinations, implying these catchment properties may be constrained to be codependent in order to satisfy the Budyko curve.

Assessment of vulnerability of forest ecosystems to climate change and adaptation planning in Nepal

NASA Astrophysics Data System (ADS)

Matin, M. A.; Chitale, V. S.

2016-12-01

Understanding ecosystem level vulnerability of forests and dependence of local communities on these ecosystems is a first step towards developing effective adaptation strategies. As forests are important components of livelihoods system for a large percentage of the population in the Himalayan region, they offer an important basis for creating and safeguarding more climate-resilient communities. Increased frequency, duration, and/or severity of drought and heat stress, changes in winter ecology, and pest and fire outbreaksunder climate change scenarios could fundamentally alter the composition, productivity and biogeography of forests affecting the potential ecosystem services offered and forest-based livelihoods. Hence, forest ecosystem vulnerability assessment to climate change and the development of a knowledgebase to identify and support relevant adaptation strategies is identified as an urgent need. Climate change vulnerability is measured as a function of exposure, sensitivity and the adaptive capacity of the system towards climate variability and extreme events. Effective adaptation to climate change depends on the availability of two important prerequisites: a) information on what, where, and how to adapt, and b) availability of resources to implement the adaptation measures. In the present study, we introduce the concept of two way multitier approach, which can support effective identification and implementation of adaptation measures in Nepal and the framework can be replicated in other countries in the HKH region. The assessment of overall vulnerability of forests comprises of two components: 1) understanding the relationship between exposure and sensitivity and positive feedback from adaptive capacity of forests; 2) quantifying the dependence of local communities on these ecosystems. We use climate datasets from Bioclim and biophysical products from MODIS, alongwith field datasets. We report that most of the forests along the high altitude areas and few patches in midhills and terai (plains) in Central Nepal depict moderate to high vulnerability of forests, while the forests from most of the other areas experience low vulnerability. Based on the matrix of vulnerability and dependence we suggest adaptation footprints for prioritization of adaptation measures on the ground.

Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network

PubMed Central

Zeng, Songwei; Hu, Haigen; Xu, Lihong; Li, Guanghui

2012-01-01

This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production. PMID:22778587

Robustness and Recovery of Lifeline Infrastructure and Ecosystem Networks

NASA Astrophysics Data System (ADS)

Bhatia, U.; Ganguly, A. R.

2015-12-01

Disruptive events, both natural and man-made, can have widespread impacts on both natural systems and lifeline infrastructure networks leading to the loss of biodiversity and essential functionality, respectively. Projected sea-level rise and climate change can further increase the frequency and severity of large-scale floods on urban-coastal megacities. Nevertheless, Failure in infrastructure systems can trigger cascading impacts on dependent ecosystems, and vice-versa. An important consideration in the behavior of the isolated networks and inter-connected networks following disruptive events is their resilience, or the ability of the network to "bounce back" to a pre-disaster state. Conventional risk analysis and subsequent risk management frameworks have focused on identifying the components' vulnerability and strengthening of the isolated components to withstand these disruptions. But high interconnectedness of these systems, and evolving nature of hazards, particularly in the context of climate extremes, make the component level analysis unrealistic. In this study, we discuss the complex network-based resilience framework to understand fragility and recovery strategies for infrastructure systems impacted by climate-related hazards. We extend the proposed framework to assess the response of ecological networks to multiple species loss and design the restoration management framework to identify the most efficient restoration sequence of species, which can potentially lead to disproportionate gains in biodiversity.

The variability of runoff and soil erosion in the Brazilian Cerrado biome due to the potential land use and climate changes

NASA Astrophysics Data System (ADS)

Alexandre Ayach Anache, Jamil; Wendland, Edson; Malacarne Pinheiro Rosalem, Lívia; Srivastava, Anurag; Flanagan, Dennis

2017-04-01

Changes in land use and climate can influence runoff and soil loss, threatening soil and water conservation in the Cerrado biome in Brazil. Due to the lack of long term observed data for runoff and soil erosion in Brazil, the adoption of a process-based model was necessary, representing the variability of both variables in a continuous simulation approach. Thus, we aimed to calibrate WEPP (Water Erosion Prediction Project) model for different land uses (undisturbed Cerrado, fallow, pasture, and sugarcane) under subtropical conditions inside the Cerrado biome; predict runoff and soil erosion for these different land uses; and simulate runoff and soil erosion considering climate change scenarios. We performed the model calibration using a 4-year dataset of observed runoff and soil loss in four different land uses (undisturbed Cerrado, fallow, pasture, and sugarcane). The WEPP model components (climate, topography, soil, and management) were calibrated according to field data. However, soil and management were optimized according to each land use using a parameter estimation tool. The observations were conducted between 2012 and 2015 in experimental plots (5 m width, 20 m length, 9% slope gradient, 3 replicates per treatment). The simulations were done using the calibrated WEPP model components, but changing the 4-year observed climate file by a 100-year dataset created with CLIGEN (weather generator) based on regional climate statistics. Afterwards, using MarkSim DSSAT Weather File Generator, runoff and soil loss were simulated using future climate scenarios for 2030, 2060, and 2090. To analyze the data, we used non-parametric statistics as data do not follow normal distribution. The results show that WEPP model had an acceptable performance for the considered conditions. In addition, both land use and climate can influence on runoff and soil loss rates. Potential climate changes which consider the increase of rainfall intensities and depths in the studied region may increase the variability and rates for runoff and soil erosion. However, the climate did not change the differences and similarities between the rates of the four analyzed land uses. The runoff behavior is distinct for all land uses, but for soil loss we found similarities between pasture and undisturbed Cerrado, suggesting that soil sustainability could be reached when the management follows conservation principles.

NASA Goddard Space Flight Center presents Enhancing Standards Based Science Curriculum through NASA Content Relevancy: A Model for Sustainable Teaching-Research Integration Dr. Robert Gabrys, Raquel Marshall, Dr. Evelina Felicite-Maurice, Erin McKinley

NASA Astrophysics Data System (ADS)

Marshall, R. H.; Gabrys, R.

2016-12-01

NASA Goddard Space Flight Center has developed a systemic educator professional development model for the integration of NASA climate change resources into the K-12 classroom. The desired outcome of this model is to prepare teachers in STEM disciplines to be globally engaged and knowledgeable of current climate change research and its potential for content relevancy alignment to standard-based curriculum. The application and mapping of the model is based on the state education needs assessment, alignment to the Next Generation Science Standards (NGSS), and implementation framework developed by the consortium of district superintendents and their science supervisors. In this presentation, we will demonstrate best practices for extending the concept of inquiry-based and project-based learning through the integration of current NASA climate change research into curriculum unit lessons. This model includes a significant teacher development component focused on capacity development for teacher instruction and pedagogy aimed at aligning NASA climate change research to related NGSS student performance expectations and subsequent Crosscutting Concepts, Science and Engineering Practices, and Disciplinary Core Ideas, a need that was presented by the district steering committee as critical for ensuring sustainability and high-impact in the classroom. This model offers a collaborative and inclusive learning community that connects classroom teachers to NASA climate change researchers via an ongoing consultant/mentoring approach. As a result of the first year of implementation of this model, Maryland teachers are implementing NGSS unit lessons that guide students in open-ended research based on current NASA climate change research.

Constraining Carbonaceous Aerosol Climate Forcing by Bridging Laboratory, Field and Modeling Studies

NASA Astrophysics Data System (ADS)

Dubey, M. K.; Aiken, A. C.; Liu, S.; Saleh, R.; Cappa, C. D.; Williams, L. R.; Donahue, N. M.; Gorkowski, K.; Ng, N. L.; Mazzoleni, C.; China, S.; Sharma, N.; Yokelson, R. J.; Allan, J. D.; Liu, D.

2014-12-01

Biomass and fossil fuel combustion emits black (BC) and brown carbon (BrC) aerosols that absorb sunlight to warm climate and organic carbon (OC) aerosols that scatter sunlight to cool climate. The net forcing depends strongly on the composition, mixing state and transformations of these carbonaceous aerosols. Complexities from large variability of fuel types, combustion conditions and aging processes have confounded their treatment in models. We analyse recent laboratory and field measurements to uncover fundamental mechanism that control the chemical, optical and microphysical properties of carbonaceous aerosols that are elaborated below: Wavelength dependence of absorption and the single scattering albedo (ω) of fresh biomass burning aerosols produced from many fuels during FLAME-4 was analysed to determine the factors that control the variability in ω. Results show that ω varies strongly with fire-integrated modified combustion efficiency (MCEFI)—higher MCEFI results in lower ω values and greater spectral dependence of ω (Liu et al GRL 2014). A parameterization of ω as a function of MCEFI for fresh BB aerosols is derived from the laboratory data and is evaluated by field data, including BBOP. Our laboratory studies also demonstrate that BrC production correlates with BC indicating that that they are produced by a common mechanism that is driven by MCEFI (Saleh et al NGeo 2014). We show that BrC absorption is concentrated in the extremely low volatility component that favours long-range transport. We observe substantial absorption enhancement for internally mixed BC from diesel and wood combustion near London during ClearFlo. While the absorption enhancement is due to BC particles coated by co-emitted OC in urban regions, it increases with photochemical age in rural areas and is simulated by core-shell models. We measure BrC absorption that is concentrated in the extremely low volatility components and attribute it to wood burning. Our results support enhanced light absorption by internally mixed BC parameterizations in models and identify mixed biomass and fossil combustion regions where this effect is large. We unify the treatment of carbonaceous aerosol components and their interactions to simplify and verify their representation in climate models, and re-evaluate their direct radiative forcing.

Climate Change and Public Health Surveillance: Toward a Comprehensive Strategy.

PubMed

Moulton, Anthony Drummond; Schramm, Paul John

Climate change poses a host of serious threats to human health that robust public health surveillance systems can help address. It is unknown, however, whether existing surveillance systems in the United States have adequate capacity to serve that role, nor what actions may be needed to develop adequate capacity. Our goals were to review efforts to assess and strengthen the capacity of public health surveillance systems to support health-related adaptation to climate change in the United States and to determine whether additional efforts are warranted. Building on frameworks issued by the Intergovernmental Panel on Climate Change and the Centers for Disease Control and Prevention, we specified 4 core components of public health surveillance capacity relevant to climate change health threats. Using standard methods, we next identified and analyzed multiple assessments of the existing, relevant capacity of public health surveillance systems as well as attempts to improve that capacity. We also received information from selected national public health associations. Multiple federal, state, and local public health agencies, professional associations, and researchers have made valuable, initial efforts to assess and strengthen surveillance capacity. These efforts, however, have been made by entities working independently and without the benefit of a shared conceptual framework or strategy. Their principal focus has been on identifying suitable indicators and data sources largely to the exclusion of other core components of surveillance capacity. A more comprehensive and strategic approach is needed to build the public health surveillance capacity required to protect the health of Americans in a world of rapidly evolving climate change. Public health practitioners and policy makers at all levels can use the findings and issues reviewed in this article as they lead design and execution of a coordinated, multisector strategic plan to create and sustain that capacity.

Climate Change and Public Health Surveillance: Toward a Comprehensive Strategy

PubMed Central

Moulton, Anthony Drummond; Schramm, Paul John

2017-01-01

Context Climate change poses a host of serious threats to human health that robust public health surveillance systems can help address. It is unknown, however, whether existing surveillance systems in the United States have adequate capacity to serve that role, nor what actions may be needed to develop adequate capacity. Objective Our goals were to review efforts to assess and strengthen the capacity of public health surveillance systems to support health-related adaptation to climate change in the United States and to determine whether additional efforts are warranted. Methods Building on frameworks issued by the Intergovernmental Panel on Climate Change and the Centers for Disease Control and Prevention, we specified 4 core components of public health surveillance capacity relevant to climate change health threats. Using standard methods, we next identified and analyzed multiple assessments of the existing, relevant capacity of public health surveillance systems as well as attempts to improve that capacity. We also received information from selected national public health associations. Findings Multiple federal, state, and local public health agencies, professional associations, and researchers have made valuable, initial efforts to assess and strengthen surveillance capacity. These efforts, however, have been made by entities working independently and without the benefit of a shared conceptual framework or strategy. Their principal focus has been on identifying suitable indicators and data sources largely to the exclusion of other core components of surveillance capacity. Conclusions A more comprehensive and strategic approach is needed to build the public health surveillance capacity required to protect the health of Americans in a world of rapidly evolving climate change. Public health practitioners and policy makers at all levels can use the findings and issues reviewed in this article as they lead design and execution of a coordinated, multisector strategic plan to create and sustain that capacity. PMID:28169865

Composition and structure of Pinus koraiensis mixed forest respond to spatial climatic changes.

PubMed

Zhang, Jingli; Zhou, Yong; Zhou, Guangsheng; Xiao, Chunwang

2014-01-01

Although some studies have indicated that climate changes can affect Pinus koraiensis mixed forest, the responses of composition and structure of Pinus koraiensis mixed forests to climatic changes are unknown and the key climatic factors controlling the composition and structure of Pinus koraiensis mixed forest are uncertain. Field survey was conducted in the natural Pinus koraiensis mixed forests along a latitudinal gradient and an elevational gradient in Northeast China. In order to build the mathematical models for simulating the relationships of compositional and structural attributes of the Pinus koraiensis mixed forest with climatic and non-climatic factors, stepwise linear regression analyses were performed, incorporating 14 dependent variables and the linear and quadratic components of 9 factors. All the selected new models were computed under the +2°C and +10% precipitation and +4°C and +10% precipitation scenarios. The Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month were observed to be key climatic factors controlling the stand densities and total basal areas of Pinus koraiensis mixed forest. Increased summer temperatures and precipitations strongly enhanced the stand densities and total basal areas of broadleaf trees but had little effect on Pinus koraiensis under the +2°C and +10% precipitation scenario and +4°C and +10% precipitation scenario. These results show that the Max Temperature of Warmest Month, Mean Temperature of Warmest Quarter and Precipitation of Wettest Month are key climatic factors which shape the composition and structure of Pinus koraiensis mixed forest. Although the Pinus koraiensis would persist, the current forests dominated by Pinus koraiensis in the region would all shift and become broadleaf-dominated forests due to the dramatic increase of broadleaf trees under the future global warming and increased precipitation.

Elevation Control on Vegetation Organization in a Semiarid Ecosystem in Central New Mexico

NASA Astrophysics Data System (ADS)

Nudurupati, S. S.; Istanbulluoglu, E.; Adams, J. M.; Hobley, D. E. J.; Gasparini, N. M.; Tucker, G. E.; Hutton, E. W. H.

2015-12-01

Many semiarid and desert ecosystems are characterized by patchy and dynamic vegetation. Topography plays a commanding role on vegetation patterns. It is observed that plant biomes and biodiversity vary systematically with slope and aspect, from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations. In this study, we investigate the role of elevation dependent climatology on vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. An ecohydrologic cellular automaton model developed within Landlab (component based modeling framework) is used. The model couples local vegetation dynamics (that simulate biomass production based on local soil moisture and potential evapotranspiration) and plant establishment and mortality based on competition for resources and space. This model is driven by elevation dependent rainfall pulses and solar radiation. The domain is initialized with randomly assigned plant types and the model parameters that couple plant response with soil moisture are systematically changed. Climate perturbation experiments are conducted to examine spatial vegetation organization and associated timescales. Model results reproduce elevation and aspect controls on observed vegetation patterns indicating that this model captures necessary and sufficient conditions that explain these observed ecohydrological patterns.

Inter-annual Variability of Evapotranspiration in a Semi-arid Oak-savanna Ecosystem: Measured and Modeled Buffering to Precipitation Changes

NASA Astrophysics Data System (ADS)

Raz-Yaseef, N.; Sonnentag, O.; Kobayashi, H.; Baldocchi, D. D.

2010-12-01

Precipitation (P) is the primary control on vegetation dynamics and productivity, implying that climate induced disturbances in frequency and timing of P are intimately coupled with fluxes of carbon, water and energy. Future climate change is expected to increase extreme rainfall events as well as droughts, suggesting linked vegetation changes to an unknown extent. Semi-arid climates experience large inter-annual variability (IAV) in P, creating natural conditions adequate to study how year-to-year changes in P affect atmosphere-biosphere fluxes. We used a 10-year flux database collected at a semi-arid savanna site in order to: (1) define IAV in P by means of frequency and timing; (2) investigate how changes in P affect the ecohydrology of the forest and its partitioning into the main vapor fluxes, and (3) evaluate model capability to predict IAV of carbon and water fluxes above and below the canopy. This is based on the perception that the capability of process-oriented models to construct the deviation, and not the average, is important in order to correctly predict ecosystem sensitivity to climate change. Our research site was a low density and low LAI (0.8) semi-arid (P=523±180 mm yr-1) savanna site, combined of oaks and grass, and located at Tonzi ranch, California. Measurements of carbon and water fluxes above and below the tree canopy using eddy covariance and supplementary measurements have been made since 2001. Measured fluxes were compared to modeled based on two bio-meteorological process-oriented ecosystem models: BEPS and 3D-CAONAK. Our results show that IAV in P was large, and standard deviation (STD) was 38% of the average. Accordingly, the wet soil period (measured volumetric water content > 8%) varied between 156 days in dry years to 301 days in wet years. IAV of the vapor fluxes were lower than that of P (STD was 17% for the trees and 23% for the floor components), suggesting on ecosystem buffering to changes in P. The timing of grass green up was correlated with the timing of first rains, emphasizing the higher dependence of the floor component on P, as reflected in higher IAV of the grasses compared to the trees. On average, models simulated annual fluxes well (R2>0.93), but IAV of the trees was higher than measured (24%), mostly due to model underestimation during dry years. A threshold at P~500 mm yr-1 was observed (both in measurements and modeled results), above which tree transpiration barely increased. The high IAV of the floor component was not replicated in the models (SDV=5%), although this flux accounted for 55% of total ET. Based on our study we conclude that trees in this semi-arid ecosystem have developed adaptive mechanisms that buffer themselves from the year-to-year variations in precipitation.

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

Not Available

The regional suitability of underground construction as a climate control technique is discussed with reference to (1) a bioclimatic analysis of long-term weather data for 29 locations in the United States to determine appropriate above ground climate control techniques, (2) a data base of synthesized ground temperatures for the coterminous United States, and (3) monthly dew point ground temperature comparisons for identifying the relative likelihood of condensation from one region to another. It is concluded that the suitability of earth tempering as a practice and of specific earth-sheltered design stereotypes varies geographically; while the subsurface almost always provides a thermalmore » advantage on its own terms when compared to above ground climatic data, it can, nonetheless, compromise the effectiveness of other, regionally more important climate control techniques. Also contained in the report are reviews of above and below ground climate mapping schemes related to human comfort and architectural design, and detailed description of a theoretical model of ground temperature, heat flow, and heat storage in the ground. Strategies of passive climate control are presented in a discussion of the building bioclimatic analysis procedure which has been applied in a computer analysis of 30 years of weather data for each of 29 locations in the United States.« less

Satellite-based Assessment of Climate Controls on US Burned Area

NASA Technical Reports Server (NTRS)

Morton, D. C.; Collatz, G. J.; Wang, D.; Randerson, J. T.; Giglio, L.; Chen, Y.

2012-01-01

Climate regulates fire activity through the buildup and drying of fuels and the conditions for fire ignition and spread. Understanding the dynamics of contemporary climate-fire relationships at national and sub-national scales is critical to assess the likelihood of changes in future fire activity and the potential options for mitigation and adaptation. Here, we conducted the first national assessment of climate controls on US fire activity using two satellite-based estimates of monthly burned area (BA), the Global Fire Emissions Database (GFED, 1997 2010) and Monitoring Trends in Burn Severity (MTBS, 1984 2009) BA products. For each US National Climate Assessment (NCA) region, we analyzed the relationships between monthly BA and potential evaporation (PE) derived from reanalysis climate data at 0.5 resolution. US fire activity increased over the past 25 yr, with statistically significant increases in MTBS BA for entire US and the Southeast and Southwest NCA regions. Monthly PE was strongly correlated with US fire activity, yet the climate driver of PE varied regionally. Fire season temperature and shortwave radiation were the primary controls on PE and fire activity in the Alaska, while water deficit (precipitation PE) was strongly correlated with fire activity in the Plains regions and Northwest US. BA and precipitation anomalies were negatively correlated in all regions, although fuel-limited ecosystems in the Southern Plains and Southwest exhibited positive correlations with longer lead times (6 12 months). Fire season PE in creased from the 1980s 2000s, enhancing climate-driven fire risk in the southern and western US where PE-BA correlations were strongest. Spatial and temporal patterns of increasing fire season PE and BA during the 1990s 2000s highlight the potential sensitivity of US fire activity to climate change in coming decades. However, climatefire relationships at the national scale are complex, based on the diversity of fire types, ecosystems, and ignition sources within each NCA region. Changes in the seasonality or magnitude of climate anomalies are therefore unlikely to result in uniform changes in US fire activity.

Assessing Extratropical Influence on Tropical Climatology and Variability with Regional Coupled Data Assimilation

NASA Astrophysics Data System (ADS)

Lu, F.; Liu, Z.; Liu, Y.; Zhang, S.; Jacob, R. L.

2017-12-01

The Regional Coupled Data Assimilation (RCDA) method is introduced as a tool to study coupled climate dynamics and teleconnections. The RCDA method is built on an ensemble-based coupled data assimilation (CDA) system in a coupled general circulation model (CGCM). The RCDA method limits the data assimilation to the desired model components (e.g. atmosphere) and regions (e.g. the extratropics), and studies the ensemble-mean model response (e.g. tropical response to "observed" extratropical atmospheric variability). When applied to the extratropical influence on tropical climate, the RCDA method has shown some unique advantages, namely the combination of a fully coupled model, real-world observations and an ensemble approach. Tropical variability (e.g. El Niño-Southern Oscillation or ENSO) and climatology (e.g. asymmetric Inter-Tropical Convergence Zone or ITCZ) were initially thought to be determined mostly by local forcing and ocean-atmosphere interaction in the tropics. Since late 20th century, numerous studies have showed that extratropical forcing could affect, or even largely determine some aspects of the tropical climate. Due to the coupled nature of the climate system, however, the challenge of determining and further quantifying the causality of extratropical forcing on the tropical climate remains. Using the RCDA method, we have demonstrated significant control of extratropical atmospheric forcing on ENSO variability in a CGCM, both with model-generated and real-world observation datasets. The RCDA method has also shown robust extratropical impact on the tropical double-ITCZ bias in a CGCM. The RCDA method has provided the first systematic and quantitative assessment of extratropical influence on tropical climatology and variability by incorporating real world observations in a CGCM.

Advancing Climate Change and Impacts Science Through Climate Informatics

NASA Astrophysics Data System (ADS)

Lenhardt, W.; Pouchard, L. C.; King, A. W.; Branstetter, M. L.; Kao, S.; Wang, D.

2010-12-01

This poster will outline the work to date on developing a climate informatics capability at Oak Ridge National Laboratory (ORNL). The central proposition of this effort is that the application of informatics and information science to the domain of climate change science is an essential means to bridge the realm of high performance computing (HPC) and domain science. The goal is to facilitate knowledge capture and the creation of new scientific insights. For example, a climate informatics capability will help with the understanding and use of model results in domain sciences that were not originally in the scope. From there, HPC can also benefit from feedback as the new approaches may lead to better parameterization in the models. In this poster we will summarize the challenges associated with climate change science that can benefit from the systematic application of informatics and we will highlight our work to date in creating the climate informatics capability to address these types of challenges. We have identified three areas that are particularly challenging in the context of climate change science: 1) integrating model and observational data across different spatial and temporal scales, 2) model linkages, i.e. climate models linked to other models such as hydrologic models, and 3) model diagnostics. Each of these has a methodological component and an informatics component. Our project under way at ORNL seeks to develop new approaches and tools in the context of linking climate change and water issues. We are basing our work on the following four use cases: 1) Evaluation/test of CCSM4 biases in hydrology (precipitation, soil water, runoff, river discharge) over the Rio Grande Basin. User: climate modeler. 2) Investigation of projected changes in hydrology of Rio Grande Basin using the VIC (Variable Infiltration Capacity Macroscale) Hydrologic Model. User: watershed hydrologist/modeler. 3) Impact of climate change on agricultural productivity of the Rio Grande Basin. User: climate impact scientist, agricultural economist. 4) Renegotiation of the 1944 “Treaty for the Utilization of Waters of the Colorado and Tijuana Rivers and of the Rio Grande”. User: A US State Department analyst or their counterpart in Mexico.

Data near processing support for climate data analysis

NASA Astrophysics Data System (ADS)

Kindermann, Stephan; Ehbrecht, Carsten; Hempelmann, Nils

2016-04-01

Climate data repositories grow in size exponentially. Scalable data near processing capabilities are required to meet future data analysis requirements and to replace current "data download and process at home" workflows and approaches. On one hand side, these processing capabilities should be accessible via standardized interfaces (e.g. OGC WPS), on the other side a large variety of processing tools, toolboxes and deployment alternatives have to be supported and maintained at the data/processing center. We present a community approach of a modular and flexible system supporting the development, deployment and maintenace of OGC-WPS based web processing services. This approach is organized in an open source github project (called "bird-house") supporting individual processing services ("birds", e.g. climate index calculations, model data ensemble calculations), which rely on basic common infrastructural components (e.g. installation and deployment recipes, analysis code dependencies management). To support easy deployment at data centers as well as home institutes (e.g. for testing and development) the system supports the management of the often very complex package dependency chain of climate data analysis packages as well as docker based packaging and installation. We present a concrete deployment scenario at the German Climate Computing Center (DKRZ). The DKRZ one hand side hosts a multi-petabyte climate archive which is integrated e.g. into the european ENES and worldwide ESGF data infrastructure, and on the other hand hosts an HPC center supporting (model) data production and data analysis. The deployment scenario also includes openstack based data cloud services to support data import and data distribution for bird-house based WPS web processing services. Current challenges for inter-institutionnal deployments of web processing services supporting the european and international climate modeling community as well as the climate impact community are highlighted. Also aspects supporting future WPS based cross community usage scenarios supporting data reuse and data provenance aspects are reflected.

Plant Invasions in China – Challenges and Chances

PubMed Central

Axmacher, Jan C.; Sang, Weiguo

2013-01-01

Invasive species cause serious environmental and economic harm and threaten global biodiversity. We set out to investigate how quickly invasive plant species are currently spreading in China and how their resulting distribution patterns are linked to socio-economic and environmental conditions. A comparison of the invasive plant species density (log species/log area) reported in 2008 with current data shows that invasive species were originally highly concentrated in the wealthy, southeastern coastal provinces of China, but they are currently rapidly spreading inland. Linear regression models based on the species density and turnover of invasive plants as dependent parameters and principal components representing key socio-economic and environmental parameters as predictors indicate strong positive links between invasive plant density and the overall phytodiversity and associated climatic parameters. Principal components representing socio-economic factors and endemic plant density also show significant positive links with invasive plant density. Urgent control and eradication measures are needed in China's coastal provinces to counteract the rapid inland spread of invasive plants. Strict controls of imports through seaports need to be accompanied by similarly strict controls of the developing horticultural trade and underpinned by awareness campaigns for China's increasingly affluent population to limit the arrival of new invaders. Furthermore, China needs to fully utilize its substantial native phytodiversity, rather than relying on exotics, in current large-scale afforestation projects and in the creation of urban green spaces. PMID:23691164

Youth Climate Summits: Empowering & Engaging Youth to Lead on Climate Change

NASA Astrophysics Data System (ADS)

Kretser, J.

2017-12-01

The Wild Center's Youth Climate Summits is a program that engages youth in climate literacy from knowledge and understanding to developing action in their schools and communities. Each Youth Climate Summit is a one to three day event that brings students and teachers together to learn about climate change science, impacts and solutions at a global and local level. Through speakers, workshops and activities, the Summit culminates in a student-driven Climate Action Plan that can be brought back to schools and communities. The summits have been found to be powerful vehicles for inspiration, learning, community engagement and youth leadership development. Climate literacy with a focus on local climate impacts and solutions is a key component of the Youth Climate Summit. The project-based learning surrounding the creation of a unique, student driven, sustainability and Climate Action Plan promotes leadership skills applicable and the tools necessary for a 21st Century workforce. Student driven projects range from school gardens and school energy audits to working with NYS officials to commit to going 100% renewable electricty at the three state-owned downhill ski facilities. The summit model has been scaled and replicated in other communities in New York State, Vermont, Ohio, Michigan and Washington states as well as internationally in Finland, Germany and Sri Lanka.

Creating "Intelligent" Climate Model Ensemble Averages Using a Process-Based Framework

NASA Astrophysics Data System (ADS)

Baker, N. C.; Taylor, P. C.

2014-12-01

The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is often used to add value to model projections: consensus projections have been shown to consistently outperform individual models. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, certain models reproduce climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables—e.g., outgoing longwave radiation and surface temperature. Metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument and surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing weighted and unweighted model ensembles. For example, one tested metric weights the ensemble by how well models reproduce the time-series probability distribution of the cloud forcing component of reflected shortwave radiation. The weighted ensemble for this metric indicates lower simulated precipitation (up to .7 mm/day) in tropical regions than the unweighted ensemble: since CMIP5 models have been shown to overproduce precipitation, this result could indicate that the metric is effective in identifying models which simulate more realistic precipitation. Ultimately, the goal of the framework is to identify performance metrics for advising better methods for ensemble averaging models and create better climate predictions.

The Decadal Climate Prediction Project (DCPP) contribution to CMIP6

DOE PAGES

Boer, George J.; Smith, Douglas M.; Cassou, Christophe; ...

2016-01-01

The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Predictionmore » (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Furthermore, groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.« less

Inspiring Inquiry: Scientists, science teachers, and GK-12 students learning climate science together

NASA Astrophysics Data System (ADS)

Stwertka, C.; Blonquist, J.; Feener, D.

2010-12-01

A major communication gap exists between climate scientists, educators, and society. As a result, findings from climate research, potential implications of climate change, and possible mitigation strategies are not fully understood and accepted outside of the climate science community. A good way to begin bridging the gap is to teach climate science to students in public schools. TGLL (Think Globally, Learn Locally) is an NSF GK-12 program based at the University of Utah, which partners graduate students in the biological, geological and atmospheric sciences with middle and high school teachers in the Salt Lake City School District to improve the communication skills of Fellows and enhance inquiry-based science teaching and learning in the classroom. Each TGLL Fellow works in the same classroom(s) throughout the year, developing his or her scientific communication skills while providing teachers with content knowledge, resources, classroom support, and enhancing the experience of students such that science becomes an interesting and accessible tool for acquiring knowledge. The TGLL Fellows work closely as a group to develop inquiry-based teaching modules (a series of lessons) and a field trip that involve students in doing authentic science. Lessons are designed to apply national and Utah core curriculum concepts to broader scientific issues such as habitat alteration, pollution and disturbance, invasive species, and infectious disease, with the focus of the 2010-2011 school year being climate change. The TGLL Global Climate Change module contains lesson plans on climate temporal and spatial scales, temperature variation, energy balance, the carbon cycle, the greenhouse effect, climate feedback loops, anthropogenic climate change indicators, climate change consequences and impacts, and actions students can take to reduce greenhouse gas emissions. The capstone experience for the module is a “Backyard Climate Change” field trip to a local pristine canyon. Students will map and measure the carbon dioxide flux of various ecosystem components, measure the albedo of various surfaces, learn about micro-scale climates and atmospheric pollen transport, measure water and air quality, and observe habitat alteration. Through the module and fieldtrip, TGLL Fellows aim to build student and teacher knowledge about climate change and create lasting projects that are adapted into the core science curriculum.

Estimating the numerical diapycnal mixing in an eddy-permitting ocean model

NASA Astrophysics Data System (ADS)

Megann, Alex

2018-01-01

Constant-depth (or "z-coordinate") ocean models such as MOM4 and NEMO have become the de facto workhorse in climate applications, having attained a mature stage in their development and are well understood. A generic shortcoming of this model type, however, is a tendency for the advection scheme to produce unphysical numerical diapycnal mixing, which in some cases may exceed the explicitly parameterised mixing based on observed physical processes, and this is likely to have effects on the long-timescale evolution of the simulated climate system. Despite this, few quantitative estimates have been made of the typical magnitude of the effective diapycnal diffusivity due to numerical mixing in these models. GO5.0 is a recent ocean model configuration developed jointly by the UK Met Office and the National Oceanography Centre. It forms the ocean component of the GC2 climate model, and is closely related to the ocean component of the UKESM1 Earth System Model, the UK's contribution to the CMIP6 model intercomparison. GO5.0 uses version 3.4 of the NEMO model, on the ORCA025 global tripolar grid. An approach to quantifying the numerical diapycnal mixing in this model, based on the isopycnal watermass analysis of Lee et al. (2002), is described, and the estimates thereby obtained of the effective diapycnal diffusivity in GO5.0 are compared with the values of the explicit diffusivity used by the model. It is shown that the effective mixing in this model configuration is up to an order of magnitude higher than the explicit mixing in much of the ocean interior, implying that mixing in the model below the mixed layer is largely dominated by numerical mixing. This is likely to have adverse consequences for the representation of heat uptake in climate models intended for decadal climate projections, and in particular is highly relevant to the interpretation of the CMIP6 class of climate models, many of which use constant-depth ocean models at ¼° resolution

Impact of Active Climate Control Seats on Energy Use, Fuel Use, and CO2 Emissions

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

Kreutzer, Cory J; Rugh, John P; Titov, Eugene V

A project was developed through collaboration between Gentherm and NREL to determine the impact of climate control seats for light-duty vehicles in the United States. The project used a combination of experimentation and analysis, with experimental results providing critical input to the analysis process. First, outdoor stationary vehicle testing was performed at NREL's facility in Golden, CO using multiple occupants. Two pre-production Ford Focus electric vehicles were used for testing; one containing a standard inactive seat and the second vehicle containing a Gentherm climate control seat. Multiple maximum cool-down and steady-state cooling tests were performed in late summer conditions. Themore » two vehicles were used to determine the increase in cabin temperature when using the climate control seat in comparison to the baseline vehicle cabin temperature with a standard seat at the equivalent occupant whole-body sensation. The experiments estimated that on average, the climate control seats allowed for a 2.61 degrees Celsius increase in vehicle cabin temperature at equivalent occupant body sensation compared to the baseline vehicle. The increased cabin air temperature along with their measured energy usage were then used as inputs to the national analysis process. The national analysis process was constructed from full vehicle cabin, HVAC, and propulsion models previously developed by NREL. In addition, three representative vehicle platforms, vehicle usage patterns, and vehicle registration weighted environmental data were integrated into the analysis process. Both the baseline vehicle and the vehicle with climate control seats were simulated, using the experimentally determined cabin temperature offset of 2.61degrees Celsius and added seat energy as inputs to the climate control seat vehicle model. The U.S. composite annual fuel use savings for the climate control seats over the baseline A/C system was determined to be 5.1 gallons of gasoline per year per vehicle, corresponding to 4.0 grams of CO2/mile savings. Finally, the potential impact of 100 percent adoption of climate control seats on U.S. light-duty fleet A/C fuel use was calculated to be 1.3 billion gallons of gasoline annually with a corresponding CO2 emissions reduction of 12.7 million tons. Direct comparison of the impact of the CCS to the ventilated seat off-cycle credit was not possible because the NREL analysis calculated a combined car/truck savings and the baseline A/C CO2 emissions were higher than EPA. To enable comparison, the CCS national A/C CO2 emissions were split into car/truck components and the ventilated seat credit was scaled up. The split CO2 emissions savings due to the CCS were 3.5 g/mi for a car and 4.4 g/mi for a truck. The CCS saved an additional 2.0 g/mi and 2.5 g/mi over the adjusted ventilated seat credit for a car and truck, respectively.« less

Vulnerability and Tradeoffs of Dairy Farmers to the Impacts of Climate Variability and Change in India

NASA Astrophysics Data System (ADS)

Radhakrishnan, A.; Gupta, J.; R, D.

2016-12-01

In recent years climate variability has threatened the sustainability of dairy animals and dairy farming in India. The study aims at assessing the vulnerability and tradeoffs of Dairy Based Livelihoods to Climate Variability and Change in the Western Ghat ecosystem and for this purpose; data were aggregated to an overall Livelihood Vulnerability Index (LVI) to Climate Change underlying the principles of IPCC, using 28 indicators and trade-off between vulnerability and milk production was calculated. Data were collected through Participatory Rural Appraisal and personal interviews from 360 randomly selected dairy farmers of three states of Western Ghat region, complemented by thirty years of gridded weather data and livestock data. The index score of dairy based livelihoods of many regions were negative. Lanja taluka of Maharashtra has highest level of vulnerability with overall LVI value -4.17 with 48% farmers falling in highly vulnerable category. There is also significant tradeoff between milk production and components of LVI. Thus our research will provide an important basis for policy makers to develop appropriate adaptation strategies for alarming situation and decision making for farmers to minimize the risk of dairy sector to climate variability.

A computational approach to climate science education with CLIMLAB

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2017-12-01

CLIMLAB is a Python-based software toolkit for interactive, process-oriented climate modeling for use in education and research. It is motivated by the need for simpler tools and more reproducible workflows with which to "fill in the gaps" between blackboard-level theory and the results of comprehensive climate models. With CLIMLAB you can interactively mix and match physical model components, or combine simpler process models together into a more comprehensive model. I use CLIMLAB in the classroom to put models in the hands of students (undergraduate and graduate), and emphasize a hierarchical, process-oriented approach to understanding the key emergent properties of the climate system. CLIMLAB is equally a tool for climate research, where the same needs exist for more robust, process-based understanding and reproducible computational results. I will give an overview of CLIMLAB and an update on recent developments, including: a full-featured, well-documented, interactive implementation of a widely-used radiation model (RRTM) packaging with conda-forge for compiler-free (and hassle-free!) installation on Mac, Windows and Linux interfacing with xarray for i/o and graphics with gridded model data a rich and growing collection of examples and self-computing lecture notes in Jupyter notebook format

Effectiveness-weighted control method for a cooling system

DOEpatents

Campbell, Levi A.; Chu, Richard C.; David, Milnes P.; Ellsworth Jr., Michael J.; Iyengar, Madhusudan K.; Schmidt, Roger R.; Simons, Robert E.

2015-12-15

Energy efficient control of cooling system cooling of an electronic system is provided based, in part, on weighted cooling effectiveness of the components. The control includes automatically determining speed control settings for multiple adjustable cooling components of the cooling system. The automatically determining is based, at least in part, on weighted cooling effectiveness of the components of the cooling system, and the determining operates to limit power consumption of at least the cooling system, while ensuring that a target temperature associated with at least one of the cooling system or the electronic system is within a desired range by provisioning, based on the weighted cooling effectiveness, a desired target temperature change among the multiple adjustable cooling components of the cooling system. The provisioning includes provisioning applied power to the multiple adjustable cooling components via, at least in part, the determined control settings.

Selecting climate simulations for impact studies based on multivariate patterns of climate change.

PubMed

Mendlik, Thomas; Gobiet, Andreas

In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics. The online version of this article (doi:10.1007/s10584-015-1582-0) contains supplementary material, which is available to authorized users.

Improved attribution of climate forcing to emissions by pollutant and sector

NASA Astrophysics Data System (ADS)

Shindell, D. T.

2009-12-01

Evaluating multi-component climate change mitigation strategies requires knowledge of the diverse direct and indirect effects of emissions. Methane, ozone and aerosols are linked through atmospheric chemistry so that emissions of a single pollutant can affect several species. I will show new calculations of atmospheric composition changes, radiative forcing, and the global warming potential (GWP) for increased emissions of tropospheric ozone and aerosol precursors in a coupled composition-climate model. The results demonstrate that gas-aerosol interactions substantially alter the relative importance of the various emissions, suggesting revisions to the GWPs used in international carbon trading. Additionally, I will present results showing how the net climate impact of particular activities depends strongly upon non-CO2 forcing agents for some sectors. These results will be highlighted by discussing the interplay between air quality emissions controls and climate for the case of emissions from coal-fired power plants. The changing balance between CO2 and air quality pollutants from coal plants may have contributed to the 20th century spatial and temporal patterns of climate change, and is likely to continue to do so as more and more plants are constructed in Asia.

Health and Climate Impacts of Rural Residential Energy Transition in China

NASA Astrophysics Data System (ADS)

Tao, Shu; Ru, Muye; Du, Wei; Zhu, Xi; Zhong, Qirui

2017-04-01

Over the last two to three decades, energy mix in rural China transit dramatically owing to rapid socioeconomic development. It is expected that such transition can result in changes in emissions of climate forcing components and air pollutants, consequently environmental and climate impacts. Such impacts were quantified by a nationwide survey on rural residential energy consumption, compilation of a series of emission inventories, modeling of atmospheric transport of pollutants, assessment on health risk induced by exposure to ambient air pollutants, and evaluation on rural residential emission originated climate forcing components. Co-benefit of the transition on both health and climate is demonstrated.

Energy-based and process-based constraints on aerosol-climate interaction

NASA Astrophysics Data System (ADS)

Suzuki, K.; Sato, Y.; Takemura, T.; Michibata, T.; Goto, D.; Oikawa, E.

2017-12-01

Recent advance in both satellite observations and global modeling provides us with a novel opportunity to investigate the long-standing aerosol-climate interaction issue at a fundamental process level, particularly with a combined use of them. In this presentation, we will highlight our recent progress in understanding the aerosol-cloud-precipitation interaction and its implication for global climate with a synergistic use of a state-of-the-art global climate model (MIROC), a global cloud-resolving model (NICAM) and recent satellite observations (A-Train). In particular, we explore two different aspects of the aerosol-climate interaction issue, i.e. (i) the global energy balance perspective with its modulation due to aerosols and (ii) the process-level characteristics of the aerosol-induced perturbations to cloud and precipitation. For the former, climate model simulations are used to quantify how components of global energy budget are modulated by the aerosol forcing. The moist processes are shown to be a critical pathway that links the forcing efficacy and the hydrologic sensitivity arising from aerosol perturbations. Effects of scattering (e.g. sulfate) and absorbing (e.g. black carbon) aerosols are compared in this context to highlight their distinctively different impacts on climate and hydrologic cycle. The aerosol-induced modulation of moist processes is also investigated in the context of the second aspect above to facilitate recent arguments on possible overestimates of the aerosol-cloud interaction in climate models. Our recent simulations with NICAM are shown to highlight how diverse responses of cloud to aerosol perturbation, which have been failed to represent in traditional climate models, are reproduced by the high-resolution global model with sophisticated cloud microphysics. We will discuss implications of these findings for a linkage between the two aspects above to aid advance process-based understandings of the aerosol-climate interaction and also to mitigate a "dichotomy" recently found by the authors between the two aspects in the context of the climate projection.

Residential expansion as a continental threat to U.S. coastal ecosystems

Treesearch

J.G. Bartlett; D.M. Mageean; R.J. O' Connor

2000-01-01

Spatially extensive analysis of satellite, climate, and census data reveals human-environment interactions of regional or continental concern in the United States. A grid-based principal components analysis of Bureau of Census variables revealed two independent demographic phenomena, a-settlement reflecting traditional human settlement patterns and p-settlement...

The first decade of the Massachusetts Tobacco Control Program.

PubMed Central

Koh, Howard K.; Judge, Christine M.; Robbins, Harriet; Celebucki, Carolyn Cobb; Walker, Deborah K.; Connolly, Gregory N.

2005-01-01

This article provides a comprehensive overview of the first decade of the Massachusetts Tobacco Control Program (MTCP). Born after Massachusetts passed a 1992 ballot initiative raising cigarette excise taxes to fund the program, MTCP greatly reduced statewide cigarette consumption before being reduced to a skeletal state by funding cuts. The article describes the program's components and goals, details outcomes, presents a summary of policy accomplishments, and reviews the present status of MTCP in the current climate of national and state fiscal crises. The first decade of the MTCP offers many lessons learned for the future of tobacco control. PMID:16224981

The first decade of the Massachusetts Tobacco Control Program.

PubMed

Koh, Howard K; Judge, Christine M; Robbins, Harriet; Celebucki, Carolyn Cobb; Walker, Deborah K; Connolly, Gregory N

2005-01-01

This article provides a comprehensive overview of the first decade of the Massachusetts Tobacco Control Program (MTCP). Born after Massachusetts passed a 1992 ballot initiative raising cigarette excise taxes to fund the program, MTCP greatly reduced statewide cigarette consumption before being reduced to a skeletal state by funding cuts. The article describes the program's components and goals, details outcomes, presents a summary of policy accomplishments, and reviews the present status of MTCP in the current climate of national and state fiscal crises. The first decade of the MTCP offers many lessons learned for the future of tobacco control.

Estimates of spatial and temporal variation of energy crops biomass yields in the US

NASA Astrophysics Data System (ADS)

Song, Y.; Jain, A. K.; Landuyt, W.; Kheshgi, H. S.

2013-12-01

Perennial grasses, such as switchgrass (Panicum viragatum) and Miscanthus (Miscanthus x giganteus) have been identified for potential use as biomass feedstocks in the US. Current research on perennial grass biomass production has been evaluated on small-scale plots. However, the extent to which this potential can be realized at a landscape-scale will depend on the biophysical potential to grow these grasses with minimum possible amount of land that needs to be diverted from food to fuel production. To assess this potential three questions about the biomass yield for these grasses need to be answered: (1) how the yields for different grasses are varied spatially and temporally across the US; (2) whether the yields are temporally stable or not; and (3) how the spatial and temporal trends in yields of these perennial grasses are controlled by limiting factors, including soil type, water availability, climate, and crop varieties. To answer these questions, the growth processes of the perennial grasses are implemented into a coupled biophysical, physiological and biogeochemical model (ISAM). The model has been applied to quantitatively investigate the spatial and temporal trends in biomass yields for over the period 1980 -2010 in the US. The bioenergy grasses considered in this study include Miscanthus, Cave-in-Rock switchgrass and Alamo switchgrass. The effects of climate, soil and topography on the spatial and temporal trends of biomass yields are quantitatively analyzed using principal component analysis and GIS based geographically weighted regression. The spatial temporal trend results are evaluated further to classify each part of the US into four homogeneous potential yield zones: high and stable yield zone (HS), high but unstable yield zone (HU), low and stable yield zone (LS) and low but unstable yield zone (LU). Our preliminary results indicate that the yields for perennial grasses among different zones are strongly related to the different controlling factors. For example, the yield in HS zone is depended on soil and topography factors. However, the yields in HU zone are more controlled by climate factors, leading to a large uncertainty in yield potential of bioenergy grasses under future climate change.

Better retention through game-play - EcoChains: Arctic Crisis card game

NASA Astrophysics Data System (ADS)

Pfirman, S. L.; Lee, J.; O'Garra, T.; Bachrach, E.

2015-12-01

Increasingly games are being used in formal and informal education with the goal of improving student/participant understanding of content knowledge through enhanced engagement. While most games are fun by design, few controlled studies have been conducted to assess games' potential for learning gains in comparison with traditional educational approaches. Without evidence for learning, it can be difficult to justify incorporating STEM games in curricula and other programming. In this study we assess the impact of a game called EcoChains (http://thepolarhub.org/project/ecochains-arctic-crisis) on learning, using a controlled experiment. The EcoChains: Arctic Crisis card game gives players the opportunity to learn about the components of an Arctic marine food web, the reliance of some species on sea ice, and the potential impacts of future changes on the ecosystem. EcoChains was developed under the Polar Learning and Responding: PoLAR Climate Change Education Partnership (thepolarhub.org). EcoChains aligns with Next Generation Science Standards LS2 Ecosystems: Interactions, Energy, and Dynamics and ESS3 Earth and Human Activity. Participants in this experiment (n=41) were randomly assigned to either play EcoChains or to read a magazine-style article with similar content (the control). Questionnaires, mapping exercises and a 4-week follow-up survey were used to identify changes in participant knowledge of climate change and the Arctic region, attitudes and beliefs about climate change and its impacts, information-seeking behaviors, systems thinking, impressions of and engagement with the intervention experience. Analysis indicates that the game was as effective as, and in some respects more effective than, the article at teaching participants about climate change and the Arctic region and ecosystems. The follow up survey found that game players recalled new information better than those who read the article. Participants were also more engaged in the game than the article, they found it to be more fun, they were happier while playing than while reading, and they were more likely to recommend the game to others. These findings indicate that game-based learning can improve retention of new content knowledge as well as engagement in subject matter.

Interactive, process-oriented climate modeling with CLIMLAB

NASA Astrophysics Data System (ADS)

Rose, B. E. J.

2016-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The Jupyter Notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields.

Welcome to NASA's Earth Science Enterprise. Version 3

NASA Technical Reports Server (NTRS)

2001-01-01

There are strong scientific indications that natural change in the Earth system is being accelerated by human intervention. As a result, planet Earth faces the possibility of rapid environmental changes that would have a profound impact on all nations. However, we do not fully understand either the short-term effects of our activities, or their long-term implications - many important scientific questions remain unanswered. The National Aeronautics and Space Administration (NASA) is working with the national and international scientific communities to establish a sound scientific basis for addressing these critical issues through research efforts coordinated under the U.S. Global Change Research Program, the International Geosphere-Biosphere Program, and the World Climate Research Program. The Earth Science Enterprise is NASA's contribution to the U.S. Global Change Research Program. NASA's Earth Science Enterprise will use space- and surface-based measurement systems to provide the scientific basis for understanding global change. The space-based components will provide a constellation of satellites to monitor the Earth from space. A major component of the Earth Science Enterprise is the Earth Observing System (EOS). The overall objective of the EOS Program is to determine the extent, causes, and regional consequences of global climate change. EOS will provide sustained space-based observations that will allow researchers to monitor climate variables over time to determine trends. A constellation of EOS satellites will acquire global data, beginning in 1998 and extending well into the 21st century.

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

PubMed

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

2006-07-01

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

Thermal Storage System for Electric Vehicle Cabin Heating Component and System Analysis

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

LaClair, Tim J; Gao, Zhiming; Abdelaziz, Omar

Cabin heating of current electric vehicle (EV) designs is typically provided using electrical energy from the traction battery, since waste heat is not available from an engine as in the case of a conventional automobile. In very cold climatic conditions, the power required for space heating of an EV can be of a similar magnitude to that required for propulsion of the vehicle. As a result, its driving range can be reduced very significantly during the winter season, which limits consumer acceptance of EVs and results in increased battery costs to achieve a minimum range while ensuring comfort to themore » EV driver. To minimize the range penalty associated with EV cabin heating, a novel climate control system that includes thermal energy storage from an advanced phase change material (PCM) has been designed for use in EVs and plug-in hybrid electric vehicles (PHEVs). The present paper focuses on the modeling and analysis of this electrical PCM-Assisted Thermal Heating System (ePATHS) and is a companion to the paper Design and Testing of a Thermal Storage System for Electric Vehicle Cabin Heating. A detailed heat transfer model was developed to simulate the PCM heat exchanger that is at the heart of the ePATHS and was subsequently used to analyze and optimize its design. The results from this analysis were integrated into a MATLAB Simulink system model to simulate the fluid flow, pressure drop and heat transfer in all components of the ePATHS. The system model was then used to predict the performance of the climate control system in the vehicle and to evaluate control strategies needed to achieve the desired temperature control in the cabin. The analysis performed to design the ePATHS is described in detail and the system s predicted performance in a vehicle HVAC system is presented.« less

Prediction of the potential global distribution for Biomphalaria straminea, an intermediate host for Schistosoma mansoni

PubMed Central

Yang, Ya; Cheng, Wanting; Wu, Xiaoying; Huang, Shaoyu; Deng, Zhuohui; Zeng, Xin; Yang, Yu; Wu, Zhongdao; Chen, Yue; Zhou, Yibiao; Jiang, Qingwu

2018-01-01

Background Schistosomiasis is a snail-borne parasitic disease and is endemic in many tropical and subtropical countries. Biomphalaria straminea, an intermediate host for Schistosoma mansoni, is native to the southeastern part of South America and has established in other regions of South America, Central America and southern China during the last decades. S. mansoni is endemic in Africa, the Middle East, South America and the Caribbean. Knowledge of the potential global distribution of this snail is essential for risk assessment, monitoring, disease prevention and control. Methods and findings A comprehensive database of cross-continental occurrence for B. straminea was compiled to construct ecological models. We used several approaches to investigate the distribution of B. straminea, including direct comparison of climatic conditions, principal component analysis and niche overlap analyses to detect niche shifts. We also investigated the impacts of bioclimatic and human factors, and then used the bioclimatic and footprint layers to predict the potential distribution of B. straminea at global scale. We detected niche shifts accompanying the invasions of B. straminea in the Americas and China. The introduced populations had enlarged its habitats to subtropical regions where annual mean temperature is relatively low. Annual mean temperature, isothermality and temperature seasonality were identified as most important climatic features for the occurrence of B. straminea. Additionally, human factors improved the model prediction (P<0.001). Our model showed that under current climate conditions the snail should mostly be confined to the tropic and subtropic regions, including South America, Central America, Sub-Saharan Africa and Southeast Asia. Conclusions Our results confirmed that niche shifts took place in the invasions of B. straminea, in which bioclimatic and human factors played an important role. Our model predicted the global distribution of B. straminea based on habitat suitability, which would help for prioritizing monitoring and management efforts for B. straminea control in the context of ongoing climate change and human disturbances. PMID:29813073

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

NASA Astrophysics Data System (ADS)

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

2012-11-01

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

Independent Blade Pitch Controller Design for a Three-Bladed Turbine Using Disturbance Accommodating Control

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

Wang, Na; Wright, Alan D.; Johnson, Kathryn E.

Two independent pitch controllers (IPCs) based on the disturbance accommodating control (DAC) algorithm are designed for the three-bladed Controls Advanced Research Turbine to regulate rotor speed and to mitigate blade root flapwise bending loads in above-rated wind speed. One of the DAC-based IPCs is designed based on a transformed symmetrical-asymmetrical (TSA) turbine model, with wind disturbances being modeled as a collective horizontal component and an asymmetrical linear shear component. Another DAC-based IPC is designed based on a multiblade coordinate (MBC) transformed turbine model, with a horizontal component and a vertical shear component being modeled as step waveform disturbance. Both ofmore » the DAC-based IPCs are found via a regulation equation solved by Kronecker product. Actuator dynamics are considered in the design processes to compensate for actuator phase delay. The simulation study shows the effectiveness of the proposed DAC-based IPCs compared to a proportional-integral (PI) collective pitch controller (CPC). Improvement on rotor speed regulation and once-per-revolution and twice-per-revolution load reductions has been observed in the proposed IPC designs.« less

Independent Blade Pitch Controller Design for a Three-Bladed Turbine Using Disturbance Accommodating Control: Preprint

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

Wang, Na; Wright, Alan D.; Johnson, Kathryn E.

Two independent pitch controllers (IPCs) based on the disturbance accommodating control (DAC) algorithm are designed for the three-bladed Controls Advanced Research Turbine to regulate rotor speed and to mitigate blade root flapwise bending loads in above-rated wind speed. One of the DAC-based IPCs is designed based on a transformed symmetrical-asymmetrical (TSA) turbine model, with wind disturbances being modeled as a collective horizontal component and an asymmetrical linear shear component. Another DAC-based IPC is designed based on a multiblade coordinate (MBC) transformed turbine model, with a horizontal component and a vertical shear component being modeled as step waveform disturbance. Both ofmore » the DAC-based IPCs are found via a regulation equation solved by Kronecker product. Actuator dynamics are considered in the design processes to compensate for actuator phase delay. The simulation study shows the effectiveness of the proposed DAC-based IPCs compared to a proportional-integral (PI) collective pitch controller (CPC). Improvement on rotor speed regulation and once-per-revolution and twice-per-revolution load reductions has been observed in the proposed IPC designs.« less

Initial component control in disparity vergence: a model-based study.

PubMed

Horng, J L; Semmlow, J L; Hung, G K; Ciuffreda, K J

1998-02-01

The dual-mode theory for the control of disparity-vergence eye movements states that two components control the response to a step change in disparity. The initial component uses a motor preprogram to drive the eyes to an approximate final position. This initial component is followed by activation of a late component operating under visual feedback control that reduces residual disparity to within fusional limits. A quantitative model based on a pulse-step controller, similar to that postulated for saccadic eye movements, has been developed to represent the initial component. This model, an adaptation of one developed by Zee et al. [1], provides accurate simulations of isolated initial component movements and is compatible with the known underlying neurophysiology and existing neurophysiological data. The model has been employed to investigate the difference in dynamics between convergent and divergent movements. Results indicate that the pulse-control component active in convergence is reduced or absent from the control signals of divergence movements. This suggests somewhat different control structures of convergence versus divergence, and is consistent with other directional asymmetries seen in horizontal vergence.

Climate Scenarios for the NASA / USAID SERVIR Project: Challenges for Multiple Planning Horizons

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Roberts, J. B.; Lyon, B.; Funk, C.; Bosilovich, M. G.

2014-01-01

SERVIR, an acronym meaning "to serve" in Spanish, is a joint venture between NASA and the U.S. Agency for International Development (USAID) which provides satellite-based Earth observation data, modeling, and science applications to help developing nations in Central America, East Africa and the Himalayas improve environmental decision making. Anticipating climate variability / climate change impacts has now become an important component of the SERVIR efforts to build capacity in these regions. Uncertainty in hydrometeorological components of climate variations and exposure to extreme events across scales from weather to climate are of particular concern. We report here on work to construct scenarios or outlooks that are being developed as input drivers for decision support systems (DSSs) in a variety of settings. These DSSs are being developed jointly by a broad array NASA Applied Science Team (AST) Investigations and user communities in the three SERVIR Hub Regions, Central America, East Africa and the Himalayas. Issues span hydrologic / water resources modeling, agricultural productivity, and forest carbon reserves. The scenarios needed for these efforts encompass seasonal forecasts, interannual outlooks, and likely decadal / multi-decadal trends. Providing these scenarios across the different AST efforts enables some level of integration in considering regional responses to climate events. We will discuss a number of challenges in developing this continuum of scenarios including the identification and "mining" of predictability, addressing multiple continental regions, issues of downscaling global model integrations to regional / local applications (i.e. hydrologic and crop modeling). We compare / contrast the role of the U.S. National Multi- Model Experiment initiative in seasonal forecasts and the CMIP-5 climate model experiments in supporting these efforts. Examples of these scenarios, their use, and an assessment of their utility as well as limitations will be presented.

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).

A Regional Climate Model Evaluation System based on contemporary Satellite and other Observations for Assessing Regional Climate Model Fidelity

NASA Astrophysics Data System (ADS)

Waliser, D. E.; Kim, J.; Mattman, C.; Goodale, C.; Hart, A.; Zimdars, P.; Lean, P.

2011-12-01

Evaluation of climate models against observations is an essential part of assessing the impact of climate variations and change on regionally important sectors and improving climate models. Regional climate models (RCMs) are of a particular concern. RCMs provide fine-scale climate needed by the assessment community via downscaling global climate model projections such as those contributing to the Coupled Model Intercomparison Project (CMIP) that form one aspect of the quantitative basis of the IPCC Assessment Reports. The lack of reliable fine-resolution observational data and formal tools and metrics has represented a challenge in evaluating RCMs. Recent satellite observations are particularly useful as they provide a wealth of information and constraints on many different processes within the climate system. Due to their large volume and the difficulties associated with accessing and using contemporary observations, however, these datasets have been generally underutilized in model evaluation studies. Recognizing this problem, NASA JPL and UCLA have developed the Regional Climate Model Evaluation System (RCMES) to help make satellite observations, in conjunction with in-situ and reanalysis datasets, more readily accessible to the regional modeling community. The system includes a central database (Regional Climate Model Evaluation Database: RCMED) to store multiple datasets in a common format and codes for calculating and plotting statistical metrics to assess model performance (Regional Climate Model Evaluation Tool: RCMET). This allows the time taken to compare model data with satellite observations to be reduced from weeks to days. RCMES is a component of the recent ExArch project, an international effort for facilitating the archive and access of massive amounts data for users using cloud-based infrastructure, in this case as applied to the study of climate and climate change. This presentation will describe RCMES and demonstrate its utility using examples from RCMs applied to the southwest US as well as to Africa based on output from the CORDEX activity. Application of RCMES to the evaluation of multi-RCM hindcast for CORDEX-Africa will be presented in a companion paper in A41.

Local climatic adaptation in a widespread microorganism.

PubMed

Leducq, Jean-Baptiste; Charron, Guillaume; Samani, Pedram; Dubé, Alexandre K; Sylvester, Kayla; James, Brielle; Almeida, Pedro; Sampaio, José Paulo; Hittinger, Chris Todd; Bell, Graham; Landry, Christian R

2014-02-22

Exploring the ability of organisms to locally adapt is critical for determining the outcome of rapid climate changes, yet few studies have addressed this question in microorganisms. We investigated the role of a heterogeneous climate on adaptation of North American populations of the wild yeast Saccharomyces paradoxus. We found abundant among-strain variation for fitness components across a range of temperatures, but this variation was only partially explained by climatic variation in the distribution area. Most of fitness variation was explained by the divergence of genetically distinct groups, distributed along a north-south cline, suggesting that these groups have adapted to distinct climatic conditions. Within-group fitness components were correlated with climatic conditions, illustrating that even ubiquitous microorganisms locally adapt and harbour standing genetic variation for climate-related traits. Our results suggest that global climatic changes could lead to adaptation to new conditions within groups, or changes in their geographical distributions.

A climate-based spatiotemporal prediction for dengue fever epidemics: a case study in southern Taiwan

NASA Astrophysics Data System (ADS)

Yu, H.-L.; Yang, S.-J.; Lin, Y.-C.

2012-04-01

Dengue Fever (DF) has been identified by the World Health organization (WHO) as one of the most serious vector-borne infectious diseases in tropical and sub-tropical areas. DF has been one of the most important epidemics in Taiwan which occur annually especially in southern Taiwan during summer and autumn. Most DF studies have focused mainly on temporal DF patterns and its close association with climatic covariates, whereas few studies have investigated the spatial DF patterns (spatial dependence and clustering) and composite space-time effects of the DF epidemics. The present study proposes a spatio-temporal DF prediction approach based on stochastic Bayesian Maximum Entropy (BME) analysis. Core and site-specific knowledge bases are considered, including climate and health datasets under conditions of uncertainty, space-time dependence functions, and a Poisson regression model of climatic variables contributing to DF occurrences in southern Taiwan during 2007, when the highest number of DF cases was recorded in the history of Taiwan epidemics (over 2000). The obtained results show that the DF outbreaks in the study area are highly influenced by climatic conditions. Furthermore, the analysis can provide the required "one-week-ahead" outbreak warnings based on spatio-temporal predictions of DF distributions. Therefore, the proposed analysis can provide the Taiwan Disease Control Agency with a valuable tool to timely identify, control, and even efficiently prevent DF spreading across space-time.

Development of risk-based air quality management strategies under impacts of climate change.

PubMed

Liao, Kuo-Jen; Amar, Praveen; Tagaris, Efthimios; Russell, Armistead G

2012-05-01

Climate change is forecast to adversely affect air quality through perturbations in meteorological conditions, photochemical reactions, and precursor emissions. To protect the environment and human health from air pollution, there is an increasing recognition of the necessity of developing effective air quality management strategies under the impacts of climate change. This paper presents a framework for developing risk-based air quality management strategies that can help policy makers improve their decision-making processes in response to current and future climate change about 30-50 years from now. Development of air quality management strategies under the impacts of climate change is fundamentally a risk assessment and risk management process involving four steps: (1) assessment of the impacts of climate change and associated uncertainties; (2) determination of air quality targets; (3) selections of potential air quality management options; and (4) identification of preferred air quality management strategies that minimize control costs, maximize benefits, or limit the adverse effects of climate change on air quality when considering the scarcity of resources. The main challenge relates to the level of uncertainties associated with climate change forecasts and advancements in future control measures, since they will significantly affect the risk assessment results and development of effective air quality management plans. The concept presented in this paper can help decision makers make appropriate responses to climate change, since it provides an integrated approach for climate risk assessment and management when developing air quality management strategies. Development of climate-responsive air quality management strategies is fundamentally a risk assessment and risk management process. The risk assessment process includes quantification of climate change impacts on air quality and associated uncertainties. Risk management for air quality under the impacts of climate change includes determination of air quality targets, selections of potential management options, and identification of effective air quality management strategies through decision-making models. The risk-based decision-making framework can also be applied to develop climate-responsive management strategies for the other environmental dimensions and assess costs and benefits of future environmental management policies.

Identifying Local Scale Climate Zones of Urban Heat Island from HJ-1B Satellite Data Using Self-Organizing Maps

NASA Astrophysics Data System (ADS)

Wei, C. Z.; Blaschke, T.

2016-10-01

With the increasing acceleration of urbanization, the degeneration of the environment and the Urban Heat Island (UHI) has attracted more and more attention. Quantitative delineation of UHI has become crucial for a better understanding of the interregional interaction between urbanization processes and the urban environment system. First of all, our study used medium resolution Chinese satellite data-HJ-1B as the Earth Observation data source to derive parameters, including the percentage of Impervious Surface Areas, Land Surface Temperature, Land Surface Albedo, Normalized Differential Vegetation Index, and object edge detector indicators (Mean of Inner Border, Mean of Outer border) in the city of Guangzhou, China. Secondly, in order to establish a model to delineate the local climate zones of UHI, we used the Principal Component Analysis to explore the correlations between all these parameters, and estimate their contributions to the principal components of UHI zones. Finally, depending on the results of the PCA, we chose the most suitable parameters to classify the urban climate zones based on a Self-Organization Map (SOM). The results show that all six parameters are closely correlated with each other and have a high percentage of cumulative (95%) in the first two principal components. Therefore, the SOM algorithm automatically categorized the city of Guangzhou into five classes of UHI zones using these six spectral, structural and climate parameters as inputs. UHI zones have distinguishable physical characteristics, and could potentially help to provide the basis and decision support for further sustainable urban planning.

Interactive Nature of Climate Change and Aerosol Forcing

NASA Technical Reports Server (NTRS)

Nazarenko, L.; Rind, D.; Tsigaridis, K.; Del Genio, A. D.; Kelley, M.; Tausnev, N.

2017-01-01

The effect of changing cloud cover on climate, based on cloud-aerosol interactions, is one of the major unknowns for climate forcing and climate sensitivity. It has two components: (1) the impact of aerosols on clouds and climate due to in-situ interactions (i.e., rapid response); and (2) the effect of aerosols on the cloud feedback that arises as climate changes - climate feedback response. We examine both effects utilizing the NASA GISS ModelE2 to assess the indirect effect, with both mass-based and microphysical aerosol schemes, in transient twentieth-century simulations. We separate the rapid response and climate feedback effects by making simulations with a coupled version of the model as well as one with no sea surface temperature or sea ice response (atmosphere-only simulations). We show that the indirect effect of aerosols on temperature is altered by the climate feedbacks following the ocean response, and this change differs depending upon which aerosol model is employed. Overall the effective radiative forcing (ERF) for the direct effect of aerosol-radiation interaction (ERFari) ranges between -0.2 and -0.6 W/sq m for atmosphere-only experiments while the total effective radiative forcing, including the indirect effect (ERFari+aci) varies between about -0.4 and -1.1 W/sq m for atmosphere-only simulations; both ranges are in agreement with those given in IPCC (2013). Including the full feedback of the climate system lowers these ranges to -0.2 to -0.5 W/sq m for ERFari, and -0.3 to -0.74 W/sq m for ERFari+aci. With both aerosol schemes, the climate change feedbacks have reduced the global average indirect radiative effect of atmospheric aerosols relative to what the emission changes would have produced, at least partially due to its effect on tropical upper tropospheric clouds.

Severity of climate change dictates the direction of biophysical feedbacks of vegetation change to Arctic climate

NASA Astrophysics Data System (ADS)

Zhang, Wenxin; Jansson, Christer; Miller, Paul; Smith, Ben; Samuelsson, Patrick

2014-05-01

Vegetation-climate feedbacks induced by vegetation dynamics under climate change alter biophysical properties of the land surface that regulate energy and water exchange with the atmosphere. Simulations with Earth System Models applied at global scale suggest that the current warming in the Arctic has been amplified, with large contributions from positive feedbacks, dominated by the effect of reduced surface albedo as an increased distribution, cover and taller stature of trees and shrubs mask underlying snow, darkening the surface. However, these models generally employ simplified representation of vegetation dynamics and structure and a coarse grid resolution, overlooking local or regional scale details determined by diverse vegetation composition and landscape heterogeneity. In this study, we perform simulations using an advanced regional coupled vegetation-climate model (RCA-GUESS) applied at high resolution (0.44×0.44° ) over the Arctic Coordinated Regional Climate Downscaling Experiment (CORDEX-Arctic) domain. The climate component (RCA4) is forced with lateral boundary conditions from EC-EARTH CMIP5 simulations for three representative concentration pathways (RCP 2.6, 4.5, 8.5). Vegetation-climate response is simulated by the individual-based dynamic vegetation model (LPJ-GUESS), accounting for phenology, physiology, demography and resource competition of individual-based vegetation, and feeding variations of leaf area index and vegetative cover fraction back to the climate component, thereby adjusting surface properties and surface energy fluxes. The simulated 2m air temperature, precipitation, vegetation distribution and carbon budget for the present period has been evaluated in another paper. The purpose of this study is to elucidate the spatial and temporal characteristics of the biophysical feedbacks arising from vegetation shifts in response to different CO2 concentration pathways and their associated climate change. Our results indicate that the albedo feedback dominates simulated warming in spring in all three scenarios, while in summer, evapotranspiration feedback, governing the partitioning of the return energy flux from the surface to the atmosphere into latent and sensible heat, exerts evaporative cooling effects, the magnitude of which depends on the severity of climate change, in turn driven by the underlying GHG emissions pathway, resulting in shift in the sign of net biophysical at higher levels of warming. Spatially, western Siberia is identified as the most susceptible location, experiencing the potential to reverse biophysical feedbacks in all seasons. We further analyze how the pattern of vegetation shifts triggers different signs of net effects of biophysical feedbacks.

Geo-climatic heterogeneity in self-reported asthma, allergic rhinitis and chronic bronchitis in Italy.

PubMed

Pesce, G; Bugiani, M; Marcon, A; Marchetti, P; Carosso, A; Accordini, S; Antonicelli, L; Cogliani, E; Pirina, P; Pocetta, G; Spinelli, F; Villani, S; de Marco, R

2016-02-15

Several studies highlighted a great variability, both between and within countries, in the prevalence of asthma and chronic airways diseases. To evaluate if geo-climatic variations can explain the heterogeneity in the prevalence of asthma and respiratory diseases in Italy. Between 2006 and 2010, a postal screening questionnaire on respiratory health was administered to 18,357 randomly selected subjects, aged 20-44, living in 7 centers in northern, central, and southern Italy. A random-effects meta-analysis was fitted to evaluate the between-centers heterogeneity in the prevalence of asthma, asthma-like symptoms, allergic rhinitis, and chronic bronchitis (CB). A principal component analysis (PCA) was performed to synthetize the geo-climatic information (annual mean temperature, range of temperature, annual rainfalls, global solar radiations, altitude, distance from the sea) of all the 110 Italian province capital towns. The associations between these geo-climatic components obtained with PCA and the prevalence of respiratory diseases were analyzed through meta-regression models. 10,464 (57%) subjects responded to the questionnaire. There was a significant between-centers heterogeneity in the prevalence of asthma (I(2)=59.5%, p=0.022) and CB (I(2)=60.5%, p=0.019), but not in that of asthma-like symptoms or allergic rhinitis. Two independent geo-climatic components explaining together about 80% of the overall geo-climatic variability were identified: the first principally summarized the climatic variables; the second the topographic ones. Variations in the prevalence of asthma across centers were significantly associated with differences in the climatic component (p=0.017), but not with differences in the topographic one. Our findings suggest that climate play a role in determining the between-center heterogeneity in the prevalence of asthma in Italy, with higher prevalence in dry-hot Mediterranean climates, and lower in rainy-cold northern climates. Copyright © 2015 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

This study examines the variations of climate variables and rice yield and quantifies the relationships among them using multiple linear regression, principal component analysis, and support vector machine (SVM) analysis in southwest Nigeria. The climate and yield data used was for a period of 36 years between 1980 and 2015. Similar to the observed decrease ( P < 0.001) in rice yield, pan evaporation, solar radiation, and wind speed declined significantly. Eight principal components exhibited an eigenvalue > 1 and explained 83.1% of the total variance of predictor variables. The SVM regression function using the scores of the first principal component explained about 75% of the variance in rice yield data and linear regression about 64%. SVM regression between annual solar radiation values and yield explained 67% of the variance. Only the first component of the principal component analysis (PCA) exhibited a clear long-term trend and sometimes short-term variance similar to that of rice yield. Short-term fluctuations of the scores of the PC1 are closely coupled to those of rice yield during the 1986-1993 and the 2006-2013 periods thereby revealing the inter-annual sensitivity of rice production to climate variability. Solar radiation stands out as the climate variable of highest influence on rice yield, and the influence was especially strong during monsoon and post-monsoon periods, which correspond to the vegetative, booting, flowering, and grain filling stages in the study area. The outcome is expected to provide more in-depth regional-specific climate-rice linkage for screening of better cultivars that can positively respond to future climate fluctuations as well as providing information that may help optimized planting dates for improved radiation use efficiency in the study area.

NAME Modeling and Climate Process Team

NASA Astrophysics Data System (ADS)

Schemm, J. E.; Williams, L. N.; Gutzler, D. S.

2007-05-01

NAME Climate Process and Modeling Team (CPT) has been established to address the need of linking climate process research to model development and testing activities for warm season climate prediction. The project builds on two existing NAME-related modeling efforts. One major component of this project is the organization and implementation of a second phase of NAMAP, based on the 2004 season. NAMAP2 will re-examine the metrics proposed by NAMAP, extend the NAMAP analysis to transient variability, exploit the extensive observational database provided by NAME 2004 to analyze simulation targets of special interest, and expand participation. Vertical column analysis will bring local NAME observations and model outputs together in a context where key physical processes in the models can be evaluated and improved. The second component builds on the current NAME-related modeling effort focused on the diurnal cycle of precipitation in several global models, including those implemented at NCEP, NASA and GFDL. Our activities will focus on the ability of the operational NCEP Global Forecast System (GFS) to simulate the diurnal and seasonal evolution of warm season precipitation during the NAME 2004 EOP, and on changes to the treatment of deep convection in the complicated terrain of the NAMS domain that are necessary to improve the simulations, and ultimately predictions of warm season precipitation These activities will be strongly tied to NAMAP2 to ensure technology transfer from research to operations. Results based on experiments conducted with the NCEP CFS GCM will be reported at the conference with emphasis on the impact of horizontal resolution in predicting warm season precipitation over North America.

Estimating mean long-term hydrologic budget components for watersheds and counties: An application to the commonwealth of Virginia, USA

USGS Publications Warehouse

Sanford, Ward E.; Nelms, David L.; Pope, Jason P.; Selnick, David L.

2015-01-01

Mean long-term hydrologic budget components, such as recharge and base flow, are often difficult to estimate because they can vary substantially in space and time. Mean long-term fluxes were calculated in this study for precipitation, surface runoff, infiltration, total evapotranspiration (ET), riparian ET, recharge, base flow (or groundwater discharge) and net total outflow using long-term estimates of mean ET and precipitation and the assumption that the relative change in storage over that 30-year period is small compared to the total ET or precipitation. Fluxes of these components were first estimated on a number of real-time-gaged watersheds across Virginia. Specific conductance was used to distinguish and separate surface runoff from base flow. Specific-conductance (SC) data were collected every 15 minutes at 75 real-time gages for approximately 18 months between March 2007 and August 2008. Precipitation was estimated for 1971-2000 using PRISM climate data. Precipitation and temperature from the PRISM data were used to develop a regression-based relation to estimate total ET. The proportion of watershed precipitation that becomes surface runoff was related to physiographic province and rock type in a runoff regression equation. A new approach to estimate riparian ET using seasonal SC data gave results consistent with those from other methods. Component flux estimates from the watersheds were transferred to flux estimates for counties and independent cities using the ET and runoff regression equations. Only 48 of the 75 watersheds yielded sufficient data, and data from these 48 were used in the final runoff regression equation. Final results for the study are presented as component flux estimates for all counties and independent cities in Virginia. The method has the potential to be applied in many other states in the U.S. or in other regions or countries of the world where climate and stream flow data are plentiful.

Estimation of Remote Microclimates from Weather Station Data with Applications to Landscape Architecture.

NASA Astrophysics Data System (ADS)

Brown, Robert Douglas

Several components of a system for quantitative application of climatic statistics to landscape planning and design (CLIMACS) have been developed. One component model (MICROSIM) estimated the microclimate at the top of a remote crop using physically-based models and inputs of weather station data. Temperatures at the top of unstressed, uniform crops on flat terrain within 1600 m of a recording weather station were estimated within 1.0 C 96% of the time for a corn crop and 92% of the time for a soybean crop. Crop top winds were estimated within 0.4 m/s 92% of the time for corn and 100% of the time for soybean. This is of sufficient accuracy for application in landscape planning and design models. A physically-based model (COMFA) was developed for the determination of outdoor human thermal comfort from microclimate inputs. Estimated versus measured comfort levels in a wide range of environments agreed with a correlation coefficient of r = 0.91. Using these components, the CLIMACS concept has been applied to a typical planning example. Microclimate data were generated from weather station information using MICROSIM, then input to COMFA and to a house energy consumption model called HOTCAN to derive quantitative climatic justification for design decisions.

Climate and land use controls over terrestrial water use efficiency in monsoon Asia.

Treesearch

Hanqin Tian; Chaoqun Lu; Guangsheng Chen; Xiaofeng Xu; Mingliang Liu; et al

2011-01-01

Much concern has been raised regarding how and to what extent climate change and intensive human activities have altered water use efficiency (WUE, amount of carbon uptake per unit of water use) in monsoon Asia. By using a process-based ecosystem model [dynamic land ecosystem model (DLEM)], we examined effects of climate change, land use/cover change, and land...

Weather and climate

NASA Technical Reports Server (NTRS)

1975-01-01

Recommendations for using space observations of weather and climate to aid in solving earth based problems are given. Special attention was given to: (1) extending useful forecasting capability of space systems, (2) reducing social, economic, and human losses caused by weather, (3) development of space system capability to manage and control air pollutant concentrations, and (4) establish mechanisms for the national examination of deliberate and inadvertent means for modifying weather and climate.

A parametric approach for simultaneous bias correction and high-resolution downscaling of climate model rainfall

NASA Astrophysics Data System (ADS)

Mamalakis, Antonios; Langousis, Andreas; Deidda, Roberto; Marrocu, Marino

2017-03-01

Distribution mapping has been identified as the most efficient approach to bias-correct climate model rainfall, while reproducing its statistics at spatial and temporal resolutions suitable to run hydrologic models. Yet its implementation based on empirical distributions derived from control samples (referred to as nonparametric distribution mapping) makes the method's performance sensitive to sample length variations, the presence of outliers, the spatial resolution of climate model results, and may lead to biases, especially in extreme rainfall estimation. To address these shortcomings, we propose a methodology for simultaneous bias correction and high-resolution downscaling of climate model rainfall products that uses: (a) a two-component theoretical distribution model (i.e., a generalized Pareto (GP) model for rainfall intensities above a specified threshold u*, and an exponential model for lower rainrates), and (b) proper interpolation of the corresponding distribution parameters on a user-defined high-resolution grid, using kriging for uncertain data. We assess the performance of the suggested parametric approach relative to the nonparametric one, using daily raingauge measurements from a dense network in the island of Sardinia (Italy), and rainfall data from four GCM/RCM model chains of the ENSEMBLES project. The obtained results shed light on the competitive advantages of the parametric approach, which is proved more accurate and considerably less sensitive to the characteristics of the calibration period, independent of the GCM/RCM combination used. This is especially the case for extreme rainfall estimation, where the GP assumption allows for more accurate and robust estimates, also beyond the range of the available data.

Child Centred Approach to Climate Change and Health Adaptation through Schools in Bangladesh: A Cluster Randomised Intervention Trial

PubMed Central

Kabir, Md Iqbal; Rahman, Md Bayzidur; Smith, Wayne; Lusha, Mirza Afreen Fatima; Milton, Abul Hasnat

2015-01-01

Background Bangladesh is one of the most vulnerable countries to climate change. People are getting educated at different levels on how to deal with potential impacts. One such educational mode was the preparation of a school manual, for high school students on climate change and health protection endorsed by the National Curriculum and Textbook Board, which is based on a 2008 World Health Organization manual. The objective of this study was to test the effectiveness of the manual in increasing the knowledge level of the school children about climate change and health adaptation. Methods This cluster randomized intervention trial involved 60 schools throughout Bangladesh, with 3293 secondary school students participating. School upazilas (sub-districts) were randomised into intervention and control groups, and two schools from each upazila were randomly selected. All year seven students from both groups of schools sat for a pre-test of 30 short questions of binary response. A total of 1515 students from 30 intervention schools received the intervention through classroom training based on the school manual and 1778 students of the 30 control schools did not get the manual but a leaflet on climate change and health issues. Six months later, a post-intervention test of the same questionnaire used in the pre-test was performed at both intervention and control schools. The pre and post test scores were analysed along with the demographic data by using random effects model. Results None of the various school level and student level variables were significantly different between the control and intervention group. However, the intervention group had a 17.42% (95% CI: 14.45 to 20.38, P = <0.001) higher score in the post-test after adjusting for pre-test score and other covariates in a multi-level linear regression model. Conclusions These results suggest that school-based intervention for climate change and health adaptation is effective for increasing the knowledge level of school children on this topic. PMID:26252381

Child Centred Approach to Climate Change and Health Adaptation through Schools in Bangladesh: A Cluster Randomised Intervention Trial.

PubMed

Kabir, Md Iqbal; Rahman, Md Bayzidur; Smith, Wayne; Lusha, Mirza Afreen Fatima; Milton, Abul Hasnat

2015-01-01

Bangladesh is one of the most vulnerable countries to climate change. People are getting educated at different levels on how to deal with potential impacts. One such educational mode was the preparation of a school manual, for high school students on climate change and health protection endorsed by the National Curriculum and Textbook Board, which is based on a 2008 World Health Organization manual. The objective of this study was to test the effectiveness of the manual in increasing the knowledge level of the school children about climate change and health adaptation. This cluster randomized intervention trial involved 60 schools throughout Bangladesh, with 3293 secondary school students participating. School upazilas (sub-districts) were randomised into intervention and control groups, and two schools from each upazila were randomly selected. All year seven students from both groups of schools sat for a pre-test of 30 short questions of binary response. A total of 1515 students from 30 intervention schools received the intervention through classroom training based on the school manual and 1778 students of the 30 control schools did not get the manual but a leaflet on climate change and health issues. Six months later, a post-intervention test of the same questionnaire used in the pre-test was performed at both intervention and control schools. The pre and post test scores were analysed along with the demographic data by using random effects model. None of the various school level and student level variables were significantly different between the control and intervention group. However, the intervention group had a 17.42% (95% CI: 14.45 to 20.38, P = <0.001) higher score in the post-test after adjusting for pre-test score and other covariates in a multi-level linear regression model. These results suggest that school-based intervention for climate change and health adaptation is effective for increasing the knowledge level of school children on this topic.

Climatic change controls productivity variation in global grasslands

PubMed Central

Gao, Qingzhu; Zhu, Wenquan; Schwartz, Mark W.; Ganjurjav, Hasbagan; Wan, Yunfan; Qin, Xiaobo; Ma, Xin; Williamson, Matthew A.; Li, Yue

2016-01-01

Detection and identification of the impacts of climate change on ecosystems have been core issues in climate change research in recent years. In this study, we compared average annual values of the normalized difference vegetation index (NDVI) with theoretical net primary productivity (NPP) values based on temperature and precipitation to determine the effect of historic climate change on global grassland productivity from 1982 to 2011. Comparison of trends in actual productivity (NDVI) with climate-induced potential productivity showed that the trends in average productivity in nearly 40% of global grassland areas have been significantly affected by climate change. The contribution of climate change to variability in grassland productivity was 15.2–71.2% during 1982–2011. Climate change contributed significantly to long-term trends in grassland productivity mainly in North America, central Eurasia, central Africa, and Oceania; these regions will be more sensitive to future climate change impacts. The impacts of climate change on variability in grassland productivity were greater in the Western Hemisphere than the Eastern Hemisphere. Confirmation of the observed trends requires long-term controlled experiments and multi-model ensembles to reduce uncertainties and explain mechanisms. PMID:27243565

Benthic-Pelagic Coupling in Biogeochemical and Climate Models: Existing Approaches, Recent developments and Roadblocks

NASA Astrophysics Data System (ADS)

Arndt, Sandra

2016-04-01

Marine sediments are key components in the Earth System. They host the largest carbon reservoir on Earth, provide the only long term sink for atmospheric CO2, recycle nutrients and represent the most important climate archive. Biogeochemical processes in marine sediments are thus essential for our understanding of the global biogeochemical cycles and climate. They are first and foremost, donor controlled and, thus, driven by the rain of particulate material from the euphotic zone and influenced by the overlying bottom water. Geochemical species may undergo several recycling loops (e.g. authigenic mineral precipitation/dissolution) before they are either buried or diffuse back to the water column. The tightly coupled and complex pelagic and benthic process interplay thus delays recycling flux, significantly modifies the depositional signal and controls the long-term removal of carbon from the ocean-atmosphere system. Despite the importance of this mutual interaction, coupled regional/global biogeochemical models and (paleo)climate models, which are designed to assess and quantify the transformations and fluxes of carbon and nutrients and evaluate their response to past and future perturbations of the climate system either completely neglect marine sediments or incorporate a highly simplified representation of benthic processes. On the other end of the spectrum, coupled, multi-component state-of-the-art early diagenetic models have been successfully developed and applied over the past decades to reproduce observations and quantify sediment-water exchange fluxes, but cannot easily be coupled to pelagic models. The primary constraint here is the high computation cost of simulating all of the essential redox and equilibrium reactions within marine sediments that control carbon burial and benthic recycling fluxes: a barrier that is easily exacerbated if a variety of benthic environments are to be spatially resolved. This presentation provides an integrative overview of the benthic-pelagic coupling that accounts for the complex process interplay from the euphotic ocean to the deep sediment. It explores the intensity of the benthic-pelagic coupling across different environments and from the seasonal to the geological timescale. Different modelling approaches of coupling sediment and water column dynamics in regional/global biogeochemical models and (paleo)climate models are critically evaluated and their most important limitations, as well as the implications for our ability to predict the response of the global carbon cycle to past or future perturbations is discussed. Finally, the presentation identifies major roadblocks to the development of new model approaches and highlights how new techniques, new observational and laboratory data, as well as a close interdisciplinary collaboration can overcome these roadblocks.

Evaluation of the multi-model CORDEX-Africa hindcast using RCMES

NASA Astrophysics Data System (ADS)

Kim, J.; Waliser, D. E.; Lean, P.; Mattmann, C. A.; Goodale, C. E.; Hart, A.; Zimdars, P.; Hewitson, B.; Jones, C.

2011-12-01

Recent global climate change studies have concluded with a high confidence level that the observed increasing trend in the global-mean surface air temperatures since mid-20th century is triggered by the emission of anthropogenic greenhouse gases (GHGs). The increase in the global-mean temperature due to anthropogenic emissions is nearly monotonic and may alter the climatological norms resulting in a new climate normal. In the presence of anthropogenic climate change, assessing regional impacts of the altered climate state and developing the plans for mitigating any adverse impacts are an important concern. Assessing future climate state and its impact remains a difficult task largely because of the uncertainties in future emissions and model errors. Uncertainties in climate projections propagates into impact assessment models and result in uncertainties in the impact assessments. In order to facilitate the evaluation of model data, a fundamental step for assessing model errors, the JPL Regional Climate Model Evaluation System (RCMES: Lean et al. 2010; Hart et al. 2011) has been developed through a joint effort of the investigators from UCLA and JPL. RCMES is also a regional climate component of a larger worldwide ExArch project. We will present the evaluation of the surface temperatures and precipitation from multiple RCMs participating in the African component of the Coordinated Regional Climate Downscaling Experiment (CORDEX) that has organized a suite of regional climate projection experiments in which multiple RCMs and GCMs are incorporated. As a part of the project, CORDEX organized a 20-year regional climate hindcast study in order to quantify and understand the uncertainties originating from model errors. Investigators from JPL, UCLA, and the CORDEX-Africa team collaborate to analyze the RCM hindcast data using RCMES. The analysis is focused on measuring the closeness between individual regional climate model outputs as well as their ensembles and observed data. The model evaluation is quantified in terms of widely used metrics. Details on the conceptual outline and architecture of RCMES is presented in two companion papers "The Regional climate model Evaluation System (RCMES) based on contemporary satellite and other observations for assessing regional climate model fidelity" and "A Reusable Framework for Regional Climate Model Evaluation" in GC07 and IN30, respectively.

Public Health Nurses’ Knowledge and Attitudes Regarding Climate Change

PubMed Central

Chaudry, Rosemary V.; Mac Crawford, John

2011-01-01

Background: Climate change affects human health, and health departments are urged to act to reduce the severity of these impacts. Yet little is known about the perspective of public health nurses—the largest component of the public health workforce—regarding their roles in addressing health impacts of climate change. Objectives: We determined the knowledge and attitudes of public health nurses concerning climate change and the role of public health nursing in divisions of health departments in addressing health-related impacts of climate change. Differences by demographic subgroups were explored. Methods: An online survey was distributed to nursing directors of U.S. health departments (n = 786) with Internet staff directories. Results: Respondents (n = 176) were primarily female, white public health nursing administrators with ≥ 5 years of experience. Approximately equal percentages of respondents self-identified as having moderate, conservative, and liberal political views. Most agreed that the earth has experienced climate change and that climate change is somewhat controllable. Respondents identified an average of 5 of the 12 listed health-related impacts of climate change, but the modal response was zero impact. Public health nursing was perceived as having responsibility to address health-related impacts of climate change but lacking the ability to address these impacts. Conclusions: Public health nurses view the environment as under threat and see a role for nursing divisions in addressing health effects of climate change. However, they recognize the limited resources and personnel available to devote to this endeavor. PMID:22128069

Story telling and social action: engaging young people to act on climate change

NASA Astrophysics Data System (ADS)

Cordero, E.

2014-12-01

The realization that well designed graphs and clearly worded summaries were not enough to spur the public and policy makers towards an appropriate understanding of our planet encouraged me to search for other ways to share climate stories with the general public. After co-authoring a popular book on food and climate change and giving many talks to the general public, it struck me that young people were largely missing from the dialogue, and little meaningful progress was being made to design effective solutions. I then started working with faculty and students from the Film and Animation Departments at San Jose State University to develop stories about climate change that would be engaging to younger audiences. The result was the Green Ninja Project, based around the Green Ninja, a superhero who focuses on solutions to climate change using humor and silliness to soften what can be a somewhat challenging topic. The Project includes a) The Green Ninja Show - a series of YouTube videos (over 1,000,000 views) highlighting actions young people can take to reduce climate change, b) The Green Ninja Film Festival where students tell their own climate solutions stories, and c) a collection of educational resources that help teachers bring climate science topics into their classroom using hands-on activities. A key component to this work is promoting social action experiences, so that young people can understand how their actions can make a difference. Based on these experiences, I will provide my own reflections on the challenges and opportunities of communicating climate change with young people.

Downscaling large-scale circulation to local winter climate using neural network techniques

NASA Astrophysics Data System (ADS)

Cavazos Perez, Maria Tereza

1998-12-01

The severe impacts of climate variability on society reveal the increasing need for improving regional-scale climate diagnosis. A new downscaling approach for climate diagnosis is developed here. It is based on neural network techniques that derive transfer functions from the large-scale atmospheric controls to the local winter climate in northeastern Mexico and southeastern Texas during the 1985-93 period. A first neural network (NN) model employs time-lagged component scores from a rotated principal component analysis of SLP, 500-hPa heights, and 1000-500 hPa thickness as predictors of daily precipitation. The model is able to reproduce the phase and, to some decree, the amplitude of large rainfall events, reflecting the influence of the large-scale circulation. Large errors are found over the Sierra Madre, over the Gulf of Mexico, and during El Nino events, suggesting an increase in the importance of meso-scale rainfall processes. However, errors are also due to the lack of randomization of the input data and the absence of local atmospheric predictors such as moisture. Thus, a second NN model uses time-lagged specific humidity at the Earth's surface and at the 700 hPa level, SLP tendency, and 700-500 hPa thickness as input to a self-organizing map (SOM) that pre-classifies the atmospheric fields into different patterns. The results from the SOM classification document that negative (positive) anomalies of winter precipitation over the region are associated with: (1) weaker (stronger) Aleutian low; (2) stronger (weaker) North Pacific high; (3) negative (positive) phase of the Pacific North American pattern; and (4) La Nina (El Nino) events. The SOM atmospheric patterns are then used as input to a feed-forward NN that captures over 60% of the daily rainfall variance and 94% of the daily minimum temperature variance over the region. This demonstrates the ability of artificial neural network models to simulate realistic relationships on daily time scales. The results of this research also reveal that the SOM pre-classification of days with similar atmospheric conditions succeeded in emphasizing the differences of the atmospheric variance conducive to extreme events. This resulted in a downscaling NN model that is highly sensitive to local-scale weather anomalies associated with El Nino and extreme cold events.

Organizational Culture and Climate and Mental Health Provider Attitudes Toward Evidence-Based Practice

PubMed Central

Aarons, Gregory A.; Sawitzky, Angelina C.

2006-01-01

Mental health provider attitudes toward adopting evidence-based practice (EBP) are associated with organizational context and provider individual differences. Organizational culture and climate are contextual factors that can affect staff acceptance of innovation. This study examined the association of organizational culture and climate with attitudes toward adopting EBP. Participants were 301 public sector mental health service providers from 49 programs providing mental health services for youths and families. Correlation analyses and multilevel hierarchical regressions, controlling for effects of provider characteristics, showed that constructive culture was associated with more positive attitudes toward adoption of EBP and poor organizational climates with perceived divergence of usual practice and EBP. Behavioral health organizations may benefit from consideration of how culture and climate affect staff attitudes toward change in practice. PMID:17183411

Organizational Culture and Climate and Mental Health Provider Attitudes Toward Evidence-Based Practice.

PubMed

Aarons, Gregory A; Sawitzky, Angelina C

2006-02-01

Mental health provider attitudes toward adopting evidence-based practice (EBP) are associated with organizational context and provider individual differences. Organizational culture and climate are contextual factors that can affect staff acceptance of innovation. This study examined the association of organizational culture and climate with attitudes toward adopting EBP. Participants were 301 public sector mental health service providers from 49 programs providing mental health services for youths and families. Correlation analyses and multilevel hierarchical regressions, controlling for effects of provider characteristics, showed that constructive culture was associated with more positive attitudes toward adoption of EBP and poor organizational climates with perceived divergence of usual practice and EBP. Behavioral health organizations may benefit from consideration of how culture and climate affect staff attitudes toward change in practice.

Climate Model Diagnostic Analyzer Web Service System

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Li, J.; Zhang, J.; Wang, W.

2015-12-01

Both the National Research Council Decadal Survey and the latest Intergovernmental Panel on Climate Change Assessment Report stressed the need for the comprehensive and innovative evaluation of climate models with the synergistic use of global satellite observations in order to improve our weather and climate simulation and prediction capabilities. The abundance of satellite observations for fundamental climate parameters and the availability of coordinated model outputs from CMIP5 for the same parameters offer a great opportunity to understand and diagnose model biases in climate models. In addition, the Obs4MIPs efforts have created several key global observational datasets that are readily usable for model evaluations. However, a model diagnostic evaluation process requires physics-based multi-variable comparisons that typically involve large-volume and heterogeneous datasets, making them both computationally- and data-intensive. In response, we have developed a novel methodology to diagnose model biases in contemporary climate models and implementing the methodology as a web-service based, cloud-enabled, provenance-supported climate-model evaluation system. The evaluation system is named Climate Model Diagnostic Analyzer (CMDA), which is the product of the research and technology development investments of several current and past NASA ROSES programs. The current technologies and infrastructure of CMDA are designed and selected to address several technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. In particular, we have three key technology components: (1) diagnostic analysis methodology; (2) web-service based, cloud-enabled technology; (3) provenance-supported technology. The diagnostic analysis methodology includes random forest feature importance ranking, conditional probability distribution function, conditional sampling, and time-lagged correlation map. We have implemented the new methodology as web services and incorporated the system into the Cloud. We have also developed a provenance management system for CMDA where CMDA service semantics modeling, service search and recommendation, and service execution history management are designed and implemented.

Ocean Drilling Program Records of the Last Five Million Years: A View of the Ocean and Climate System During a Warm Period and a Major Climate Transition

NASA Astrophysics Data System (ADS)

Ravelo, A. C.

2003-12-01

The warm Pliocene (4.7 to 3.0 Ma), the most recent period in Earth's history when global equilibrium climate was warmer than today, provides the opportunity to understand what role the components of the climate system that have a long timescale of response (cryosphere and ocean) play in determining globally warm conditions, and in forcing the major global climate cooling after 3.0 Ma. Because sediments of this age are well preserved in many locations in the world's oceans, we can potentially study this warm period in detail. One major accomplishment of the Ocean Drilling Program is the recovery of long continuous sediment sequences from all ocean basins that span the last 5.0 Ma. Dozens of paleoceanographers have generated climate records from these sediments. I will present a synthesis of these data to provide a global picture of the Pliocene warm period, the transition to the cold Pleistocene period, and changes in climate sensitivity related to this transition. In the Pliocene warm period, tropical sea surface temperature (SST) and global climate patterns suggest average conditions that resemble modern El Ni¤os, and deep ocean reconstructions indicate enhanced thermohaline overturning and reduced density and nutrient stratification. The data indicate that the warm conditions were not related to tectonic changes in ocean basin shape compared to today, rather they reflect the long term adjustment of the climate system to stronger than modern radiative forcing. The warm Pliocene to cold Pleistocene transition provides an opportunity to study the feedbacks of various components of the climate system. The marked onset of significant Northern hemisphere glaciation (NHG) at 2.75 Ma occurred in concert with a reduction in deep ocean ventilation, but cooling in subtropical and tropical regions was more gradual until Walker circulation was established in a major step at 2.0 Ma. Thus, regional high latitude ice albedo feedbacks, rather than low latitude processes, must have been primarily responsible for NHG at 2.75 Ma. And, regional air-sea feedbacks in the tropics, rather than ice sheet expansion, must have been primarily responsible for the marked increase in Walker circulation at 2.0 Ma. Finally, the detailed timing of events from different regions suggests that a tectonic `threshold' cannot explain the warm to cold climate transition. Studies of the last 5.0 Ma can also be used to understand how climate responds to changes in the Earth's radiative budget because seasonal and latitudinal variations in solar forcing are extremely well known, and many of the records that have been generated have the resolution and age control appropriate for the study of the climate response to these variations (Milankovitch cycles). In particular, how feedbacks operate when the mean climate state is warm versus cold can be studied. There is clear evidence that the amplitude of the climate response to solar forcing depends on the background mean state. In other words, the sensitivity of the climate to small perturbations in solar forcing has changed with time, and the balance of evidence indicates that tropical conditions, not high latitude conditions (such as ice sheet size) control this sensitivity. In sum, the Ocean Drilling Program has provided scientists with a window into the Pliocene warm period, and an opportunity to understand the workings of the ocean-climate system

An assessment of consistence of exhaust gas emission test results obtained under controlled NEDC conditions

NASA Astrophysics Data System (ADS)

Balawender, K.; Jaworski, A.; Kuszewski, H.; Lejda, K.; Ustrzycki, A.

2016-09-01

Measurements concerning emissions of pollutants contained in automobile combustion engine exhaust gases is of primary importance in view of their harmful impact on the natural environment. This paper presents results of tests aimed at determining exhaust gas pollutant emissions from a passenger car engine obtained under repeatable conditions on a chassis dynamometer. The test set-up was installed in a controlled climate chamber allowing to maintain the temperature conditions within the range from -20°C to +30°C. The analysis covered emissions of such components as CO, CO2, NOx, CH4, THC, and NMHC. The purpose of the study was to assess repeatability of results obtained in a number of tests performed as per NEDC test plan. The study is an introductory stage of a wider research project concerning the effect of climate conditions and fuel type on emission of pollutants contained in exhaust gases generated by automotive vehicles.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Psychometric Evaluation of an Instrument for Measuring Organizational Climate for Quality: Evidence From a National Sample of Infection Preventionists.

PubMed

Pogorzelska-Maziarz, Monika; Nembhard, Ingrid M; Schnall, Rebecca; Nelson, Shanelle; Stone, Patricia W

2016-09-01

In recent years, there has been increased interest in measuring the climate for infection prevention; however, reliable and valid instruments are lacking. This study tested the psychometric properties of the Leading a Culture of Quality for Infection Prevention (LCQ-IP) instrument measuring the infection prevention climate in a sample of 972 infection preventionists from acute care hospitals. An exploratory principal component analysis showed that the instrument had structural validity and captured 4 factors related to the climate for infection prevention: Psychological Safety, Prioritization of Quality, Supportive Work Environment, and Improvement Orientation. LCQ-IP exhibited excellent internal consistency, with a Cronbach α of .926. Criterion validity was supported with overall LCQ-IP scores, increasing with the number of evidence-based prevention policies in place (P = .047). This psychometrically sound instrument may be helpful to researchers and providers in assessing climate for quality related to infection prevention. © The Author(s) 2015.

Effects of climate change on soil moisture over China from 1960-2006

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Liu, J.

2009-01-01

Soil moisture is an important variable in the climate system and it has sensitive impact on the global climate. Obviously it is one of essential components in the climate change study. The Integrated Biosphere Simulator (IBIS) is used to evaluate the spatial and temporal patterns of soil moisture across China under the climate change conditions for the period 1960-2006. Results show that the model performed better in warm season than in cold season. Mean errors (ME) are within 10% for all the months and root mean squared errors (RMSE) are within 10% except winter season. The model captured the spatial variability higher than 50% in warm seasons. Trend analysis based on the Mann-Kendall method indicated that soil moisture in most area of China is decreased especially in the northern China. The areas with significant increasing trends in soil moisture mainly locate at northwestern China and small areas in southeastern China and eastern Tibet plateau. ?? 2009 IEEE.

Engaging Key Stakeholders in Climate Change: A Community-Based Project for Youth-Led Participatory Climate Action

NASA Astrophysics Data System (ADS)

Trott, Carlie D.

Few studies have examined how youth think about, and take action on climate change and far fewer have sought to facilitate their engagement using participatory methods. This dissertation evaluated the impacts of Science, Camera, Action! (SCA), a novel after-school program that combined climate change education with participatory action through photovoice. The specific aims of this study were to: (1) Evaluate the impacts of SCA on youth participants' climate change knowledge, attitudes, and behaviors; (2) Examine how SCA participation served to empower youth agency; and (3) Explore SCA's influence on youths' science engagement. Participants were 55 youths (ages 10 to 12) across three Boys and Girls Club sites in Northern Colorado. SCA's Science component used interactive activities to demonstrate the interrelationships between Earth's changing climate, ecosystems, and sustainable actions within communities. Photovoice, SCA's Camera component, was used to explore youths' climate change perspectives and to identify opportunities for their active engagement. Finally, SCA's Action component aimed to cultivate youth potential as agents of change in their families and communities through the development and implementation of youth-led action projects. Action projects included local policy advocacy, a tree-planting campaign, a photo gallery opening, development of a website, and the establishment of a Boys and Girls Club community garden. To evaluate SCA impacts, a combination of survey and focus group methods were used. Following the program, youth demonstrated increased knowledge of the scientific and social dimensions of the causes and consequences of climate change, as well as its solutions through human action. Though participants expressed a mix of positive (e.g., hope) and negative (e.g., sadness) emotions about climate change, they left the program with an increased sense of respect for nature, an enhanced sense of environmental responsibility, and a greater sense of urgency towards the need for climate change action. Further, participants reported increased engagement in personal pro-environmental behaviors, an enhanced sense of agency in the context of climate change, and provided strong evidence of their role as agents of change in family and community contexts. Through SCA, participants gained a deeper appreciation for science (e.g., in school, careers, and society) and reported increased interest, participation, confidence, and performance in school science. Findings contribute to the vast and growing psychology literature on climate change perceptions and action, and from the understudied perspective of youth. Through a combination of innovative methods and interactive projects, the youth in this study gained a number of psychosocial and educational benefits, while tangibly contributing to the sustainable transformation of their families and communities. Findings of this dissertation have implications for educational programs, youth organizing, and interventions aimed to strengthen youths' active engagement with critical social and scientific issues that impact their lives.

Dynamical adjustment of Scandinavian glacier mass-balance time series

NASA Astrophysics Data System (ADS)

Bonan, D.; Christian, J. E.; Christianson, K. A.

2017-12-01

Glacier mass wastage is often cited as one of the most visible manifestations of anthropogenic climate change. Annual glacier mass-balance is related to local climate and atmospheric circulation, as it is defined as the yearly sum of accumulation and ablation—processes that are strongly influenced by year-to-year fluctuations in precipitation and temperature. Glacier response to a climatic trend can, however, be masked by internal variability in atmospheric circulation, and by non-climatic factors (such as topographic control, wind deposition, and incident solar radiation). Thus, unambiguous attribution of a negative glacier mass-balance trend to anthropogenic forcing remains challenging. Maritime glacier mass-balance records may be especially difficult to interpret due to the high winter balances from decadal-scale climate oscillations and the relatively short time series. Here we examine the influence of climate and atmospheric circulation variability on 14 Norwegian glaciers that span 20° of latitude, from southern Norway to Svalbard. We use dynamical adjustment—a statistical method based on partial least squares regression—to identify the components of variability within the mass-balance records that are associated with the time-varying sea level pressure (SLP) and sea surface temperature (SST) fields. We find that 30-50% of the variance in the winter mass-balance records of the glaciers in southern Norway is explained by using sea level pressure as a predictor. The leading SLP predictor pattern mimics the spatial signature of the North Atlantic Oscillation (NAO), indicating that winter balance is strongly influenced by the NAO. Moreover, the adjusted mass-balance records indicate a geographic trend: the southern Norwegian glaciers have significant negative trends in the summer balance that remain negative after adjustment, while the more northern glaciers have negative winter balance trends that only become significant after adjustment. We look into anthropogenic warming to explain the trends after dynamical adjustment.

Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

PubMed Central

Hu, Haigen; Xu, Lihong; Wei, Ruihua; Zhu, Bingkun

2011-01-01

This paper investigates the issue of tuning the Proportional Integral and Derivative (PID) controller parameters for a greenhouse climate control system using an Evolutionary Algorithm (EA) based on multiple performance measures such as good static-dynamic performance specifications and the smooth process of control. A model of nonlinear thermodynamic laws between numerous system variables affecting the greenhouse climate is formulated. The proposed tuning scheme is tested for greenhouse climate control by minimizing the integrated time square error (ITSE) and the control increment or rate in a simulation experiment. The results show that by tuning the gain parameters the controllers can achieve good control performance through step responses such as small overshoot, fast settling time, and less rise time and steady state error. Besides, it can be applied to tuning the system with different properties, such as strong interactions among variables, nonlinearities and conflicting performance criteria. The results implicate that it is a quite effective and promising tuning method using multi-objective optimization algorithms in the complex greenhouse production. PMID:22163927

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

Boer, George J.; Smith, Douglas M.; Cassou, Christophe

The Decadal Climate Prediction Project (DCPP) is a coordinated multi-model investigation into decadal climate prediction, predictability, and variability. The DCPP makes use of past experience in simulating and predicting decadal variability and forced climate change gained from the fifth Coupled Model Intercomparison Project (CMIP5) and elsewhere. It builds on recent improvements in models, in the reanalysis of climate data, in methods of initialization and ensemble generation, and in data treatment and analysis to propose an extended comprehensive decadal prediction investigation as a contribution to CMIP6 (Eyring et al., 2016) and to the WCRP Grand Challenge on Near Term Climate Predictionmore » (Kushnir et al., 2016). The DCPP consists of three components. Component A comprises the production and analysis of an extensive archive of retrospective forecasts to be used to assess and understand historical decadal prediction skill, as a basis for improvements in all aspects of end-to-end decadal prediction, and as a basis for forecasting on annual to decadal timescales. Component B undertakes ongoing production, analysis and dissemination of experimental quasi-real-time multi-model forecasts as a basis for potential operational forecast production. Component C involves the organization and coordination of case studies of particular climate shifts and variations, both natural and naturally forced (e.g. the “hiatus”, volcanoes), including the study of the mechanisms that determine these behaviours. Furthermore, groups are invited to participate in as many or as few of the components of the DCPP, each of which are separately prioritized, as are of interest to them.The Decadal Climate Prediction Project addresses a range of scientific issues involving the ability of the climate system to be predicted on annual to decadal timescales, the skill that is currently and potentially available, the mechanisms involved in long timescale variability, and the production of forecasts of benefit to both science and society.« less

The Community Climate System Model Version 4

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

Gent, Peter R.; Danabasoglu, Gokhan; Donner, Leo J.

The fourth version of the Community Climate System Model (CCSM4) was recently completed and released to the climate community. This paper describes developments to all the CCSM components, and documents fully coupled pre-industrial control runs compared to the previous version, CCSM3. Using the standard atmosphere and land resolution of 1{sup o} results in the sea surface temperature biases in the major upwelling regions being comparable to the 1.4{sup o} resolution CCSM3. Two changes to the deep convection scheme in the atmosphere component result in the CCSM4 producing El Nino/Southern Oscillation variability with a much more realistic frequency distribution than themore » CCSM3, although the amplitude is too large compared to observations. They also improve the representation of the Madden-Julian Oscillation, and the frequency distribution of tropical precipitation. A new overflow parameterization in the ocean component leads to an improved simulation of the deep ocean density structure, especially in the North Atlantic. Changes to the CCSM4 land component lead to a much improved annual cycle of water storage, especially in the tropics. The CCSM4 sea ice component uses much more realistic albedos than the CCSM3, and the Arctic sea ice concentration is improved in the CCSM4. An ensemble of 20th century simulations runs produce an excellent match to the observed September Arctic sea ice extent from 1979 to 2005. The CCSM4 ensemble mean increase in globally-averaged surface temperature between 1850 and 2005 is larger than the observed increase by about 0.4 C. This is consistent with the fact that the CCSM4 does not include a representation of the indirect effects of aerosols, although other factors may come into play. The CCSM4 still has significant biases, such as the mean precipitation distribution in the tropical Pacific Ocean, too much low cloud in the Arctic, and the latitudinal distributions of short-wave and long-wave cloud forcings.« less

Assessment of Satellite Radiometry in the Visible Domain

NASA Technical Reports Server (NTRS)

Melin, Frederick; Franz, Bryan A.

2014-01-01

Marine reflectance and chlorophyll-a concentration are listed among the Essential Climate Variables by the Global Climate Observing System. To contribute to climate research, the satellite ocean color data records resulting from successive missions need to be consistent and well characterized in terms of uncertainties. This chapter reviews various approaches that can be used for the assessment of satellite ocean color data. Good practices for validating satellite products with in situ data and the current status of validation results are illustrated. Model-based approaches and inter-comparison techniques can also contribute to characterize some components of the uncertainty budget, while time series analysis can detect issues with the instrument radiometric characterization and calibration. Satellite data from different missions should also provide a consistent picture in scales of variability, including seasonal and interannual signals. Eventually, the various assessment approaches should be combined to create a fully characterized climate data record from satellite ocean color.

Framework for Probabilistic Projections of Energy-Relevant Streamflow Indicators under Climate Change Scenarios for the U.S.

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

Wagener, Thorsten; Mann, Michael; Crane, Robert

2014-04-29

This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach tomore » establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.« less

Aerosol physicochemical properties in relation to meteorology: Case studies in urban, marine, and arid settings

NASA Astrophysics Data System (ADS)

Wonaschuetz, Anna

Atmospheric aerosols are a highly relevant component of the climate system affecting atmospheric radiative transfer and the hydrological cycle. As opposed to other key atmospheric constituents with climatic relevance, atmospheric aerosol particles are highly heterogeneous in time and space with respect to their size, concentration, chemical composition and physical properties. Many aspects of their life cycle are not understood, making them difficult to represent in climate models and hard to control as a pollutant. Aerosol-cloud interactions in particular are infamous as a major source of uncertainty in future climate predictions. Field measurements are an important source of information for the modeling community and can lead to a better understanding of chemical and microphysical processes. In this study, field data from urban, marine, and arid settings are analyzed and the impact of meteorological conditions on the evolution of aerosol particles while in the atmosphere is investigated. Particular attention is given to organic aerosols, which are a poorly understood component of atmospheric aerosols. Local wind characteristics, solar radiation, relative humidity and the presence or absence of clouds and fog are found to be crucial factors in the transport and chemical evolution of aerosol particles. Organic aerosols in particular are found to be heavily impacted by processes in the liquid phase (cloud droplets and aerosol water). The reported measurements serve to improve the process-level understanding of aerosol evolution in different environments and to inform the modeling community by providing realistic values for input parameters and validation of model calculations.

Evaluation of a new CNRM-CM6 model version for seasonal climate predictions

NASA Astrophysics Data System (ADS)

Volpi, Danila; Ardilouze, Constantin; Batté, Lauriane; Dorel, Laurant; Guérémy, Jean-François; Déqué, Michel

2017-04-01

This work presents the quality assessment of a new version of the Météo-France coupled climate prediction system, which has been developed in the EU COPERNICUS Climate Change Services framework to carry out seasonal forecast. The system is based on the CNRM-CM6 model, with Arpege-Surfex 6.2.2 as atmosphere/land component and Nemo 3.2 as ocean component, which has directly embedded the sea-ice component Gelato 6.0. In order to have a robust diagnostic, the experiment is composed by 60 ensemble members generated with stochastic dynamic perturbations. The experiment has been performed over a 37-year re-forecast period from 1979 to 2015, with two start dates per year, respectively in May 1st and November 1st. The evaluation of the predictive skill of the model is shown under two perspectives: on the one hand, the ability of the model to faithfully respond to positive or negative ENSO, NAO and QBO events, independently of the predictability of these events. Such assessment is carried out through a composite analysis, and shows that the model succeeds in reproducing the main patterns for 2-meter temperature, precipitation and geopotential height at 500 hPa during the winter season. On the other hand, the model predictive skill of the same events (positive and negative ENSO, NAO and QBO) is evaluated.

Biological forcing controls the chemistry of the coral exoskeleton

NASA Astrophysics Data System (ADS)

Meibom, A.; Mostefaoui, S.; Cuif, J.; Yurimoto, H.; Dauphin, Y.; Houlbreque, F.; Dunbar, R.; Constantz, B.

2006-12-01

A multitude of marine organisms produce calcium carbonate skeletons that are used extensively to reconstruct water temperature variability of the tropical and subtropical oceans - a key parameter in global climate-change models. Such paleo-climate reconstructions are based on the notion that skeletal oxygen isotopic composition and certain trace-element abundances (e.g., Sr/Ca and Mg/Ca ratios) vary in response to changes in the water temperature. However, it is a fundamental problem that poorly understood biological processes introduce large compositional deviations from thermodynamic equilibrium and hinder precise calibrations of many paleo-climate proxies. Indeed, the role of water temperature in controlling the composition of the skeleton is far from understood. We have studied trace-element abundances as well as oxygen and carbon isotopic compositions of individual skeletal components in the zooxanthellate and non-zooxanthellate corals at ultra-structural, i.e. micrometer to sub-micrometer length scales. From this body of work we draw the following, generalized conclusions: 1) Centers of calcification (COC) are not in equilibrium with seawater. Notably, the Sr/Ca ratio is higher than expected for aragonite equilibrium with seawater at the temperature at which the skeleton was formed. Furthermore, the COC are further away from equilibrium with seawater than fibrous skeleton in terms of stable isotope composition. 2) COC are dramatically different from the fibrous aragonite skeleton in terms of trace element composition. 3) Neither trace element nor stable isotope variations in the fibrous (bulk) part of the skeleton are directly related to changes in SST. In fact, changes in SST can have very little to do with the observed compositional variations. 4) Trace element variations in the fibrous (bulk) part of the skeleton are not related to the activity of zooxanthellae. These observations are directly relevant to the issue of biological versus non-biological control over skeleton composition and will be discussed.

Stream Discharge and Evapotranspiration Responses to Climate Change and Their Associated Uncertainties in a Large Semi-Arid Basin

NASA Astrophysics Data System (ADS)

Bassam, S.; Ren, J.

2017-12-01

Predicting future water availability in watersheds is very important for proper water resources management, especially in semi-arid regions with scarce water resources. Hydrological models have been considered as powerful tools in predicting future hydrological conditions in watershed systems in the past two decades. Streamflow and evapotranspiration are the two important components in watershed water balance estimation as the former is the most commonly-used indicator of the overall water budget estimation, and the latter is the second biggest component of water budget (biggest outflow from the system). One of the main concerns in watershed scale hydrological modeling is the uncertainties associated with model prediction, which could arise from errors in model parameters and input meteorological data, or errors in model representation of the physics of hydrological processes. Understanding and quantifying these uncertainties are vital to water resources managers for proper decision making based on model predictions. In this study, we evaluated the impacts of different climate change scenarios on the future stream discharge and evapotranspiration, and their associated uncertainties, throughout a large semi-arid basin using a stochastically-calibrated, physically-based, semi-distributed hydrological model. The results of this study could provide valuable insights in applying hydrological models in large scale watersheds, understanding the associated sensitivity and uncertainties in model parameters, and estimating the corresponding impacts on interested hydrological process variables under different climate change scenarios.

Effects of the Positive Action program on achievement and discipline: two matched-control comparisons.

PubMed

Flay, B R; Allred, C G; Ordway, N

2001-06-01

This paper reports on the effectiveness of an integrated comprehensive school model for character development, problem behavior prevention, and academic achievement enhancement. The Positive Action program consists of a school curriculum, together with schoolwide climate, family, and community components. As evaluated here, the yearly K-6 curriculum consists of over 140 fifteen-to-twenty-minute lessons per year delivered in school classrooms on an almost daily basis. The program is based on theories of self-concept, learning, behavior, and school ecology. We use a matched control design and school-level achievement and disciplinary data to evaluate program effects on student performance and behavior in two separate school districts. The program improved achievement by 16% in one district and 52% in another, and reduced disciplinary referrals by 78% in one district and 85% in the other. We discuss implications of these replicated findings for the prevention of substance abuse and violence, the improvement of school performance, and the reform of American schools.

Mathematics applied to the climate system: outstanding challenges and recent progress

PubMed Central

Williams, Paul D.; Cullen, Michael J. P.; Davey, Michael K.; Huthnance, John M.

2013-01-01

The societal need for reliable climate predictions and a proper assessment of their uncertainties is pressing. Uncertainties arise not only from initial conditions and forcing scenarios, but also from model formulation. Here, we identify and document three broad classes of problems, each representing what we regard to be an outstanding challenge in the area of mathematics applied to the climate system. First, there is the problem of the development and evaluation of simple physically based models of the global climate. Second, there is the problem of the development and evaluation of the components of complex models such as general circulation models. Third, there is the problem of the development and evaluation of appropriate statistical frameworks. We discuss these problems in turn, emphasizing the recent progress made by the papers presented in this Theme Issue. Many pressing challenges in climate science require closer collaboration between climate scientists, mathematicians and statisticians. We hope the papers contained in this Theme Issue will act as inspiration for such collaborations and for setting future research directions. PMID:23588054

Generalized provisional seed zones for native plants

Treesearch

Andrew D. Bower; J. Bradley St.Clair; Vicky Erickson

2014-01-01

Deploying well-adapted and ecologically appropriate plant materials is a core component of successful restoration projects. We have developed generalized provisional seed zones that can be applied to any plant species in the United States to help guide seed movement. These seed zones are based on the intersection of high-resolution climatic data for winter minimum...

Supporting UK adaptation: building services for the next set of UK climate projections

NASA Astrophysics Data System (ADS)

Fung, Fai; Lowe, Jason

2016-04-01

As part of the Climate Change Act 2008, the UK Government sets out a national adaptation programme to address the risks and opportunities identified in a national climate change risk assessment (CCRA) every five years. The last risk assessment in 2012 was based on the probabilistic projections for the UK published in 2009 (UKCP09). The second risk assessment will also use information from UKCP09 alongside other evidence on climate projections. However, developments in the science of climate projeciton, and evolving user needs (based partly on what has been learnt about the diverse user requirements of the UK adaptation community from the seven years of delivering and managing UKCP09 products, market research and the peer-reviewed literature) suggest now is an appropriate time to update the projections and how they are delivered. A new set of UK climate projections are now being produced to upgrade UKCP09 to reflect the latest developments in climate science, the first phase of which will be delivered in 2018 to support the third CCRA. A major component of the work is the building of a tailored service to support users of the new projections during their development and to involve users in key decisions so that the projections are of most use. We will set out the plan for the new climate projections that seek to address the evolving user need. We will also present a framework which aims to (i) facilitate the dialogue between users, boundary organisations and producers, reflecting their different decision-making roles (ii) produce scientifically robust, user-relevant climate information (iii) provide the building blocks for developing further climate services to support adaptation activities in the UK.

Anthropogenic Increase Of Soil Erosion In The Gangetic Plain Revealed By Geochemical Budget Of Erosion

NASA Astrophysics Data System (ADS)

Galy, V.; France-Lanord, C.; Galy, A.; Gaillardet, J.

2007-12-01

Tectonic and climatic factors are the key natural variables controlling the erosion through complex interactions. Nonetheless, over the last few hundred years, human activity also exerts a dominant control in response to extensive land use. The geochemical budget of erosion allows the balance between the different erosion processes to be quantified. The chemical composition of river sediment results from the chemical composition of the source rock modified by (1) weathering reactions occurring during erosion and (2) physical segregation during transport. If erosion is at steady state, the difference between the chemical composition of source rocks and that of river sediments must therefore be counterbalanced by the dissolved flux. However, climatic variations or anthropic impact can induce changes in the erosion distribution in a given basin resulting in non steady state erosion. Using a mass balance approach, the comparison of detailed geochemical data on river sediments with the current flux of dissolved elements allows the steady state hypothesis to be tested. In this study, we present a geochemical budget of weathering for the Ganga basin, one of the most densely populated basin in the world, based on detailed sampling of Himalayan rivers and of the Ganga in the delta. Sampling includes depth profile in the river, to assess the variability generated by transport processes. Himalayan river sediments are described by the dilution of an aluminous component (micas + clays + feldspars) by quartz. Ganga sediments on the other hand correspond to the mixing of bedload, similar to coarse Himalayan sediments, with an aluminous component highly depleted in alkaline elements. Compared with the dissolved flux, the depletion of alkaline elements in Ganga sediments shows that the alkaline weathering budget is imbalanced. This imbalance results from an overabundance of fine soil material in the Ganga sediment relative to other less weathered material directly derived from Himalaya. Based on the average composition of the suspended load and of floodplain soils, we estimate that 250x106 t/yr i.e. 5 t/ha/yr is eroded from soil surfaces of the Ganga floodplain. This enhanced soil erosion is likely triggered by intense deforestation and change in land use due to increasing human activity in the basin.

Environmental optimal control strategies based on plant canopy photosynthesis responses and greenhouse climate model

NASA Astrophysics Data System (ADS)

Deng, Lujuan; Xie, Songhe; Cui, Jiantao; Liu, Tao

2006-11-01

It is the essential goal of intelligent greenhouse environment optimal control to enhance income of cropper and energy save. There were some characteristics such as uncertainty, imprecision, nonlinear, strong coupling, bigger inertia and different time scale in greenhouse environment control system. So greenhouse environment optimal control was not easy and especially model-based optimal control method was more difficult. So the optimal control problem of plant environment in intelligent greenhouse was researched. Hierarchical greenhouse environment control system was constructed. In the first level data measuring was carried out and executive machine was controlled. Optimal setting points of climate controlled variable in greenhouse was calculated and chosen in the second level. Market analysis and planning were completed in third level. The problem of the optimal setting point was discussed in this paper. Firstly the model of plant canopy photosynthesis responses and the model of greenhouse climate model were constructed. Afterwards according to experience of the planting expert, in daytime the optimal goals were decided according to the most maximal photosynthesis rate principle. In nighttime on plant better growth conditions the optimal goals were decided by energy saving principle. Whereafter environment optimal control setting points were computed by GA. Compared the optimal result and recording data in real system, the method is reasonable and can achieve energy saving and the maximal photosynthesis rate in intelligent greenhouse

Assessing the impact of future land use and land cover changes on climate over Brazilian semiarid

NASA Astrophysics Data System (ADS)

Cunha, A. M.; Alvalá, R. S.; Kubota, P. Y.; Vieira, R.

2013-12-01

The continental surface vegetal cover has been considerably changed by human activities, mainly through natural vegetation conversion in grasslands. Such changes in surface cover may impact the regional and global climates, through of the changes in biophysical processes and CO2 exchanges between vegetation and atmosphere. In recent decades, most of the Brazilian territory has been presenting transformation in the land use/cover spatial patterns. The typical vegetation of the Brazilian semiarid, known as caatinga (closed shrubland) had been replaced by pasture lands. Based on that, the main objective of this work was to investigate the impacts of future land cover and land use changes (LCLUC) on surface processes and on the climate of Brazilian semiarid region. Numerical experiments using the AGCM/CPTEC/IBIS were performed in order to investigate the impacts of LCLUC on the climate of Brazilian semiarid due to the replacement of natural vegetation by pasture and degraded areas. The climate impacts of LUCC were assessed using climate simulations considering two scenarios of vegetation distribution: i) Potential Vegetation (Control) and ii) Future scenario of the vegetation: maximum pasture limited by areas of desert and semidesert. These degraded areas were obtained from the future projection of the biome distribution in South America developed by Salazar Velasquez (2009) using CPTEC PVMReg and emission scenarios A2 of the Intergovernmental Panel on Climate Change (IPCC). In general, the simulation results showed that the LCLUC, due to the changes in relevant surface variables, has caused alterations in local and neighborhood regions climate. The LCLUC leads to a decrease in mean rainfall during dry season at study area. A meridional dipole pattern with near surface temperature increase (reduction) in the northern (southern) areas of semiarid was found. The results also highlight that LUCC led to changes in the components of the surface energy and carbon balance. These results suggest that LCLUC, even on a small scale in Brazil's semiarid region, can cause climate impacts, in local and regional scale. Finally, we highlight that the diagnosis of the evolution of LUCC and its climatic implications are essential to guide policy makers in regard to resources application and on policies development, in order to achieve a better management and planning for this important region of the country.

Carbon balance of a subarctic meadow under 3 r{ C warming - unravelling respiration}

NASA Astrophysics Data System (ADS)

Silvennoinen, Hanna; Bárcena, Téresa G.; Moni, Christophe; Szychowski, Marcin; Rajewicz, Paulina; Höglind, Mats; Rasse, Daniel P.

2016-04-01

Boreal and arctic terrestrial ecosystems are central to the climate change debate, as the warming is expected to be disproportionate as compared to world averages. Northern areas contain large terrestrial carbon (C) stocks further increasing the interest in the C cycle's fate in changing climate. In 2013, we started an ecosystem warming experiment at a meadow in Eastern Finnmark, NE Norway. The meadow was on a clay soil and its vegetation was common meadow grasses and clover. Typical local agronomy was applied. The study site featured ten 4m-wide hexagonal plots, five control and five actively warmed plots in randomized complete block design. Each of the warmed plots was continuously maintained 3 ° C above its associated control plot with infrared heaters controlled by canopy thermal sensors. In 2014-2015, we measured net ecosystem exchange (NEE) and respiration twice per week during growth seasons from preinstalled collars of each site with dynamic, temperature-controlled chambers combined to an infrared analyzer. Despite warming-induced differences in yield, species composition and root biomass, neither the NEE nor the respiration responded to the warming, all sites remaining equal sinks for C. Following this observation, we carried out an additional experiment in 2015 where we aimed at partitioning the total CO2 flux to microbial and plant respiration as well as at recording the growth season variation of those parameters in situ. Here, we used an approach based on natural abundances of 13C. The δ13C signature of both autotrophic plant respiration and heterotrophic microbial respiration were obtained in targeted incubations (Snell et al. 2014). Then, the δ13C -signature of the total soil respiration was determined in the field by Keeling approach with dynamic dark chambers combined to CRDS. Proportions of autotrophic and heterotrophic components in total soil respiration were then derived based on 13C mixing model. Incubations were repeated at early, mid and late growth season and field measurements conducted once per week throughout the growth season. We observed differences in the partitioning of the total soil respiration over the three periods: plant respiration consistently dominated in the control plots (60-100 %), whereas the warmed plots exhibited a considerably higher share of microbial respiration in the autumn (70 %; p= 0.03). The share of microbial respiration was also elevated in spring as compared to the control sites. These results indicate that 1)Partitioning exhibits seasonal variation 2) Warmer climate may induce a larger proportion of δ13C-enriched C being decomposed. At our site, warming had little effect on total respiration but enhanced microbial respiration at the expense of plant respiration at early and late growth season. Therefore, even if the local CO2 budgets remained unaffected by the warming climate it may be important to pay attention to the resilience of soil C on a longer run. References: Snell HSK et al. 2014. Rapid Commun. Mass Spectrom. 28: 2341-2351.

Statistical structure of intrinsic climate variability under global warming

NASA Astrophysics Data System (ADS)

Zhu, Xiuhua; Bye, John; Fraedrich, Klaus

2017-04-01

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

Control of Space-Based Electron Beam Free Form Fabrication

NASA Technical Reports Server (NTRS)

Seifzer. W. J.; Taminger, K. M.

2007-01-01

Engineering a closed-loop control system for an electron beam welder for space-based additive manufacturing is challenging. For earth and space based applications, components must work in a vacuum and optical components become occluded with metal vapor deposition. For extraterrestrial applications added components increase launch weight, increase complexity, and increase space flight certification efforts. Here we present a software tool that closely couples path planning and E-beam parameter controls into the build process to increase flexibility. In an environment where data collection hinders real-time control, another approach is considered that will still yield a high quality build.

A comparison of high-resolution pollen-inferred climate data from central Minnesota, USA, to 19th century US military fort climate data and tree-ring inferred climate reconstructions

NASA Astrophysics Data System (ADS)

St Jacques, J.; Cumming, B. F.; Sauchyn, D.; Vanstone, J. R.; Dickenson, J.; Smol, J. P.

2013-12-01

A vital component of paleoclimatology is the validation of paleoclimatological reconstructions. Unfortunately, there is scant instrumental data prior to the 20th century available for this. Hence, typically, we can only do long-term validation using other proxy-inferred climate reconstructions. Minnesota, USA, with its long military fort climate records beginning in 1820 and early dense network of climate stations, offers a rare opportunity for proxy validation. We compare a high-resolution (4-year), millennium-scale, pollen-inferred paleoclimate record derived from varved Lake Mina in central Minnesota to early military fort records and dendroclimatological records. When inferring a paleoclimate record from a pollen record, we rely upon the pollen-climate relationship being constant in time. However, massive human impacts have significantly altered vegetation; and the relationship between modern instrumental climate data and the modern pollen rain becomes altered from what it was in the past. In the Midwest, selective logging, fire suppression, deforestation and agriculture have strongly influenced the modern pollen rain since Euro-American settlement in the mid-1800s. We assess the signal distortion introduced by using the conventional method of modern post-settlement pollen and climate calibration sets to infer climate at Lake Mina from pre-settlement pollen data. Our first February and May temperature reconstructions are based on a pollen dataset contemporaneous with early settlement to which corresponding climate data from the earliest instrumental records has been added to produce a 'pre-settlement' calibration set. The second February and May temperature reconstructions are based on a conventional 'modern' pollen-climate dataset from core-top pollen samples and modern climate normals. The temperature reconstructions are then compared to the earliest instrumental records from Fort Snelling, Minnesota, and it is shown that the reconstructions based on the pre-settlement calibration set give much more credible reconstructions. We then compare the temperature reconstructions based upon the two calibration sets for AD 1116-2002. Significant signal flattening and bias exist when using the conventional modern pollen-climate calibration set rather than the pre-settlement pollen-climate calibration set, resulting in an overestimation of Little Ice Age monthly mean temperatures of 0.5-1.5 oC. Therefore, regional warming from anthropogenic global warming is significantly underestimated when using the conventional method of building pollen-climate calibration sets. We also compare the Lake Mina pollen-inferred effective moisture record to early 19th century climate data and to a four-century tree-ring inferred moisture reconstruction based upon sites in Minnesota and the Dakotas. This comparison shows that regional tree-ring reconstructions are biased towards dry conditions and record wet periods poorly relative to high-resolution pollen reconstructions, giving a false impression of regional aridity. It also suggests that varve chronologies should be based upon cross-dating to ensure a more accurate chronology.

Five-year external reviews of the eight Department of Interior Climate Science Centers: Alaska Climate Science Center

USGS Publications Warehouse

Shasby, Mark; Dolloff, C. Andrew; Hicke, Jeffrey A.; Marcot, Bruce G.; McCarl, Bruce; McMahon, Gerard; Morton, John M.

2017-01-01

This report primarily addresses the first two purposes of the review while providing comments on the third as identified by the science review team (SRT). A separate report of recommendations for the recompetition, based upon compiled observation from all three reviews conducted in 2016, was submitted to NCCWSC on April 15, 2016 to assist with the development of recompetition documents. To further address host-university administrative competencies and efficiencies, separate interviews of host-university faculty and administrators were conducted by NCCWSC staff in conjunction with the on-site component of the reviews.

The Changing Climate.

ERIC Educational Resources Information Center

Schneider, Stephen H.

1989-01-01

Discusses the global change of climate. Presents the trend of climate change with graphs. Describes mathematical climate models including expressions for the interacting components of the ocean-atmosphere system and equations representing the basic physical laws governing their behavior. Provides three possible responses on the change. (YP)

Climate change and North American rangelands: Assessment of mitigation and adaptation strategies

Treesearch

Linda A. Joyce; David D. Briske; Joel R. Brown; H. Wayne Polley; Bruce A. McCarl; Derek W. Bailey

2013-01-01

Recent climatic trends and climate model projections indicate that climate change will modify rangeland ecosystem functions and the services and livelihoods that they provision. Recent history has demonstrated that climatic variability has a strong influence on both ecological and social components of rangeland systems and that these systems possess substantial...

Teaching the Intersection of Climate and Society

NASA Astrophysics Data System (ADS)

Thomson, C.; Ting, M.; Orlove, B. S.

2014-12-01

As the first program of its kind, the M.A. in Climate and Society at Columbia University educates students on how climate affects society and vice versa. The 12-month interdisciplinary Master's program is designed to allow students from a wide variety of backgrounds to gain knowledge in climate science and a deep understanding of social sciences and how they related to climate. There are currently more than 250 alumni applying their skills in fields including energy, economics, disaster mitigation, journalism and climate research in more than a dozen countries worldwide. The presentation will highlight three key components of the program that have contributed to its growth and helped alumni become brokers that can effectively put climate science in the hands of the public and policymakers for the benefit of society. Those components include working with other academic departments at Columbia to successfully integrate social science classes into the curriculum; the development of the course Applications in Climate and Society to help students make an overt link between climate and its impacts on society; and providing students with hands-on activities with practitioners in climate-related fields.

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

USGS Publications Warehouse

Nadeau, Christopher P.; Fuller, Angela K.

2015-01-01

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

Multifarious anchovy and sardine regimes in the Humboldt Current System during the last 150 years.

PubMed

Salvatteci, Renato; Field, David; Gutiérrez, Dimitri; Baumgartner, Tim; Ferreira, Vicente; Ortlieb, Luc; Sifeddine, Abdel; Grados, Daniel; Bertrand, Arnaud

2018-03-01

The Humboldt Current System (HCS) has the highest production of forage fish in the world, although it is highly variable and the future of the primary component, anchovy, is uncertain in the context of global warming. Paradigms based on late 20th century observations suggest that large-scale forcing controls decadal-scale fluctuations of anchovy and sardine across different boundary currents of the Pacific. We develop records of anchovy and sardine fluctuations since 1860 AD using fish scales from multiple sites containing laminated sediments and compare them with Pacific basin-scale and regional indices of ocean climate variability. Our records reveal two main anchovy and sardine phases with a timescale that is not consistent with previously proposed periodicities. Rather, the regime shifts in the HCS are related to 3D habitat changes driven by changes in upwelling intensity from both regional and large-scale forcing. Moreover, we show that a long-term increase in coastal upwelling translates via a bottom-up mechanism to top predators suggesting that the warming climate, at least up to the start of the 21st century, was favorable for fishery productivity in the HCS. © 2017 John Wiley & Sons Ltd.

Spatial distribution of sand fly species (Psychodidae: Phlebtominae), ecological niche, and climatic regionalization in zoonotic foci of cutaneous leishmaniasis, southwest of Iran.

PubMed

Ebrahimi, Sahar; Bordbar, Ali; Rastaghi, Ahmad R Esmaeili; Parvizi, Parviz

2016-06-01

Cutaneous leishmaniasis (CL) is a complex vector-borne disease caused by Leishmania parasites that are transmitted by the bite of several species of infected female phlebotomine sand flies. Monthly factor analysis of climatic variables indicated fundamental variables. Principal component-based regionalization was used for recognition of climatic zones using a clustering integrated method that identified five climatic zones based on factor analysis. To investigate spatial distribution of the sand fly species, the kriging method was used as an advanced geostatistical procedure in the ArcGIS modeling system that is beneficial to design measurement plans and to predict the transmission cycle in various regions of Khuzestan province, southwest of Iran. However, more than an 80% probability of P. papatasi was observed in rainy and temperate bio-climatic zones with a high potential of CL transmission. Finding P. sergenti revealed the probability of transmission and distribution patterns of a non-native vector of CL in related zones. These findings could be used as models indicating climatic zones and environmental variables connected to sand fly presence and vector distribution. Furthermore, this information is appropriate for future research efforts into the ecology of Phlebotomine sand flies and for the prevention of CL vector transmission as a public health priority. © 2016 The Society for Vector Ecology.

Separating sensitivity from exposure in assessing extinction risk from climate change.

PubMed

Dickinson, Maria G; Orme, C David L; Suttle, K Blake; Mace, Georgina M

2014-11-04

Predictive frameworks of climate change extinction risk generally focus on the magnitude of climate change a species is expected to experience and the potential for that species to track suitable climate. A species' risk of extinction from climate change will depend, in part, on the magnitude of climate change the species experiences, its exposure. However, exposure is only one component of risk. A species' risk of extinction will also depend on its intrinsic ability to tolerate changing climate, its sensitivity. We examine exposure and sensitivity individually for two example taxa, terrestrial amphibians and mammals. We examine how these factors are related among species and across regions and how explicit consideration of each component of risk may affect predictions of climate change impacts. We find that species' sensitivities to climate change are not congruent with their exposures. Many highly sensitive species face low exposure to climate change and many highly exposed species are relatively insensitive. Separating sensitivity from exposure reveals patterns in the causes and drivers of species' extinction risk that may not be evident solely from predictions of climate change. Our findings emphasise the importance of explicitly including sensitivity and exposure to climate change in assessments of species' extinction risk.

Separating sensitivity from exposure in assessing extinction risk from climate change

PubMed Central

Dickinson, Maria G.; Orme, C. David L.; Suttle, K. Blake; Mace, Georgina M.

2014-01-01

Predictive frameworks of climate change extinction risk generally focus on the magnitude of climate change a species is expected to experience and the potential for that species to track suitable climate. A species' risk of extinction from climate change will depend, in part, on the magnitude of climate change the species experiences, its exposure. However, exposure is only one component of risk. A species' risk of extinction will also depend on its intrinsic ability to tolerate changing climate, its sensitivity. We examine exposure and sensitivity individually for two example taxa, terrestrial amphibians and mammals. We examine how these factors are related among species and across regions and how explicit consideration of each component of risk may affect predictions of climate change impacts. We find that species' sensitivities to climate change are not congruent with their exposures. Many highly sensitive species face low exposure to climate change and many highly exposed species are relatively insensitive. Separating sensitivity from exposure reveals patterns in the causes and drivers of species' extinction risk that may not be evident solely from predictions of climate change. Our findings emphasise the importance of explicitly including sensitivity and exposure to climate change in assessments of species' extinction risk. PMID:25367429

Ensembles-based predictions of climate change impacts on bioclimatic zones in Northeast Asia

NASA Astrophysics Data System (ADS)

Choi, Y.; Jeon, S. W.; Lim, C. H.; Ryu, J.

2017-12-01

Biodiversity is rapidly declining globally and efforts are needed to mitigate this continually increasing loss of species. Clustering of areas with similar habitats can be used to prioritize protected areas and distribute resources for the conservation of species, selection of representative sample areas for research, and evaluation of impacts due to environmental changes. In this study, Northeast Asia (NEA) was classified into 14 bioclimatic zones using statistical techniques, which are correlation analysis and principal component analysis (PCA), and the iterative self-organizing data analysis technique algorithm (ISODATA). Based on these bioclimatic classification, we predicted shift of bioclimatic zones due to climate change. The input variables include the current climatic data (1960-1990) and the future climatic data of the HadGEM2-AO model (RCP 4.5(2050, 2070) and 8.5(2050, 2070)) provided by WorldClim. Using these data, multi-modeling methods including maximum likelihood classification, random forest, and species distribution modelling have been used to project the impact of climate change on the spatial distribution of bioclimatic zones within NEA. The results of various models were compared and analyzed by overlapping each result. As the result, significant changes in bioclimatic conditions can be expected throughout the NEA by 2050s and 2070s. The overall zones moved upward and some zones were predicted to disappear. This analysis provides the basis for understanding potential impacts of climate change on biodiversity and ecosystem. Also, this could be used more effectively to support decision making on climate change adaptation.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Impact of Climate Change and Human Intervention on River Flow Regimes

NASA Astrophysics Data System (ADS)

Singh, Rajendra; Mittal, Neha; Mishra, Ashok

2017-04-01

Climate change and human interventions like dam construction bring freshwater ecosystem under stress by changing flow regime. It is important to analyse their impact at a regional scale along with changes in the extremes of temperature and precipitation which further modify the flow regime components such as magnitude, timing, frequency, duration, and rate of change of flow. In this study, the Kangsabati river is chosen to analyse the hydrological alterations in its flow regime caused by dam, climate change and their combined impact using Soil and Water Assessment Tool (SWAT) and the Indicators of Hydrologic Alteration (IHA) program based on the Range of Variability Approach (RVA). Results show that flow variability is significantly reduced due to dam construction with high flows getting absorbed and pre-monsoon low flows being augmented by the reservoir. Climate change alone reduces the high peaks whereas a combination of dam and climate change significantly reduces variability by affecting both high and low flows, thereby further disrupting the functioning of riverine ecosystems. Analysis shows that in the Kangsabati basin, influence of dam is greater than that of the climate change, thereby emphasising the significance of direct human intervention. Keywords: Climate change, human impact, flow regime, Kangsabati river, SWAT, IHA, RVA.

A data fusion-based drought index

NASA Astrophysics Data System (ADS)

Azmi, Mohammad; Rüdiger, Christoph; Walker, Jeffrey P.

2016-03-01

Drought and water stress monitoring plays an important role in the management of water resources, especially during periods of extreme climate conditions. Here, a data fusion-based drought index (DFDI) has been developed and analyzed for three different locations of varying land use and climate regimes in Australia. The proposed index comprehensively considers all types of drought through a selection of indices and proxies associated with each drought type. In deriving the proposed index, weekly data from three different data sources (OzFlux Network, Asia-Pacific Water Monitor, and MODIS-Terra satellite) were employed to first derive commonly used individual standardized drought indices (SDIs), which were then grouped using an advanced clustering method. Next, three different multivariate methods (principal component analysis, factor analysis, and independent component analysis) were utilized to aggregate the SDIs located within each group. For the two clusters in which the grouped SDIs best reflected the water availability and vegetation conditions, the variables were aggregated based on an averaging between the standardized first principal components of the different multivariate methods. Then, considering those two aggregated indices as well as the classifications of months (dry/wet months and active/non-active months), the proposed DFDI was developed. Finally, the symbolic regression method was used to derive mathematical equations for the proposed DFDI. The results presented here show that the proposed index has revealed new aspects in water stress monitoring which previous indices were not able to, by simultaneously considering both hydrometeorological and ecological concepts to define the real water stress of the study areas.

Evapotranspiration variability and its association with vegetation dynamics in the Nile Basin, 2002–2011

USGS Publications Warehouse

Alemu, Henok; Senay, Gabriel B.; Kaptue, Armel T.; Kovalskyy, Valeriy

2014-01-01

Evapotranspiration (ET) is a vital component in land-atmosphere interactions. In drylands, over 90% of annual rainfall evaporates. The Nile Basin in Africa is about 42% dryland in a region experiencing rapid population growth and development. The relationship of ET with climate, vegetation and land cover in the basin during 2002–2011 is analyzed using thermal-based Simplified Surface Energy Balance Operational (SSEBop) ET, Normalized Difference Vegetation Index (NDVI)-based MODIS Terrestrial (MOD16) ET, MODIS-derived NDVI as a proxy for vegetation productivity and rainfall from Tropical Rainfall Measuring Mission (TRMM). Interannual variability and trends are analyzed using established statistical methods. Analysis based on thermal-based ET revealed that >50% of the study area exhibited negative ET anomalies for 7 years (2009, driest), while >60% exhibited positive ET anomalies for 3 years (2007, wettest). NDVI-based monthly ET correlated strongly (r > 0.77) with vegetation than thermal-based ET (0.52 < r < 0.73) at p < 0.001. Climate-zone averaged thermal-based ET anomalies positively correlated (r = 0.6, p < 0.05) with rainfall in 4 of the 9 investigated climate zones. Thermal-based and NDVI-based ET estimates revealed minor discrepancies over rainfed croplands (60 mm/yr higher for thermal-based ET), but a significant divergence over wetlands (440 mm/yr higher for thermal-based ET). Only 5% of the study area exhibited statistically significant trends in ET.

Climate Variability In The Euro-atlantic Sector As Simulated By Echam4

NASA Astrophysics Data System (ADS)

Menezes, I.; Corte-Real, J.; Ramos, A.; Conde, F.

The atmosphere is a fundamental component of the climate system and its influence in local and global climates results from its composition, structure and motion. The best available tools to simulate future climates are coupled atmosphere-ocean general circulation models (AOGCMs), ECHAM4 (T42 L19)[1] being a very relevant exam- ple of such a model due to its elaborated parametrizations of physical processes. The purpose of this work is twofold : (1) to assess the ability of ECHAM4 in reproducing the reference climate of 1961-1990, over the Euro-Atlantic sector (29N-71N; 67W- 59E) in terms of mean sea level pressure, surface temperature and total precipitation; (2) to evaluate the expected changes of the same climate elements in a warmer world. To attain the first goal the ECHAMSs control run output is compared with observed data obtained from the Climatic Research Unit (CRU data set)[2-5]; to achieve the second objective, the modelSs control run is compared with its transient run forced by greenhouse gases. In both cases, comparisons are made in terms of mean values, variability in space and time and extremes. References [1] E. Roeckner, K. Arpe, L. Bengtsson, M. Christoph, M. Claussen, L. Dümenil, M. Esch, M. Giorgetta, U. Schlese, and U. Schulzweida, 1996: The atmospheric gen- eral circulation model ECHAM4: Model description and simulation of present-day climate. Max Planck Institut für Meteorologie, Report No. 218, Hamburg, Germany, 90 pp. [2] M. Hulme, D. Conway, P.D. Jones, T. Jiang, E.M. Barrow, and C. Turney (1995), Construction of a 1961-90 European climatology for climate change impacts and mod- elling applications, Int. J. Climatol., 15, 1333-1363. [3] M. Hulme (1994), The cost of climate data U a European experience, Weather, 49, 168-175. [4] M. Hulme, and M.G. New (1997), Dependence of large-scale precipitation clima- tologies on temporal and spatial sampling, J. Climate, 10, 1099-1113. 1 [5] C.J. Willmot, S.M. Robeson and M.J. Janis (1996), Comparison of approaches for estimating time-averaged precipitation using data from the United States, Int. J. Cli- matol., 16, 1103-1115. 2

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.

Historical cover trends in a sagebrush steppe ecosystem from 1985 to 2013: Links with climate, disturbance, and management

USGS Publications Warehouse

Shi, Hua; Rigge, Matthew B.; Homer, Collin G.; Xian, George Z.; Meyer, Debbie; Bunde, Brett

2017-01-01

Understanding the causes and consequences of component change in sagebrush steppe is crucial for evaluating ecosystem sustainability. The sagebrush (Artemisia spp.) steppe ecosystem of the northwest USA has been impacted by the invasion of exotic grasses, increasing fire return intervals, changing land management practices, and fragmentation, often lowering the overall resilience to change. We utilized contemporary and historical Landsat imagery, field data, and regression tree models to produce fractional cover maps of rangeland components (shrub, sagebrush, herbaceous, bare ground, and litter) through the last 30 years. Our main goals were to (1) investigate rangeland component trends over 30 years, (2) evaluate the magnitude and direction of trends in components and climate drivers and their relationship, and (3) assess component trends influenced by climate. Results indicated that over the study period, shrub, sage, herbaceous, and litter cover decreased, while bare ground cover increased. Measured rates of change ranged from − 0.14% decade−1 for shrub cover to 0.05% decade−1 for bare ground, whereas herbaceous and litter cover trends were negligible. Net landscape cover changes were consistent with expectations of climate change and disturbance producing a loss of biotic cover, and converting a portion of shrub and sagebrush to herbaceous cover. Overall, fire and related successional recovery was the greatest change agent for all components in terms of area and cover change, while increasing minimum temperature, at a rate of 0.66°C decade−1, was found to be the most significant climate driver.

CLIMATE CHANGE IN THE UPPER GREAT LAKES REGION: A WORKSHOP REPORT

EPA Science Inventory

This paper, "Coping With Climate Change", argues that adaptation is an important strategy for protecting human health, ecosystems, and economic activity as the climate changes. Adaptation is an essential component of any portfolio of actions that comprise U.S. climate change poli...

Thermal battery for portable climate control

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

Narayanan, S; Li, XS; Yang, S

2015-07-01

Current technologies that provide climate control in the transportation sector are quite inefficient. In gasoline-powered vehicles, the use of air-conditioning is known to result in higher emissions of greenhouse gases and pollutants apart from decreasing the gas-mileage. On the other hand, for electric vehicles (EVs), a drain in the onboard electric battery due to the operation of heating and cooling system results in a substantial decrease in the driving range. As an alternative to the conventional climate control system, we are developing an adsorption-based thermal battery (ATB), which is capable of storing thermal energy, and delivering both heating and coolingmore » on demand, while requiring minimal electric power supply. Analogous to an electrical battery, the ATB can be charged for reuse. Furthermore, it promises to be compact, lightweight, and deliver high performance, which is desirable for mobile applications. In this study, we describe the design and operation of the ATB-based climate control system. We present a general theoretical framework to determine the maximum achievable heating and cooling performance using the ATB. The framework is then applied to study the feasibility of ATB integration in EVs, wherein we analyze the use of NaX zeolite-water as the adsorbent-refrigerant pair. In order to deliver the necessary heating and cooling performance, exceeding 2.5 kW h thermal capacity for EVs, the analysis determines the optimal design and operating conditions. While the use of the ATB in EVs can potentially enhance its driving range, it can also be used for climate control in conventional gasoline vehicles, as well as residential and commercial buildings as a more efficient and environmentally-friendly alternative. (C) 2015 Elsevier Ltd. All rights reserved.« less

Impact of climate change upon vector born diseases in Europe and Africa using ENSEMBLES Regional Climate Models

NASA Astrophysics Data System (ADS)

Caminade, Cyril; Morse, Andy

2010-05-01

Climate variability is an important component in determining the incidence of a number of diseases with significant human/animal health and socioeconomic impacts. The most important diseases affecting health are vector-borne, such as malaria, Rift Valley Fever and including those that are tick borne, with over 3 billion of the world population at risk. Malaria alone is responsible for at least one million deaths annually, with 80% of malaria deaths occurring in sub-Saharan Africa. The climate has a large impact upon the incidence of vector-borne diseases; directly via the development rates and survival of both the pathogen and the vector, and indirectly through changes in the environmental conditions. A large ensemble of regional climate model simulations has been produced within the ENSEMBLES project framework for both the European and African continent. This work will present recent progress in human and animal disease modelling, based on high resolution climate observations and regional climate simulations. Preliminary results will be given as an illustration, including the impact of climate change upon bluetongue (disease affecting the cattle) over Europe and upon malaria and Rift Valley Fever over Africa. Malaria scenarios based on RCM ensemble simulations have been produced for West Africa. These simulations have been carried out using the Liverpool Malaria Model. Future projections highlight that the malaria incidence decreases at the northern edge of the Sahel and that the epidemic belt is shifted southward in autumn. This could lead to significant public health problems in the future as the demography is expected to dramatically rise over Africa for the 21st century.

Comprehensive quality assessment based specific chemical profiles for geographic and tissue variation in Gentiana rigescens using HPLC and FTIR method combined with principal component analysis

NASA Astrophysics Data System (ADS)

Li, Jie; Zhang, Ji; Zhao, Yan-Li; Huang, Heng-Yu; Wang, Yuan-Zhong

2017-12-01

Roots, stems, leaves and flowers of Longdan (Gentiana rigescens Franch. ex Hemsl) were collected from six geographic origins of Yunnan Province (n = 240) to implement the quality assessment based on contents of gentiopicroside, loganic acid, sweroside and swertiamarin and chemical profile using HPLC-DAD and FTIR method combined with principal component analysis (PCA). The content of gentiopicroside (major iridoid glycoside) was the highest in G. rigescens, regardless of tissue and geographic origin. The level of swertiamarin was the lowest, even unable to be detected in samples from Kunming and Qujing. Significant correlations (p < 0.05) between gentiopicroside, loganic acid, sweroside and swertiamarin were found at inter- or intra-tissues, which were highly depended on geographic origins, indicating the influence of environmental conditions on the conversion and transport of secondary metabolites in G. rigescens. Furthermore, samples were reasonably classified as three clusters along large producing areas where have similar climate conditions, characterized by carbohydrates, phenols, benzoates, terpenoids, aliphatic alcohols, aromatic hydrocarbons, and so forth. The present work provided global information on the chemical profile and contents of major iridoid glycosides in G. rigescens originated from six different origins, which is helpful for controlling quality of herbal medicines systematically.

Comprehensive Quality Assessment Based Specific Chemical Profiles for Geographic and Tissue Variation in Gentiana rigescens Using HPLC and FTIR Method Combined with Principal Component Analysis

PubMed Central

Li, Jie; Zhang, Ji; Zhao, Yan-Li; Huang, Heng-Yu; Wang, Yuan-Zhong

2017-01-01

Roots, stems, leaves, and flowers of Longdan (Gentiana rigescens Franch. ex Hemsl) were collected from six geographic origins of Yunnan Province (n = 240) to implement the quality assessment based on contents of gentiopicroside, loganic acid, sweroside and swertiamarin and chemical profile using HPLC-DAD and FTIR method combined with principal component analysis (PCA). The content of gentiopicroside (major iridoid glycoside) was the highest in G. rigescens, regardless of tissue and geographic origin. The level of swertiamarin was the lowest, even unable to be detected in samples from Kunming and Qujing. Significant correlations (p < 0.05) between gentiopicroside, loganic acid, sweroside, and swertiamarin were found at inter- or intra-tissues, which were highly depended on geographic origins, indicating the influence of environmental conditions on the conversion and transport of secondary metabolites in G. rigescens. Furthermore, samples were reasonably classified as three clusters along large producing areas where have similar climate conditions, characterized by carbohydrates, phenols, benzoates, terpenoids, aliphatic alcohols, aromatic hydrocarbons, and so forth. The present work provided global information on the chemical profile and contents of major iridoid glycosides in G. rigescens originated from six different origins, which is helpful for controlling quality of herbal medicines systematically. PMID:29312929

Melanin-based colour polymorphism responding to climate change.

PubMed

Roulin, Alexandre

2014-11-01

Climate warming leads to a decrease in biodiversity. Organisms can deal with the new prevailing environmental conditions by one of two main routes, namely evolving new genetic adaptations or through phenotypic plasticity to modify behaviour and physiology. Melanin-based colouration has important functions in animals including a role in camouflage and thermoregulation, protection against UV-radiation and pathogens and, furthermore, genes involved in melanogenesis can pleiotropically regulate behaviour and physiology. In this article, I review the current evidence that differently coloured individuals are differentially sensitive to climate change. Predicting which of dark or pale colour variants (or morphs) will be more penalized by climate change will depend on the adaptive function of melanism in each species as well as how the degree of colouration covaries with behaviour and physiology. For instance, because climate change leads to a rise in temperature and UV-radiation and dark colouration plays a role in UV-protection, dark individuals may be less affected from global warming, if this phenomenon implies more solar radiation particularly in habitats of pale individuals. In contrast, as desertification increases, pale colouration may expand in those regions, whereas dark colourations may expand in regions where humidity is predicted to increase. Dark colouration may be also indirectly selected by climate warming because genes involved in the production of melanin pigments confer resistance to a number of stressful factors including those associated with climate warming. Furthermore, darker melanic individuals are commonly more aggressive than paler conspecifics, and hence they may better cope with competitive interactions due to invading species that expand their range in northern latitudes and at higher altitudes. To conclude, melanin may be a major component involved in adaptation to climate warming, and hence in animal populations melanin-based colouration is likely to change as an evolutionary or plastic response to climate warming. © 2014 John Wiley & Sons Ltd.

Effects of primitive photosynthesis on Earth's early climate system

NASA Astrophysics Data System (ADS)

Ozaki, Kazumi; Tajika, Eiichi; Hong, Peng K.; Nakagawa, Yusuke; Reinhard, Christopher T.

2018-01-01

The evolution of different forms of photosynthetic life has profoundly altered the activity level of the biosphere, radically reshaping the composition of Earth's oceans and atmosphere over time. However, the mechanistic impacts of a primitive photosynthetic biosphere on Earth's early atmospheric chemistry and climate are poorly understood. Here, we use a global redox balance model to explore the biogeochemical and climatological effects of different forms of primitive photosynthesis. We find that a hybrid ecosystem of H2-based and Fe2+-based anoxygenic photoautotrophs—organisms that perform photosynthesis without producing oxygen—gives rise to a strong nonlinear amplification of Earth's methane (CH4) cycle, and would thus have represented a critical component of Earth's early climate system before the advent of oxygenic photosynthesis. Using a Monte Carlo approach, we find that a hybrid photosynthetic biosphere widens the range of geochemical conditions that allow for warm climate states well beyond either of these metabolic processes acting in isolation. Our results imply that the Earth's early climate was governed by a novel and poorly explored set of regulatory feedbacks linking the anoxic biosphere and the coupled H, C and Fe cycles. We suggest that similar processes should be considered when assessing the potential for sustained habitability on Earth-like planets with reducing atmospheres.

Sustainability of integrated land and water resources management in the face of climate and land use changes

NASA Astrophysics Data System (ADS)

Setegn, Shimelis

2017-04-01

Sustainable development integrates economic development, social development, and environmental protection. Land and Water resources are under severe pressure from increasing populations, fast development, deforestation, intensification of agriculture and the degrading environment in many part of the world. The demand for adequate and safe supplies of water is becoming crucial especially in the overpopulated urban centers of the Caribbean islands. Moreover, population growth coupled with environmental degradation and possible adverse impacts of land use and climate change are major factors limiting freshwater resource availability. The main objective of this study is to develop a hydrological model and analyze the spatiotemporal variability of hydrological processes in the Caribbean islands of Puerto Rico and Jamaica. Physically based eco-hydrological model was developed and calibrated in the Rio Grande Manati and Wag water watershed. Spatial distribution of annual hydrological processes, water balance components for wet and dry years, and annual hydrological water balance of the watershed are discussed. The impact of land use and climate change are addressed in the watersheds. Appropriate nature based adaptation strategies were evaluated. The study will present a good understanding of advantages and disadvantages of nature-based solutions for adapting climate change, hydro-meteorological risks and other extreme hydrological events.

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

USGS Publications Warehouse

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

2004-01-01

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

21 CFR 11.200 - Electronic signature components and controls.

Code of Federal Regulations, 2011 CFR

2011-04-01

... signature components and controls. (a) Electronic signatures that are not based upon biometrics shall: (1... signatures based upon biometrics shall be designed to ensure that they cannot be used by anyone other than...

21 CFR 11.200 - Electronic signature components and controls.

Code of Federal Regulations, 2013 CFR

2013-04-01

... signature components and controls. (a) Electronic signatures that are not based upon biometrics shall: (1... signatures based upon biometrics shall be designed to ensure that they cannot be used by anyone other than...

21 CFR 11.200 - Electronic signature components and controls.

Code of Federal Regulations, 2012 CFR

2012-04-01

... signature components and controls. (a) Electronic signatures that are not based upon biometrics shall: (1... signatures based upon biometrics shall be designed to ensure that they cannot be used by anyone other than...

21 CFR 11.200 - Electronic signature components and controls.

Code of Federal Regulations, 2014 CFR

2014-04-01

... signature components and controls. (a) Electronic signatures that are not based upon biometrics shall: (1... signatures based upon biometrics shall be designed to ensure that they cannot be used by anyone other than...

Will the Arctic Land Surface become Wetter or Drier in Response to a Warming Climate

NASA Astrophysics Data System (ADS)

Hinzman, L. D.; Rawlins, M.; Serreze, M.; Vorosmarty, C. J.; Walsh, J. E.

2015-12-01

There is much concern about a potentially "accelerated" hydrologic cycle, with associated extremes in weather and climate-related phenomena. Whether this translates into wetter or drier conditions across arctic landscapes remains an open question. Arctic ecosystems differ substantially from those in temperate regions, largely due to the interactions of extremes in climate and land surface characteristics. Ice-rich permafrost prevents percolation of rainfall or snowmelt water, often maintaining a moist to saturated active layer where the permafrost table is shallow. Permafrost may also block the lateral movement of groundwater, and act as a confining unit for water in sub- or intra-permafrost aquifers. However, as permafrost degrades, profound changes in interactions between groundwater and surface water occur that affect the partitioning among the water balance components with subsequent impacts to the surface energy balance and essential ecosystem processes. Most simulations of arctic climate project sustained increases in temperature and gradual increases in precipitation over the 21st century. However, most climatic models do not correctly represent the essential controls that permafrost exerts on hydrological, ecological, and climatological processes. If warming continues as projected, we expect large-scale changes in surface hydrology as permafrost degrades. Where groundwater gradients are downward (i.e. surface water will infiltrate to subsurface groundwater), as in most cases, we may expect improved drainage and drier soils, which would result in reduced evaporation and transpiration (ET). In some special cases, where the groundwater gradient is upward (as in many wetlands or springs) surface soils may become wetter or inundated as permafrost degrades. Further, since soil moisture is a primary factor controlling ecosystem processes, interactions between ecosystems, GHG emissions, and high-latitude climate must also be considered highly uncertain. These inter-dependent processes will exert primary controls on several important feedback processes and vary across space and time in some as yet, unknown way.

Assessment of Folsom Lake Watershed response to historical and potential future climate scenarios

USGS Publications Warehouse

Carpenter, Theresa M.; Georgakakos, Konstantine P.

2000-01-01

An integrated forecast-control system was designed to allow the profitable use of ensemble forecasts for the operational management of multi-purpose reservoirs. The system ingests large-scale climate model monthly precipitation through the adjustment of the marginal distribution of reservoir-catchment precipitation to reflect occurrence of monthly climate precipitation amounts in the extreme terciles of their distribution. Generation of ensemble reservoir inflow forecasts is then accomplished with due account for atmospheric- forcing and hydrologic- model uncertainties. These ensemble forecasts are ingested by the decision component of the integrated system, which generates non- inferior trade-off surfaces and, given management preferences, estimates of reservoir- management benefits over given periods. In collaboration with the Bureau of Reclamation and the California Nevada River Forecast Center, the integrated system is applied to Folsom Lake in California to evaluate the benefits for flood control, hydroelectric energy production, and low flow augmentation. In addition to retrospective studies involving the historical period 1964-1993, system simulations were performed for the future period 2001-2030, under a control (constant future greenhouse-gas concentrations assumed at the present levels) and a greenhouse-gas- increase (1-% per annum increase assumed) scenario. The present paper presents and validates ensemble 30-day reservoir- inflow forecasts under a variety of situations. Corresponding reservoir management results are presented in Yao and Georgakakos, A., this issue. Principle conclusions of this paper are that the integrated system provides reliable ensemble inflow volume forecasts at the 5-% confidence level for the majority of the deciles of forecast frequency, and that the use of climate model simulations is beneficial mainly during high flow periods. It is also found that, for future periods with potential sharp climatic increases of precipitation amount and to maintain good reliability levels, operational ensemble inflow forecasting should involve atmospheric forcing from appropriate climatic periods.

Combined fishing and climate forcing in the southern Benguela upwelling ecosystem: an end-to-end modelling approach reveals dampened effects.

PubMed

Travers-Trolet, Morgane; Shin, Yunne-Jai; Shannon, Lynne J; Moloney, Coleen L; Field, John G

2014-01-01

The effects of climate and fishing on marine ecosystems have usually been studied separately, but their interactions make ecosystem dynamics difficult to understand and predict. Of particular interest to management, the potential synergism or antagonism between fishing pressure and climate forcing is analysed in this paper, using an end-to-end ecosystem model of the southern Benguela ecosystem, built from coupling hydrodynamic, biogeochemical and multispecies fish models (ROMS-N2P2Z2D2-OSMOSE). Scenarios of different intensities of upwelling-favourable wind stress combined with scenarios of fishing top-predator fish were tested. Analyses of isolated drivers show that the bottom-up effect of the climate forcing propagates up the food chain whereas the top-down effect of fishing cascades down to zooplankton in unfavourable environmental conditions but dampens before it reaches phytoplankton. When considering both climate and fishing drivers together, it appears that top-down control dominates the link between top-predator fish and forage fish, whereas interactions between the lower trophic levels are dominated by bottom-up control. The forage fish functional group appears to be a central component of this ecosystem, being the meeting point of two opposite trophic controls. The set of combined scenarios shows that fishing pressure and upwelling-favourable wind stress have mostly dampened effects on fish populations, compared to predictions from the separate effects of the stressors. Dampened effects result in biomass accumulation at the top predator fish level but a depletion of biomass at the forage fish level. This should draw our attention to the evolution of this functional group, which appears as both structurally important in the trophic functioning of the ecosystem, and very sensitive to climate and fishing pressures. In particular, diagnoses considering fishing pressure only might be more optimistic than those that consider combined effects of fishing and environmental variability.

Combined Fishing and Climate Forcing in the Southern Benguela Upwelling Ecosystem: An End-to-End Modelling Approach Reveals Dampened Effects

PubMed Central

Travers-Trolet, Morgane; Shin, Yunne-Jai; Shannon, Lynne J.; Moloney, Coleen L.; Field, John G.

2014-01-01

The effects of climate and fishing on marine ecosystems have usually been studied separately, but their interactions make ecosystem dynamics difficult to understand and predict. Of particular interest to management, the potential synergism or antagonism between fishing pressure and climate forcing is analysed in this paper, using an end-to-end ecosystem model of the southern Benguela ecosystem, built from coupling hydrodynamic, biogeochemical and multispecies fish models (ROMS-N2P2Z2D2-OSMOSE). Scenarios of different intensities of upwelling-favourable wind stress combined with scenarios of fishing top-predator fish were tested. Analyses of isolated drivers show that the bottom-up effect of the climate forcing propagates up the food chain whereas the top-down effect of fishing cascades down to zooplankton in unfavourable environmental conditions but dampens before it reaches phytoplankton. When considering both climate and fishing drivers together, it appears that top-down control dominates the link between top-predator fish and forage fish, whereas interactions between the lower trophic levels are dominated by bottom-up control. The forage fish functional group appears to be a central component of this ecosystem, being the meeting point of two opposite trophic controls. The set of combined scenarios shows that fishing pressure and upwelling-favourable wind stress have mostly dampened effects on fish populations, compared to predictions from the separate effects of the stressors. Dampened effects result in biomass accumulation at the top predator fish level but a depletion of biomass at the forage fish level. This should draw our attention to the evolution of this functional group, which appears as both structurally important in the trophic functioning of the ecosystem, and very sensitive to climate and fishing pressures. In particular, diagnoses considering fishing pressure only might be more optimistic than those that consider combined effects of fishing and environmental variability. PMID:24710351

Spring-fen habitat islands in a warming climate: Partitioning the effects of mesoclimate air and water temperature on aquatic and terrestrial biota.

PubMed

Horsák, Michal; Polášková, Vendula; Zhai, Marie; Bojková, Jindřiška; Syrovátka, Vít; Šorfová, Vanda; Schenková, Jana; Polášek, Marek; Peterka, Tomáš; Hájek, Michal

2018-09-01

Climate warming and associated environmental changes lead to compositional shifts and local extinctions in various ecosystems. Species closely associated with rare island-like habitats such as groundwater-dependent spring fens can be severely threatened by these changes due to a limited possibility to disperse. It is, however, largely unknown to what extent mesoclimate affects species composition in spring fens, where microclimate is buffered by groundwater supply. We assembled an original landscape-scale dataset on species composition of the most waterlogged parts of isolated temperate spring fens in the Western Carpathian Mountains along with continuously measured water temperature and hydrological, hydrochemical, and climatic conditions. We explored a set of hypotheses about the effects of mesoclimate air and local spring-water temperature on compositional variation of aquatic (macroinvertebrates), semi-terrestrial (plants) and terrestrial (land snails) components of spring-fen biota, categorized as habitat specialists and other species (i.e. matrix-derived). Water temperature did not show a high level of correlation with mesoclimate. For all components, fractions of compositional variation constrained to temperature were statistically significant and higher for habitat specialists than for other species. The importance of air temperature at the expense of water temperature and its fluctuation clearly increased with terrestriality, i.e. from aquatic macroinvertebrates via vegetation (bryophytes and vascular plants) to land snails, with January air temperature being the most important factor for land snails and plant specialists. Some calcareous-fen specialists with a clear distribution centre in temperate Europe showed a strong affinity to climatically cold sites in our study area and may hence be considered as threatened by climate warming. We conclude that prediction models solely based on air temperature may provide biased estimates of future changes in spring fen communities, because their aquatic and semiterrestrial components are largely affected by water temperature that is modified by local hydrological and landscape settings. Copyright © 2018 Elsevier B.V. All rights reserved.

Detection and Attribution of Regional Climate Change

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

Bala, G; Mirin, A

2007-01-19

We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and oceanmore » circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.« less

An Overview of the Future Development of Climate and Earth System Models for Scientific and Policy Use (Invited)

NASA Astrophysics Data System (ADS)

Washington, W. M.

2010-12-01

The development of climate and earth system models has been regarded primarily as the making of scientific tools to study the complex nature of the Earth’s climate. These models have a long history starting with very simple physical models based on fundamental physics in the 1960s and over time they have become much more complex with atmospheric, ocean, sea ice, land/vegetation, biogeochemical, glacial and ecological components. The policy use aspects of these models did not start in the 1960s and 1970s as decision making tools but were used to answer fundamental scientific questions such as what happens when the atmospheric carbon dioxide concentration increases or is doubled. They gave insights into the various interactions and were extensively compared with observations. It was realized that models of the earlier time periods could only give first order answers to many of the fundamental policy questions. As societal concerns about climate change rose, the policy questions of anthropogenic climate change became better defined; they were mostly concerned with the climate impacts of increasing greenhouse gases, aerosols, and land cover change. In the late 1980s, the United Nations set up the Intergovernmental Panel on Climate Change to perform assessments of the published literature. Thus, the development of climate and Earth system models became intimately linked to the need to not only improve our scientific understanding but also answering fundamental policy questions. In order to meet this challenge, the models became more complex and realistic so that they could address these policy oriented science questions such as rising sea level. The presentation will discuss the past and future development of global climate and earth system models for science and policy purposes. Also to be discussed is their interactions with economic integrated assessment models, regional and specialized models such as river transport or ecological components. As an example of one development pathway, the NSF/Department of Energy supported Community Climate System and Earth System Models will be featured in the presentation. Computational challenges will also part of the discussion.

Precipitation extremes and their relation to climatic indices in the Pacific Northwest USA

NASA Astrophysics Data System (ADS)

Zarekarizi, Mahkameh; Rana, Arun; Moradkhani, Hamid

2018-06-01

There has been focus on the influence of climate indices on precipitation extremes in the literature. Current study presents the evaluation of the precipitation-based extremes in Columbia River Basin (CRB) in the Pacific Northwest USA. We first analyzed the precipitation-based extremes using statistically (ten GCMs) and dynamically downscaled (three GCMs) past and future climate projections. Seven precipitation-based indices that help inform about the flood duration/intensity are used. These indices help in attaining first-hand information on spatial and temporal scales for different service sectors including energy, agriculture, forestry etc. Evaluation of these indices is first performed in historical period (1971-2000) followed by analysis of their relation to large scale tele-connections. Further we mapped these indices over the area to evaluate the spatial variation of past and future extremes in downscaled and observational data. The analysis shows that high values of extreme indices are clustered in either western or northern parts of the basin for historical period whereas the northern part is experiencing higher degree of change in the indices for future scenario. The focus is also on evaluating the relation of these extreme indices to climate tele-connections in historical period to understand their relationship with extremes over CRB. Various climate indices are evaluated for their relationship using Principal Component Analysis (PCA) and Singular Value Decomposition (SVD). Results indicated that, out of 13 climate tele-connections used in the study, CRB is being most affected inversely by East Pacific (EP), Western Pacific (WP), East Atlantic (EA) and North Atlaentic Oscillation (NAO).

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

NASA Astrophysics Data System (ADS)

Davy, Richard; Esau, Igor

2015-04-01

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

Rainfall extremes, weather and climatic characterization over complex terrain: A data-driven approach based on signal enhancement methods and extreme value modeling

NASA Astrophysics Data System (ADS)

Pineda, Luis E.; Willems, Patrick

2017-04-01

Weather and climatic characterization of rainfall extremes is both of scientific and societal value for hydrometeorogical risk management, yet discrimination of local and large-scale forcing remains challenging in data-scarce and complex terrain environments. Here, we present an analysis framework that separate weather (seasonal) regimes and climate (inter-annual) influences using data-driven process identification. The approach is based on signal-to-noise separation methods and extreme value (EV) modeling of multisite rainfall extremes. The EV models use a semi-automatic parameter learning [1] for model identification across temporal scales. At weather scale, the EV models are combined with a state-based hidden Markov model [2] to represent the spatio-temporal structure of rainfall as persistent weather states. At climatic scale, the EV models are used to decode the drivers leading to the shift of weather patterns. The decoding is performed into a climate-to-weather signal subspace, built via dimension reduction of climate model proxies (e.g. sea surface temperature and atmospheric circulation) We apply the framework to the Western Andean Ridge (WAR) in Ecuador and Peru (0-6°S) using ground data from the second half of the 20th century. We find that the meridional component of winds is what matters for the in-year and inter-annual variability of high rainfall intensities alongside the northern WAR (0-2.5°S). There, low-level southerly winds are found as advection drivers for oceanic moist of the normal-rainy season and weak/moderate the El Niño (EN) type; but, the strong EN type and its unique moisture surplus is locally advected at lowlands in the central WAR. Moreover, the coastal ridges, south of 3°S dampen meridional airflows, leaving local hygrothermal gradients to control the in-year distribution of rainfall extremes and their anomalies. Overall, we show that the framework, which does not make any prior assumption on the explanatory power of the weather and climate drivers, allows identification of well-known features of the regional climate in a purely data-driven fashion. Thus, this approach shows potential for characterization of precipitation extremes in data-scarce and orographically complex regions in which model reconstructions are the only climate proxies References [1] Mínguez, R., F.J. Méndez, C. Izaguirre, M. Menéndez, and I.J. Losada (2010), Pseudooptimal parameter selection of non-stationary generalized extreme value models for environmental variables, Environ. Modell. Softw. 25, 1592-1607. [2] Pineda, L., P. Willems (2016), Multisite Downscaling of Seasonal Predictions to Daily Rainfall Characteristics over Pacific-Andean River Basins in Ecuador and Peru using a non-homogenous hidden Markov model, J. Hydrometeor, 17(2), 481-498, doi:10.1175/JHM-D-15-0040.1, http://journals.ametsoc.org/doi/full/10.1175/JHM-D-15-0040.1

Climatic niche evolution in New World monkeys (Platyrrhini).

PubMed

Duran, Andressa; Meyer, Andreas L S; Pie, Marcio R

2013-01-01

Despite considerable interest in recent years on species distribution modeling and phylogenetic niche conservatism, little is known about the way in which climatic niches change over evolutionary time. This knowledge is of major importance to understand the mechanisms underlying limits of species distributions, as well as to infer how different lineages might be affected by anthropogenic climate change. In this study we investigate the tempo and mode climatic niche evolution in New World monkeys (Platyrrhini). Climatic conditions found throughout the distribution of 140 primate species were investigated using a principal component analysis, which indicated that mean temperature (particularly during the winter) is the most important climatic correlate of platyrrhine geographical distributions, accounting for nearly half of the interspecific variation in climatic niches. The effects of precipitation were associated with the second principal component, particularly with respect to the dry season. When models of trait evolution were fit to scores on each of the principal component axes, significant phylogenetic signal was detected for PC1 scores, but not for PC2 scores. Interestingly, although all platyrrhine families occupied comparable regions of climatic space, some aotid species such as Aotus lemurinus, A. jorgehernandezi, and A. miconax show highly distinctive climatic niches associated with drier conditions (high PC2 scores). This shift might have been made possible by their nocturnal habits, which could serve as an exaptation that allow them to be less constrained by humidity during the night. These results underscore the usefulness of investigating explicitly the tempo and mode of climatic niche evolution and its role in determining species distributions.

Impact of climate change and management on N-balance of (pre-) alpine grassland soils

NASA Astrophysics Data System (ADS)

Fu, Jin; Lu, Haiyan; Feng, Jinchao; Diaz-Pines, Eugenio; Gasche, Rainer; Dannenmann, Michael; Butterbach-bahl, Klaus; Kiese, Ralf

2014-05-01

On a global perspective terrestrial biosphere hosts significant pools of nitrogen. Due to cool and moist climatic conditions alpine grassland soils of moderate elevation (app. 1000m) in particular, have large quantities of nitrogen (N) and are important source of reactive nitrogen (Nr). The ability of grassland soil to conserve N may be influenced by changes in management and climate. In the framework of the TERENO project funded by Helmholtz Association and BMBF, IMK-IFU installed a lysimeter network with undisturbed intact grassland soil cores (area 1 m2, depth 1.5 m, 2-3 t of soil) at three sites along a natural altitudinal and thus climate gradient. The lysimeter network consisting of 36 lysimeters and is run for Climate Change research with a long term perspective (>10years). For investigation of Climate Change effect the space for time approach is followed, where lysimeters were translocated along the climate gradient, with some lysimeters remaining at the sites as controls. At all sites two different fertilizer application rates as manure were applied (extensive: 120 kg N ha-1 yr 1; intensive: 300 kg N ha-1 yr-1). The different components of the water balance i.e. precipitation, evapotranspiration and groundwater recharge of each lysimeter are measured by precision weighting of the lysimeters and a separate container for collection of seepage water at the lower boundary condition (1.4m). In addition, soil moisture and temperature are measured in 10, 30, 50, 140 cm soil depth. Soil water in 10, 30, 50 and 140 cm soil depth is sampled with suction cups. Water samples are collected regularly every 2 weeks and at higher frequency (e.g. 3 times a week) after fertilization and cutting events, and analyzed for concentration of DON, NH4+ and NO3-. Greenhouse Gas (GHG) emissions (CO2, N2O and CH4) were measured manually with static chamber technique by GC as well as with automatic chambers via a new developed robot system and QCL Laser. On the basis of the results obtained Climate Change lead to an increase in N2O emission only in spring, summer and autumn but to a significant decrease during winter period. Due to the higher decrease in winter the annual N2O losses were lower under Climate Change. Furthermore a significant increase in N2 emissions could be observed. N2 to N2O ratio was up to 60 at the control site and up to 85 under Climate Change conditions, and both forms of gaseous losses showed an event based pattern (freeze-thaw, fertilization, precipitation). Climate Change leaded to a significant increase in nitrate leaching, whereas leaching of ammonium and DON remained unaffected. Intensive fertilization resulted in increased N-uptake by plants as well as increased NO3- leaching. Effect of Climate Change on nitrate leaching and N2O emission is more pronounced under extensive management. This is most likely due to the fact that under Climate Change conditions largest part of N applied was taken up by the plants and is no longer available for other processes.

Actively controlling coolant-cooled cold plate configuration

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

Chainer, Timothy J.; Parida, Pritish R.

Cooling apparatuses are provided to facilitate active control of thermal and fluid dynamic performance of a coolant-cooled cold plate. The cooling apparatus includes the cold plate and a controller. The cold plate couples to one or more electronic components to be cooled, and includes an adjustable physical configuration. The controller dynamically varies the adjustable physical configuration of the cold plate based on a monitored variable associated with the cold plate or the electronic component(s) being cooled by the cold plate. By dynamically varying the physical configuration, the thermal and fluid dynamic performance of the cold plate are adjusted to, formore » example, optimally cool the electronic component(s), and at the same time, reduce cooling power consumption used in cooling the electronic component(s). The physical configuration can be adjusted by providing one or more adjustable plates within the cold plate, the positioning of which may be adjusted based on the monitored variable.« less

The Future is Now: Reducing Psychological Distance to Increase Public Engagement with Climate Change.

PubMed

Jones, Charlotte; Hine, Donald W; Marks, Anthony D G

2017-02-01

Many people perceive climate change as psychologically distant-a set of uncertain events that might occur far in the future, impacting distant places and affecting people dissimilar to themselves. In this study, we employed construal level theory to investigate whether a climate change communication intervention could increase public engagement by reducing the psychological distance of climate change. Australian residents (N = 333) were randomly assigned to one of two treatment conditions: one framed to increase psychological distance to climate change (distal frame), and the other framed to reduce psychological distance (proximal frame). Participants then completed measures of psychological distance of climate change impacts, climate change concern, and intentions to engage in mitigation behavior. Principal components analysis indicated that psychological distance to climate change was best conceptualized as a multidimensional construct consisting of four components: geographic, temporal, social, and uncertainty. Path analysis revealed the effect of the treatment frame on climate change concern and intentions was fully mediated by psychological distance dimensions related to uncertainty and social distance. Our results suggest that climate communications framed to reduce psychological distance represent a promising strategy for increasing public engagement with climate change. © 2016 Society for Risk Analysis.

Climate Process Team "Representing calving and iceberg dynamics in global climate models"

NASA Astrophysics Data System (ADS)

Sergienko, O. V.; Adcroft, A.; Amundson, J. M.; Bassis, J. N.; Hallberg, R.; Pollard, D.; Stearns, L. A.; Stern, A. A.

2016-12-01

Iceberg calving accounts for approximately 50% of the ice mass loss from the Greenland and Antarctic ice sheets. By changing a glacier's geometry, calving can also significantly perturb the glacier's stress-regime far upstream of the grounding line. This process can enhance discharge of ice across the grounding line. Once calved, icebergs drift into the open ocean where they melt, injecting freshwater to the ocean and affecting the large-scale ocean circulation. The spatial redistribution of the freshwater flux have strong impact on sea-ice formation and its spatial variability. A Climate Process Team "Representing calving and iceberg dynamics in global climate models" was established in the fall 2014. The major objectives of the CPT are: (1) develop parameterizations of calving processes that are suitable for continental-scale ice-sheet models that simulate the evolution of the Antarctic and Greenland ice sheets; (2) compile the data sets of the glaciological and oceanographic observations that are necessary to test, validate and constrain the developed parameterizations and models; (3) develop a physically based iceberg component for inclusion in the large-scale ocean circulation model. Several calving parameterizations based suitable for various glaciological settings have been developed and implemented in a continental-scale ice sheet model. Simulations of the present-day Antarctic and Greenland ice sheets show that the ice-sheet geometric configurations (thickness and extent) are sensitive to the calving process. In order to guide the development as well as to test calving parameterizations, available observations (of various kinds) have been compiled and organized into a database. Monthly estimates of iceberg distribution around the coast of Greenland have been produced with a goal of constructing iceberg size distribution and probability functions for iceberg occurrence in particular regions. A physically based iceberg model component was used in a GFDL global climate model. The simulation results show that the Antarctic iceberg calving-size distribution affects iceberg trajectories, determines where iceberg meltwater enters the ocean and the increased ice-berg freshwater transport leads to increased sea-ice growth around much of the East Antarctic coastline.

Operative air temperature data for different measures applied on a building envelope in warm climate.

PubMed

Baglivo, Cristina; Congedo, Paolo Maria

2018-04-01

Several technical combinations have been evaluated in order to design high energy performance buildings for the warm climate. The analysis has been developed in several steps, avoiding the use of HVAC systems. The methodological approach of this study is based on a sequential search technique and it is shown on the paper entitled "Envelope Design Optimization by Thermal Modeling of a Building in a Warm Climate" [1]. The Operative Air Temperature trends (TOP), for each combination, have been plotted through a dynamic simulation performed using the software TRNSYS 17 (a transient system simulation program, University of Wisconsin, Solar Energy Laboratory, USA, 2010). Starting from the simplest building configuration consisting of 9 rooms (equal-sized modules of 5 × 5 m 2 ), the different building components are sequentially evaluated until the envelope design is optimized. The aim of this study is to perform a step-by-step simulation, simplifying as much as possible the model without making additional variables that can modify their performances. Walls, slab-on-ground floor, roof, shading and windows are among the simulated building components. The results are shown for each combination and evaluated for Brindisi, a city in southern Italy having 1083 degrees day, belonging to the national climatic zone C. The data show the trends of the TOP for each measure applied in the case study for a total of 17 combinations divided into eight steps.

School Climate: An Essential Component of a Comprehensive School Safety Plan

ERIC Educational Resources Information Center

Stark, Heidi

2017-01-01

The intentional assessment and management of school climate is an essential component of a comprehensive school safety plan. The value of this preventive aspect of school safety is often diminished as schools invest resources in physical security measures as a narrowly focused effort to increase school safety (Addington, 2009). This dissertation…

The Characteristics of Earth System Thinking of Science Gifted Students in relation to Climate Changes

NASA Astrophysics Data System (ADS)

Chung, Duk Ho; Cho, Kyu Seong; Hong, Deok Pyo; Park, Kyeong Jin

2016-04-01

This study aimed to investigate the perception of earth system thinking of science gifted students in future problem solving (FPS) in relation to climate changes. In order to this study, the research problem associated with climate changes was developed through a literature review. The thirty seven science gifted students participated in lessons. The ideas in problem solving process of science gifted students were analyzed using the semantic network analysis method. The results are as follows. In the problem solving processes, science gifted students are ''changes of the sunlight by water layer'', ''changes of the Earth''s temperature'', ''changes of the air pressure'', '' change of the wind and weather''were represented in order. On other hand, regard to earth system thinking for climate changes, while science gifted students were used sub components related to atmospheres frequently, they were used sub components related to biosphere, geosphere, and hydrosphere a little. But, the analytical results of the structural relationship between the sub components related to earth system, they were recognised that biosphere, geosphere, and hydrosphere used very important in network structures. In conclusion, science gifted students were understood well that components of the earth system are influencing each other. Keywords : Science gifted students, Future problem solving, Climate change, Earth system thinking

Large-Scale Circulation and Climate Variability. Chapter 5

NASA Technical Reports Server (NTRS)

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

2017-01-01

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

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.

Computer Controlled Portable Greenhouse Climate Control System for Enhanced Energy Efficiency

NASA Astrophysics Data System (ADS)

Datsenko, Anthony; Myer, Steve; Petties, Albert; Hustek, Ryan; Thompson, Mark

2010-04-01

This paper discusses a student project at Kettering University focusing on the design and construction of an energy efficient greenhouse climate control system. In order to maintain acceptable temperatures and stabilize temperature fluctuations in a portable plastic greenhouse economically, a computer controlled climate control system was developed to capture and store thermal energy incident on the structure during daylight periods and release the stored thermal energy during dark periods. The thermal storage mass for the greenhouse system consisted of a water filled base unit. The heat exchanger consisted of a system of PVC tubing. The control system used a programmable LabView computer interface to meet functional specifications that minimized temperature fluctuations and recorded data during operation. The greenhouse was a portable sized unit with a 5' x 5' footprint. Control input sensors were temperature, water level, and humidity sensors and output control devices were fan actuating relays and water fill solenoid valves. A Graphical User Interface was developed to monitor the system, set control parameters, and to provide programmable data recording times and intervals.

Simulation of the present-day climate with the climate model INMCM5

NASA Astrophysics Data System (ADS)

Volodin, E. M.; Mortikov, E. V.; Kostrykin, S. V.; Galin, V. Ya.; Lykossov, V. N.; Gritsun, A. S.; Diansky, N. A.; Gusev, A. V.; Iakovlev, N. G.

2017-12-01

In this paper we present the fifth generation of the INMCM climate model that is being developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences (INMCM5). The most important changes with respect to the previous version (INMCM4) were made in the atmospheric component of the model. Its vertical resolution was increased to resolve the upper stratosphere and the lower mesosphere. A more sophisticated parameterization of condensation and cloudiness formation was introduced as well. An aerosol module was incorporated into the model. The upgraded oceanic component has a modified dynamical core optimized for better implementation on parallel computers and has two times higher resolution in both horizontal directions. Analysis of the present-day climatology of the INMCM5 (based on the data of historical run for 1979-2005) shows moderate improvements in reproduction of basic circulation characteristics with respect to the previous version. Biases in the near-surface temperature and precipitation are slightly reduced compared with INMCM4 as well as biases in oceanic temperature, salinity and sea surface height. The most notable improvement over INMCM4 is the capability of the new model to reproduce the equatorial stratospheric quasi-biannual oscillation and statistics of sudden stratospheric warmings.

Controlled cooling of an electronic system based on projected conditions

DOEpatents

David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.

2016-05-17

Energy efficient control of a cooling system cooling an electronic system is provided based, in part, on projected conditions. The control includes automatically determining an adjusted control setting(s) for an adjustable cooling component(s) of the cooling system. The automatically determining is based, at least in part, on projected power consumed by the electronic system at a future time and projected temperature at the future time of a heat sink to which heat extracted is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on an experimentally obtained model(s) relating the targeted temperature and power consumption of the adjustable cooling component(s) of the cooling system.

Controlled cooling of an electronic system based on projected conditions

DOEpatents

David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.

2015-08-18

Energy efficient control of a cooling system cooling an electronic system is provided based, in part, on projected conditions. The control includes automatically determining an adjusted control setting(s) for an adjustable cooling component(s) of the cooling system. The automatically determining is based, at least in part, on projected power consumed by the electronic system at a future time and projected temperature at the future time of a heat sink to which heat extracted is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on an experimentally obtained model(s) relating the targeted temperature and power consumption of the adjustable cooling component(s) of the cooling system.

A Coupled Economic and Physical Model of Coastal Adaptation and Abandonment: Are human occupied coastlines a bubble waiting to burst?

NASA Astrophysics Data System (ADS)

McNamara, D.; Keeler, A.

2011-12-01

Policy discussions of adaptation by coastal residents to increasing rates of sea level rise and changing frequency of damaging storms have focused on community land use planning processes. This view neglects the role that market dynamics and climate change expectations play in the way coastal communities choose among risk mitigation options and manage land use decisions in an environment of escalating risks. We use a model coupling physical coastal processes with an agent-based model of behavior in real estate and mitigation markets to examine the interplay of climate-driven coastal hazards, collective mitigation decisions, and individual beliefs. The physical component model simulates barrier island processes that respond to both storms and slow scale dynamics associated with sea level rise. The economic component model is an agent-based model of economic behavior where agents are rational economic actors working off different assessments of future climate-driven events. Agents differentially update their beliefs based on a) how much emphasis they give to observed coastal changes and b) how much weight they give to scientific predictions. In essence, agents differ along a spectrum of how much they believe that the past is the best guide to the future and how quickly they react to new information. We use the coupled model to explore three questions of interest to coastal policy. First, how do the interplay of costal processes, beliefs, and mitigation choices affect the level and stability of real estate prices? Second, how does this interplay affect the incentives for community investments in shoreline protection? Third, how do expectations and reactions to observed events, as well as mitigation investments, affect the built environment in circumstances when climate risks reach very high levels? This last question relates to a key aspect of climate change adaptation on the coast - when does mitigation give way to abandonment as an optimal adaptation strategy? Results suggest that subjective expectations about climate risk and about the effectiveness of mitigation in high-risk environments are critical in determining when the market starts to reflect the possibility that property might no longer be inhabitable. Results will be presented that contrast the dynamics of abandonment over a range of sea level rise and storminess scenarios.

Hydrological Climate Classification: Can We Improve on Köppen-Geiger?

NASA Astrophysics Data System (ADS)

Knoben, W.; Woods, R. A.; Freer, J. E.

2017-12-01

Classification is essential in the study of complex natural systems, yet hydrology so far has no formal way to structure the climate forcing which underlies hydrologic response. Various climate classification systems can be borrowed from other disciplines but these are based on different organizing principles than a hydrological classification might use. From gridded global data we calculate a gridded aridity index, an aridity seasonality index and a rain-vs-snow index, which we use to cluster global locations into climate groups. We then define the membership degree of nearly 1100 catchments to each of our climate groups based on each catchment's climate and investigate the extent to which streamflow responses within each climate group are similar. We compare this climate classification approach with the often-used Köppen-Geiger classification, using statistical tests based on streamflow signature values. We find that three climate indices are sufficient to distinguish 18 different climate types world-wide. Climates tend to change gradually in space and catchments can thus belong to multiple climate groups, albeit with different degrees of membership. Streamflow responses within a climate group tend to be similar, regardless of the catchments' geographical proximity. A Wilcoxon two-sample test based on streamflow signature values for each climate group shows that the new classification can distinguish different flow regimes using this classification scheme. The Köppen-Geiger approach uses 29 climate classes but is less able to differentiate streamflow regimes. Climate forcing exerts a strong control on typical hydrologic response and both change gradually in space. This makes arbitrary hard boundaries in any classification scheme difficult to defend. Any hydrological classification should thus acknowledge these gradual changes in forcing. Catchment characteristics (soil or vegetation type, land use, etc) can vary more quickly in space than climate does, which can explain streamflow differences between geographically close locations. Summarizing, this work shows that hydrology needs its own way to structure climate forcing, acknowledging that climates vary gradually on a global scale and explicitly including those climate aspects that drive seasonal changes in hydrologic regimes.

Climatically induced interannual variability in aboveground production in forest-tundra and northern taiga of central Siberia.

PubMed

Knorre, Anastasia A; Kirdyanov, Alexander V; Vaganov, Eugene A

2006-02-01

To investigate the variability of primary production of boreal forest ecosystems under the current climatic changes, we compared the dynamics of annual increments and productivity of the main components of plant community (trees, shrubs, mosses) at three sites in the north of Siberia (Russia). Annual radial growth of trees and shrubs was mostly defined by summer temperature regime (positive correlation), but climatic response of woody plants was species specific and depends on local conditions. Dynamics of annual increments of mosses were opposite to tree growth. The difference in climatic response of the different vegetation components of the forest ecosystems indicates that these components seem to be adapted to use climatic conditions during the short and severe northern summer, and decreasing in annual production of one component is usually combined with the increase of other component productivity. Average productivity in the northern forest ecosystems varies from 0.05 to 0.14 t ha(-1) year(-1) for trees, from 0.05 to 0.18 t ha(-1) year(-1) for shrubs and from 0.54 to 0.66 t ha(-1) year(-1) for mosses. Higher values of tree productivity combined with lower annual moss productivity were found in sites in northern taiga in comparison with forest-tundra. Different tendencies in the productivity of the dominant species from each vegetation level (trees, shrubs, mosses) were indicated for the last 10 years studied (1990-1999): while productivity of mosses is increasing, productivity of trees is decreasing, but there is no obvious trend in the productivity of shrubs. Our results show that in the long term, the main contribution to changes in annual biomass productivity in forest-tundra and northern taiga ecosystems under the predicted climatic changes will be determined by living ground cover.

Applications of a thermal-based two-source energy balance model using Priestley-Taylor approach for surface temperature partitioning (TSEB_PTT) under advective conditions

USDA-ARS?s Scientific Manuscript database

Operational application of the two source energy balance model (TSEB) which can estimate evaportranspiration (ET) and the components evaporation (E), transpiration (T) of the land surface in different climates is very useful for many applications in hydrology and agriculture. The TSEB model uses an ...

Geospatial application of the Water Erosion Prediction Project (WEPP) Model

Treesearch

D. C. Flanagan; J. R. Frankenberger; T. A. Cochrane; C. S. Renschler; W. J. Elliot

2011-01-01

The Water Erosion Prediction Project (WEPP) model is a process-based technology for prediction of soil erosion by water at hillslope profile, field, and small watershed scales. In particular, WEPP utilizes observed or generated daily climate inputs to drive the surface hydrology processes (infiltration, runoff, ET) component, which subsequently impacts the rest of the...

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

DOE PAGES

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.; ...

2017-02-21

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, geneticmore » mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.« less

Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

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

Tanger, Paul; Klassen, Stephen; Mojica, Julius P.

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, geneticmore » mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.« less

Identifying natural and anthropogenic sources of metals in urban and rural soils using GIS-based data, PCA, and spatial interpolation

PubMed Central

Davis, Harley T.; Aelion, C. Marjorie; McDermott, Suzanne; Lawson, Andrew B.

2009-01-01

Determining sources of neurotoxic metals in rural and urban soils is important for mitigating human exposure. Surface soil from four areas with significant clusters of mental retardation and developmental delay (MR/DD) in children, and one control site were analyzed for nine metals and characterized by soil type, climate, ecological region, land use and industrial facilities using readily-available GIS-based data. Kriging, principal component analysis (PCA) and cluster analysis (CA) were used to identify commonalities of metal distribution. Three MR/DD areas (one rural and two urban) had similar soil types and significantly higher soil metal concentrations. PCA and CA results suggested that Ba, Be and Mn were consistently from natural sources; Pb and Hg from anthropogenic sources; and As, Cr, Cu, and Ni from both sources. Arsenic had low commonality estimates, was highly associated with a third PCA factor, and had a complex distribution, complicating mitigation strategies to minimize concentrations and exposures. PMID:19361902

Creating "Intelligent" Ensemble Averages Using a Process-Based Framework

NASA Astrophysics Data System (ADS)

Baker, Noel; Taylor, Patrick

2014-05-01

The CMIP5 archive contains future climate projections from over 50 models provided by dozens of modeling centers from around the world. Individual model projections, however, are subject to biases created by structural model uncertainties. As a result, ensemble averaging of multiple models is used to add value to individual model projections and construct a consensus projection. Previous reports for the IPCC establish climate change projections based on an equal-weighted average of all model projections. However, individual models reproduce certain climate processes better than other models. Should models be weighted based on performance? Unequal ensemble averages have previously been constructed using a variety of mean state metrics. What metrics are most relevant for constraining future climate projections? This project develops a framework for systematically testing metrics in models to identify optimal metrics for unequal weighting multi-model ensembles. The intention is to produce improved ("intelligent") unequal-weight ensemble averages. A unique aspect of this project is the construction and testing of climate process-based model evaluation metrics. A climate process-based metric is defined as a metric based on the relationship between two physically related climate variables—e.g., outgoing longwave radiation and surface temperature. Several climate process metrics are constructed using high-quality Earth radiation budget data from NASA's Clouds and Earth's Radiant Energy System (CERES) instrument in combination with surface temperature data sets. It is found that regional values of tested quantities can vary significantly when comparing the equal-weighted ensemble average and an ensemble weighted using the process-based metric. Additionally, this study investigates the dependence of the metric weighting scheme on the climate state using a combination of model simulations including a non-forced preindustrial control experiment, historical simulations, and several radiative forcing Representative Concentration Pathway (RCP) scenarios. Ultimately, the goal of the framework is to advise better methods for ensemble averaging models and create better climate predictions.

The Value of GRACE Data in Improving, Assessing and Evaluating Land Surface and Climate Models

NASA Astrophysics Data System (ADS)

Yang, Z.

2011-12-01

I will review how the Gravity Recovery and Climate Experiment (GRACE) satellite measurements have improved land surface models that are developed for weather, climate, and hydrological studies. GRACE-derived terrestrial water storage (TWS) changes have been successfully used to assess and evaluate the improved representations of land-surface hydrological processes such as groundwater-soil moisture interaction, frozen soil and infiltration, and the topographic control on runoff production, as evident in the simulations from the latest Noah-MP, the Community Land Model, and the Community Climate System Model. GRACE data sets have made it possible to estimate key terrestrial water storage components (snow mass, surface water, groundwater or water table depth), biomass, and surface water fluxes (evapotranspiration, solid precipitation, melt of snow/ice). Many of the examples will draw from my Land, Environment and Atmosphere Dynamics group's work on land surface model developments, snow mass retrieval, and multi-sensor snow data assimilation using the ensemble Karman filter and the ensemble Karman smoother. Finally, I will briefly outline some future directions in using GRACE in land surface modeling.

Using ARM Observations to Evaluate Climate Model Simulations of Land-Atmosphere Coupling on the U.S. Southern Great Plains

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

Phillips, Thomas J.; Klein, Stephen A.; Ma, Hsi -Yen

Several independent measurements of warm-season soil moisture and surface atmospheric variables recorded at the ARM Southern Great Plains (SGP) research facility are used to estimate the terrestrial component of land-atmosphere coupling (LAC) strength and its regional uncertainty. The observations reveal substantial variation in coupling strength, as estimated from three soil moisture measurements at a single site, as well as across six other sites having varied soil and land cover types. The observational estimates then serve as references for evaluating SGP terrestrial coupling strength in the Community Atmospheric Model coupled to the Community Land Model. These coupled model components are operatedmore » in both a free-running mode and in a controlled configuration, where the atmospheric and land states are reinitialized daily, so that they do not drift very far from observations. Although the controlled simulation deviates less from the observed surface climate than its free-running counterpart, the terrestrial LAC in both configurations is much stronger and displays less spatial variability than the SGP observational estimates. Preliminary investigation of vegetation leaf area index (LAI) substituted for soil moisture suggests that the overly strong coupling between model soil moisture and surface atmospheric variables is associated with too much evaporation from bare ground and too little from the vegetation cover. Lastly, these results imply that model surface characteristics such as LAI, as well as the physical parameterizations involved in the coupling of the land and atmospheric components, are likely to be important sources of the problematical LAC behaviors.« less

Using ARM Observations to Evaluate Climate Model Simulations of Land-Atmosphere Coupling on the U.S. Southern Great Plains

DOE PAGES

Phillips, Thomas J.; Klein, Stephen A.; Ma, Hsi -Yen; ...

2017-10-13

Several independent measurements of warm-season soil moisture and surface atmospheric variables recorded at the ARM Southern Great Plains (SGP) research facility are used to estimate the terrestrial component of land-atmosphere coupling (LAC) strength and its regional uncertainty. The observations reveal substantial variation in coupling strength, as estimated from three soil moisture measurements at a single site, as well as across six other sites having varied soil and land cover types. The observational estimates then serve as references for evaluating SGP terrestrial coupling strength in the Community Atmospheric Model coupled to the Community Land Model. These coupled model components are operatedmore » in both a free-running mode and in a controlled configuration, where the atmospheric and land states are reinitialized daily, so that they do not drift very far from observations. Although the controlled simulation deviates less from the observed surface climate than its free-running counterpart, the terrestrial LAC in both configurations is much stronger and displays less spatial variability than the SGP observational estimates. Preliminary investigation of vegetation leaf area index (LAI) substituted for soil moisture suggests that the overly strong coupling between model soil moisture and surface atmospheric variables is associated with too much evaporation from bare ground and too little from the vegetation cover. Lastly, these results imply that model surface characteristics such as LAI, as well as the physical parameterizations involved in the coupling of the land and atmospheric components, are likely to be important sources of the problematical LAC behaviors.« less

A Multidisciplinary Approach to Assessing the Causal Components of Climate Change

NASA Astrophysics Data System (ADS)

Gosnold, W. D.; Todhunter, P. E.; Dong, X.; Rundquist, B.; Majorowicz, J.; Blackwell, D. D.

2004-05-01

Separation of climate forcing by anthropogenic greenhouse gases from natural radiative climate forcing is difficult because the composite temperature signal in the meteorological and multi-proxy temperature records cannot be resolved directly into radiative forcing components. To address this problem, we have initiated a large-scale, multidisciplinary project to test coherence between ground surface temperatures (GST) reconstructed from borehole T-z profiles, surface air temperatures (SAT), soil temperatures, and solar radiation. Our hypothesis is that radiative heating and heat exchange between the ground and the air directly control the ground surface temperature. Consequently, borehole T-z measurements at multi-year intervals spanning time periods when solar radiation, soil and air temperatures have been recorded should enable comparison of the thermal energy stored in the ground to these quantities. If coherence between energy storage, solar radiation, GST, SAT and multi-proxy temperature data can be discerned for a one or two decade scale, synthesis of GST and multi-proxy data over the past several centuries may enable us to separately determine the anthropogenic and natural forcings of climate change. The data we are acquiring include: (1) New T-z measurements in boreholes previously used in paleoclimate and heat flow research in Canada and the United States from the 1970's to the present. (2) Meteorological data from the US Historical Climatology Network and the Automated Weather Data Network of the High Plains Regional Climate Center, and Environment Canada. (3) Direct and remotely sensed data on land use, environment, and soil properties at selected borehole and meteorological sites for the periods between borehole observations. The project addresses three related questions: What is the coherence between the GST, SAT, soil temperatures and solar radiation? Have microclimate changes at borehole sites and climate stations affected temperature trends? If good coherence is obtained, can the coherence between thermal energy stored in the ground and radiative forcing during the time between T-z measurements be extended several centuries into the past?

Comparison of Surface Mountain Climate With Equivalent Free Air Parameters Extracted From NCEP/NCAR Reanalysis: Kilimanjaro, Tanzania.

NASA Astrophysics Data System (ADS)

Pepin, N. C.; Hardy, D.; Duane, W.; Losleben, M.

2007-12-01

It is difficult to predict future climate changes in areas of complex relief, since mountains generate their own climates distinct from the free atmosphere. Thus trends in climate at the mountain surface are different from those in the free air. We compare surface climate (temperature and vapour pressure) measured at seven elevations on the south-western slope of Kilimanjaro, the tallest free standing mountain in Africa, with equivalent observations in the free atmosphere from NCEP/NCAR reanalysis data for September 2004 to January 2006. Correlations between daily surface and free air temperature anomalies are greatest at low elevations below 2500 metres, meaning that synoptic (inter-diurnal) variability is the major control here. However, temperatures and moisture on the higher slopes above the treeline (3000 m) are decoupled from the free atmosphere, showing intense heating/cooling by day/night and import of moisture from lower elevations during the day. The lower forested slopes thus act as a moisture source, with large vapour pressure excesses reported in comparison with the free atmosphere (>5 hPa) which move upslope during daylight and subside downslope at night. Strong seasonal contrasts are shown in the vigour of the montane thermal circulation, but interactions with free air circulation (as represented by flow indices developed from reanalysis wind components) are complex. Upper air flow strength and direction (at 500 mb) have limited influence on surface heating and upslope moisture advection, which are dominated by the diurnal cycle rather than inter-diurnal synoptic controls. Thus local changes in surface characteristics (e.g. deforestation) could have a direct influence on the mountain climate of Kilimanjaro, making the upper slopes somewhat divorced from larger scale advective changes associated with global warming.

Climate Change Impacts on Sediment Transport In a Lowland Watershed System: Controlling Processes and Projection

NASA Astrophysics Data System (ADS)

al Aamery, N. M. H.; Mahoney, D. T.; Fox, J.

2017-12-01

Future climate change projections suggest extreme impacts on watershed hydrologic systems for some regions of the world including pronounced increases in surface runoff and instream flows. Yet, there remains a lack of research focused on how future changes in hydrologic extremes, as well as relative hydrologic mean changes, impact sediment redistribution within a watershed and sediment flux from a watershed. The authors hypothesized that variations in mean and extreme changes in turn may impact sediments in depositional and erosional dominance in a manner that may not be obvious to the watershed manager. Therefore, the objectives of this study were to investigate the inner processes connecting the combined effect of extreme climate change projections on the vegetation, upland erosion, and instream processes to produce changes in sediment redistribution within watersheds. To do so, research methods were carried out by the authors including simulating sediment processes in forecast and hindcast periods for a lowland watershed system. Publically available climate realizations from several climate factors and the Soil Water Assessment Tool (SWAT) were used to predict hydrologic conditions for the South Elkhorn Watershed in central Kentucky, USA to 2050. The results of the simulated extreme and mean hydrological components were used in simulating upland erosion with the connectivity processes consideration and thereafter used in building and simulating the instream erosion and deposition of sediment processes with the consideration of surface fine grain lamina (SFGL) layer controlling the benthic ecosystem. Results are used to suggest the dominance of erosional and depositional redistribution of sediments under different scenarios associated with extreme and mean hydrologic forecasting. The results are discussed in reference to the benthic ecology of the stream system providing insight on how water managers might consider sediment redistribution in a changing climate.

Processes Controlling Baseflow and Climatic Warming Effects in Merced River, Sierra Nevada, California

NASA Astrophysics Data System (ADS)

Liu, F.; Conklin, M. H.; Shaw, G.; Bales, R. C.; Conrad, M. E.; Rice, R.

2006-12-01

Sources of streamflow in Merced River were determined using stable isotopes and chemical tracers in order to improve our understanding of hydrologic controls on streamflow and their relationship with climatic warming in the region. Samples were collected from streamflow, groundwater, and natural springs from 2003 to 2006. Both stable isotopes and specific conductivity in streamflow showed a strong seasonality, with lower values from April to July during the snowmelt season, higher values from August to October during dry season, and intermediate values from November to March during winter rainfall and snowfall. Two components controlling baseflow (streamflow from August to October) in the Upper Merced River were identified: shallow subsurface runoff from snowmelt infiltration and groundwater from fractured bedrock. Conductivity in baseflow increased rapidly with discharge, following a power law (R2 > 0.96, p < 0.05), and peaked in October, indicating that the contribution of shallow subsurface runoff to baseflow was significant but decreased rapidly from August to October. Baseflow appears to be very sensitive to the snowmelt timing and regime. From 1976 to 2005, during a period of increasing temperature in the region, streamflow tended to decrease significantly during October (p < 0.05) and increase during March (p < 0.05). However, total annual precipitation did not change significantly, indicating that the shift in baseflow discharge is a result of the early onset of snowmelt due to climatic warming. If climatic warming continues in the region, baseflow in the Sierra Nevada may continue decreasing and water supply may suffer increased stress during the late summer, high water-demand period.

Exploring Preschoolers' Engagement and Perceived Physical Competence in an Autonomy-Based Object Control Skill Intervention: A Preliminary Study

ERIC Educational Resources Information Center

Logan, Samuel; Robinson, Leah; Webster, E. Kipling; Barber, Laura

2013-01-01

The purpose of this study was to describe children's engagement during two (high and low) autonomy-based climates. Twenty-five preschool children participated in a nine-week object control skill intervention. Children completed the object control subscale of the Test of Gross Motor Development 2nd Edition and the perceived physical competence…

21 CFR 11.200 - Electronic signature components and controls.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 21 Food and Drugs 1 2010-04-01 2010-04-01 false Electronic signature components and controls. 11... SERVICES GENERAL ELECTRONIC RECORDS; ELECTRONIC SIGNATURES Electronic Signatures § 11.200 Electronic signature components and controls. (a) Electronic signatures that are not based upon biometrics shall: (1...

Regional and global implications of land-use change and climate change

NASA Astrophysics Data System (ADS)

Stauffer, Heidi Lada

This dissertation has two main components. The first is a longterm regional climate modeling study of the effects of different types of land use changes on Southeast Asian climate under present-day climate conditions and under future projected climate conditions at the end of the 21st Century. The focus of the second component is to estimate daily heat index for projected extreme temperatures at the end of the 21st Century and projecting the number of people affected by those heat conditions. The first component of this study uses a high-resolution regional climate model centered on the Southeast Asian region to compare two land use change scenarios under modern climate and future projected climate conditions. Results from experiments under modern climate conditions indicate that changes in regional climate including widespread surface cooling, increased precipitation, and increased latent heat flux are primarily due to deforestation. As expected from other studies, future climate projections indicate increasing surface temperature and total precipitation. However, the combination of increasing global temperatures and irrigation appears to increase latent heat flux and evapotranspiration, leading to decrease in the surface temperature nearly the same magnitude, increasing both specific humidity and relative humidity. The increasing relative humidity causes low clouds to form, and the net surface solar absorbed flux decreases in response, which further cools the surface. These results imply that deforestation and irrigation have differing complex regional climate responses and the presence of irrigation could mask future surface temperature increases, at least in the short term and reinforce the importance of incorporating land use changes, particularly irrigation, into any studies of future regional climate. The second component of this study uses global daily maximum heat indices derived from future climate future climate simulations for 2098 and projected population density to estimate how many people will be affected by rising temperatures. Our results show that over 4 billion people annually will experience prolonged periods of Danger heat index conditions, under which heat exhaustion and heat stroke are likely. In addition, a majority of people subjected to prolonged high heat stress conditions are located in tropical developing nations, such as those in south and Southeast Asia, where population density is high and large numbers of people work outdoors. Many countries in these regions lack the resources to mitigate the impact of heat stress on the large numbers of people likely to experience heat-related illness and death.

Contemporary group estimates adjusted for climatic effects provide a finer definition of the unknown environmental challenges experienced by growing pigs.

PubMed

Guy, S Z Y; Li, L; Thomson, P C; Hermesch, S

2017-12-01

Environmental descriptors derived from mean performances of contemporary groups (CGs) are assumed to capture any known and unknown environmental challenges. The objective of this paper was to obtain a finer definition of the unknown challenges, by adjusting CG estimates for the known climatic effects of monthly maximum air temperature (MaxT), minimum air temperature (MinT) and monthly rainfall (Rain). As the unknown component could include infection challenges, these refined descriptors may help to better model varying responses of sire progeny to environmental infection challenges for the definition of disease resilience. Data were recorded from 1999 to 2013 at a piggery in south-east Queensland, Australia (n = 31,230). Firstly, CG estimates of average daily gain (ADG) and backfat (BF) were adjusted for MaxT, MinT and Rain, which were fitted as splines. In the models used to derive CG estimates for ADG, MaxT and MinT were significant variables. The models that contained these significant climatic variables had CG estimates with a lower variance compared to models without significant climatic variables. Variance component estimates were similar across all models, suggesting that these significant climatic variables accounted for some known environmental variation captured in CG estimates. No climatic variables were significant in the models used to derive the CG estimates for BF. These CG estimates were used to categorize environments. There was no observable sire by environment interaction (Sire×E) for ADG when using the environmental descriptors based on CG estimates on BF. For the environmental descriptors based on CG estimates of ADG, there was significant Sire×E only when MinT was included in the model (p = .01). Therefore, this new definition of the environment, preadjusted by MinT, increased the ability to detect Sire×E. While the unknown challenges captured in refined CG estimates need verification for infection challenges, this may provide a practical approach for the genetic improvement of disease resilience. © 2017 Blackwell Verlag GmbH.

Appendix A: Ecoprovinces of the Central North American Cordillera and adjacent plains

Treesearch

Dennis A. Demarchi

1994-01-01

The fundamental difference between the map presented here and other regional ecosystem classifications is that this map's ecological units are based on climatic processes rather than vegetation communities (map appears at the end of this appendix). Macroclimatic processes are the physical and thermodynamic interaction between climatic controls, or the relatively...

A Mechanistically Informed User-Friendly Model to Predict Greenhouse Gas (GHG) Fluxes and Carbon Storage from Coastal Wetlands

NASA Astrophysics Data System (ADS)

Abdul-Aziz, O. I.; Ishtiaq, K. S.

2015-12-01

We present a user-friendly modeling tool on MS Excel to predict the greenhouse gas (GHG) fluxes and estimate potential carbon sequestration from the coastal wetlands. The dominant controls of wetland GHG fluxes and their relative mechanistic linkages with various hydro-climatic, sea level, biogeochemical and ecological drivers were first determined by employing a systematic data-analytics method, including Pearson correlation matrix, principal component and factor analyses, and exploratory partial least squares regressions. The mechanistic knowledge and understanding was then utilized to develop parsimonious non-linear (power-law) models to predict wetland carbon dioxide (CO2) and methane (CH4) fluxes based on a sub-set of climatic, hydrologic and environmental drivers such as the photosynthetically active radiation, soil temperature, water depth, and soil salinity. The models were tested with field data for multiple sites and seasons (2012-13) collected from the Waquoit Bay, MA. The model estimated the annual wetland carbon storage by up-scaling the instantaneous predicted fluxes to an extended growing season (e.g., May-October) and by accounting for the net annual lateral carbon fluxes between the wetlands and estuary. The Excel Spreadsheet model is a simple ecological engineering tool for coastal carbon management and their incorporation into a potential carbon market under a changing climate, sea level and environment. Specifically, the model can help to determine appropriate GHG offset protocols and monitoring plans for projects that focus on tidal wetland restoration and maintenance.

Spatiotemporal patterns of evapotranspiration in response to multiple environmental factors simulated by the Community Land Model

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

Shi, Xiaoying; Mao, Jiafu; Thornton, Peter E

In this study, spatial and temporal patterns of evapotranspiration (ET) over the period of 1982-2008 are investigated and attributed to multiple environmental factors using the Community Land Model version 4 (CLM4). Our results show that CLM4 captures the spatial distribution and interannual variability of ET well when compared to observation-based estimates derived from the FLUXNET network of eddy covariance towers using the model tree ensembles (MTE) approach. We find that climate trends and variability dominate predicted variability in ET. Elevated atmospheric CO2 concentration also plays an important role in modulating the trend of predicted ET over most land areas, andmore » functions as the dominant factor controlling ET changes over North America, South America and Asia regions. Compared to the effect of climate change and CO2 concentration, the roles of other factors such as nitrogen deposition, land use change and aerosol deposition are less pronounced and regionally dependent. For example, the aerosol deposition contribution is the third-most important factor for trends of ET over Europe, while it has the smallest impact on ET trend over other regions. As ET is a dominant component of the terrestrial water cycle, our results suggest that environmental factors like elevated CO2, nitrogen and aerosol depositions, and land use and land cover change, in addition to climate, could have significant impact on future projections of water resources and water cycle dynamics at global and regional scales.« less

A multiresolution method for climate system modeling: application of spherical centroidal Voronoi tessellations

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

Ringler, Todd; Ju, Lili; Gunzburger, Max

2008-11-14

During the next decade and beyond, climate system models will be challenged to resolve scales and processes that are far beyond their current scope. Each climate system component has its prototypical example of an unresolved process that may strongly influence the global climate system, ranging from eddy activity within ocean models, to ice streams within ice sheet models, to surface hydrological processes within land system models, to cloud processes within atmosphere models. These new demands will almost certainly result in the develop of multiresolution schemes that are able, at least regionally, to faithfully simulate these fine-scale processes. Spherical centroidal Voronoimore » tessellations (SCVTs) offer one potential path toward the development of a robust, multiresolution climate system model components. SCVTs allow for the generation of high quality Voronoi diagrams and Delaunay triangulations through the use of an intuitive, user-defined density function. In each of the examples provided, this method results in high-quality meshes where the quality measures are guaranteed to improve as the number of nodes is increased. Real-world examples are developed for the Greenland ice sheet and the North Atlantic ocean. Idealized examples are developed for ocean–ice shelf interaction and for regional atmospheric modeling. In addition to defining, developing, and exhibiting SCVTs, we pair this mesh generation technique with a previously developed finite-volume method. Our numerical example is based on the nonlinear, shallow water equations spanning the entire surface of the sphere. This example is used to elucidate both the potential benefits of this multiresolution method and the challenges ahead.« less

Potassium Management for Improving Growth and Grain Yield of Maize (Zea mays L.) under Moisture Stress Condition

PubMed Central

Amanullah; Iqbal, Asif; Irfanullah; Hidayat, Zeeshan

2016-01-01

Potassium (K) fertilizer management is beneficial for improving growth, yield and yield components of field crops under moisture stress condition in semiarid climates. Field experiments were conducted to study the response of maize (Zea mays L., cv. Azam) to foliar and soil applied K during summer 2013 and 2014. The experiments were carried out at the Agronomy Research Farm of The University of Agriculture Peshawar, Northwest Pakistan under limited irrigation (moisture stress) condition. It was concluded from the results that application of foliar K at the rate of 1–3% and foliar Zn at the rate of 0.1–0.2% was more beneficial in terms of better growth, higher yield and yield components of maize under moisture stress condition. Early spray (vegetative stage) resulted in better growth and higher yield than late spray (reproductive stage). Soil K treated plots (rest) plots performed better than control (K not applied) in terms of improved growth, higher yield and yield components of maize crop. The results further demonstrated that increasing the rate of soil applied K up to 90 kg P ha−1 in two equal splits (50% each at sowing and knee height) improve growth and maize productivity under semiarid climates. PMID:27694964

Potassium Management for Improving Growth and Grain Yield of Maize (Zea mays L.) under Moisture Stress Condition.

PubMed

Amanullah; Iqbal, Asif; Irfanullah; Hidayat, Zeeshan

2016-10-03

Potassium (K) fertilizer management is beneficial for improving growth, yield and yield components of field crops under moisture stress condition in semiarid climates. Field experiments were conducted to study the response of maize (Zea mays L., cv. Azam) to foliar and soil applied K during summer 2013 and 2014. The experiments were carried out at the Agronomy Research Farm of The University of Agriculture Peshawar, Northwest Pakistan under limited irrigation (moisture stress) condition. It was concluded from the results that application of foliar K at the rate of 1-3% and foliar Zn at the rate of 0.1-0.2% was more beneficial in terms of better growth, higher yield and yield components of maize under moisture stress condition. Early spray (vegetative stage) resulted in better growth and higher yield than late spray (reproductive stage). Soil K treated plots (rest) plots performed better than control (K not applied) in terms of improved growth, higher yield and yield components of maize crop. The results further demonstrated that increasing the rate of soil applied K up to 90 kg P ha -1 in two equal splits (50% each at sowing and knee height) improve growth and maize productivity under semiarid climates.

Significance of direct and indirect impacts of climate change on groundwater resources in the Olifants River basin: A review

NASA Astrophysics Data System (ADS)

Nkhonjera, German K.; Dinka, Megersa O.

2017-11-01

This paper considers the extent and usefulness of reviewing existing literature on the significance of direct and indirect impacts of climate change on groundwater resources with emphasis on examples from the Olifants River basin. Here, the existing literature were extensively reviewed, with discussions centred mainly on the impacts of climate change on groundwater resources and challenges in modelling climate change impacts on groundwater resources. Since in the hydrological cycle, the hydrological components such as evaporation, temperature, precipitation, and groundwater, are the major drivers of the present and future climate, a detailed discussion is done on the impact of climate change on these hydrological components to determine to what extent the hydrological cycle has already been affected as a result of climate change. The uncertainties, constraints and limitations in climate change research have also been reviewed. In addition to the research gaps discussed here, the emphasis on the need of extensive climate change research on the continent, especially as climate change impacts on groundwater, is discussed. Overall, the importance of conducting further research in climate change, understanding the significance of the impact of climate change on water resources such as groundwater, and taking actions to effectively meet the adaptation needs of the people, emerge as an important theme in this review.

Coarse-grained component concurrency in Earth system modeling: parallelizing atmospheric radiative transfer in the GFDL AM3 model using the Flexible Modeling System coupling framework

NASA Astrophysics Data System (ADS)

Balaji, V.; Benson, Rusty; Wyman, Bruce; Held, Isaac

2016-10-01

Climate models represent a large variety of processes on a variety of timescales and space scales, a canonical example of multi-physics multi-scale modeling. Current hardware trends, such as Graphical Processing Units (GPUs) and Many Integrated Core (MIC) chips, are based on, at best, marginal increases in clock speed, coupled with vast increases in concurrency, particularly at the fine grain. Multi-physics codes face particular challenges in achieving fine-grained concurrency, as different physics and dynamics components have different computational profiles, and universal solutions are hard to come by. We propose here one approach for multi-physics codes. These codes are typically structured as components interacting via software frameworks. The component structure of a typical Earth system model consists of a hierarchical and recursive tree of components, each representing a different climate process or dynamical system. This recursive structure generally encompasses a modest level of concurrency at the highest level (e.g., atmosphere and ocean on different processor sets) with serial organization underneath. We propose to extend concurrency much further by running more and more lower- and higher-level components in parallel with each other. Each component can further be parallelized on the fine grain, potentially offering a major increase in the scalability of Earth system models. We present here first results from this approach, called coarse-grained component concurrency, or CCC. Within the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS), the atmospheric radiative transfer component has been configured to run in parallel with a composite component consisting of every other atmospheric component, including the atmospheric dynamics and all other atmospheric physics components. We will explore the algorithmic challenges involved in such an approach, and present results from such simulations. Plans to achieve even greater levels of coarse-grained concurrency by extending this approach within other components, such as the ocean, will be discussed.

Component-Based Modelling for Scalable Smart City Systems Interoperability: A Case Study on Integrating Energy Demand Response Systems.

PubMed

Palomar, Esther; Chen, Xiaohong; Liu, Zhiming; Maharjan, Sabita; Bowen, Jonathan

2016-10-28

Smart city systems embrace major challenges associated with climate change, energy efficiency, mobility and future services by embedding the virtual space into a complex cyber-physical system. Those systems are constantly evolving and scaling up, involving a wide range of integration among users, devices, utilities, public services and also policies. Modelling such complex dynamic systems' architectures has always been essential for the development and application of techniques/tools to support design and deployment of integration of new components, as well as for the analysis, verification, simulation and testing to ensure trustworthiness. This article reports on the definition and implementation of a scalable component-based architecture that supports a cooperative energy demand response (DR) system coordinating energy usage between neighbouring households. The proposed architecture, called refinement of Cyber-Physical Component Systems (rCPCS), which extends the refinement calculus for component and object system (rCOS) modelling method, is implemented using Eclipse Extensible Coordination Tools (ECT), i.e., Reo coordination language. With rCPCS implementation in Reo, we specify the communication, synchronisation and co-operation amongst the heterogeneous components of the system assuring, by design scalability and the interoperability, correctness of component cooperation.

Component-Based Modelling for Scalable Smart City Systems Interoperability: A Case Study on Integrating Energy Demand Response Systems

PubMed Central

Palomar, Esther; Chen, Xiaohong; Liu, Zhiming; Maharjan, Sabita; Bowen, Jonathan

2016-01-01

Smart city systems embrace major challenges associated with climate change, energy efficiency, mobility and future services by embedding the virtual space into a complex cyber-physical system. Those systems are constantly evolving and scaling up, involving a wide range of integration among users, devices, utilities, public services and also policies. Modelling such complex dynamic systems’ architectures has always been essential for the development and application of techniques/tools to support design and deployment of integration of new components, as well as for the analysis, verification, simulation and testing to ensure trustworthiness. This article reports on the definition and implementation of a scalable component-based architecture that supports a cooperative energy demand response (DR) system coordinating energy usage between neighbouring households. The proposed architecture, called refinement of Cyber-Physical Component Systems (rCPCS), which extends the refinement calculus for component and object system (rCOS) modelling method, is implemented using Eclipse Extensible Coordination Tools (ECT), i.e., Reo coordination language. With rCPCS implementation in Reo, we specify the communication, synchronisation and co-operation amongst the heterogeneous components of the system assuring, by design scalability and the interoperability, correctness of component cooperation. PMID:27801829

Potential relocation of climatic environments suggests high rates of climate displacement within the North American protection network

Treesearch

Enric Batllori; Marc-Andre Parisien; Sean A. Parks; Max A. Moritz; Carol Miller

2017-01-01

Ongoing climate change may undermine the effectiveness of protected area networks in preserving the set of biotic components and ecological processes they harbor, thereby jeopardizing their conservation capacity into the future. Metrics of climate change, particularly rates and spatial patterns of climatic alteration, can help assess potential threats. Here, we perform...

Response of Landscapes of the Sikhote-Alin Western Slopes to the Middle-Late Holocene Climatic Changes

NASA Astrophysics Data System (ADS)

Razzhigaeva, N. G.; Ganzey, L. A.; Panichev, A. M.; Grebennikova, T. A.; Mokhova, L. M.; Kopoteva, T. A.; Kudryavtseva, E. P.; Arslanov, Kh. A.; Maksimov, F. E.; Starikova, A. A.; Zakusin, S. V.

2017-12-01

The response of landscape biotic components of the western slope of the Sikhote-Alin Mountains (Bikin River middle flow) to the Middle-Late Holocene climate changes is discussed. The paleoreconstruction object was the Krasny Yar mari, which developed under the control of multidirectional short-term climatic changes. The last millennium was marked by particularly rapid and frequent changes in the local landscapes. The closely spaced orographic barrier strongly affected the development of biotic components and changes in the swamp hydrological regime. The moisture dynamics within the river catchment considerably controlled the development and change of the peat-forming plants. Several stages of the mari development were reconstructed; each began from the accumulation of eutrophic peat. It was followed by the transitional eutrophic-mesotrophic stage, with a higher role of atmospheric supply. The larch forests appeared in this part of the valley within the Atlantic-Subboreal cooling period. Korean pine developed in the forest vegetation in the low mountain relief at the beginning of the Subboreal and became one of the leading trees 2.6-2.3 ka BP. The lower role of the Korean pine and birch forest expansion in the first half of the Subatlantic could be related to the fires. The broadleaf-Korean pine forests became widespread in the Medieval Warm Period. Local swamp landscapes changed dramatically in the Little Ice Age, while the slope vegetation was not subject to any major changes. The landscapes were also affected by the fires, which became more frequent. The derivative communities with birch appeared on the mari. Moreover, this part of the valley was occasionally subject to heavy flooding.

A Study on Components of Internal Control-Based Administrative System in Secondary Schools

ERIC Educational Resources Information Center

Montri, Paitoon; Sirisuth, Chaiyuth; Lammana, Preeda

2015-01-01

The aim of this study was to study the components of the internal control-based administrative system in secondary schools, and make a Confirmatory Factor Analysis (CFA) to confirm the goodness of fit of empirical data and component model that resulted from the CFA. The study consisted of three steps: 1) studying of principles, ideas, and theories…

Quantifying climatic controls on river network topology across scales

NASA Astrophysics Data System (ADS)

Ranjbar Moshfeghi, S.; Hooshyar, M.; Wang, D.; Singh, A.

2017-12-01

Branching structure of river networks is an important topologic and geomorphologic feature that depends on several factors (e.g. climate, tectonic). However, mechanisms that cause these drainage patterns in river networks are poorly understood. In this study, we investigate the effects of varying climatic forcing on river network topology and geomorphology. For this, we select 20 catchments across the United States with different long-term climatic conditions quantified by climate aridity index (AI), defined here as the ratio of mean annual potential evaporation (Ep) to precipitation (P), capturing variation in runoff and vegetation cover. The river networks of these catchments are extracted, using a curvature-based method, from high-resolution (1 m) digital elevation models and several metrics such as drainage density, branching angle, and width functions are computed. We also use a multiscale-entropy-based approach to quantify the topologic irregularity and structural richness of these river networks. Our results reveal systematic impacts of climate forcing on the structure of river networks.

Transient simulations of historical climate change including interactive carbon emissions from land-use change.

NASA Astrophysics Data System (ADS)

Matveev, A.; Matthews, H. D.

2009-04-01

Carbon fluxes from land conversion are among the most uncertain variables in our understanding of the contemporary carbon cycle, which limits our ability to estimate both the total human contribution to current climate forcing and the net effect of terrestrial biosphere changes on atmospheric CO2 increases. The current generation of coupled climate-carbon models have made significant progress in simulating the coupled climate and carbon cycle response to anthropogenic CO2 emissions, but do not typically include land-use change as a dynamic component of the simulation. In this work we have incorporated a book-keeping land-use carbon accounting model into the University of Victoria Earth System Climate Model (UVic ESCM), and intermediate-complexity coupled climate-carbon model. The terrestrial component of the UVic ESCM allows an aerial competition of five plant functional types (PFTs) in response to climatic conditions and area availability, and tracks the associated changes in affected carbon pools. In order to model CO2 emissions from land conversion in the terrestrial component of the model, we calculate the allocation of carbon to short and long-lived wood products following specified land-cover change, and use varying decay timescales to estimate CO2 emissions. We use recently available spatial datasets of both crop and pasture distributions to drive a series of transient simulations and estimate the net contribution of human land-use change to historical carbon emissions and climate change.

Investigating Mars South Residual CO2 Cap with a Global Climate Model

NASA Technical Reports Server (NTRS)

Kahre, M. A.; Dequaire, J.; Hollingsworth, J. L.; Haberle, R. M.

2016-01-01

The CO2 cycle is one of the three controlling climate cycles on Mars. One aspect of the CO2 cycle that is not yet fully understood is the existence of a residual CO2 ice cap that is offset from the south pole. Previous investigations suggest that the atmosphere may control the placement of the south residual cap (e.g., Colaprete et al., 2005). These investigations show that topographically forced stationary eddies in the south during southern hemisphere winter produce colder atmospheric temperatures and increased CO2 snowfall over the hemisphere where the residual cap resides. Since precipitated CO2 ice produces higher surface albedos than directly deposited CO2 ice, it is plausible that CO2 snowfall resulting from the zonally asymmetric atmospheric circulation produces surface ice albedos high enough to maintain a residual cap only in one hemisphere. The goal of the current work is to further evaluate Colaprete et al.'s hypothesis by investigating model-predicted seasonally varying snowfall patterns in the southern polar region and the atmospheric circulation components that control them.

14 CFR 35.42 - Components of the propeller control system.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 14 Aeronautics and Space 1 2010-01-01 2010-01-01 false Components of the propeller control system... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: PROPELLERS Tests and Inspections § 35.42 Components of the propeller control system. The applicant must demonstrate by tests, analysis based on tests, or service...

14 CFR 35.42 - Components of the propeller control system.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 14 Aeronautics and Space 1 2011-01-01 2011-01-01 false Components of the propeller control system... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: PROPELLERS Tests and Inspections § 35.42 Components of the propeller control system. The applicant must demonstrate by tests, analysis based on tests, or service...

14 CFR 35.42 - Components of the propeller control system.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 14 Aeronautics and Space 1 2013-01-01 2013-01-01 false Components of the propeller control system... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: PROPELLERS Tests and Inspections § 35.42 Components of the propeller control system. The applicant must demonstrate by tests, analysis based on tests, or service...

14 CFR 35.42 - Components of the propeller control system.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 14 Aeronautics and Space 1 2012-01-01 2012-01-01 false Components of the propeller control system... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: PROPELLERS Tests and Inspections § 35.42 Components of the propeller control system. The applicant must demonstrate by tests, analysis based on tests, or service...

14 CFR 35.42 - Components of the propeller control system.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 14 Aeronautics and Space 1 2014-01-01 2014-01-01 false Components of the propeller control system... TRANSPORTATION AIRCRAFT AIRWORTHINESS STANDARDS: PROPELLERS Tests and Inspections § 35.42 Components of the propeller control system. The applicant must demonstrate by tests, analysis based on tests, or service...

Staying silent about safety issues: Conceptualizing and measuring safety silence motives.

PubMed

Manapragada, Archana; Bruk-Lee, Valentina

2016-06-01

Communication between employees and supervisors about safety-related issues is an important component of a safe workplace. When supervisors receive information from employees about safety issues, they may gain otherwise-missed opportunities to correct these issues and/or prevent negative safety outcomes. A series of three studies were conducted to identify various safety silence motives, which describe the reasons that employees do not speak up to supervisors about safety-related issues witnessed in the workplace, and to develop a tool to assess these motives. Results suggest that employees stay silent about safety issues based on perceptions of altering relationships with others (relationship-based), perceptions of the organizational climate (climate-based), the assessment of the safety issue (issue-based), or characteristics of the job (job-based). We developed a 17-item measure to assess these four motives, and initial evidence was found for the construct and incremental validity of the safety silence motives measure in a sample of nurses. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessment of future impacts of potential climate change scenarios on aquifer recharge in continental Spain

NASA Astrophysics Data System (ADS)

Pulido-Velazquez, David; Collados-Lara, Antonio-Juan; Alcalá, Francisco J.

2017-04-01

This research proposes and applies a method to assess potential impacts of future climatic scenarios on aquifer rainfall recharge in wide and varied regions. The continental Spain territory was selected to show the application. The method requires to generate future series of climatic variables (precipitation, temperature) in the system to simulate them within a previously calibrated hydrological model for the historical data. In a previous work, Alcalá and Custodio (2014) used the atmospheric chloride mass balance (CMB) method for the spatial evaluation of average aquifer recharge by rainfall over the whole of continental Spain, by assuming long-term steady conditions of the balance variables. The distributed average CMB variables necessary to calculate recharge were estimated from available variable-length data series of variable quality and spatial coverage. The CMB variables were regionalized by ordinary kriging at the same 4976 nodes of a 10 km x 10 km grid. Two main sources of uncertainty affecting recharge estimates (given by the coefficient of variation, CV), induced by the inherent natural variability of the variables and from mapping were segregated. Based on these stationary results we define a simple empirical rainfall-recharge model. We consider that spatiotemporal variability of rainfall and temperature are the most important climatic feature and variables influencing potential aquifer recharge in natural regime. Changes in these variables can be important in the assessment of future potential impacts of climatic scenarios over spatiotemporal renewable groundwater resource. For instance, if temperature increases, actual evapotranspitration (EA) will increases reducing the available water for others groundwater balance components, including the recharge. For this reason, instead of defining an infiltration rate coefficient that relates precipitation (P) and recharge we propose to define a transformation function that allows estimating the spatial distribution of recharge (both average value and its uncertainty) from the difference in P and EA in each area. A complete analysis of potential short-term (2016-2045) future climate scenarios in continental Spain has been performed by considering different sources of uncertainty. It is based on the historical climatic data for the period 1976-2005 and the climatic models simulations (for the control [1976-2005] and future scenarios [2016-2045]) performed in the frame of the CORDEX EU project. The most pessimistic emission scenario (RCP8.5) has been considered. For the RCP8.5 scenario we have analyzed the time series generated by simulating with 5 Regional Climatic models (CCLM4-8-17, RCA4, HIRHAM5, RACMO22E, and WRF331F) nested to 4 different General Circulation Models (GCMs). Two different conceptual approaches (bias correction and delta change techniques) have been applied to generate potential future climate scenarios from these data. Different ensembles of obtained time series have been proposed to obtain more representative scenarios by considering all the simulations or only those providing better approximations to the historical statistics based on a multicriteria analysis. This was a step to analyze future potential impacts on the aquifer recharge by simulating them within a rainfall-recharge model. This research has been supported by the CGL2013-48424-C2-2-R (MINECO) and the PMAFI/06/14 (UCAM) projects.

Climate and the Carbon Cycle

NASA Astrophysics Data System (ADS)

Manley, Jim

2017-04-01

Climate and the Carbon Cycle EOS3a Science in tomorrow's classroom Students, like too much of the American public, are largely unaware or apathetic to the changes in world climate and the impact that these changes have for life on Earth. A study conducted by Michigan State University and published in 2011 by Science Daily titled 'What carbon cycle? College students lack scientific literacy, study finds'. This study relates how 'most college students in the United States do not grasp the scientific basis of the carbon cycle - an essential skill in understanding the causes and consequences of climate change.' The study authors call for a new approach to teaching about climate. What if teachers better understood vital components of Earth's climate system and were able to impart his understanding to their students? What if students based their responses to the information taught not on emotion, but on a deeper understanding of the forces driving climate change, their analysis of the scientific evidence and in the context of earth system science? As a Middle School science teacher, I have been given the opportunity to use a new curriculum within TERC's EarthLabs collection, Climate and the Carbon Cycle, to awaken those brains and assist my students in making personal lifestyle choices based on what they had learned. In addition, with support from TERC and The University of Texas Institute for Geophysics I joined others to begin training other teachers on how to implement this curriculum in their classrooms to expose their students to our changing climate. Through my poster, I will give you (1) a glimpse into the challenges faced by today's science teachers in communicating the complicated, but ever-deepening understanding of the linkages between natural and human-driven factors on climate; (2) introduce you to a new module in the EarthLabs curriculum designed to expose teachers and students to global scientific climate data and instrumentation; and (3) illustrate how student worldviews are changed though exposure to the latest in scientific discovery and understanding.

Integrated model-experimental framework to assess carbon cycle components in disturbed mountainous terrain

NASA Astrophysics Data System (ADS)

Stenzel, J.; Hudiburg, T. W.; Berardi, D.; McNellis, B.; Walsh, E.

2017-12-01

In forests vulnerable to drought and fire, there is critical need for in situ carbon and water balance measurements that can be integrated with earth system modeling to predict climate feedbacks. Model development can be improved by measurements that inform a mechanistic understanding of the component fluxes of net carbon uptake (i.e., NPP, autotrophic and heterotrophic respiration) and water use, with specific focus on responses to climate and disturbance. By integrating novel field-based instrumental technology, existing datasets, and state-of-the-art earth system modeling, we are attempting to 1) quantify the spatial and temporal impacts of forest thinning on regional biogeochemical cycling and climate 2) evaluate the impact of forest thinning on forest resilience to drought and disturbance in the Northern Rockies ecoregion. The combined model-experimental framework enables hypothesis testing that would otherwise be impossible because the use of new in situ high temporal resolution field technology allows for research in remote and mountainous terrains that have been excluded from eddy-covariance techniques. Our preliminary work has revealed some underlying difficulties with the new instrumentation that has led to new ideas and modified methods to correctly measure the component fluxes. Our observations of C balance following the thinning operations indicate that the recovery period (source to sink) is longer than hypothesized. Finally, we have incorporated a new plant functional type parameterization for Northern Rocky mixed-conifer into our simulation modeling using regional and site observations.

Multi-decadal Hydrological Retrospective: Case study of Amazon floods and droughts

NASA Astrophysics Data System (ADS)

Wongchuig Correa, Sly; Paiva, Rodrigo Cauduro Dias de; Espinoza, Jhan Carlo; Collischonn, Walter

2017-06-01

Recently developed methodologies such as climate reanalysis make it possible to create a historical record of climate systems. This paper proposes a methodology called Hydrological Retrospective (HR), which essentially simulates large rainfall datasets, using this as input into hydrological models to develop a record of past hydrology, making it possible to analyze past floods and droughts. We developed a methodology for the Amazon basin, where studies have shown an increase in the intensity and frequency of hydrological extreme events in recent decades. We used eight large precipitation datasets (more than 30 years) as input for a large scale hydrological and hydrodynamic model (MGB-IPH). HR products were then validated against several in situ discharge gauges controlling the main Amazon sub-basins, focusing on maximum and minimum events. For the most accurate HR, based on performance metrics, we performed a forecast skill of HR to detect floods and droughts, comparing the results with in-situ observations. A statistical temporal series trend was performed for intensity of seasonal floods and droughts in the entire Amazon basin. Results indicate that HR could represent most past extreme events well, compared with in-situ observed data, and was consistent with many events reported in literature. Because of their flow duration, some minor regional events were not reported in literature but were captured by HR. To represent past regional hydrology and seasonal hydrological extreme events, we believe it is feasible to use some large precipitation datasets such as i) climate reanalysis, which is mainly based on a land surface component, and ii) datasets based on merged products. A significant upward trend in intensity was seen in maximum annual discharge (related to floods) in western and northwestern regions and for minimum annual discharge (related to droughts) in south and central-south regions of the Amazon basin. Because of the global coverage of rainfall datasets, this methodology can be transferred to other regions for better estimation of future hydrological behavior and its impact on society.

Supervisors matter more than you think: components of a mission-centered organizational climate.

PubMed

Butcher, A H

1994-01-01

A study was conducted in a medical center among a diverse sample of employees to examine whether components of organizational climate related to workers' knowledge of the organization's mission and mission-centered values. Findings supported a mediated relationship between supervisor behaviors, mission knowledge, and customer service orientation (the organization's key mission value). Employee perceptions of coworker and organizational support and knowledge of their own performance expectations also related positively to customer service orientation. Results suggest that supervisors are in an ideal position to disseminate a mission-centered climate. Practical applications of these findings for management wishing to develop mission-centered climates in health care organizations are discussed.

The U.S. Geological Survey Monthly Water Balance Model Futures Portal

USGS Publications Warehouse

Bock, Andy

2017-03-16

Simulations of future climate suggest profiles of temperature and precipitation may differ significantly from those in the past. These changes in climate will likely lead to changes in the hydrologic cycle. As such, natural resource managers are in need of tools that can provide estimates of key components of the hydrologic cycle, uncertainty associated with the estimates, and limitations associated with the climate forcing data used to estimate these components. To help address this need, the U.S. Geological Survey Monthly Water Balance Model Futures Portal (https://my.usgs.gov/mows/) provides a user friendly interface to deliver hydrologic and meteorological variables for monthly historic and potential future climatic conditions across the continental United States.

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

Earth Science Week 2009, "Understanding Climate", Highlights and News Clippings

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

Robeck, Edward C.

2010-01-05

The American Geological Institute (AGI) proposes to expand its influential Earth Science Week Program in 2009, with the support of the U.S. Department of Energy, to disseminate DOE's key messages, information, and resources on climate education and to include new program components. These components, ranging from online resources to live events and professional networks, would significantly increase the reach and impact of AGI's already successful geoscience education and public awareness effort in the United States and abroad in 2009, when the campaign's theme will be "Understanding Climate."

Highway pavement performance test for colored thin anti-skidding layers

NASA Astrophysics Data System (ADS)

Gao, Wei; Cui, Wei; Xu, Ming

2018-03-01

Based on the actual service condition of highway pavement colored thin anti-skidding layers, with materials of color quartz sand and two-component acrylic resin as basis, we designed such tests as the bond strength, shearing strength, tear strength, fatigue performance and aggregate polished value, and included the freeze-thaw cycle and de-icing salt and other factors in the experiment, connecting with the climate characteristics of circumpolar latitude and low altitude in Heilongjiang province. Through the pavement performance test, it is confirmed that the colored thin anti-skidding layers can adapt to cold and humid climate conditions, and its physical mechanical properties are good.

The Community Cloud retrieval for CLimate (CC4CL) - Part 2: The optimal estimation approach

NASA Astrophysics Data System (ADS)

McGarragh, Gregory R.; Poulsen, Caroline A.; Thomas, Gareth E.; Povey, Adam C.; Sus, Oliver; Stapelberg, Stefan; Schlundt, Cornelia; Proud, Simon; Christensen, Matthew W.; Stengel, Martin; Hollmann, Rainer; Grainger, Roy G.

2018-06-01

The Community Cloud retrieval for Climate (CC4CL) is a cloud property retrieval system for satellite-based multispectral imagers and is an important component of the Cloud Climate Change Initiative (Cloud_cci) project. In this paper we discuss the optimal estimation retrieval of cloud optical thickness, effective radius and cloud top pressure based on the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm. Key to this method is the forward model, which includes the clear-sky model, the liquid water and ice cloud models, the surface model including a bidirectional reflectance distribution function (BRDF), and the "fast" radiative transfer solution (which includes a multiple scattering treatment). All of these components and their assumptions and limitations will be discussed in detail. The forward model provides the accuracy appropriate for our retrieval method. The errors are comparable to the instrument noise for cloud optical thicknesses greater than 10. At optical thicknesses less than 10 modeling errors become more significant. The retrieval method is then presented describing optimal estimation in general, the nonlinear inversion method employed, measurement and a priori inputs, the propagation of input uncertainties and the calculation of subsidiary quantities that are derived from the retrieval results. An evaluation of the retrieval was performed using measurements simulated with noise levels appropriate for the MODIS instrument. Results show errors less than 10 % for cloud optical thicknesses greater than 10. Results for clouds of optical thicknesses less than 10 have errors up to 20 %.

Ocean angular momentum signals in a climate model and implications for Earth rotation

NASA Astrophysics Data System (ADS)

Ponte, R. M.; Rajamony, J.; Gregory, J. M.

2002-03-01

Estimates of ocean angular momentum (OAM) provide an integrated measure of variability in ocean circulation and mass fields and can be directly related to observed changes in Earth rotation. We use output from a climate model to calculate 240 years of 3-monthly OAM values (two equatorial terms L1 and L2, related to polar motion or wobble, and axial term L3, related to length of day variations) representing the period 1860-2100. Control and forced runs permit the study of the effects of natural and anthropogenically forced climate variability on OAM. All OAM components exhibit a clear annual cycle, with large decadal modulations in amplitude, and also longer period fluctuations, all associated with natural climate variability in the model. Anthropogenically induced signals, inferred from the differences between forced and control runs, include an upward trend in L3, related to inhomogeneous ocean warming and increases in the transport of the Antarctic Circumpolar Current, and a significantly weaker seasonal cycle in L2 in the second half of the record, related primarily to changes in seasonal bottom pressure variability in the Southern Ocean and North Pacific. Variability in mass fields is in general more important to OAM signals than changes in circulation at the seasonal and longer periods analyzed. Relation of OAM signals to changes in surface atmospheric forcing are discussed. The important role of the oceans as an excitation source for the annual, Chandler and Markowitz wobbles, is confirmed. Natural climate variability in OAM and related excitation is likely to measurably affect the Earth rotation, but anthropogenically induced effects are comparatively weak.

Topography: dusting for the fingerprints of mantle dynamics

NASA Astrophysics Data System (ADS)

Faccenna, C.; Becker, T. W.

2016-12-01

The surface of the Earth is an ever-changing expression of the dynamic processes occurring deep in the mantle and at and above its surface, but our ability to "read" landscapes in terms of their underlying tectonic or climatic forcing is rudimentary. During the last decade, particular attention has been drawn to the deep, convection-related component of topography, induced by the stress produced at the base of the lithosphere by mantle flow, and its relevance compared to the (iso)static component. Despite much progress, several issues, including the magnitude and rate of this dynamic component, remain open. Here, we use key sites from convergent margins (e.g., the Apennines) and from intraplate settings (e.g., Ethiopia) to estimate the amplitude and rate of topography change and to disentangle the dynamic from the static component. On the base of those and other examples, we introduce the concept of a Topographic Fingerprint: any combination of mantle, crustal and surface processes that will result in a distinctive, thus predictable, topographic expression.

Educational process in modern climatology within the web-GIS platform "Climate"

NASA Astrophysics Data System (ADS)

Gordova, Yulia; Gorbatenko, Valentina; Gordov, Evgeny; Martynova, Yulia; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2013-04-01

These days, common to all scientific fields the problem of training of scientists in the environmental sciences is exacerbated by the need to develop new computational and information technology skills in distributed multi-disciplinary teams. To address this and other pressing problems of Earth system sciences, software infrastructure for information support of integrated research in the geosciences was created based on modern information and computational technologies and a software and hardware platform "Climate» (http://climate.scert.ru/) was developed. In addition to the direct analysis of geophysical data archives, the platform is aimed at teaching the basics of the study of changes in regional climate. The educational component of the platform includes a series of lectures on climate, environmental and meteorological modeling and laboratory work cycles on the basics of analysis of current and potential future regional climate change using Siberia territory as an example. The educational process within the Platform is implemented using the distance learning system Moodle (www.moodle.org). This work is partially supported by the Ministry of education and science of the Russian Federation (contract #8345), SB RAS project VIII.80.2.1, RFBR grant #11-05-01190a, and integrated project SB RAS #131.

Elementary Student Perceptions of School Climate and Associations with Individual and School Factors

ERIC Educational Resources Information Center

La Salle, Tamika P.; Zabek, Faith; Meyers, Joel

2016-01-01

School climate has increasingly been recognized as an essential component of school improvement owing to the established associations between a positive school climate and academic outcomes for students. Our study examines associations among a brief measure of school climate assessing elementary student perceptions and the College and Career Ready…

Undergraduate Climate Education: Motivations, Strategies, Successes, and Support

ERIC Educational Resources Information Center

Kirk, Karin B.; Gold, Anne U.; Ledley, Tamara Shapiro; Sullivan, Susan Buhr; Manduca, Cathryn A.; Mogk, David W.; Wiese, Katryn

2014-01-01

Climate literacy is an essential component of a strategy to comprehend and confront the grand challenge of global climate change. However, scientific complexity, societal implications, and political associations make climate change a difficult but important topic to teach. In this paper we report on the results of a survey of undergraduate faculty…

A Computing Infrastructure for Supporting Climate Studies

NASA Astrophysics Data System (ADS)

Yang, C.; Bambacus, M.; Freeman, S. M.; Huang, Q.; Li, J.; Sun, M.; Xu, C.; Wojcik, G. S.; Cahalan, R. F.; NASA Climate @ Home Project Team

2011-12-01

Climate change is one of the major challenges facing us on the Earth planet in the 21st century. Scientists build many models to simulate the past and predict the climate change for the next decades or century. Most of the models are at a low resolution with some targeting high resolution in linkage to practical climate change preparedness. To calibrate and validate the models, millions of model runs are needed to find the best simulation and configuration. This paper introduces the NASA effort on Climate@Home project to build a supercomputer based-on advanced computing technologies, such as cloud computing, grid computing, and others. Climate@Home computing infrastructure includes several aspects: 1) a cloud computing platform is utilized to manage the potential spike access to the centralized components, such as grid computing server for dispatching and collecting models runs results; 2) a grid computing engine is developed based on MapReduce to dispatch models, model configuration, and collect simulation results and contributing statistics; 3) a portal serves as the entry point for the project to provide the management, sharing, and data exploration for end users; 4) scientists can access customized tools to configure model runs and visualize model results; 5) the public can access twitter and facebook to get the latest about the project. This paper will introduce the latest progress of the project and demonstrate the operational system during the AGU fall meeting. It will also discuss how this technology can become a trailblazer for other climate studies and relevant sciences. It will share how the challenges in computation and software integration were solved.

The CLIMATE schools combined study: a cluster randomised controlled trial of a universal Internet-based prevention program for youth substance misuse, depression and anxiety.

PubMed

Teesson, Maree; Newton, Nicola C; Slade, Tim; Chapman, Cath; Allsop, Steve; Hides, Leanne; McBride, Nyanda; Mewton, Louise; Tonks, Zoe; Birrell, Louise; Brownhill, Louise; Andrews, Gavin

2014-02-05

Anxiety, depressive and substance use disorders account for three quarters of the disability attributed to mental disorders and frequently co-occur. While programs for the prevention and reduction of symptoms associated with (i) substance use and (ii) mental health disorders exist, research is yet to determine if a combined approach is more effective. This paper describes the study protocol of a cluster randomised controlled trial to evaluate the effectiveness of the CLIMATE Schools Combined intervention, a universal approach to preventing substance use and mental health problems among adolescents. Participants will consist of approximately 8400 students aged 13 to 14-years-old from 84 secondary schools in New South Wales, Western Australia and Queensland, Australia. The schools will be cluster randomised to one of four groups; (i) CLIMATE Schools Combined intervention; (ii) CLIMATE Schools - Substance Use; (iii) CLIMATE Schools - Mental Health, or (iv) Control (Health and Physical Education as usual). The primary outcomes of the trial will be the uptake and harmful use of alcohol and other drugs, mental health symptomatology and anxiety, depression and substance use knowledge. Secondary outcomes include substance use related harms, self-efficacy to resist peer pressure, general disability, and truancy. The link between personality and substance use will also be examined. Compared to students who receive the universal CLIMATE Schools - Substance Use, or CLIMATE Schools - Mental Health or the Control condition (who received usual Health and Physical Education), we expect students who receive the CLIMATE Schools Combined intervention to show greater delays to the initiation of substance use, reductions in substance use and mental health symptoms, and increased substance use and mental health knowledge. This trial is registered with the Australian and New Zealand Clinical Trials registry, ACTRN12613000723785.

Argumentation Key to Communicating Climate Change to the Public

NASA Astrophysics Data System (ADS)

Bleicher, R. E.; Lambert, J. L.

2012-12-01

Argumentation plays an important role in how we communicate climate change science to the public and is a key component integrated throughout the Next Generation Science Standards. A scientific argument can be described as a disagreement between explanations with data being used to justify each position. Argumentation is social process where two or more individuals construct and critique arguments (Kuhn & Udell, 2003; Nussbaum, 1997). Sampson, Grooms, and Walker's (2011) developed a framework for understanding the components of a scientific argument. The three components start with a claim (a conjecture, conclusion, explanation, or an answer to a research question). This claim must fit the evidence (observations that show trends over time, relationships between variables or difference between groups). The evidence must be justified with reasoning (explains how the evidence supports the explanation and whey it should count as support). In a scientific argument, or debate, the controversy focuses on how data were collected, what data can or should be included, and what inferences can be made based on a set of evidence. Toulmin's model (1969) also includes rebutting or presenting an alternative explanation supported by counter evidence and reasoning of why the alternative is not the appropriate explanation for the question of the problem. The process of scientific argumentation should involve the construction and critique of scientific arguments, one that involves the consideration of alternative hypotheses (Lawson, 2003). Scientific literacy depends as much on the ability to refute and recognize poor scientific arguments as much as it does on the ability to present an effective argument based on good scientific data (Osborne, 2010). Argument is, therefore, a core feature of science. When students learn to construct a sound scientific argument, they demonstrate critical thinking and a mastery of the science being taught. To present a convincing argument in support of climate change, students must have a sound foundation in the science underlying it. One place to lay this foundation is in the high school science classroom. For students to gain a good conceptual understanding of climate change science, teachers need a sound understanding of climate change and effective resources to teach it to students. Teacher professional development opportunities are required to provide this background as well as establish collaborative curriculum planning opportunities on the school site (Shulman, 2007). Various strategies for and challenges of implementing argumentation with preservice and practicing teachers will be discussed in this session, as well as ways that argumentation skills can help the broader public evaluate claims of climate skeptics. In the field of argumentation theory, Goodwin (2010) has designed a strategy for developing the ability to make effective scientific arguments. The goal is to establish trust even when there is strong disagreement. At the core, a student fully acknowledges the uncertainty involved in the complex science underlying climate change. This has the effect of establishing some degree of trust. In other words, teachers or students trying to explain climate change to others might be perceived as more trustworthy if they openly declare that there are degrees of uncertainty in different aspects of climate change science (American Meteorological Society, 2011).

Use of COTS in the Multimission Advanced Ground Intelligent Control (MAGIC) program

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

Crowley, N.L.

1997-11-01

This tutorial will discuss the experiences of the Space System Technologies Division of the USAF Phillips Laboratory (PL/VTS) in developing a COTS-based satellite control system. The system`s primary use is a testbed for new technologies that are intended for future integration into the operational satellite control system. As such, the control system architecture must be extremely open and flexible so we can integrate new components and functions easily and also provide our system to contractors for their component work. The system is based on commercial hardware, is based on Windows NT, and makes the maximum use of COTS components andmore » industry standards.« less

Evaluation of statistically downscaled GCM output as input for hydrological and stream temperature simulation in the Apalachicola–Chattahoochee–Flint River Basin (1961–99)

USGS Publications Warehouse

Hay, Lauren E.; LaFontaine, Jacob H.; Markstrom, Steven

2014-01-01

The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks.The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output.Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

DOE PAGES

O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.; ...

2016-09-28

Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. Here, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide rangemore » of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. Furthermore, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2°C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. In order to serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.« less

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

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

O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.

2016-01-01

Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate amore » wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.« less

The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

NASA Astrophysics Data System (ADS)

O'Neill, Brian C.; Tebaldi, Claudia; van Vuuren, Detlef P.; Eyring, Veronika; Friedlingstein, Pierre; Hurtt, George; Knutti, Reto; Kriegler, Elmar; Lamarque, Jean-Francois; Lowe, Jason; Meehl, Gerald A.; Moss, Richard; Riahi, Keywan; Sanderson, Benjamin M.

2016-09-01

Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017-2018 time frame, and output from the climate model projections made available and analyses performed over the 2018-2020 period.

Understanding Climate Uncertainty with an Ocean Focus

NASA Astrophysics Data System (ADS)

Tokmakian, R. T.

2009-12-01

Uncertainty in climate simulations arises from various aspects of the end-to-end process of modeling the Earth’s climate. First, there is uncertainty from the structure of the climate model components (e.g. ocean/ice/atmosphere). Even the most complex models are deficient, not only in the complexity of the processes they represent, but in which processes are included in a particular model. Next, uncertainties arise from the inherent error in the initial and boundary conditions of a simulation. Initial conditions are the state of the weather or climate at the beginning of the simulation and other such things, and typically come from observations. Finally, there is the uncertainty associated with the values of parameters in the model. These parameters may represent physical constants or effects, such as ocean mixing, or non-physical aspects of modeling and computation. The uncertainty in these input parameters propagates through the non-linear model to give uncertainty in the outputs. The models in 2020 will no doubt be better than today’s models, but they will still be imperfect, and development of uncertainty analysis technology is a critical aspect of understanding model realism and prediction capability. Smith [2002] and Cox and Stephenson [2007] discuss the need for methods to quantify the uncertainties within complicated systems so that limitations or weaknesses of the climate model can be understood. In making climate predictions, we need to have available both the most reliable model or simulation and a methods to quantify the reliability of a simulation. If quantitative uncertainty questions of the internal model dynamics are to be answered with complex simulations such as AOGCMs, then the only known path forward is based on model ensembles that characterize behavior with alternative parameter settings [e.g. Rougier, 2007]. The relevance and feasibility of using "Statistical Analysis of Computer Code Output" (SACCO) methods for examining uncertainty in ocean circulation due to parameter specification will be described and early results using the ocean/ice components of the CCSM climate model in a designed experiment framework will be shown. Cox, P. and D. Stephenson, Climate Change: A Changing Climate for Prediction, 2007, Science 317 (5835), 207, DOI: 10.1126/science.1145956. Rougier, J. C., 2007: Probabilistic Inference for Future Climate Using an Ensemble of Climate Model Evaluations, Climatic Change, 81, 247-264. Smith L., 2002, What might we learn from climate forecasts? Proc. Nat’l Academy of Sciences, Vol. 99, suppl. 1, 2487-2492 doi:10.1073/pnas.012580599.

Hydrologic response to multimodel climate output using a physically based model of groundwater/surface water interactions

NASA Astrophysics Data System (ADS)

Sulis, M.; Paniconi, C.; Marrocu, M.; Huard, D.; Chaumont, D.

2012-12-01

General circulation models (GCMs) are the primary instruments for obtaining projections of future global climate change. Outputs from GCMs, aided by dynamical and/or statistical downscaling techniques, have long been used to simulate changes in regional climate systems over wide spatiotemporal scales. Numerous studies have acknowledged the disagreements between the various GCMs and between the different downscaling methods designed to compensate for the mismatch between climate model output and the spatial scale at which hydrological models are applied. Very little is known, however, about the importance of these differences once they have been input or assimilated by a nonlinear hydrological model. This issue is investigated here at the catchment scale using a process-based model of integrated surface and subsurface hydrologic response driven by outputs from 12 members of a multimodel climate ensemble. The data set consists of daily values of precipitation and min/max temperatures obtained by combining four regional climate models and five GCMs. The regional scenarios were downscaled using a quantile scaling bias-correction technique. The hydrologic response was simulated for the 690 km2des Anglais catchment in southwestern Quebec, Canada. The results show that different hydrological components (river discharge, aquifer recharge, and soil moisture storage) respond differently to precipitation and temperature anomalies in the multimodel climate output, with greater variability for annual discharge compared to recharge and soil moisture storage. We also find that runoff generation and extreme event-driven peak hydrograph flows are highly sensitive to any uncertainty in climate data. Finally, the results show the significant impact of changing sequences of rainy days on groundwater recharge fluxes and the influence of longer dry spells in modifying soil moisture spatial variability.

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis

NASA Astrophysics Data System (ADS)

Ahmadalipour, Ali; Rana, Arun; Moradkhani, Hamid; Sharma, Ashish

2017-04-01

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.

Analysis of utilization of desert habitats with dynamic simulation

USGS Publications Warehouse

Williams, B.K.

1986-01-01

The effects of climate and herbivores on cool desert shrubs in north-western Utah were investigated with a dynamic simulation model. Cool desert shrublands are extensively managed as grazing lands, and are defoliated annually by domestic livestock. A primary production model was used to simulate harvest yields and shrub responses under a variety of climatic regimes and defoliation patterns. The model consists of six plant components, and it is based on equations of growth analysis. Plant responses were simulated under various combinations of 20 annual weather patterns and 14 defoliation strategies. Results of the simulations exhibit some unexpected linearities in model behavior, and emphasize the importance of both the pattern of climate and the level of plant vigor in determining optimal harvest strategies. Model behaviors are interpreted in terms of shrub morphology, physiology and ecology.

Effects of changes along the risk chain on flood risk

NASA Astrophysics Data System (ADS)

Duha Metin, Ayse; Apel, Heiko; Viet Dung, Nguyen; Guse, Björn; Kreibich, Heidi; Schröter, Kai; Vorogushyn, Sergiy; Merz, Bruno

2017-04-01

Interactions of hydrological and socio-economic factors shape flood disaster risk. For this reason, assessment of flood risk ideally takes into account the whole flood risk chain from atmospheric processes, through the catchment and river system processes to the damage mechanisms in the affected areas. Since very different processes at various scales are interacting along the flood risk, the impact of the single components is rather unclear. However for flood risk management, it is required to know the controlling factor of flood damages. The present study, using the flood-prone Mulde catchment in Germany, discusses the sensitivity of flood risk to disturbances along the risk chain: How do disturbances propagate through the risk chain? How do different disturbances combine or conflict and affect flood risk? In this sensitivity analysis, the five components of the flood risk change are included. These are climate, catchment, river system, exposure and vulnerability. A model framework representing the complete risk chain is combined with observational data to understand how the sensitivities evolve along the risk chain by considering three plausible change scenarios for each of five components. The flood risk is calculated by using the Regional Flood Model (RFM) which is based on a continuous simulation approach, including rainfall-runoff, 1D river network, 2D hinterland inundation and damage estimation models. The sensitivity analysis covers more than 240 scenarios with different combinations of the five components. It is investigated how changes in different components affect risk indicators, such as the risk curve and expected annual damage (EAD). In conclusion, it seems that changes in exposure and vulnerability seem to outweigh changes in hazard.

Assimilating soil moisture into an Earth System Model

NASA Astrophysics Data System (ADS)

Stacke, Tobias; Hagemann, Stefan

2017-04-01

Several modelling studies reported potential impacts of soil moisture anomalies on regional climate. In particular for short prediction periods, perturbations of the soil moisture state may result in significant alteration of surface temperature in the following season. However, it is not clear yet whether or not soil moisture anomalies affect climate also on larger temporal and spatial scales. In an earlier study, we showed that soil moisture anomalies can persist for several seasons in the deeper soil layers of a land surface model. Additionally, those anomalies can influence root zone moisture, in particular during explicitly dry or wet periods. Thus, one prerequisite for predictability, namely the existence of long term memory, is evident for simulated soil moisture and might be exploited to improve climate predictions. The second prerequisite is the sensitivity of the climate system to soil moisture. In order to investigate this sensitivity for decadal simulations, we implemented a soil moisture assimilation scheme into the Max-Planck Institute for Meteorology's Earth System Model (MPI-ESM). The assimilation scheme is based on a simple nudging algorithm and updates the surface soil moisture state once per day. In our experiments, the MPI-ESM is used which includes model components for the interactive simulation of atmosphere, land and ocean. Artificial assimilation data is created from a control simulation to nudge the MPI-ESM towards predominantly dry and wet states. First analyses are focused on the impact of the assimilation on land surface variables and reveal distinct differences in the long-term mean values between wet and dry state simulations. Precipitation, evapotranspiration and runoff are larger in the wet state compared to the dry state, resulting in an increased moisture transport from the land to atmosphere and ocean. Consequently, surface temperatures are lower in the wet state simulations by more than one Kelvin. In terms of spatial pattern, the largest differences between both simulations are seen for continental areas, while regions with a maritime climate are least sensitive to soil moisture assimilation.

Real-Time Climate Simulations in the Interactive 3D Game Universe Sandbox ²

NASA Astrophysics Data System (ADS)

Goldenson, N. L.

2014-12-01

Exploration in an open-ended computer game is an engaging way to explore climate and climate change. Everyone can explore physical models with real-time visualization in the educational simulator Universe Sandbox ² (universesandbox.com/2), which includes basic climate simulations on planets. I have implemented a time-dependent, one-dimensional meridional heat transport energy balance model to run and be adjustable in real time in the midst of a larger simulated system. Universe Sandbox ² is based on the original game - at its core a gravity simulator - with other new physically-based content for stellar evolution, and handling collisions between bodies. Existing users are mostly science enthusiasts in informal settings. We believe that this is the first climate simulation to be implemented in a professionally developed computer game with modern 3D graphical output in real time. The type of simple climate model we've adopted helps us depict the seasonal cycle and the more drastic changes that come from changing the orbit or other external forcings. Users can alter the climate as the simulation is running by altering the star(s) in the simulation, dragging to change orbits and obliquity, adjusting the climate simulation parameters directly or changing other properties like CO2 concentration that affect the model parameters in representative ways. Ongoing visuals of the expansion and contraction of sea ice and snow-cover respond to the temperature calculations, and make it accessible to explore a variety of scenarios and intuitive to understand the output. Variables like temperature can also be graphed in real time. We balance computational constraints with the ability to capture the physical phenomena we wish to visualize, giving everyone access to a simple open-ended meridional energy balance climate simulation to explore and experiment with. The software lends itself to labs at a variety of levels about climate concepts including seasons, the Greenhouse effect, reservoirs and flows, albedo feedback, Snowball Earth, climate sensitivity, and model experiment design. Climate calculations are extended to Mars with some modifications to the Earth climate component, and could be used in lessons about the Mars atmosphere, and exploring scenarios of Mars climate history.

Interpretation of orbital scale variability in mid-latitude speleothem δ18O: Significance of growth rate controlled kinetic fractionation effects

NASA Astrophysics Data System (ADS)

Stoll, Heather; Mendez-Vicente, Ana; Gonzalez-Lemos, Saul; Moreno, Ana; Cacho, Isabel; Cheng, Hai; Edwards, R. Lawrence

2015-11-01

Oxygen isotopes have been the most widely used climate indicator in stalagmites, applied to reconstruct past changes in rainfall δ18O and cave temperature. However, the δ18O signal in speleothems may also be influenced by variable kinetic fractionation effects, here conceived broadly as fractionation effects not arising from temperature variation. The regional reproducibility of speleothem δ18O signals has been proposed as a way to distinguish the δ18O variations arising directly from changes rainfall δ18O and cave temperature, from variations due to kinetic effects which may nonetheless be influenced by climate. Here, we compare isotopic records from 5 coeval stalagmites from two proximal caves in NW Spain covering the interval 140 to 70 ka, which experienced the same primary variations in temperature and rainfall δ18O, but exhibit a large range in growth rates and temporal trends in growth rate. Stalagmites growing at faster rates near 50 μm/yr have oxygen isotopic ratios over 1‰ more negative than coeval stalagmites with very slow (5 μm/yr) growth rates. Because growth rate variations also occur over time within any given stalagmite, the measured oxygen isotopic time series for a given stalagmite includes both climatic and kinetic components. Removal of the kinetic component of variation in each stalagmite, based on the dependence of the kinetic component on growth rate, is effective at distilling a common temporal evolution of among the oxygen isotopic records of the multiple stalagmites. However, this approach is limited by the quality of the age model. For time periods characterized by very slow growth and long durations between dates, the presence of crypto-hiatus may result in average growth rates which underestimate the instantaneous speleothem deposition rates and which therefore underestimate the magnitude of kinetic effects. The stacked growth rate-corrected speleothem δ18O is influenced by orbital scale variation in the cave temperature and the δ18O of the ocean moisture source, but also by temporally variable fractionation in the hydrological cycle. The most salient trend is increased hydrological fractionation during the GI-22 period, when warmer sea surface temperatures in the subtropical Atlantic moisture source region may have favored greater precipitation amounts.

78 FR 70888 - Need for Agency Approval of a Railroad's Use of Certain Technology That Has Been Previously...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-11-27

... technologies, namely safety-critical processor-based signal or train control systems, including subsystems and... or train control system (including a subsystem or component thereof) that was in service as of June 6... processor-based signal or train control system, subsystem, or component.'' See 49 CFR 236.903. Under Subpart...

Model-Based Development of Automotive Electronic Climate Control Software

NASA Astrophysics Data System (ADS)

Kakade, Rupesh; Murugesan, Mohan; Perugu, Bhupal; Nair, Mohanan

With increasing complexity of software in today's products, writing and maintaining thousands of lines of code is a tedious task. Instead, an alternative methodology must be employed. Model-based development is one candidate that offers several benefits and allows engineers to focus on the domain of their expertise than writing huge codes. In this paper, we discuss the application of model-based development to the electronic climate control software of vehicles. The back-to-back testing approach is presented that ensures flawless and smooth transition from legacy designs to the model-based development. Simulink report generator to create design documents from the models is presented along with its usage to run the simulation model and capture the results into the test report. Test automation using model-based development tool that support the use of unique set of test cases for several testing levels and the test procedure that is independent of software and hardware platform is also presented.

Shallow peatland ecohydrology - the control of peat depth on moss productivity

NASA Astrophysics Data System (ADS)

Dixon, Simon; Kettridge, Nicholas; Moore, Paul; Devito, Kevin; Tilak, Amey; Petrone, Rich; Mendoza, Carl; Waddington, Mike

2017-04-01

Northern peatlands represent an important sink in the global carbon cycle. Shallow peatlands and marginal connective wetlands can be essential components of many northern peatland landscape mosaics, playing a vital role in landscape connectivity and wider landscape hydrology. However the ecohydrological function of these shallow, marginal systems has been largely overlooked, with peatland hydrology research focused on relatively deep bog systems. In order to predict landscape scale wetland function and its vulnerability to climate change we need to understand how these shallow connective systems function. The balance between moss productivity and water loss provide a key component of these systems, as water use efficiency controls the rate of moss growth and thus controls the amount of atmospheric carbon sequestered in peat. Understanding how productivity of shallow peatland systems responds to changes in evaporative stress will aid predictions of peatland landscape hydrological function in a changing climate. To determine the factors influencing peat productivity, water balance simulations using Hydrus 1-D were conducted over annual growing seasons for different soil profile depths, compositions and antecedent moisture conditions. Our results demonstrate a bimodal distribution of peatland responses; either primarily conserving water by limiting evapotranspiration or, maximizing productivity. For sustained periods of evaporative stress, shallow marginal systems are least able to buffer periods of evaporative stress due to limited labile water storage, and will limit evaporation, conserve water and be less productive. Conversely, where present, both deep water storage and a shallow initial water table prolong the onset of high vegetative stress, thus maximizing moss productivity. However, a total depth of 0.8 m is identified as the threshold above which increasing peat depth has no further effect on changing vegetative stress response and thus landscape function. These results are important as moss productivity, along with rate of organic matter decay are the two principle factors controlling the build-up of peat, and therefore sequestration of carbon. With a predicted increase in the frequency and size of rain events in northern latitudes our results indicate the productivity of shallow wetland systems may increase, but greater moisture availability will increase the likelihood they remain as wetlands in a changing climate.

Effect of historical land-use and climate change on tree-climate relationships in the upper Midwestern United States.

PubMed

Goring, Simon J; Williams, John W

2017-04-01

Contemporary forest inventory data are widely used to understand environmental controls on tree species distributions and to construct models to project forest responses to climate change, but the stability and representativeness of contemporary tree-climate relationships are poorly understood. We show that tree-climate relationships for 15 tree genera in the upper Midwestern US have significantly altered over the last two centuries due to historical land-use and climate change. Realised niches have shifted towards higher minimum temperatures and higher rainfall. A new attribution method implicates both historical climate change and land-use in these shifts, with the relative importance varying among genera and climate variables. Most climate/land-use interactions are compounding, in which historical land-use reinforces shifts in species-climate relationships toward wetter distributions, or confounding, in which land-use complicates shifts towards warmer distributions. Compounding interactions imply that contemporary-based models of species distributions may underestimate species resilience to climate change. © 2017 John Wiley & Sons Ltd/CNRS.

Assessing state efforts to integrate transportation, land use and climate change.

DOT National Transportation Integrated Search

2016-12-01

Climate change is increasingly recognized as a threat to life on earth. Continued emission of greenhouse gases will cause further : warming and long-lasting changes in all components of the climate system, increasing the likelihood of severe, perv...

Evidence for ice-free summers in the late Miocene central Arctic Ocean

PubMed Central

Stein, Ruediger; Fahl, Kirsten; Schreck, Michael; Knorr, Gregor; Niessen, Frank; Forwick, Matthias; Gebhardt, Catalina; Jensen, Laura; Kaminski, Michael; Kopf, Achim; Matthiessen, Jens; Jokat, Wilfried; Lohmann, Gerrit

2016-01-01

Although the permanently to seasonally ice-covered Arctic Ocean is a unique and sensitive component in the Earth's climate system, the knowledge of its long-term climate history remains very limited due to the restricted number of pre-Quaternary sedimentary records. During Polarstern Expedition PS87/2014, we discovered multiple submarine landslides along Lomonosov Ridge. Removal of younger sediments from steep headwalls has led to exhumation of Miocene sediments close to the seafloor. Here we document the presence of IP25 as a proxy for spring sea-ice cover and alkenone-based summer sea-surface temperatures >4 °C that support a seasonal sea-ice cover with an ice-free summer season being predominant during the late Miocene in the central Arctic Ocean. A comparison of our proxy data with Miocene climate simulations seems to favour either relatively high late Miocene atmospheric CO2 concentrations and/or a weak sensitivity of the model to simulate the magnitude of high-latitude warming in a warmer than modern climate. PMID:27041737

A Feasibility Study of Life-Extending Controls for Aircraft Turbine Engines Using a Generic Air Force Model (Preprint)

DTIC Science & Technology

2006-12-01

intelligent control algorithm embedded in the FADEC . This paper evaluates the LEC, based on critical components research, to demonstrate how an...control action, engine component life usage, and designing an intelligent control algorithm embedded in the FADEC . This paper evaluates the LEC, based on...simulation code for each simulator. One is typically configured to operate as a Full- Authority Digital Electronic Controller ( FADEC

Separating physical and biological controls on ten-year evapotranspiration fluctuations in an irrigated cropland in the North China Plain

NASA Astrophysics Data System (ADS)

Lei, Huimin

2016-04-01

The North China Plain, the largest agricultural production area in China, is a water-limited region where more than 50% of the nation's wheat and 33% of its maize production is grown. Evapotranspiration (ET) is a major component of the water balance in this agricultural ecosystem. Thus, hydrological cycle is very sensitive to the seasonal and interannual variability in ET. Understanding the variability in ET at different temporal scales and identifying out the dominant factor among the climatic factors (i.e., physical factors), crop factors (i.e., biological factors), and anthropogenic factors (i.e., irrigation) regulating ET is vital for promoting the development of agro-hydrological modeling. However, little is known about how ecosystem-level ET of irrigated cropland responds to these physical and biological factors over the long term, e.g., greater than 10 years. We have operated an eddy-covariance tower in a winter wheat-summer maize cropland for a 10-year period from 2005 through 2015, providing continuous measurements of ET and its relevant variables. The 10-year measurement period covers episodes of extremely high to low annual precipitation and higher air temperatures. The 10-year dataset provides opportunity to investigate the response of site-specific ecosystem ET to the variability of environmental factors. In this study, we reconcile an agro-hydrological model and the observations, to separate the physical and biological controls on ET fluctuations at different temporal scales. First, the model is calibrated carefully based on the observations. Second, a number of model runs are designed to disentangle the influence of climate, irrigation and biological drivers through constrained simulations. The climate drivers include precipitation, air temperature, air humidity, wind speed, and solar radiation, and the biological drivers include leaf area index and leaf-level stomatal conductance. In addition, the impacts of the variability in irrigation on ET will be studied. Last, based on the numerical runs, the dominant factor at each temporal scale (i.e., from weekly to annual) is identified.

A national framework for monitoring and reporting on environmental sustainability in Canada.

PubMed

Marshall, I B; Scott Smith, C A; Selby, C J

1996-01-01

In 1991, a collaborative project to revise the terrestrial component of a national ecological framework was undertaken with a wide range of stakeholders. This spatial framework consists of multiple, nested levels of ecological generalization with linkages to existing federal and provincial scientific databases. The broadest level of generalization is the ecozone. Macroclimate, major vegetation types and subcontinental scale physiographic formations constitute the definitive components of these major ecosystems. Ecozones are subdivided into approximately 200 ecoregions which are based on properties like regional physiography, surficial geology, climate, vegetation, soil, water and fauna. The ecozone and ecoregion levels of the framework have been depicted on a national map coverage at 1:7 500 000 scale. Ecoregions have been subdivided into ecodistricts based primarily on landform, parent material, topography, soils, waterbodies and vegetation at a scale (1:2 000 000) useful for environmental resource management, monitoring and modelling activities. Nested within the ecodistricts are the polygons that make up the Soil Landscapes of Canada series of 1:1 000 000 scale soil maps. The framework is supported by an ARC-INFO GIS at Agriculture Canada. The data model allows linkage to associated databases on climate, land use and socio-economic attributes.

Future malaria spatial pattern based on the potential global warming impact in South and Southeast Asia.

PubMed

Khormi, Hassan M; Kumar, Lalit

2016-11-21

We used the Model for Interdisciplinary Research on Climate-H climate model with the A2 Special Report on Emissions Scenarios for the years 2050 and 2100 and CLIMEX software for projections to illustrate the potential impact of climate change on the spatial distributions of malaria in China, India, Indochina, Indonesia, and The Philippines based on climate variables such as temperature, moisture, heat, cold and dryness. The model was calibrated using data from several knowledge domains, including geographical distribution records. The areas in which malaria has currently been detected are consistent with those showing high values of the ecoclimatic index in the CLIMEX model. The match between prediction and reality was found to be high. More than 90% of the observed malaria distribution points were associated with the currently known suitable climate conditions. Climate suitability for malaria is projected to decrease in India, southern Myanmar, southern Thailand, eastern Borneo, and the region bordering Cambodia, Malaysia and the Indonesian islands, while it is expected to increase in southern and south-eastern China and Taiwan. The climatic models for Anopheles mosquitoes presented here should be useful for malaria control, monitoring, and management, particularly considering these future climate scenarios.

SPRUCE experiment data infrastructure

NASA Astrophysics Data System (ADS)

Krassovski, M.; Hanson, P. J.; Boden, T.; Riggs, J.; Nettles, W. R.; Hook, L. A.

2013-12-01

The Carbon Dioxide Information Analysis Center (CDIAC) at Oak Ridge National Laboratory (ORNL), USA has provided scientific data management support for the US Department of Energy and international climate change science since 1982. Among the many data activities CDIAC performs are design and implementation of the data systems. One current example is the data system and network for SPRUCE experiment. The SPRUCE experiment (http://mnspruce.ornl.gov) is the primary component of the Terrestrial Ecosystem Science Scientific Focus Area of ORNL's Climate Change Program, focused on terrestrial ecosystems and the mechanisms that underlie their responses to climatic change. The experimental work is to be conducted in a bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). The site is located at the southern margin of the boreal peatland forest. Experimental work in the 8.1-ha S1 bog will be a climate change manipulation focusing on the combined responses to multiple levels of warming at ambient or elevated CO2 (eCO2) levels. The experiment provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, the cycling and release of CO2 and CH4 to the atmosphere). The manipulation will evaluate the response of the existing biological communities to a range of warming levels from ambient to +9°C, provided via large, modified open-top chambers. The ambient and +9°C warming treatments will also be conducted at eCO2 (in the range of 800 to 900 ppm). Both direct and indirect effects of these experimental perturbations will be analyzed to develop and refine models needed for full Earth system analyses. SPRUCE provides wide range continuous and discrete measurements. To successfully manage SPRUCE data flow and support climate change research, CDIAC has designed flexible data collection system using proven network technologies and taking advantage of existing software components. The SPRUCE data system comprised primarily of a set of network components, relational database, a web server to monitor data collection status, FTP server and replication/backup arrangement. Later the data interface on the existing website will be expanded to allow users to query the SPRUCE collection in a variety of ways and then subset, visualize and download the data. From the perspective of data stewardship, on the other hand, this system is designed for CDIAC to easily control database content, automate data movement, track data provenance, manage metadata content, and handle additions and corrections. In this presentation, we share our approaches to meet the challenges of designing and constructing data system for managing sources of high volume in situ observations in a remote location. It will demonstrate the dataflow starting from the sensors and ending at the archiving/distribution points, discuss types of hardware and software used, and examine considerations that were used to choose them.

From the ocean to a salt marsh: towards understanding iron reduction processes with FORC-PCA.

NASA Astrophysics Data System (ADS)

Muraszko, J. R.; Lascu, I.; Collins, S. M.; Harrison, R. J.

2017-12-01

Biogenic magnetic minerals are a high fidelity recorder of climate change. Their sensitivity to sedimentary redox conditions and bottom water ventilation have the potential to provide useful insights into past diagenetic conditions. However, the mechanisms controlling preservation and dissolution of magnetosomes are not fully understood, thus undermining the reliability of the paleomagnetic records in marine environments. Recovering information about the diagenetic past of the sediment is a crucial challenge; specifically, the biogenic components need to be identified and unmixed from the bulk magnetic signal. We address the issue in this study by applying Principal Component Analysis on First Order Reversal Curve diagrams (FORC-PCA) in case studies of cores obtained from the Iberian Margin and the sedimentologically active coastal salt marshes of Norfolk. We demonstrate the applicability of FORC-PCA as a new environmental proxy, yielding a high resolution temporal marine record of environmental changes reflected in magnetic composition over the last 194 kyr. The strongest variations are observed in the microbially derived components, the bulk properties of the sediment being controlled by a low coercivity SP-SD component which is generally anticorrelated with the magnetosome signal. Supported by TEM studies, we suggest the prevalence of clusters of nano-particles of magnetite associated with iron reduction. To further investigate the mechanisms controlling these processes, the active sedimentary environment of Norfolk was chosen as a case study of early diagenesis controlled by strong vertical geochemical gradients.