CEOS SEO and GISS Meeting

NASA Technical Reports Server (NTRS)

Killough, Brian; Stover, Shelley

2008-01-01

The Committee on Earth Observation Satellites (CEOS) provides a brief to the Goddard Institute for Space Studies (GISS) regarding the CEOS Systems Engineering Office (SEO) and current work on climate requirements and analysis. A "system framework" is provided for the Global Earth Observation System of Systems (GEOSS). SEO climate-related tasks are outlined including the assessment of essential climate variable (ECV) parameters, use of the "systems framework" to determine relevant informational products and science models and the performance of assessments and gap analyses of measurements and missions for each ECV. Climate requirements, including instruments and missions, measurements, knowledge and models, and decision makers, are also outlined. These requirements would establish traceability from instruments to products and services allowing for benefit evaluation of instruments and measurements. Additionally, traceable climate requirements would provide a better understanding of global climate models.

Interaction of the Climate System and the Solid Earth: Analysis of Observations and Models

NASA Technical Reports Server (NTRS)

Bryan, Frank

2001-01-01

Under SENH funding we have carried out a number of diverse analyses of interactions of the climate system (atmosphere, ocean, land surface hydrology) with the solid Earth. While the original work plan emphasized analysis of excitation of variations in Earth rotation, with a lesser emphasis on time variable gravity, opportunities that developed during the proposal period in connection with preparations for the GRACE mission led us to a more balanced effort between these two topics. The results of our research are outlined in several topical sections: (1) oceanic excitation of variations in Earth rotation; (2) short period atmosphere-ocean excitation of variations in Earth rotation; (3) analysis of coupled climate system simulation; (4) observing system simulation studies for GRACE mission design; and (5) oceanic response to atmospheric pressure loading.

Arctic melt ponds and bifurcations in the climate system

NASA Astrophysics Data System (ADS)

Sudakov, I.; Vakulenko, S. A.; Golden, K. M.

2015-05-01

Understanding how sea ice melts is critical to climate projections. In the Arctic, melt ponds that develop on the surface of sea ice floes during the late spring and summer largely determine their albedo - a key parameter in climate modeling. Here we explore the possibility of a conceptual sea ice climate model passing through a bifurcation point - an irreversible critical threshold as the system warms, by incorporating geometric information about melt pond evolution. This study is based on a bifurcation analysis of the energy balance climate model with ice-albedo feedback as the key mechanism driving the system to bifurcation points.

Uncertainty Analysis of Coupled Socioeconomic-Cropping Models: Building Confidence in Climate Change Decision-Support Tools for Local Stakeholders

NASA Astrophysics Data System (ADS)

Malard, J. J.; Rojas, M.; Adamowski, J. F.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

While cropping models represent the biophysical aspects of agricultural systems, system dynamics modelling offers the possibility of representing the socioeconomic (including social and cultural) aspects of these systems. The two types of models can then be coupled in order to include the socioeconomic dimensions of climate change adaptation in the predictions of cropping models.We develop a dynamically coupled socioeconomic-biophysical model of agricultural production and its repercussions on food security in two case studies from Guatemala (a market-based, intensive agricultural system and a low-input, subsistence crop-based system). Through the specification of the climate inputs to the cropping model, the impacts of climate change on the entire system can be analysed, and the participatory nature of the system dynamics model-building process, in which stakeholders from NGOs to local governmental extension workers were included, helps ensure local trust in and use of the model.However, the analysis of climate variability's impacts on agroecosystems includes uncertainty, especially in the case of joint physical-socioeconomic modelling, and the explicit representation of this uncertainty in the participatory development of the models is important to ensure appropriate use of the models by the end users. In addition, standard model calibration, validation, and uncertainty interval estimation techniques used for physically-based models are impractical in the case of socioeconomic modelling. We present a methodology for the calibration and uncertainty analysis of coupled biophysical (cropping) and system dynamics (socioeconomic) agricultural models, using survey data and expert input to calibrate and evaluate the uncertainty of the system dynamics as well as of the overall coupled model. This approach offers an important tool for local decision makers to evaluate the potential impacts of climate change and their feedbacks through the associated socioeconomic system.

Evaluating Options for Improving California's Drought Resilience

NASA Astrophysics Data System (ADS)

Ray, P. A.; Schwarz, A.; Wi, S.; Correa, M.; Brown, C.

2015-12-01

Through a unique collaborative arrangement, the University of Massachusetts (UMass) and the California Department of Water Resources (DWR) have together performed a baseline climate change analysis of the California state (State Water Project) and federal (Central Valley Project) water systems. The first step in the baseline analysis was development of an improved basinwide hydrologic model covering a large area of California including all major tributaries to the state and federal water systems. The CalLite modeling system used by DWR for planning purposes allowed simulation of the system of reservoirs, rivers, control points, and deliveries which are then used to create performance metrics that quantify a wide range of system characteristics including water deliveries, water quality, and environmental/ecological factors. A baseline climate stress test was conducted to identify current vulnerabilities to climate change through the linking of the modeling chain with Decision Scaling concepts through the UMass bottom-up climate stress-testing algorithm. This procedure allowed the first comprehensive climate stress analysis of the California state and federal water systems not constrained by observed historical variability and wet-dry year sequences. A forward-looking drought vulnerability and adaptation assessment of the water systems based on this workflow is ongoing and preliminary results will be presented. Presentation of results will include discussion of the collaborative arrangement between DWR and UMass, which is instrumental to both the success of the research and the education of policy makers.

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.

Exploring and Analyzing Climate Variations Online by Using MERRA-2 data at GES DISC

NASA Astrophysics Data System (ADS)

Shen, S.; Ostrenga, D.; Vollmer, B.; Kempler, S.

2016-12-01

NASA Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) (http://giovanni.sci.gsfc.nasa.gov/giovanni/) is a web-based data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. The system enables basic statistical analysis and comparisons of multiple variables. This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional remote sensing and model data sets from a number of NASA data centers. Recently, long term global assimilated atmospheric, land, and ocean data have been integrated into the system that enables quick exploration and analysis of climate data without downloading, and preprocessing the data. Example data include climate reanalysis from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) which provides data beginning 1980 to present; land data from NASA Global Land Data Assimilation System (GLDAS) which assimilates data from 1948 to 2012; as well as ocean biological data from NASA Ocean Biogeochemical Model (NOBM) which assimilates data from 1998 to 2012. This presentation, using surface air temperature, precipitation, ozone, and aerosol, etc. from MERRA-2, demonstrates climate variation analysis with Giovanni at selected regions.

Exploring and Analyzing Climate Variations Online by Using NASA MERRA-2 Data at GES DISC

NASA Technical Reports Server (NTRS)

Shen, Suhung; Ostrenga, Dana M.; Vollmer, Bruce E.; Kempler, Steven J.

2016-01-01

NASA Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure) (http:giovanni.sci.gsfc.nasa.govgiovanni) is a web-based data visualization and analysis system developed by the Goddard Earth Sciences Data and Information Services Center (GES DISC). Current data analysis functions include Lat-Lon map, time series, scatter plot, correlation map, difference, cross-section, vertical profile, and animation etc. The system enables basic statistical analysis and comparisons of multiple variables. This web-based tool facilitates data discovery, exploration and analysis of large amount of global and regional remote sensing and model data sets from a number of NASA data centers. Long term global assimilated atmospheric, land, and ocean data have been integrated into the system that enables quick exploration and analysis of climate data without downloading, preprocessing, and learning data. Example data include climate reanalysis data from NASA Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) which provides data beginning in 1980 to present; land data from NASA Global Land Data Assimilation System (GLDAS), which assimilates data from 1948 to 2012; as well as ocean biological data from NASA Ocean Biogeochemical Model (NOBM), which provides data from 1998 to 2012. This presentation, using surface air temperature, precipitation, ozone, and aerosol, etc. from MERRA-2, demonstrates climate variation analysis with Giovanni at selected regions.

Knowledge Discovery from Climate Data using Graph-Based Methods

NASA Astrophysics Data System (ADS)

Steinhaeuser, K.

2012-04-01

Climate and Earth sciences have recently experienced a rapid transformation from a historically data-poor to a data-rich environment, thus bringing them into the realm of the Fourth Paradigm of scientific discovery - a term coined by the late Jim Gray (Hey et al. 2009), the other three being theory, experimentation and computer simulation. In particular, climate-related observations from remote sensors on satellites and weather radars, in situ sensors and sensor networks, as well as outputs of climate or Earth system models from large-scale simulations, provide terabytes of spatio-temporal data. These massive and information-rich datasets offer a significant opportunity for advancing climate science and our understanding of the global climate system, yet current analysis techniques are not able to fully realize their potential benefits. We describe a class of computational approaches, specifically from the data mining and machine learning domains, which may be novel to the climate science domain and can assist in the analysis process. Computer scientists have developed spatial and spatio-temporal analysis techniques for a number of years now, and many of them may be applicable and/or adaptable to problems in climate science. We describe a large-scale, NSF-funded project aimed at addressing climate science question using computational analysis methods; team members include computer scientists, statisticians, and climate scientists from various backgrounds. One of the major thrusts is in the development of graph-based methods, and several illustrative examples of recent work in this area will be presented.

Climate variability and demand growth as drivers of water scarcity in the Turkwel river basin: a bottom-up risk assessment of a data-sparse basin in Kenya

NASA Astrophysics Data System (ADS)

Hirpa, F. A.; Dyer, E.; Hope, R.; Dadson, S. J.

2017-12-01

Sustainable water management and allocation are essential for maintaining human well-being, sustaining healthy ecosystems, and supporting steady economic growth. The Turkwel river basin, located in north-western Kenya, experiences a high level of water scarcity due to its arid climate, high rainfall variability, and rapidly growing water demand. However, due to sparse hydro-climatic data and limited literature, the water resources system of the basin has been poorly understood. Here we apply a bottom-up climate risk assessment method to estimate the resilience of the basin's water resources system to growing demand and climate stressors. First, using a water resource system model and historical climate data, we construct a climate risk map that depicts the way in which the system responds to climate change and variability. Then we develop a set of water demand scenarios to identify the conditions that potentially lead to the risk of unmet water demand and groundwater depletion. Finally, we investigate the impact of climate change and variability by stress testing these development scenarios against historically strong El Niño/Southern Oscillation (ENSO) years and future climate projections from multiple Global Circulation Models (GCMs). The results reveal that climate variability and increased water demand are the main drivers of water scarcity in the basin. Our findings show that increases in water demand due to expanded irrigation and population growth exert the strongest influence on the ability of the system to meet water resource supply requirements, and in all cases considered increase the impacts of droughts caused by future climate variability. Our analysis illustrates the importance of combining analysis of future climate risks with other development decisions that affect water resources planning. Policy and investment decisions which maximise water use efficiency in the present day are likely to impart resilience to climate change and variability under a wide range of future scenarios and therefore constitute low regret measures for climate adaptation.

A New Trans-Disciplinary Approach to Regional Integrated Assessment of Climate Impact and Adaptation in Agricultural Systems (Invited)

NASA Astrophysics Data System (ADS)

Antle, J. M.; Valdivia, R. O.; Jones, J.; Rosenzweig, C.; Ruane, A. C.

2013-12-01

This presentation provides an overview of the new methods developed by researchers in the Agricultural Model Inter-comparison and Improvement Project (AgMIP) for regional climate impact assessment and analysis of adaptation in agricultural systems. This approach represents a departure from approaches in the literature in several dimensions. First, the approach is based on the analysis of agricultural systems (not individual crops) and is inherently trans-disciplinary: it is based on a deep collaboration among a team of climate scientists, agricultural scientists and economists to design and implement regional integrated assessments of agricultural systems. Second, in contrast to previous approaches that have imposed future climate on models based on current socio-economic conditions, this approach combines bio-physical and economic models with a new type of pathway analysis (Representative Agricultural Pathways) to parameterize models consistent with a plausible future world in which climate change would be occurring. Third, adaptation packages for the agricultural systems in a region are designed by the research team with a level of detail that is useful to decision makers, such as research administrators and donors, who are making agricultural R&D investment decisions. The approach is illustrated with examples from AgMIP's projects currently being carried out in Africa and South Asia.

Data management and analysis for the Earth System Grid

NASA Astrophysics Data System (ADS)

Williams, D. N.; Ananthakrishnan, R.; Bernholdt, D. E.; Bharathi, S.; Brown, D.; Chen, M.; Chervenak, A. L.; Cinquini, L.; Drach, R.; Foster, I. T.; Fox, P.; Hankin, S.; Henson, V. E.; Jones, P.; Middleton, D. E.; Schwidder, J.; Schweitzer, R.; Schuler, R.; Shoshani, A.; Siebenlist, F.; Sim, A.; Strand, W. G.; Wilhelmi, N.; Su, M.

2008-07-01

The international climate community is expected to generate hundreds of petabytes of simulation data within the next five to seven years. This data must be accessed and analyzed by thousands of analysts worldwide in order to provide accurate and timely estimates of the likely impact of climate change on physical, biological, and human systems. Climate change is thus not only a scientific challenge of the first order but also a major technological challenge. In order to address this technological challenge, the Earth System Grid Center for Enabling Technologies (ESG-CET) has been established within the U.S. Department of Energy's Scientific Discovery through Advanced Computing (SciDAC)-2 program, with support from the offices of Advanced Scientific Computing Research and Biological and Environmental Research. ESG-CET's mission is to provide climate researchers worldwide with access to the data, information, models, analysis tools, and computational capabilities required to make sense of enormous climate simulation datasets. Its specific goals are to (1) make data more useful to climate researchers by developing Grid technology that enhances data usability; (2) meet specific distributed database, data access, and data movement needs of national and international climate projects; (3) provide a universal and secure web-based data access portal for broad multi-model data collections; and (4) provide a wide-range of Grid-enabled climate data analysis tools and diagnostic methods to international climate centers and U.S. government agencies. Building on the successes of the previous Earth System Grid (ESG) project, which has enabled thousands of researchers to access tens of terabytes of data from a small number of ESG sites, ESG-CET is working to integrate a far larger number of distributed data providers, high-bandwidth wide-area networks, and remote computers in a highly collaborative problem-solving environment.

The Appropriateness of a California Student and Staff Survey for Measuring Middle School Climate. REL 2014-039

ERIC Educational Resources Information Center

Hanson, Thomas; Voight, Adam

2014-01-01

A growing number of states and school districts use school climate assessments in progress reporting systems and are interested in incorporating these assessments into accountability systems. This analysis of response data from middle school students and teachers on the California School Climate, Health, and Learning Survey examines the…

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

NASA Technical Reports Server (NTRS)

Johnson, Donald R.

1998-01-01

The goal of this research is the continued development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. This work involves a combination of modeling and analysis efforts involving 4DDA datasets and simulations from the University of Wisconsin (UW) hybrid isentropic-sigma (theta-sigma) coordinate model and the GEOS GCM.

2014 Earth System Grid Federation and Ultrascale Visualization Climate Data Analysis Tools Conference Report

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

Williams, Dean N.

2015-01-27

The climate and weather data science community met December 9–11, 2014, in Livermore, California, for the fourth annual Earth System Grid Federation (ESGF) and Ultrascale Visualization Climate Data Analysis Tools (UV-CDAT) Face-to-Face (F2F) Conference, hosted by the Department of Energy, National Aeronautics and Space Administration, National Oceanic and Atmospheric Administration, the European Infrastructure for the European Network of Earth System Modelling, and the Australian Department of Education. Both ESGF and UVCDATremain global collaborations committed to developing a new generation of open-source software infrastructure that provides distributed access and analysis to simulated and observed data from the climate and weather communities.more » The tools and infrastructure created under these international multi-agency collaborations are critical to understanding extreme weather conditions and long-term climate change. In addition, the F2F conference fosters a stronger climate and weather data science community and facilitates a stronger federated software infrastructure. The 2014 F2F conference detailed the progress of ESGF, UV-CDAT, and other community efforts over the year and sets new priorities and requirements for existing and impending national and international community projects, such as the Coupled Model Intercomparison Project Phase Six. Specifically discussed at the conference were project capabilities and enhancements needs for data distribution, analysis, visualization, hardware and network infrastructure, standards, and resources.« less

Climate information for public health: the role of the IRI climate data library in an integrated knowledge system.

PubMed

del Corral, John; Blumenthal, M Benno; Mantilla, Gilma; Ceccato, Pietro; Connor, Stephen J; Thomson, Madeleine C

2012-09-01

Public health professionals are increasingly concerned about the potential impact of climate variability and change on health outcomes. Protecting public health from the vagaries of climate requires new working relationships between the public health sector and the providers of climate data and information. The Climate Information for Public Health Action initiative at the International Research Institute for Climate and Society (IRI) is designed to increase the public health community's capacity to understand, use and demand appropriate climate data and climate information to mitigate the public health impacts of the climate. Significant challenges to building the capacity of health professionals to use climate information in research and decision-making include the difficulties experienced by many in accessing relevant and timely quality controlled data and information in formats that can be readily incorporated into specific analysis with other data sources. We present here the capacities of the IRI climate data library and show how we have used it to build an integrated knowledge system in the support of the use of climate and environmental information in climate-sensitive decision-making with respect to health. Initiated as an aid facilitating exploratory data analysis for climate scientists, the IRI climate data library has emerged as a powerful tool for interdisciplinary researchers focused on topics related to climate impacts on society, including health.

Modeling and Analysis of Global and Regional Climate Change in Relation to Atmospheric Hydrologic Processes

NASA Technical Reports Server (NTRS)

Johnson, Donald R.

2001-01-01

This research was directed to the development and application of global isentropic modeling and analysis capabilities to describe hydrologic processes and energy exchange in the climate system, and discern regional climate change. An additional objective was to investigate the accuracy and theoretical limits of global climate predictability which are imposed by the inherent limitations of simulating trace constituent transport and the hydrologic processes of condensation, precipitation and cloud life cycles.

Reconstruction of the dynamics of the climatic system from time-series data

PubMed Central

Nicolis, C.; Nicolis, G.

1986-01-01

The oxygen isotope record of the last million years, as provided by a deep sea core sediment, is analyzed by a method recently developed in the theory of dynamical systems. The analysis suggests that climatic variability is the manifestation of a chaotic dynamics described by an attractor of fractal dimensionality. A quantitative measure of the limited predictability of the climatic system is provided by the evaluation of the time-correlation function and the largest positive Lyapounov exponent of the system. PMID:16593650

Abrupt climate change and extinction events

NASA Technical Reports Server (NTRS)

Crowley, Thomas J.

1988-01-01

There is a growing body of theoretical and empirical support for the concept of instabilities in the climate system, and indications that abrupt climate change may in some cases contribute to abrupt extinctions. Theoretical indications of instabilities can be found in a broad spectrum of climate models (energy balance models, a thermohaline model of deep-water circulation, atmospheric general circulation models, and coupled ocean-atmosphere models). Abrupt transitions can be of several types and affect the environment in different ways. There is increasing evidence for abrupt climate change in the geologic record and involves both interglacial-glacial scale transitions and the longer-term evolution of climate over the last 100 million years. Records from the Cenozoic clearly show that the long-term trend is characterized by numerous abrupt steps where the system appears to be rapidly moving to a new equilibrium state. The long-term trend probably is due to changes associated with plate tectonic processes, but the abrupt steps most likely reflect instabilities in the climate system as the slowly changing boundary conditions caused the climate to reach some threshold critical point. A more detailed analysis of abrupt steps comes from high-resolution studies of glacial-interglacial fluctuations in the Pleistocene. Comparison of climate transitions with the extinction record indicates that many climate and biotic transitions coincide. The Cretaceous-Tertiary extinction is not a candidate for an extinction event due to instabilities in the climate system. It is quite possible that more detailed comparisons and analysis will indicate some flaws in the climate instability-extinction hypothesis, but at present it appears to be a viable candidate as an alternate mechanism for causing abrupt environmental changes and extinctions.

Educational and Scientific Applications of Climate Model Diagnostic Analyzer

NASA Astrophysics Data System (ADS)

Lee, S.; Pan, L.; Zhai, C.; Tang, B.; Kubar, T. L.; Zhang, J.; Bao, Q.

2016-12-01

Climate Model Diagnostic Analyzer (CMDA) is a web-based information system designed for the climate modeling and model analysis community to analyze climate data from models and observations. CMDA provides tools to diagnostically analyze climate data for model validation and improvement, and to systematically manage analysis provenance for sharing results with other investigators. CMDA utilizes cloud computing resources, multi-threading computing, machine-learning algorithms, web service technologies, and provenance-supporting technologies to address technical challenges that the Earth science modeling and model analysis community faces in evaluating and diagnosing climate models. As CMDA infrastructure and technology have matured, we have developed the educational and scientific applications of CMDA. Educationally, CMDA supported the summer school of the JPL Center for Climate Sciences for three years since 2014. In the summer school, the students work on group research projects where CMDA provide datasets and analysis tools. Each student is assigned to a virtual machine with CMDA installed in Amazon Web Services. A provenance management system for CMDA is developed to keep track of students' usages of CMDA, and to recommend datasets and analysis tools for their research topic. The provenance system also allows students to revisit their analysis results and share them with their group. Scientifically, we have developed several science use cases of CMDA covering various topics, datasets, and analysis types. Each use case developed is described and listed in terms of a scientific goal, datasets used, the analysis tools used, scientific results discovered from the use case, an analysis result such as output plots and data files, and a link to the exact analysis service call with all the input arguments filled. For example, one science use case is the evaluation of NCAR CAM5 model with MODIS total cloud fraction. The analysis service used is Difference Plot Service of Two Variables, and the datasets used are NCAR CAM total cloud fraction and MODIS total cloud fraction. The scientific highlight of the use case is that the CAM5 model overall does a fairly decent job at simulating total cloud cover, though simulates too few clouds especially near and offshore of the eastern ocean basins where low clouds are dominant.

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

NASA Astrophysics Data System (ADS)

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

2008-12-01

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

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

NASA Astrophysics Data System (ADS)

Kolokolov, Yury; Monovskaya, Anna

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

ARCAS (ACACIA Regional Climate-data Access System) -- a Web Access System for Climate Model Data Access, Visualization and Comparison

NASA Astrophysics Data System (ADS)

Hakkarinen, C.; Brown, D.; Callahan, J.; hankin, S.; de Koningh, M.; Middleton-Link, D.; Wigley, T.

2001-05-01

A Web-based access system to climate model output data sets for intercomparison and analysis has been produced, using the NOAA-PMEL developed Live Access Server software as host server and Ferret as the data serving and visualization engine. Called ARCAS ("ACACIA Regional Climate-data Access System"), and publicly accessible at http://dataserver.ucar.edu/arcas, the site currently serves climate model outputs from runs of the NCAR Climate System Model for the 21st century, for Business as Usual and Stabilization of Greenhouse Gas Emission scenarios. Users can select, download, and graphically display single variables or comparisons of two variables from either or both of the CSM model runs, averaged for monthly, seasonal, or annual time resolutions. The time length of the averaging period, and the geographical domain for download and display, are fully selectable by the user. A variety of arithmetic operations on the data variables can be computed "on-the-fly", as defined by the user. Expansions of the user-selectable options for defining analysis options, and for accessing other DOD-compatible ("Distributed Ocean Data System-compatible") data sets, residing at locations other than the NCAR hardware server on which ARCAS operates, are planned for this year. These expansions are designed to allow users quick and easy-to-operate web-based access to the largest possible selection of climate model output data sets available throughout the world.

Vulnerability of Thai rice production to simultaneous climate and socioeconomic changes: a double exposure analysis

NASA Astrophysics Data System (ADS)

Sangpenchan, R.

2011-12-01

This research explores the vulnerability of Thai rice production to simultaneous exposure by climate and socioeconomic change -- so-called "double exposure." Both processes influence Thailand's rice production system, but the vulnerabilities associated with their interactions are unknown. To understand this double exposure, I adopts a mixed-method, qualitative-quantitative analytical approach consisting of three phases of analysis involving a Vulnerability Scoping Diagram, a Principal Component Analysis, and the EPIC crop model using proxy datasets collected from secondary data sources at provincial scales.The first and second phases identify key variables representing each of the three dimensions of vulnerability -- exposure, sensitivity, and adaptive capacity indicating that the greatest vulnerability in the rice production system occurs in households and areas with high exposure to climate change, high sensitivity to climate and socioeconomic stress, and low adaptive capacity. In the third phase, the EPIC crop model simulates rice yields associated with future climate change projected by CSIRO and MIROC climate models. Climate change-only scenarios project the decrease in yields by 10% from the current productivity during 2016-2025 and 30% during 2045-2054. Scenarios applying both climate change and improved technology and management practices show that a 50% increase in rice production is possible, but requires strong collaboration between sectors to advance agricultural research and technology and requires strong adaptive capacity in the rice production system characterized by well-developed social capital, social networks, financial capacity, and infrastructure and household mobility at the local scale. The vulnerability assessment and climate and crop adaptation simulations used here provide useful information to decision makers developing vulnerability reduction plans in the face of concurrent climate and socioeconomic change.

New Observationally-Based Metrics for the Analysis of Coupled Climate Model and Earth System Model Simulations of the Southern Ocean

NASA Astrophysics Data System (ADS)

Russell, J. L.

2014-12-01

The exchange of heat and carbon dioxide between the atmosphere and ocean are major controls on Earth's climate under conditions of anthropogenic forcing. The Southern Ocean south of 30°S, occupying just over ¼ of the surface ocean area, accounts for a disproportionate share of the vertical exchange of properties between the deep and surface waters of the ocean and between the surface ocean and the atmosphere; thus this region can be disproportionately influential on the climate system. Despite the crucial role of the Southern Ocean in the climate system, understanding of the particular mechanisms involved remains inadequate, and the model studies underlying many of these results are highly controversial. As part of the overall goal of working toward reducing uncertainties in climate projections, we present an analysis using new data/model metrics based on a unified framework of theory, quantitative datasets, and numerical modeling. These new metrics quantify the mechanisms, processes, and tendencies relevant to the role of the Southern Ocean in climate.

ClimateSpark: An In-memory Distributed Computing Framework for Big Climate Data Analytics

NASA Astrophysics Data System (ADS)

Hu, F.; Yang, C. P.; Duffy, D.; Schnase, J. L.; Li, Z.

2016-12-01

Massive array-based climate data is being generated from global surveillance systems and model simulations. They are widely used to analyze the environment problems, such as climate changes, natural hazards, and public health. However, knowing the underlying information from these big climate datasets is challenging due to both data- and computing- intensive issues in data processing and analyzing. To tackle the challenges, this paper proposes ClimateSpark, an in-memory distributed computing framework to support big climate data processing. In ClimateSpark, the spatiotemporal index is developed to enable Apache Spark to treat the array-based climate data (e.g. netCDF4, HDF4) as native formats, which are stored in Hadoop Distributed File System (HDFS) without any preprocessing. Based on the index, the spatiotemporal query services are provided to retrieve dataset according to a defined geospatial and temporal bounding box. The data subsets will be read out, and a data partition strategy will be applied to equally split the queried data to each computing node, and store them in memory as climateRDDs for processing. By leveraging Spark SQL and User Defined Function (UDFs), the climate data analysis operations can be conducted by the intuitive SQL language. ClimateSpark is evaluated by two use cases using the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. One use case is to conduct the spatiotemporal query and visualize the subset results in animation; the other one is to compare different climate model outputs using Taylor-diagram service. Experimental results show that ClimateSpark can significantly accelerate data query and processing, and enable the complex analysis services served in the SQL-style fashion.

Climate Considerations Of The Electricity Supply Systems In Industries

NASA Astrophysics Data System (ADS)

Asset, Khabdullin; Zauresh, Khabdullina

2014-12-01

The study is focused on analysis of climate considerations of electricity supply systems in a pellet industry. The developed analysis model consists of two modules: statistical data of active power losses evaluation module and climate aspects evaluation module. The statistical data module is presented as a universal mathematical model of electrical systems and components of industrial load. It forms a basis for detailed accounting of power loss from the voltage levels. On the basis of the universal model, a set of programs is designed to perform the calculation and experimental research. It helps to obtain the statistical characteristics of the power losses and loads of the electricity supply systems and to define the nature of changes in these characteristics. Within the module, several methods and algorithms for calculating parameters of equivalent circuits of low- and high-voltage ADC and SD with a massive smooth rotor with laminated poles are developed. The climate aspects module includes an analysis of the experimental data of power supply system in pellet production. It allows identification of GHG emission reduction parameters: operation hours, type of electrical motors, values of load factor and deviation of standard value of voltage.

Enhancement of Local Climate Analysis Tool

NASA Astrophysics Data System (ADS)

Horsfall, F. M.; Timofeyeva, M. M.; Dutton, J.

2012-12-01

The National Oceanographic and Atmospheric Administration (NOAA) National Weather Service (NWS) will enhance its Local Climate Analysis Tool (LCAT) to incorporate specific capabilities to meet the needs of various users including energy, health, and other communities. LCAT is an online interactive tool that provides quick and easy access to climate data and allows users to conduct analyses at the local level such as time series analysis, trend analysis, compositing, correlation and regression techniques, with others to be incorporated as needed. LCAT uses principles of Artificial Intelligence in connecting human and computer perceptions on application of data and scientific techniques in multiprocessing simultaneous users' tasks. Future development includes expanding the type of data currently imported by LCAT (historical data at stations and climate divisions) to gridded reanalysis and General Circulation Model (GCM) data, which are available on global grids and thus will allow for climate studies to be conducted at international locations. We will describe ongoing activities to incorporate NOAA Climate Forecast System (CFS) reanalysis data (CFSR), NOAA model output data, including output from the National Multi Model Ensemble Prediction System (NMME) and longer term projection models, and plans to integrate LCAT into the Earth System Grid Federation (ESGF) and its protocols for accessing model output and observational data to ensure there is no redundancy in development of tools that facilitate scientific advancements and use of climate model information in applications. Validation and inter-comparison of forecast models will be included as part of the enhancement to LCAT. To ensure sustained development, we will investigate options for open sourcing LCAT development, in particular, through the University Corporation for Atmospheric Research (UCAR).

Monitoring Top-of-Atmosphere Radiative Energy Imbalance for Climate Prediction

NASA Technical Reports Server (NTRS)

Lin, Bing; Chambers, Lin H.; Stackhouse, Paul W., Jr.; Minnis, Patrick

2009-01-01

Large climate feedback uncertainties limit the prediction accuracy of the Earth s future climate with an increased CO2 atmosphere. One potential to reduce the feedback uncertainties using satellite observations of top-of-atmosphere (TOA) radiative energy imbalance is explored. Instead of solving the initial condition problem in previous energy balance analysis, current study focuses on the boundary condition problem with further considerations on climate system memory and deep ocean heat transport, which is more applicable for the climate. Along with surface temperature measurements of the present climate, the climate feedbacks are obtained based on the constraints of the TOA radiation imbalance. Comparing to the feedback factor of 3.3 W/sq m/K of the neutral climate system, the estimated feedback factor for the current climate system ranges from -1.3 to -1.0 W/sq m/K with an uncertainty of +/-0.26 W/sq m/K. That is, a positive climate feedback is found because of the measured TOA net radiative heating (0.85 W/sq m) to the climate system. The uncertainty is caused by the uncertainties in the climate memory length. The estimated time constant of the climate is large (70 to approx. 120 years), implying that the climate is not in an equilibrium state under the increasing CO2 forcing in the last century.

Climate Change and the Canadian Higher Education System: An Institutional Policy Analysis

ERIC Educational Resources Information Center

Henderson, Joseph; Bieler, Andrew; McKenzie, Marcia

2017-01-01

Climate change is a pressing concern. Higher education can address the challenge, but systematic analyses of climate change in education policy are sparse. This paper addresses this gap in the literature by reporting on how Canadian postsecondary educational institutions have engaged with climate change through policy actions. We used descriptive…

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

PubMed

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

2018-04-01

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

Assessing the Organizational Social Context (OSC) of child welfare systems: implications for research and practice.

PubMed

Glisson, Charles; Green, Philip; Williams, Nathaniel J

2012-09-01

The study: (1) provides the first assessment of the a priori measurement model and psychometric properties of the Organizational Social Context (OSC) measurement system in a US nationwide probability sample of child welfare systems; (2) illustrates the use of the OSC in constructing norm-based organizational culture and climate profiles for child welfare systems; and (3) estimates the association of child welfare system-level organizational culture and climate profiles with individual caseworker-level job satisfaction and organizational commitment. The study applies confirmatory factor analysis (CFA) and hierarchical linear models (HLM) analysis to a US nationwide sample of 1,740 caseworkers from 81 child welfare systems participating in the second National Survey of Child and Adolescent Wellbeing (NSCAW II). The participating child welfare systems were selected using a national probability procedure reflecting the number of children served by child welfare systems nationwide. The a priori OSC measurement model is confirmed in this nationwide sample of child welfare systems. In addition, caseworker responses to the OSC scales generate acceptable to high scale reliabilities, moderate to high within-system agreement, and significant between-system differences. Caseworkers in the child welfare systems with the best organizational culture and climate profiles report higher levels of job satisfaction and organizational commitment. Organizational climates characterized by high engagement and functionality, and organizational cultures characterized by low rigidity are associated with the most positive work attitudes. The OSC is the first valid and reliable measure of organizational culture and climate with US national norms for child welfare systems. The OSC provides a useful measure of Organizational Social Context for child welfare service improvement and implementation research efforts which include a focus on child welfare system culture and climate. Copyright © 2012 Elsevier Ltd. All rights reserved.

Climate change and viticulture in Mediterranean climates: the complex response of socio-ecosystems. A comparative case study from France and Australia (1955-2040)

NASA Astrophysics Data System (ADS)

Lereboullet, A.-L.; Beltrando, G.; Bardsley, D. K.

2012-04-01

The wine industry is very sensitive to extreme weather events, especially to temperatures above 35°C and drought. In a context of global climate change, Mediterranean climate regions are predicted to experience higher variability in rainfall and temperatures and an increased occurrence of extreme weather events. Some viticultural systems could be particularly at risk in those regions, considering their marginal position in the growth climatic range of Vitis vinifera, the long commercial lifespan of a vineyard, the high added-value of wine and the volatile nature of global markets. The wine industry, like other agricultural systems, is inserted in complex networks of climatic and non-climatic (other physical, economical, social and legislative) components, with constant feedbacks. We use a socio-ecosystem approach to analyse the adaptation of two Mediterranean viticultural systems to recent and future increase of extreme weather events. The present analysis focuses on two wine regions with a hot-summer Mediterranean climate (CSb type in the Köppen classification): Côtes-du-Roussillon in southern France and McLaren Vale in southern Australia. Using climate data from two synoptic weather stations, Perpignan (France) and Adelaide (Australia), with time series running from 1955 to 2010, we highlight changes in rainfall patterns and an increase in the number of days with Tx >35°c since the last three decades in both regions. Climate models (DRIAS project data for France and CSIRO Mk3.5 for Australia) project similar trends in the future. To date, very few projects have focused on an international comparison of the adaptive capacity of viticultural systems to climate change with a holistic approach. Here, the analysis of climate data was complemented by twenty in-depth semi-structured interviews with key actors of the two regional wine industries, in order to analyse adaptation strategies put in place regarding recent climate evolution. This mixed-methods approach allows for a comprehensive assessment of adaptation capacity of the two viticultural systems to future climate change. The strategies of grape growers and wine producers focus on maintaining optimal yields and a constant wine style adapted to markets in a variable and uncertain climate. Their implementation and efficiency depend strongly on non-climatic factors. Thus, adaptation capacity to recent and future climate change depends strongly on adaptation to other non-climatic changes.

Reducing the Carbon Footprint of Commercial Refrigeration Systems Using Life Cycle Climate Performance Analysis: From System Design to Refrigerant Options

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

Fricke, Brian A; Abdelaziz, Omar; Vineyard, Edward Allan

In this paper, Life Cycle Climate Performance (LCCP) analysis is used to estimate lifetime direct and indirect carbon dioxide equivalent gas emissions of various refrigerant options and commercial refrigeration system designs, including the multiplex DX system with various hydrofluorocarbon (HFC) refrigerants, the HFC/R744 cascade system incorporating a medium-temperature R744 secondary loop, and the transcritical R744 booster system. The results of the LCCP analysis are presented, including the direct and indirect carbon dioxide equivalent emissions for each refrigeration system and refrigerant option. Based on the results of the LCCP analysis, recommendations are given for the selection of low GWP replacement refrigerantsmore » for use in existing commercial refrigeration systems, as well as for the selection of commercial refrigeration system designs with low carbon dioxide equivalent emissions, suitable for new installations.« less

Assessing the combined effects of urbanisation and climate change on the river water quality in an integrated urban wastewater system in the UK.

PubMed

Astaraie-Imani, Maryam; Kapelan, Zoran; Fu, Guangtao; Butler, David

2012-12-15

Climate change and urbanisation are key factors affecting the future of water quality and quantity in urbanised catchments and are associated with significant uncertainty. The work reported in this paper is an evaluation of the combined and relative impacts of climate change and urbanisation on the receiving water quality in the context of an Integrated Urban Wastewater System (IUWS) in the UK. The impacts of intervening system operational control parameters are also investigated. Impact is determined by a detailed modelling study using both local and global sensitivity analysis methods together with correlation analysis. The results obtained from the case-study analysed clearly demonstrate that climate change combined with increasing urbanisation is likely to lead to worsening river water quality in terms of both frequency and magnitude of breaching threshold dissolved oxygen and ammonium concentrations. The results obtained also reveal the key climate change and urbanisation parameters that have the largest negative impact as well as the most responsive IUWS operational control parameters including major dependencies between all these parameters. This information can be further utilised to adapt future IUWS operation and/or design which, in turn, should make these systems more resilient to future climate and urbanisation changes. Copyright © 2012 Elsevier Ltd. All rights reserved.

The water footprint of California's energy system, 1990-2012.

PubMed

Fulton, Julian; Cooley, Heather

2015-03-17

California's energy and water systems are interconnected and have evolved in recent decades in response to changing conditions and policy goals. For this analysis, we use a water footprint methodology to examine water requirements of energy products consumed in California between 1990 and 2012. We combine energy production, trade, and consumption data with estimates of the blue and green water footprints of energy products. We find that while California's total annual energy consumption increased by just 2.6% during the analysis period, the amount of water required to produce that energy grew by 260%. Nearly all of the increase in California's energy-related water footprint was associated with water use in locations outside of California, where energy products that the state consumes were, and continue to be, produced. We discuss these trends and the implications for California's future energy system as it relates to climate change and expected water management challenges inside and outside the state. Our analysis shows that while California's energy policies have supported climate mitigation efforts, they have increased vulnerability to climate impacts, especially greater hydrologic uncertainty. More integrated analysis and planning are needed to ensure that climate adaptation and mitigation strategies do not work at cross purposes.

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Probabilistic projections of 21st century climate change over Northern Eurasia

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Climate variability and vulnerability to climate change: a review

PubMed Central

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

2014-01-01

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

Data Integration Plans for the NOAA National Climate Model Portal (NCMP) (Invited)

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Williams, D. N.; Deluca, C.; Hankin, S. C.; Compo, G. P.

2010-12-01

NOAA’s National Climatic Data Center (NCDC) and its collaborators have initiated a five-year development and implementation of an operational access capability for the next generation weather and climate model datasets. The NOAA National Climate Model Portal (NCMP) is being designed using format neutral open web based standards and tools where users at all levels of expertise can gain access and understanding to many of NOAA’s climate and weather model products. NCMP will closely coordinate with and reside under the emerging NOAA Climate Services Portal (NCSP). To carry out its mission, NOAA must be able to successfully integrate model output and other data and information from all of its discipline specific areas to understand and address the complexity of many environmental problems. The NCMP will be an initial access point for the emerging NOAA Climate Services Portal (NCSP), which is the basis for unified access to NOAA climate products and services. NCMP is currently collaborating with the emerging Environmental Projection Center (EPC) expected to be developed at the Earth System Research Laboratory in Boulder CO. Specifically, NCMP is being designed to: - Enable policy makers and resource managers to make informed national and global policy decisions using integrated climate and weather model outputs, observations, information, products, and other services for the scientist and the non-scientist; - Identify model to observational interoperability requirements for climate and weather system analysis and diagnostics; - Promote the coordination of an international reanalysis observational clearinghouse (i.e.., Reanalysis.org) spanning the worlds numerical processing Center’s for an “Ongoing Analysis of the Climate System”. NCMP will initially provide access capabilities to 3 of NOAA’s high volume Reanalysis data sets of the weather and climate systems: 1) NCEP’s Climate Forecast System Reanalysis (CFS-R); 2) NOAA’s Climate Diagnostics Center/ Earth System Research Laboratory (ESRL) Twentieth Century Reanalysis Project data set (20CR, G. Compo, et al.), a historical reanalysis that will provide climate information dating back to 1850 to the present; and 3) the CPC’s Upper Air Reanlaysis. NCMP will advance the highly successful NOAA National Operational Model Archive and Distribution System (NOMADS, Rutledge, BAMS 2006), and standards already in use including Unidata’s THREDDS (TDS), PMEL’s Live Access Server (LAS) and the GrADS Data Server (GDS) from COLA; the Department of Energy (DOE) Earth System Grid (ESG) and the associated IPCC Climate model archive located at the Program for Climate Model Diagnostics and Inter-comparison (PCMDI) through the ESG; and NOAA’s Unified Access Framework (UAF) effort; and core standards developed by Open Geospatial Consortium (OGC). The format neutral OPeNDAP protocol as used in the NOMADS system will also be a key aspect of the design of NCMP.

National Centers for Environmental Prediction

Science.gov Websites

Organization Search Enter text Search Navigation Bar End Cap Search EMC Go Branches Global Climate and Weather Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Products People GLOBAL CLIMATE & WEATHER MODELING Global Forecast System (GFS) products - Please see

Risky Business and the American Climate Prospectus: Economic Risks of Climate Change in the United States"

NASA Astrophysics Data System (ADS)

Gordon, K.; Houser, T.; Kopp, R. E., III; Hsiang, S. M.; Larsen, K.; Jina, A.; Delgado, M.; Muir-Wood, R.; Rasmussen, D.; Rising, J.; Mastrandrea, M.; Wilson, P. S.

2014-12-01

The United States faces a range of economic risks from global climate change - from increased flooding and storm damage, to climate-driven changes in crop yields and labor productivity, to heat-related strains on energy and public health systems. The Risky Business Project commissioned a groundbreaking new analysis of these and other climate risks by region of the country and sector of the economy. The American Climate Prospectus (ACP) links state-of-the-art climate models with econometric research of human responses to climate variability and cutting edge private sector risk assessment tools, the ACP offers decision-makers a data driven assessment of the specific risks they face. We describe the challenge, methods, findings, and policy implications of the national risk analysis, with particular focus on methodological innovations and novel insights.

Research Review, 1983

NASA Technical Reports Server (NTRS)

1984-01-01

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

NASA and the U.S. climate program - A problem in data management

NASA Technical Reports Server (NTRS)

Quann, J. J.

1978-01-01

NASA's contribution to the total data base for the National Climate Plan will be to produce climate data sets from its experimental space observing systems and to maximize the value of these data for climate analysis and prediction. Validated data sets will be provided to NOAA for inclusion into their overall diagnostic data base. NASA data management for the Climate Plan will involve: (1) cataloging and retrieval of large integrated and distributed data sets upon user demand, and (2) the storage equivalent of 100,000 digital data tapes. It will be the largest, most complex data system ever developed by NASA

Yinong Sun | NREL

Science.gov Websites

integration Impacts of climate change on energy system evolution Energy policy analysis Education M.E.M. in . Electric Sector Climate Impacts. International Energy Workshop, Maryland. View all NREL publications for

Climate Informatics

NASA Technical Reports Server (NTRS)

Monteleoni, Claire; Schmidt, Gavin A.; Alexander, Francis J.; Niculescu-Mizil, Alexandru; Steinhaeuser, Karsten; Tippett, Michael; Banerjee, Arindam; Blumenthal, M. Benno; Ganguly, Auroop R.; Smerdon, Jason E.;

A general scientific information system to support the study of climate-related data

NASA Technical Reports Server (NTRS)

Treinish, L. A.

1984-01-01

The development and use of NASA's Pilot Climate Data System (PCDS) are discussed. The PCDS is used as a focal point for managing and providing access to a large collection of actively used data for the Earth, ocean and atmospheric sciences. The PCDS provides uniform data catalogs, inventories, and access methods for selected NASA and non-NASA data sets. Scientific users can preview the data sets using graphical and statistical methods. The system has evolved from its original purpose as a climate data base management system in response to a national climate program, into an extensive package of capabilities to support many types of data sets from both spaceborne and surface based measurements with flexible data selection and analysis functions.

Climate Risk Assessment: Technical Guidance Manual for DoD Installations and Built Environment

DTIC Science & Technology

2016-09-06

climate change risks to DoD installations and the built environment. The approach, which we call “decision-scaling,” reveals the core sensitivity of...DoD installations to climate change . It is designed to illuminate the sensitivity of installations and their supporting infrastructure systems...including water and energy, to climate changes and other uncertainties without dependence on climate change projections. In this way the analysis and

Socio-climatic Exposure of an Afghan Poppy Farmer

NASA Astrophysics Data System (ADS)

Mankin, J. S.; Diffenbaugh, N. S.

2011-12-01

Many posit that climate impacts from anthropogenic greenhouse gas emissions will have consequences for the natural and agricultural systems on which humans rely for food, energy, and livelihoods, and therefore, on stability and human security. However, many of the potential mechanisms of action in climate impacts and human systems response, as well as the differential vulnerabilities of such systems, remain underexplored and unquantified. Here I present two initial steps necessary to characterize and quantify the consequences of climate change for farmer livelihood in Afghanistan, given both climate impacts and farmer vulnerabilities. The first is a conceptual model mapping the potential relationships between Afghanistan's climate, the winter agricultural season, and the country's political economy of violence and instability. The second is a utility-based decision model for assessing farmer response sensitivity to various climate impacts based on crop sensitivities. A farmer's winter planting decision can be modeled roughly as a tradeoff between cultivating the two crops that dominate the winter growing season-opium poppy (a climate tolerant cash crop) and wheat (a climatically vulnerable crop grown for household consumption). Early sensitivity analysis results suggest that wheat yield dominates farmer decision making variability; however, such initial results may dependent on the relative parameter ranges of wheat and poppy yields. Importantly though, the variance in Afghanistan's winter harvest yields of poppy and wheat is tightly linked to household livelihood and thus, is indirectly connected to the wider instability and insecurity within the country. This initial analysis motivates my focused research on the sensitivity of these crops to climate variability in order to project farmer well-being and decision sensitivity in a warmer world.

Analysis of hydrological processes across the Northern Eurasia with recently re-developed online informational system

NASA Astrophysics Data System (ADS)

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

2016-12-01

The volume of georeferenced datasets used for hydrology and climate research is growing immensely due to recent advances in modeling, high performance computers, and sensor networks, as well as initiation of a set of large scale complex global and regional monitoring experiments. To facilitate the management and analysis of these extensive data pools we developed Web-based data management, visualization, and analysis system - RIMS - http://earthatlas.sr.unh.edu/ (Rapid Integrated Mapping and Analysis System) with a focus on hydrological applications. Recently, under collaboration with Russian colleagues from the Institute of Monitoring of Climatic and Ecological Systems SB RAS, Russia, we significantly re-designed the RIMS to include the latest Web and GIS technologies in compliance with the Open Geospatial Consortium (OGC) standards. An upgraded RIMS can be successfully applied to address multiple research problems using an extensive data archive and embedded tools for data computations, visualizations and distributions. We will demonstrate current possibility of the system providing several results of applied data analysis fulfilled for territory of the Northern Eurasia. These results will include the analysis of historical, contemporary and future changes in climate and hydrology based on station and gridded data, investigations of recent extreme hydrological events, their anomalies, causes and potential impacts, and creation and analysis of new data sets through integration of social and geophysical data.

Computer models and the evidence of anthropogenic climate change: An epistemology of variety-of-evidence inferences and robustness analysis.

PubMed

Vezér, Martin A

2016-04-01

To study climate change, scientists employ computer models, which approximate target systems with various levels of skill. Given the imperfection of climate models, how do scientists use simulations to generate knowledge about the causes of observed climate change? Addressing a similar question in the context of biological modelling, Levins (1966) proposed an account grounded in robustness analysis. Recent philosophical discussions dispute the confirmatory power of robustness, raising the question of how the results of computer modelling studies contribute to the body of evidence supporting hypotheses about climate change. Expanding on Staley's (2004) distinction between evidential strength and security, and Lloyd's (2015) argument connecting variety-of-evidence inferences and robustness analysis, I address this question with respect to recent challenges to the epistemology robustness analysis. Applying this epistemology to case studies of climate change, I argue that, despite imperfections in climate models, and epistemic constraints on variety-of-evidence reasoning and robustness analysis, this framework accounts for the strength and security of evidence supporting climatological inferences, including the finding that global warming is occurring and its primary causes are anthropogenic. Copyright © 2016 Elsevier Ltd. All rights reserved.

Applying "Climate" system to teaching basic climatology and raising public awareness of climate change issues

NASA Astrophysics Data System (ADS)

Gordova, Yulia; Okladnikov, Igor; Titov, Alexander; Gordov, Evgeny

2016-04-01

While there is a strong demand for innovation in digital learning, available training programs in the environmental sciences have no time to adapt to rapid changes in the domain content. A joint group of scientists and university teachers develops and implements an educational environment for new learning experiences in basics of climatic science and its applications. This so-called virtual learning laboratory "Climate" contains educational materials and interactive training courses developed to provide undergraduate and graduate students with profound understanding of changes in regional climate and environment. The main feature of this Laboratory is that students perform their computational tasks on climate modeling and evaluation and assessment of climate change using the typical tools of the "Climate" information-computational system, which are usually used by real-life practitioners performing such kind of research. Students have an opportunity to perform computational laboratory works using information-computational tools of the system and improve skills of their usage simultaneously with mastering the subject. We did not create an artificial learning environment to pass the trainings. On the contrary, the main purpose of association of the educational block and computational information system was to familiarize students with the real existing technologies for monitoring and analysis of data on the state of the climate. Trainings are based on technologies and procedures which are typical for Earth system sciences. Educational courses are designed to permit students to conduct their own investigations of ongoing and future climate changes in a manner that is essentially identical to the techniques used by national and international climate research organizations. All trainings are supported by lectures, devoted to the basic aspects of modern climatology, including analysis of current climate change and its possible impacts ensuring effective links between theory and practice. Along with its usage in graduate and postgraduate education, "Climate" is used as a framework for a developed basic information course on climate change for common public. In this course basic concepts and problems of modern climate change and its possible consequences are described for non-specialists. The course will also include links to relevant information resources on topical issues of Earth Sciences and a number of case studies, which are carried out for a selected region to consolidate the received knowledge.

Developing the evidence base for mainstreaming adaptation of stormwater systems to climate change.

PubMed

Gersonius, B; Nasruddin, F; Ashley, R; Jeuken, A; Pathirana, A; Zevenbergen, C

2012-12-15

In a context of high uncertainty about hydro-climatic variables, the development of updated methods for climate impact and adaptation assessment is as important, if not more important than the provision of improved climate change data. In this paper, we introduce a hybrid method to facilitate mainstreaming adaptation of stormwater systems to climate change: i.e., the Mainstreaming method. The Mainstreaming method starts with an analysis of adaptation tipping points (ATPs), which is effect-based. These are points of reference where the magnitude of climate change is such that acceptable technical, environmental, societal or economic standards may be compromised. It extends the ATP analysis to include aspects from a bottom-up approach. The extension concerns the analysis of adaptation opportunities in the stormwater system. The results from both analyses are then used in combination to identify and exploit Adaptation Mainstreaming Moments (AMMs). Use of this method will enhance the understanding of the adaptive potential of stormwater systems. We have applied the proposed hybrid method to the management of flood risk for an urban stormwater system in Dordrecht (the Netherlands). The main finding of this case study is that the application of the Mainstreaming method helps to increase the no-/low-regret character of adaptation for several reasons: it focuses the attention on the most urgent effects of climate change; it is expected to lead to potential cost reductions, since adaptation options can be integrated into infrastructure and building design at an early stage instead of being applied separately; it will lead to the development of area-specific responses, which could not have been developed on a higher scale level; it makes it possible to take account of local values and sensibilities, which contributes to increased public and political support for the adaptive strategies. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatial and Climate Literacy: Connecting Urban and Rural Students

NASA Astrophysics Data System (ADS)

Boger, R. A.; Low, R.; Mandryk, C.; Gorokhovich, Y.

2013-12-01

Through a collaboration between the University of Nebraska-Lincoln (UNL), Brooklyn College, and Lehman College, four independent but linked modules were developed and piloted in courses offered at Brooklyn College and UNL simultaneously. Module content includes climate change science and literacy principles, using geospatial technologies (GIS, GPS and remote sensing) as a vehicle to explore issues associated with global, regional, and local climate change in a concrete, quantitative and visual way using Internet resources available through NASA, NOAA, USGS, and a variety of universities and organizations. The materials take an Earth system approach and incorporate sustainability, resilience, water and watersheds, weather and climate, and food security topics throughout the semester. The research component of the project focuses on understanding the role of spatial literacy and authentic inquiry based experiences in climate change understanding and improving confidence in teaching science. In particular, engaging learners in both climate change science and GIS simultaneously provides opportunities to examine questions about the role that data manipulation, mental representation, and spatial literacy plays in students' abilities to understand the consequences and impacts of climate change. Pre and post surveys were designed to discern relationships between spatial cognitive processes and effective acquisition of climate change science concepts in virtual learning environments as well as alignment of teacher's mental models of nature of science and climate system dynamics to scientific models. The courses will again be offered simultaneously in Spring 2014 at Brooklyn College and UNL. Evaluation research will continue to examine the connections between spatial and climate literacy and teacher's mental models (via qualitative textual analysis using MAXQDA text analysis, and UCINET social network analysis programs) as well as how urban-rural learning interactions may influence climate literacy.

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.

Modeling Climate-Water Impacts on Electricity Sector Capacity Expansion: Preprint

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

Cohen, S. M.; Macknick, J.; Averyt, K.

2014-05-01

Climate change has the potential to exacerbate water availability concerns for thermal power plant cooling, which is responsible for 41% of U.S. water withdrawals. This analysis describes an initial link between climate, water, and electricity systems using the National Renewable Energy Laboratory (NREL) Regional Energy Deployment System (ReEDS) electricity system capacity expansion model. Average surface water projections from Coupled Model Intercomparison Project 3 (CMIP3) data are applied to surface water rights available to new generating capacity in ReEDS, and electric sector growth is compared with and without climate-influenced water rights. The mean climate projection has only a small impact onmore » national or regional capacity growth and water use because most regions have sufficient unappropriated or previously retired water rights to offset climate impacts. Climate impacts are notable in southwestern states that purchase fewer water rights and obtain a greater share from wastewater and other higher-cost water resources. The electric sector climate impacts demonstrated herein establish a methodology to be later exercised with more extreme climate scenarios and a more rigorous representation of legal and physical water availability.« less

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Contacts Change Log Events Calendar Numerical Forecast Systems NCEP Model Analysis and Guidance Page [< Modeling Center NOAA Center for Weather and Climate Prediction (NCWCP) 5830 University Research Court

Impact of four-dimensional data assimilation (FDDA) on urban climate analysis

NASA Astrophysics Data System (ADS)

Pan, Linlin; Liu, Yubao; Liu, Yuewei; Li, Lei; Jiang, Yin; Cheng, Will; Roux, Gregory

2015-12-01

This study investigates the impact of four-dimensional data assimilation (FDDA) on urban climate analysis, which employs the NCAR (National Center for Atmospheric Research) WRF (the weather research and forecasting model) based on climate FDDA (CFDDA) technology to develop an urban-scale microclimatology database for the Shenzhen area, a rapidly developing metropolitan located along the southern coast of China, where uniquely high-density observations, including ultrahigh-resolution surface AWS (automatic weather station) network, radio sounding, wind profilers, radiometers, and other weather observation platforms, have been installed. CFDDA is an innovative dynamical downscaling regional climate analysis system that assimilates diverse regional observations; and has been employed to produce a 5 year multiscale high-resolution microclimate analysis by assimilating high-density observations at Shenzhen area. The CFDDA system was configured with four nested-grid domains at grid sizes of 27, 9, 3, and 1 km, respectively. This research evaluates the impact of assimilating high-resolution observation data on reproducing the refining features of urban-scale circulations. Two experiments were conducted with a 5 year run using CFSR (climate forecast system reanalysis) as boundary and initial conditions: one with CFDDA and the other without. The comparisons of these two experiments with observations indicate that CFDDA greatly reduces the model analysis error and is able to realistically analyze the microscale features such as urban-rural-coastal circulation, land/sea breezes, and local-hilly terrain thermal circulations. It is demonstrated that the urbanization can produce 2.5 k differences in 2 m temperatures, delays/speeds up the land/sea breeze development, and interacts with local mountain-valley circulations.

[CLIMATE CHANGE AND ALLERGIC AIRWAY DISEASE] OBSERVATIONAL,LABORATORY, AND MODELING STUDIES OF THE IMPACTS OF CLIMATE CHANGE ONALLERGIC AIRWAY DISEASE

EPA Science Inventory

Based on these data and preliminary studies, this proposal will be composed of a multiscale source-to-dose analysis approach for assessing the exposure interactions of environmental and biological systems. Once the entire modeling system is validated, it will run f...

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

HydroClimATe: hydrologic and climatic analysis toolkit

USGS Publications Warehouse

Dickinson, Jesse; Hanson, Randall T.; Predmore, Steven K.

2014-01-01

The potential consequences of climate variability and climate change have been identified as major issues for the sustainability and availability of the worldwide water resources. Unlike global climate change, climate variability represents deviations from the long-term state of the climate over periods of a few years to several decades. Currently, rich hydrologic time-series data are available, but the combination of data preparation and statistical methods developed by the U.S. Geological Survey as part of the Groundwater Resources Program is relatively unavailable to hydrologists and engineers who could benefit from estimates of climate variability and its effects on periodic recharge and water-resource availability. This report documents HydroClimATe, a computer program for assessing the relations between variable climatic and hydrologic time-series data. HydroClimATe was developed for a Windows operating system. The software includes statistical tools for (1) time-series preprocessing, (2) spectral analysis, (3) spatial and temporal analysis, (4) correlation analysis, and (5) projections. The time-series preprocessing tools include spline fitting, standardization using a normal or gamma distribution, and transformation by a cumulative departure. The spectral analysis tools include discrete Fourier transform, maximum entropy method, and singular spectrum analysis. The spatial and temporal analysis tool is empirical orthogonal function analysis. The correlation analysis tools are linear regression and lag correlation. The projection tools include autoregressive time-series modeling and generation of many realizations. These tools are demonstrated in four examples that use stream-flow discharge data, groundwater-level records, gridded time series of precipitation data, and the Multivariate ENSO Index.

A Decision Analysis Tool for Climate Impacts, Adaptations, and Vulnerabilities

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

Omitaomu, Olufemi A; Parish, Esther S; Nugent, Philip J

Climate change related extreme events (such as flooding, storms, and drought) are already impacting millions of people globally at a cost of billions of dollars annually. Hence, there are urgent needs for urban areas to develop adaptation strategies that will alleviate the impacts of these extreme events. However, lack of appropriate decision support tools that match local applications is limiting local planning efforts. In this paper, we present a quantitative analysis and optimization system with customized decision support modules built on geographic information system (GIS) platform to bridge this gap. This platform is called Urban Climate Adaptation Tool (Urban-CAT). Formore » all Urban-CAT models, we divide a city into a grid with tens of thousands of cells; then compute a list of metrics for each cell from the GIS data. These metrics are used as independent variables to predict climate impacts, compute vulnerability score, and evaluate adaptation options. Overall, the Urban-CAT system has three layers: data layer (that contains spatial data, socio-economic and environmental data, and analytic data), middle layer (that handles data processing, model management, and GIS operation), and application layer (that provides climate impacts forecast, adaptation optimization, and site evaluation). The Urban-CAT platform can guide city and county governments in identifying and planning for effective climate change adaptation strategies.« less

The Effect of Mitigation Policy on Regional Climate Impacts on the U.S. Electric Sector

NASA Astrophysics Data System (ADS)

Cohen, S. M.; Sun, Y.; Strzepek, K.; McFarland, J.; Boehlert, B.; Fant, C.

2017-12-01

Climate change can influence the U.S. electricity sector in many ways, the nature of which can be shaped by energy and environmental policy choices. Changing temperatures affect electricity demand largely through heating and cooling needs, and temperatures also affect generation and transmission system performance. Altered precipitation patterns affect the regional and seasonal distribution of surface water runoff, which changes hydropower operation and thermal cooling water availability. The extent to which these stimuli influence U.S. power sector operation and planning will depend to some extent on whether or not proactive policies are enacted to mitigate these impacts. Mitigation policies such as CO2 emissions limits or technology restrictions can change the makeup of the electricity system while reducing the extent of climate change itself. We use the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS), a U.S. electric sector capacity expansion model, to explore electric sector evolution through 2050 under alternative climate and policy assumptions. The model endogenously represents climate impacts on load, power system performance, cooling water availability, and hydropower, allowing internally consistent system responses to climate change along with projected technology, market, and policy conditions. We compare climate impacts across 5 global circulation models for a 8.5 W/m2 representative concentration pathway (RCP) without a climate mitigation policy and a 4.5 W/m2 RCP with climate mitigation. Climate drivers affect the capacity and generation mix at the national and regional levels, with relative growth of wind, solar, and natural gas-based technologies depending on local electricity system characteristics. These differences affect regional economic impacts, measured here as changes to electricity price and system costs. Mitigation policy reduces the economic and system impacts of climate change largely by moderating temperature-induced load but also by lessening water- and temperature-based performance constraints. Policy impacts are nuanced and region-specific, and this analysis underscores the importance of climate mitigation policy to regional electricity system planning decisions.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Probabilistic Estimates of Climate Impacts of the Paris Agreement and Contributions from Different Countries.

NASA Astrophysics Data System (ADS)

Sokolov, A. P.; Paltsev, S.; Chen, Y. H. H.; Monier, E.; Libardoni, A. G.; Forest, C. E.

2017-12-01

In December of 2015 during COP21 meeting in Paris almost 200 countries signed an agreement pledging to reduce their anthropogenic greenhouse gas (GHG) emissions. Recently USA announced plans to withdraw from the agreement. In this study, we estimate an impact of this decision on future climate using the MIT Integrated Global System Model, which consists of the human activity model, Economic Projection and Policy Analysis (EPPA) model, and a climate model of intermediate complexity, the MIT Earth System Model (MESM). For comparison, we also estimated impacts of possible withdrawals of China, Europe or India. In addition to the "no climate policy" scenario, we consider five emissions scenarios: Paris, Paris_no_USA, Paris_no_EUR and so on. Climate simulations were carried out from 1861 to 2005 driven by prescribed changes in GHGs and natural forcings and them continued to 2100 driven by GHG emissions produced by EPPA model. Because Paris agreement only cover the period up to 2030, last five scenarios were created assuming that emissions or carbon intensity will continue to decrease after 2030 at the same rate as in the 2020-2030 period. To account for uncertainty in climate system response to external forcing, we carry out 400 member ensembles on climate simulations for each scenario. Probability distributions for climate parameters are obtained by comparing simulated climate for 1861 to 2010 with observations. Our analysis shows that, full implementation of Paris agreement (under above-descried assumptions) will increase probability of surface air temperature in the last decade of this century increasing by less than 3oC relative to pre-industrial form about 20% for "no climate policy" to about 86%. Withdrawal of USA, China, Europe or India will decrease this probability to about 63, 67, 75 and 82%, respectively.

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

PubMed

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

2017-09-11

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Climate Change Impacts on Crop Production in Nigeria

NASA Astrophysics Data System (ADS)

Mereu, V.; Gallo, A.; Carboni, G.; Spano, D.

2011-12-01

The agricultural sector in Nigeria is particularly important for the country's food security, natural resources, and growth agenda. The cultivable areas comprise more than 70% of the total area; however, the cultivated area is about the 35% of the total area. The most important components in the food basket of the nation are cereals and tubers, which include rice, maize, corn, millet, sorghum, yam, and cassava. These crops represent about 80% of the total agricultural product in Nigeria (from NPAFS). The major crops grown in the country can be divided into food crops (produced for consumption) and export products. Despite the importance of the export crops, the primary policy of agriculture is to make Nigeria self-sufficient in its food and fiber requirements. The projected impacts of future climate change on agriculture and water resources are expected to be adverse and extensive in these area. This implies the need for actions and measures to adapt to climate change impacts, and especially as they affect agriculture, the primary sector for Nigerian economy. In the framework of the Project Climate Risk Analysis in Nigeria (founded by World Bank Contract n.7157826), a study was made to assess the potential impact of climate change on the main crops that characterize Nigerian agriculture. The DSSAT-CSM (Decision Support System for Agrotechnology Transfer - Cropping System Model) software, version 4.5 was used for the analysis. Crop simulation models included in DSSAT are tools that simulate physiological processes of crop growth, development and production by combining genetic crop characteristics and environmental (soil and weather) conditions. For each selected crop, the models were calibrated to evaluate climate change impacts on crop production. The climate data used for the analysis are derived by the Regional Circulation Model COSMO-CLM, from 1971 to 2065, at 8 km of spatial resolution. The RCM model output was "perturbed" with 10 Global Climate Models to have a wide variety of possible climate projections for the impact analysis. Multiple combinations of soil and climate conditions and crop management and varieties were considered for each Agro-Ecological Zone (AEZ) of Nigeria. A sensitivity analysis was made to evaluate the model response to changes in precipitation and temperature. The climate impact assessment was made by comparing the yield obtained with the climate data for the present period and the yield obtainable under future climate conditions. The results were analyzed at state, AEZ and country levels. The analysis shows a general reduction in crop yields in particular in the dryer regions of northern Nigeria.

Local indicators of climate change: The potential contribution of local knowledge to climate research

PubMed Central

Reyes-García, Victoria; Fernández-Llamazares, Álvaro; Guèze, Maximilien; Garcés, Ariadna; Mallo, Miguel; Vila-Gómez, Margarita; Vilaseca, Marina

2016-01-01

Local knowledge has been proposed as a place-based tool to ground-truth climate models and to narrow their geographic sensitivity. To assess the potential role of local knowledge in our quest to understand better climate change and its impacts, we first need to critically review the strengths and weaknesses of local knowledge of climate change and the potential complementarity with scientific knowledge. With this aim, we conducted a systematic, quantitative meta-analysis of published peer-reviewed documents reporting local indicators of climate change (including both local observations of climate change and observed impacts on the biophysical and the social systems). Overall, primary data on the topic are not abundant, the methodological development is incipient, and the geographical extent is unbalanced. On the 98 case studies documented, we recorded the mention of 746 local indicators of climate change, mostly corresponding to local observations of climate change (40%), but also to observed impacts on the physical (23%), the biological (19%), and the socioeconomic (18%) systems. Our results suggest that, even if local observations of climate change are the most frequently reported type of change, the rich and fine-grained knowledge in relation to impacts on biophysical systems could provide more original contributions to our understanding of climate change at local scale. PMID:27642368

Climate change as an ecosystem architect: implications to rare plant ecology, conservation, and restoration

Treesearch

Constance I. Millar

2003-01-01

Recent advances in earth system sciences have revealed significant new information relevant to rare plant ecology and conservation. Analysis of climate change at high resolution with new and precise proxies of paleotemperatures reveals a picture over the past two million years of oscillatory climate change operating simultaneously at multiple timescales. Low-frequency...

Assessment of Projected Temperature Impacts from Climate Change on the U.S. Electric Power Sector Using the Integrated Planning Model

EPA Science Inventory

The energy sector is considered to be one of the most vulnerable to climate change. This study is a first-order analysis of the potential climate change impacts on the U.S. electric power sector, measuring the energy, environmental, and economic impacts of power system changes du...

The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements in Understanding AMOC

NASA Astrophysics Data System (ADS)

Lucas, S. E.

2016-12-01

The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). This poster will present the recently funded CVP projects on improving the understanding Atlantic Meridional Overturning Circulation (AMOC), its impact on decadal predictability, and its relationship with the overall climate system.

Development of the virtual research environment for analysis, evaluation and prediction of global climate change impacts on the regional environment

NASA Astrophysics Data System (ADS)

Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander; Fazliev, Alexander

2017-04-01

Description and the first results of the Russian Science Foundation project "Virtual computational information environment for analysis, evaluation and prediction of the impacts of global climate change on the environment and climate of a selected region" is presented. The project is aimed at development of an Internet-accessible computation and information environment providing unskilled in numerical modelling and software design specialists, decision-makers and stakeholders with reliable and easy-used tools for in-depth statistical analysis of climatic characteristics, and instruments for detailed analysis, assessment and prediction of impacts of global climate change on the environment and climate of the targeted region. In the framework of the project, approaches of "cloud" processing and analysis of large geospatial datasets will be developed on the technical platform of the Russian leading institution involved in research of climate change and its consequences. Anticipated results will create a pathway for development and deployment of thematic international virtual research laboratory focused on interdisciplinary environmental studies. VRE under development will comprise best features and functionality of earlier developed information and computing system CLIMATE (http://climate.scert.ru/), which is widely used in Northern Eurasia environment studies. The Project includes several major directions of research listed below. 1. Preparation of geo-referenced data sets, describing the dynamics of the current and possible future climate and environmental changes in detail. 2. Improvement of methods of analysis of climate change. 3. Enhancing the functionality of the VRE prototype in order to create a convenient and reliable tool for the study of regional social, economic and political consequences of climate change. 4. Using the output of the first three tasks, compilation of the VRE prototype, its validation, preparation of applicable detailed description of climate change in Western Siberia, and dissemination of the Project results. Results of the first stage of the Project implementation are presented. This work is supported by the Russian Science Foundation grant No16-19-10257.

Testing a theory of organizational culture, climate and youth outcomes in child welfare systems: a United States national study.

PubMed

Williams, Nathaniel J; Glisson, Charles

2014-04-01

Theories of organizational culture and climate (OCC) applied to child welfare systems hypothesize that strategic dimensions of organizational culture influence organizational climate and that OCC explains system variance in youth outcomes. This study provides the first structural test of the direct and indirect effects of culture and climate on youth outcomes in a national sample of child welfare systems and isolates specific culture and climate dimensions most associated with youth outcomes. The study applies multilevel path analysis (ML-PA) to a U.S. nationwide sample of 2,380 youth in 73 child welfare systems participating in the second National Survey of Child and Adolescent Well-being. Youths were selected in a national, two-stage, stratified random sample design. Youths' psychosocial functioning was assessed by caregivers' responses to the Child Behavior Checklist at intake and at 18-month follow-up. OCC was assessed by front-line caseworkers' (N=1,740) aggregated responses to the Organizational Social Context measure. Comparison of the a priori and subsequent trimmed models confirmed a reduced model that excluded rigid organizational culture and explained 70% of the system variance in youth outcomes. Controlling for youth- and system-level covariates, systems with more proficient and less resistant organizational cultures exhibited more functional, more engaged, and less stressful climates. Systems with more proficient cultures and more engaged, more functional, and more stressful climates exhibited superior youth outcomes. Findings suggest child welfare administrators can support service effectiveness with interventions that improve specific dimensions of culture and climate. Copyright © 2013 Elsevier Ltd. All rights reserved.

Testing a theory of organizational culture, climate and youth outcomes in child welfare systems: A United States national study

PubMed Central

Williams, Nathaniel J.; Glisson, Charles

2013-01-01

Theories of organizational culture and climate (OCC) applied to child welfare systems hypothesize that strategic dimensions of organizational culture influence organizational climate and that OCC explains system variance in youth outcomes. This study provides the first structural test of the direct and indirect effects of culture and climate on youth outcomes in a national sample of child welfare systems and isolates specific culture and climate dimensions most associated with youth outcomes. The study applies multilevel path analysis (ML-PA) to a U.S. nationwide sample of 2,380 youth in 73 child welfare systems participating in the second National Survey of Child and Adolescent Well-being. Youths were selected in a national, two-stage, stratified random sample design. Youths’ psychosocial functioning was assessed by caregivers’ responses to the Child Behavior Checklist at intake and at 18-month follow-up. OCC was assessed by front-line caseworkers’ (N=1,740) aggregated responses to the Organizational Social Context measure. Comparison of the a priori and subsequent trimmed models confirmed a reduced model that excluded rigid organizational culture and explained 70% of the system variance in youth outcomes. Controlling for youth- and system-level covariates, systems with more proficient and less resistant organizational cultures exhibited more functional, more engaged, and less stressful climates. Systems with more proficient cultures and more engaged, more functional, and more stressful climates exhibited superior youth outcomes. Findings suggest child welfare administrators can support service effectiveness with interventions that improve specific dimensions of culture and climate. PMID:24094999

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.

Coupled socioeconomic-crop modelling for the participatory local analysis of climate change impacts on smallholder farmers in Guatemala

NASA Astrophysics Data System (ADS)

Malard, J. J.; Adamowski, J. F.; Wang, L. Y.; Rojas, M.; Carrera, J.; Gálvez, J.; Tuy, H. A.; Melgar-Quiñonez, H.

2015-12-01

The modelling of the impacts of climate change on agriculture requires the inclusion of socio-economic factors. However, while cropping models and economic models of agricultural systems are common, dynamically coupled socio-economic-biophysical models have not received as much success. A promising methodology for modelling the socioeconomic aspects of coupled natural-human systems is participatory system dynamics modelling, in which stakeholders develop mental maps of the socio-economic system that are then turned into quantified simulation models. This methodology has been successful in the water resources management field. However, while the stocks and flows of water resources have also been represented within the system dynamics modelling framework and thus coupled to the socioeconomic portion of the model, cropping models are ill-suited for such reformulation. In addition, most of these system dynamics models were developed without stakeholder input, limiting the scope for the adoption and implementation of their results. We therefore propose a new methodology for the analysis of climate change variability on agroecosystems which uses dynamically coupled system dynamics (socio-economic) and biophysical (cropping) models to represent both physical and socioeconomic aspects of the agricultural system, using two case studies (intensive market-based agricultural development versus subsistence crop-based development) from rural Guatemala. The system dynamics model component is developed with relevant governmental and NGO stakeholders from rural and agricultural development in the case study regions and includes such processes as education, poverty and food security. Common variables with the cropping models (yield and agricultural management choices) are then used to dynamically couple the two models together, allowing for the analysis of the agroeconomic system's response to and resilience against various climatic and socioeconomic shocks.

[Medication error management climate and perception for system use according to construction of medication error prevention system].

PubMed

Kim, Myoung Soo

2012-08-01

The purpose of this cross-sectional study was to examine current status of IT-based medication error prevention system construction and the relationships among system construction, medication error management climate and perception for system use. The participants were 124 patient safety chief managers working for 124 hospitals with over 300 beds in Korea. The characteristics of the participants, construction status and perception of systems (electric pharmacopoeia, electric drug dosage calculation system, computer-based patient safety reporting and bar-code system) and medication error management climate were measured in this study. The data were collected between June and August 2011. Descriptive statistics, partial Pearson correlation and MANCOVA were used for data analysis. Electric pharmacopoeia were constructed in 67.7% of participating hospitals, computer-based patient safety reporting systems were constructed in 50.8%, electric drug dosage calculation systems were in use in 32.3%. Bar-code systems showed up the lowest construction rate at 16.1% of Korean hospitals. Higher rates of construction of IT-based medication error prevention systems resulted in greater safety and a more positive error management climate prevailed. The supportive strategies for improving perception for use of IT-based systems would add to system construction, and positive error management climate would be more easily promoted.

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

NASA Astrophysics Data System (ADS)

Mantua, N.; Snover, A.

2006-12-01

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

ClimatePipes: User-Friendly Data Access, Manipulation, Analysis & Visualization of Community Climate Models

NASA Astrophysics Data System (ADS)

Chaudhary, A.; DeMarle, D.; Burnett, B.; Harris, C.; Silva, W.; Osmari, D.; Geveci, B.; Silva, C.; Doutriaux, C.; Williams, D. N.

2013-12-01

The impact of climate change will resonate through a broad range of fields including public health, infrastructure, water resources, and many others. Long-term coordinated planning, funding, and action are required for climate change adaptation and mitigation. Unfortunately, widespread use of climate data (simulated and observed) in non-climate science communities is impeded by factors such as large data size, lack of adequate metadata, poor documentation, and lack of sufficient computational and visualization resources. We present ClimatePipes to address many of these challenges by creating an open source platform that provides state-of-the-art, user-friendly data access, analysis, and visualization for climate and other relevant geospatial datasets, making the climate data available to non-researchers, decision-makers, and other stakeholders. The overarching goals of ClimatePipes are: - Enable users to explore real-world questions related to climate change. - Provide tools for data access, analysis, and visualization. - Facilitate collaboration by enabling users to share datasets, workflows, and visualization. ClimatePipes uses a web-based application platform for its widespread support on mainstream operating systems, ease-of-use, and inherent collaboration support. The front-end of ClimatePipes uses HTML5 (WebGL, Canvas2D, CSS3) to deliver state-of-the-art visualization and to provide a best-in-class user experience. The back-end of the ClimatePipes is built around Python using the Visualization Toolkit (VTK, http://vtk.org), Climate Data Analysis Tools (CDAT, http://uv-cdat.llnl.gov), and other climate and geospatial data processing tools such as GDAL and PROJ4. ClimatePipes web-interface to query and access data from remote sources (such as ESGF). Shown in the figure is climate data layer from ESGF on top of map data layer from OpenStreetMap. The ClimatePipes workflow editor provides flexibility and fine grained control, and uses the VisTrails (http://www.vistrails.org) workflow engine in the backend.

Status and Preliminary Evaluation for Chinese Re-Analysis Datasets

NASA Astrophysics Data System (ADS)

bin, zhao; chunxiang, shi; tianbao, zhao; dong, si; jingwei, liu

2016-04-01

Based on operational T639L60 spectral model, combined with Hybird_GSI assimilation system by using meteorological observations including radiosondes, buoyes, satellites el al., a set of Chinese Re-Analysis (CRA) datasets is developing by Chinese National Meteorological Information Center (NMIC) of Chinese Meteorological Administration (CMA). The datasets are run at 30km (0.28°latitude / longitude) resolution which holds higher resolution than most of the existing reanalysis dataset. The reanalysis is done in an effort to enhance the accuracy of historical synoptic analysis and aid to find out detailed investigation of various weather and climate systems. The current status of reanalysis is in a stage of preliminary experimental analysis. One-year forecast data during Jun 2013 and May 2014 has been simulated and used in synoptic and climate evaluation. We first examine the model prediction ability with the new assimilation system, and find out that it represents significant improvement in Northern and Southern hemisphere, due to addition of new satellite data, compared with operational T639L60 model, the effect of upper-level prediction is improved obviously and overall prediction stability is enhanced. In climatological analysis, compared with ERA-40, NCEP/NCAR and NCEP/DOE reanalyses, the results show that surface temperature simulates a bit lower in land and higher over ocean, 850-hPa specific humidity reflects weakened anomaly and the zonal wind value anomaly is focus on equatorial tropics. Meanwhile, the reanalysis dataset shows good ability for various climate index, such as subtropical high index, ESMI (East-Asia subtropical Summer Monsoon Index) et al., especially for the Indian and western North Pacific monsoon index. Latter we will further improve the assimilation system and dynamical simulating performance, and obtain 40-years (1979-2018) reanalysis datasets. It will provide a more comprehensive analysis for synoptic and climate diagnosis.

National Climate Assessment - Land Data Assimilation System (NCA-LDAS) Data at NASA GES DISC

NASA Technical Reports Server (NTRS)

Rui, Hualan; Teng, Bill; Vollmer, Bruce; Jasinski, Michael; Mocko, David; Kempler, Steven

2016-01-01

As part of NASA's active participation in the Interagency National Climate Assessment (NCA) program, the Goddard Space Flight Center's Hydrological Sciences Laboratory (HSL) is supporting an Integrated Terrestrial Water Analysis, by using NASA's Land Information System (LIS) and Land Data Assimilation System (LDAS) capabilities. To maximize the benefit of the NCA-LDAS, on completion of planned model runs and uncertainty analysis, NASA will provide open access to all NCA-LDAS components, including input data, output fields, and indicator data, to other NCA-teams and the general public. The NCA-LDAS data will be archived at the NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) and can be accessed via direct ftp, THREDDS, Mirador search and download, and Giovanni visualization and analysis system.

Environmental impacts of high penetration renewable energy scenarios for Europe

NASA Astrophysics Data System (ADS)

Berrill, Peter; Arvesen, Anders; Scholz, Yvonne; Gils, Hans Christian; Hertwich, Edgar G.

2016-01-01

The prospect of irreversible environmental alterations and an increasingly volatile climate pressurises societies to reduce greenhouse gas emissions, thereby mitigating climate change impacts. As global electricity demand continues to grow, particularly if considering a future with increased electrification of heat and transport sectors, the imperative to decarbonise our electricity supply becomes more urgent. This letter implements outputs of a detailed power system optimisation model into a prospective life cycle analysis framework in order to present a life cycle analysis of 44 electricity scenarios for Europe in 2050, including analyses of systems based largely on low-carbon fossil energy options (natural gas, and coal with carbon capture and storage (CCS)) as well as systems with high shares of variable renewable energy (VRE) (wind and solar). VRE curtailments and impacts caused by extra energy storage and transmission capabilities necessary in systems based on VRE are taken into account. The results show that systems based largely on VRE perform much better regarding climate change and other impact categories than the investigated systems based on fossil fuels. The climate change impacts from Europe for the year 2050 in a scenario using primarily natural gas are 1400 Tg CO2-eq while in a scenario using mostly coal with CCS the impacts are 480 Tg CO2-eq. Systems based on renewables with an even mix of wind and solar capacity generate impacts of 120-140 Tg CO2-eq. Impacts arising as a result of wind and solar variability do not significantly compromise the climate benefits of utilising these energy resources. VRE systems require more infrastructure leading to much larger mineral resource depletion impacts than fossil fuel systems, and greater land occupation impacts than systems based on natural gas. Emissions and resource requirements from wind power are smaller than from solar power.

System Dynamics to Climate-Driven Water Budget Analysis in the Eastern Snake Plains Aquifer

NASA Astrophysics Data System (ADS)

Ryu, J.; Contor, B.; Wylie, A.; Johnson, G.; Allen, R. G.

2010-12-01

Climate variability, weather extremes and climate change continue to threaten the sustainability of water resources in the western United States. Given current climate change projections, increasing temperature is likely to modify the timing, form, and intensity of precipitation events, which consequently affect regional and local hydrologic cycles. As a result, drought, water shortage, and subsequent water conflicts may become an increasing threat in monotone hydrologic systems in arid lands, such as the Eastern Snake Plain Aquifer (ESPA). The ESPA, in particular, is a critical asset in the state of Idaho. It is known as the economic lifeblood for more than half of Idaho’s population so that water resources availability and aquifer management due to climate change is of great interest, especially over the next few decades. In this study, we apply system dynamics as a methodology with which to address dynamically complex problems in ESPA’s water resources management. Aquifer recharge and discharge dynamics are coded in STELLA modeling system as input and output, respectively to identify long-term behavior of aquifer responses to climate-driven hydrological changes.

A Sustainable Early Warning System for Climate Change Impacts on Water Quality Management

NASA Astrophysics Data System (ADS)

Lee, T.; Tung, C.; Chung, N.

2007-12-01

In this era of rapid social and technological change leading to interesting life complexity and environmental displacement, both positive and negative effects among ecosystems call for a balance in which there are impacts by climate changes. Early warning systems for climate change impacts are necessary in order to allow society as a whole to properly and usefully assimilate the masses of new information and knowledge. Therefore, our research addresses to build up a sustainable early warning mechanism. The main goal is to mitigate the cumulative impacts on the environment of climate change and enhance adaptive capacities. An effective early warning system has been proven for protection. However, there is a problem that estimate future climate changes would be faced with high uncertainty. In general, take estimations for climate change impacts would use the data from General Circulation Models and take the analysis as the Intergovernmental Panel on Climate Change declared. We follow the course of the method for analyzing climate change impacts and attempt to accomplish the sustainable early warning system for water quality management. Climate changes impact not only on individual situation but on short-term variation and long-term gradually changes. This kind characteristic should adopt the suitable warning system for long-term formulation and short- term operation. To continue the on-going research of the long-term early warning system for climate change impacts on water quality management, the short-term early warning system is established by using local observation data for reappraising the warning issue. The combination of long-term and short-term system can provide more circumstantial details. In Taiwan, a number of studies have revealed that climate change impacts on water quality, especially in arid period, the concentration of biological oxygen demand may turn into worse. Rapid population growth would also inflict injury on its assimilative capacity to degenerate. To concern about those items, the sustainable early warning system is established and the initiative fall into the following categories: considering the implications for policies, applying adaptive strategies and informing the new climate changes. By setting up the framework of early warning system expectantly can defend stream area from impacts damaging and in sure the sustainable development.

A climate trend analysis of Uganda

USGS Publications Warehouse

Funk, Christopher C.; Rowland, Jim; Eilerts, Gary; White, Libby

2012-01-01

This brief report, drawing from a multi-year effort by the U.S. Agency for International Development (USAID) Famine Early Warning Systems Network (FEWS NET), identifies observed changes in rainfall and temperature in Uganda, based on an analysis of a quality-controlled, long time series of station observations throughout Uganda. Extending recent trends forward, it also provides a current and near-future context for understanding the actual nature of climate change impacts in the country, and a basis for identifying climate adaptations that may protect and improve the country's food security.

Uncertainty as Knowledge: Constraints on Policy Choices Provided by Analysis of Uncertainty

NASA Astrophysics Data System (ADS)

Lewandowsky, S.; Risbey, J.; Smithson, M.; Newell, B. R.

2012-12-01

Uncertainty forms an integral part of climate science, and it is often cited in connection with arguments against mitigative action. We argue that an analysis of uncertainty must consider existing knowledge as well as uncertainty, and the two must be evaluated with respect to the outcomes and risks associated with possible policy options. Although risk judgments are inherently subjective, an analysis of the role of uncertainty within the climate system yields two constraints that are robust to a broad range of assumptions. Those constraints are that (a) greater uncertainty about the climate system is necessarily associated with greater expected damages from warming, and (b) greater uncertainty translates into a greater risk of the failure of mitigation efforts. These ordinal constraints are unaffected by subjective or cultural risk-perception factors, they are independent of the discount rate, and they are independent of the magnitude of the estimate for climate sensitivity. The constraints mean that any appeal to uncertainty must imply a stronger, rather than weaker, need to cut greenhouse gas emissions than in the absence of uncertainty.

The future of climate science analysis in a coming era of exascale computing

NASA Astrophysics Data System (ADS)

Bates, S. C.; Strand, G.

2013-12-01

Projections of Community Earth System Model (CESM) output based on the growth of data archived over 2000-2012 at all of our computing sites (NCAR, NERSC, ORNL) show that we can expect to reach 1,000 PB (1 EB) sometime in the next decade or so. The current paradigms of using site-based archival systems to hold these data that are then accessed via portals or gateways, downloading the data to a local system, and then processing/analyzing the data will be irretrievably broken before then. From a climate modeling perspective, the expertise involved in making climate models themselves efficient on HPC systems will need to be applied to the data as well - providing fast parallel analysis tools co-resident in memory with the data, because the disk I/O bandwidth simply will not keep up with the expected arrival of exaflop systems. The ability of scientists, analysts, stakeholders and others to use climate model output to turn these data into understanding and knowledge will require significant advances in the current typical analysis tools and packages to enable these processes for these vast volumes of data. Allowing data users to enact their own analyses on model output is virtually a requirement as well - climate modelers cannot anticipate all the possibilities for analysis that users may want to do. In addition, the expertise of data scientists, and their knowledge of the model output and their knowledge of best practices in data management (metadata, curation, provenance and so on) will need to be rewarded and exploited to gain the most understanding possible from these volumes of data. In response to growing data size, demand, and future projections, the CESM output has undergone a structure evolution and the data management plan has been reevaluated and updated. The major evolution of the CESM data structure is presented here, along with the CESM experience and role within the CMIP3/CMIP5.

Thru-life impacts of driver aggression, climate, cabin thermal management, and battery thermal management on battery electric vehicle utility

NASA Astrophysics Data System (ADS)

Neubauer, Jeremy; Wood, Eric

2014-08-01

Battery electric vehicles (BEVs) offer the potential to reduce both oil imports and greenhouse gas emissions, but have a limited utility that is affected by driver aggression and effects of climate-both directly on battery temperature and indirectly through the loads of cabin and battery thermal management systems. Utility is further affected as the battery wears through life in response to travel patterns, climate, and other factors. In this paper we apply the National Renewable Energy Laboratory's Battery Lifetime Analysis and Simulation Tool for Vehicles (BLAST-V) to examine the sensitivity of BEV utility to driver aggression and climate effects over the life of the vehicle. We find the primary challenge to cold-climate BEV operation to be inefficient cabin heating systems, and to hot-climate BEV operation to be high peak on-road battery temperatures and excessive battery degradation. Active cooling systems appear necessary to manage peak battery temperatures of aggressive, hot-climate drivers, which can then be employed to maximize thru-life vehicle utility.

An Automated Method to Identify Mesoscale Convective Complexes in the Regional Climate Model Evaluation System

NASA Astrophysics Data System (ADS)

Whitehall, K. D.; Jenkins, G. S.; Mattmann, C. A.; Waliser, D. E.; Kim, J.; Goodale, C. E.; Hart, A. F.; Ramirez, P.; Whittell, J.; Zimdars, P. A.

2012-12-01

Mesoscale convective complexes (MCCs) are large (2 - 3 x 105 km2) nocturnal convectively-driven weather systems that are generally associated with high precipitation events in short durations (less than 12hrs) in various locations through out the tropics and midlatitudes (Maddox 1980). These systems are particularly important for climate in the West Sahel region, where the precipitation associated with them is a principal component of the rainfall season (Laing and Fritsch 1993). These systems occur on weather timescales and are historically identified from weather data analysis via manual and more recently automated processes (Miller and Fritsch 1991, Nesbett 2006, Balmey and Reason 2012). The Regional Climate Model Evaluation System (RCMES) is an open source tool designed for easy evaluation of climate and Earth system data through access to standardized datasets, and intrinsic tools that perform common analysis and visualization tasks (Hart et al. 2011). The RCMES toolkit also provides the flexibility of user-defined subroutines for further metrics, visualization and even dataset manipulation. The purpose of this study is to present a methodology for identifying MCCs in observation datasets using the RCMES framework. TRMM 3 hourly datasets will be used to demonstrate the methodology for 2005 boreal summer. This method promotes the use of open source software for scientific data systems to address a concern to multiple stakeholders in the earth sciences. A historical MCC dataset provides a platform with regards to further studies of the variability of frequency on various timescales of MCCs that is important for many including climate scientists, meteorologists, water resource managers, and agriculturalists. The methodology of using RCMES for searching and clipping datasets will engender a new realm of studies as users of the system will no longer be restricted to solely using the datasets as they reside in their own local systems; instead will be afforded rapid, effective, and transparent access, processing and visualization of the wealth of remote sensing datasets and climate model outputs available.

Detecting climate variations and change: New challenges for observing and data management systems

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

Karl, T.R.; Quayle, R.G.; Groisman, P.Ya.

1993-08-01

Several essential aspects of weather observing and the management of weather data related to improving knowledge of climate variations and change in the surface boundary layer and the consequences for socioeconomic and biogeophysical systems, are discussed. The issues include long-term homogeneous time series of routine weather observations; time- and space-scale resolution of datasets derived from the observations; information about observing systems, data collection systems, and data reduction algorithms; and the enhancement of weather observing systems to serve as climate observing systems. Although much has been learned from existing weather networks and methods of data management, the system is far frommore » perfect. Several vital areas have not received adequate attention. Particular improvements are needed in the interaction between network designers and climatologists; operational analyses that focus on detecting and documenting outliers and time-dependent biases within datasets; developing the means to cope with and minimize potential inhomogeneities in weather observing systems; and authoritative documentation of how various aspects of climate have or have not changed. In this last area, close attention must be given to time and space resolution of the data. In many instances the time and space resolution requirements for understanding why the climate changes are not synonymous with understanding how it has changed or varied. This is particularly true within the surface boundary layer. A standard global daily/monthly climate message should also be introduced to supplement current Global Telecommunication System's CLIMAT data. Overall, a call is made for improvements in routine weather observing, data management, and analysis systems. Routine observations have provided (and will continue to provide) most of the information regarding how the climate has changed during the last 100 years affecting where we live, work, and grow our food. 58 refs., 8 figs., 1 tab.« less

Obliquity-driven expansion of North Atlantic sea ice controls structure of the last glacial

NASA Astrophysics Data System (ADS)

Turney, Chris; Thomas, Zoe; Hutchinson, David; Bradshaw, Corey; Brook, Barry; England, Matthew; Fogwill, Christopher; Jones, Richard; Palmer, Jonathan; Hughen, Konrad; Cooper, Alan

2015-04-01

North Atlantic late-Pleistocene climate was characterised by a series of abrupt climate changes, the most extreme of which were the Dansgaard-Oeschger (D-O) events; millennial-scale oscillations that switched rapidly between cold and warm atmospheric conditions of up to Δ16°C, most strongly expressed during the period 60-30 ka. Time series analysis of palaeoclimate ice core records is one of the best ways to detect threshold behaviour in the climate system; however, some of these techniques can be age model dependent. Spectral analysis of a new Greenland-Cariaco GICC05 age model (GICC05-CB), generated by combining the GICC05 and Cariaco ∂18O chronologies, reveals a change in the dominant periodicities at ~31 ka, consistent with the cessation of the D-O events. While the GICC05-CB has the same ∂18O structure as GICC05, the different periodicity profile reveals a change in the climate system at 31 ka. Stability analysis of the ∂18O time series over the last 60 ka determines the number of states the climate experienced over time, and reveals a bifurcation in the climate system at 31 ka, switching from a bistable to a monostable state. Early warning signals of this bifurcation are also detected starting 10,000 years before the shift in the form of increasing autocorrelation and variance. This is consistent with the climate system experiencing a slow forcing towards a critical threshold. These signals are found in both the GICC05-CB and GICC05 chronologies, though the timing of the bifurcation point varies slightly. We suggest that this bifurcation is linked to a minima in obliquity, causing greatly expanded sea ice in the Labrador sea. Modelling runs from the CSIRO Mk3L Earth-system model indicates that extensive sea ice cover is established in the Labrador Sea and North Pacific at the obliquity minima centred on 28.5 ka. This expanded sea ice is thus responsible for shifting the Northern Hemisphere westerlies southwards and reducing the strength of the AMOC, preventing the establishment of the cold state from 31 ka.

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.

Evolution of carbon sinks in a changing climate.

PubMed

Fung, Inez Y; Doney, Scott C; Lindsay, Keith; John, Jasmin

2005-08-09

Climate change is expected to influence the capacities of the land and oceans to act as repositories for anthropogenic CO2 and hence provide a feedback to climate change. A series of experiments with the National Center for Atmospheric Research-Climate System Model 1 coupled carbon-climate model shows that carbon sink strengths vary with the rate of fossil fuel emissions, so that carbon storage capacities of the land and oceans decrease and climate warming accelerates with faster CO2 emissions. Furthermore, there is a positive feedback between the carbon and climate systems, so that climate warming acts to increase the airborne fraction of anthropogenic CO2 and amplify the climate change itself. Globally, the amplification is small at the end of the 21st century in this model because of its low transient climate response and the near-cancellation between large regional changes in the hydrologic and ecosystem responses. Analysis of our results in the context of comparable models suggests that destabilization of the tropical land sink is qualitatively robust, although its degree is uncertain.

Evolution of carbon sinks in a changing climate

PubMed Central

Fung, Inez Y.; Doney, Scott C.; Lindsay, Keith; John, Jasmin

2005-01-01

Climate change is expected to influence the capacities of the land and oceans to act as repositories for anthropogenic CO2 and hence provide a feedback to climate change. A series of experiments with the National Center for Atmospheric Research–Climate System Model 1 coupled carbon–climate model shows that carbon sink strengths vary with the rate of fossil fuel emissions, so that carbon storage capacities of the land and oceans decrease and climate warming accelerates with faster CO2 emissions. Furthermore, there is a positive feedback between the carbon and climate systems, so that climate warming acts to increase the airborne fraction of anthropogenic CO2 and amplify the climate change itself. Globally, the amplification is small at the end of the 21st century in this model because of its low transient climate response and the near-cancellation between large regional changes in the hydrologic and ecosystem responses. Analysis of our results in the context of comparable models suggests that destabilization of the tropical land sink is qualitatively robust, although its degree is uncertain. PMID:16061800

Climate Analytics as a Service. Chapter 11

NASA Technical Reports Server (NTRS)

Schnase, John L.

2016-01-01

Exascale computing, big data, and cloud computing are driving the evolution of large-scale information systems toward a model of data-proximal analysis. In response, we are developing a concept of climate analytics as a service (CAaaS) that represents a convergence of data analytics and archive management. With this approach, high-performance compute-storage implemented as an analytic system is part of a dynamic archive comprising both static and computationally realized objects. It is a system whose capabilities are framed as behaviors over a static data collection, but where queries cause results to be created, not found and retrieved. Those results can be the product of a complex analysis, but, importantly, they also can be tailored responses to the simplest of requests. NASA's MERRA Analytic Service and associated Climate Data Services API provide a real-world example of climate analytics delivered as a service in this way. Our experiences reveal several advantages to this approach, not the least of which is orders-of-magnitude time reduction in the data assembly task common to many scientific workflows.

Modeling human-climate interaction

NASA Astrophysics Data System (ADS)

Jacoby, Henry D.

If policymakers and the public are to be adequately informed about the climate change threat, climate modeling needs to include components far outside its conventional boundaries. An integration of climate chemistry and meteorology, oceanography, and terrestrial biology has been achieved over the past few decades. More recently the scope of these studies has been expanded to include the human systems that influence the planet, the social and ecological consequences of potential change, and the political processes that lead to attempts at mitigation and adaptation. For example, key issues—like the relative seriousness of climate change risk, the choice of long-term goals for policy, and the analysis of today's decisions when uncertainty may be reduced tomorrow—cannot be correctly understood without joint application of the natural science of the climate system and social and behavioral science aspects of human response. Though integration efforts have made significant contributions to understanding of the climate issue, daunting intellectual and institutional barriers stand in the way of needed progress. Deciding appropriate policies will be a continuing task over the long term, however, so efforts to extend the boundaries of climate modeling and assessment merit long-term attention as well. Components of the effort include development of a variety of approaches to analysis, the maintenance of a clear a division between close-in decision support and science/policy research, and the development of funding institutions that can sustain integrated research over the long haul.

Development of a database system for near-future climate change projections under the Japanese National Project SI-CAT

NASA Astrophysics Data System (ADS)

Nakagawa, Y.; Kawahara, S.; Araki, F.; Matsuoka, D.; Ishikawa, Y.; Fujita, M.; Sugimoto, S.; Okada, Y.; Kawazoe, S.; Watanabe, S.; Ishii, M.; Mizuta, R.; Murata, A.; Kawase, H.

2017-12-01

Analyses of large ensemble data are quite useful in order to produce probabilistic effect projection of climate change. Ensemble data of "+2K future climate simulations" are currently produced by Japanese national project "Social Implementation Program on Climate Change Adaptation Technology (SI-CAT)" as a part of a database for Policy Decision making for Future climate change (d4PDF; Mizuta et al. 2016) produced by Program for Risk Information on Climate Change. Those data consist of global warming simulations and regional downscaling simulations. Considering that those data volumes are too large (a few petabyte) to download to a local computer of users, a user-friendly system is required to search and download data which satisfy requests of the users. We develop "a database system for near-future climate change projections" for providing functions to find necessary data for the users under SI-CAT. The database system for near-future climate change projections mainly consists of a relational database, a data download function and user interface. The relational database using PostgreSQL is a key function among them. Temporally and spatially compressed data are registered on the relational database. As a first step, we develop the relational database for precipitation, temperature and track data of typhoon according to requests by SI-CAT members. The data download function using Open-source Project for a Network Data Access Protocol (OPeNDAP) provides a function to download temporally and spatially extracted data based on search results obtained by the relational database. We also develop the web-based user interface for using the relational database and the data download function. A prototype of the database system for near-future climate change projections are currently in operational test on our local server. The database system for near-future climate change projections will be released on Data Integration and Analysis System Program (DIAS) in fiscal year 2017. Techniques of the database system for near-future climate change projections might be quite useful for simulation and observational data in other research fields. We report current status of development and some case studies of the database system for near-future climate change projections.

Cloud Feedbacks in the Climate System: A Critical Review.

NASA Astrophysics Data System (ADS)

Stephens, Graeme L.

2005-01-01

This paper offers a critical review of the topic of cloud-climate feedbacks and exposes some of the underlying reasons for the inherent lack of understanding of these feedbacks and why progress might be expected on this important climate problem in the coming decade. Although many processes and related parameters come under the influence of clouds, it is argued that atmospheric processes fundamentally govern the cloud feedbacks via the relationship between the atmospheric circulations, cloudiness, and the radiative and latent heating of the atmosphere. It is also shown how perturbations to the atmospheric radiation budget that are induced by cloud changes in response to climate forcing dictate the eventual response of the global-mean hydrological cycle of the climate model to climate forcing. This suggests that cloud feedbacks are likely to control the bulk precipitation efficiency and associated responses of the planet's hydrological cycle to climate radiative forcings.The paper provides a brief overview of the effects of clouds on the radiation budget of the earth-atmosphere system and a review of cloud feedbacks as they have been defined in simple systems, one being a system in radiative-convective equilibrium (RCE) and others relating to simple feedback ideas that regulate tropical SSTs. The systems perspective is reviewed as it has served as the basis for most feedback analyses. What emerges is the importance of being clear about the definition of the system. It is shown how different assumptions about the system produce very different conclusions about the magnitude and sign of feedbacks. Much more diligence is called for in terms of defining the system and justifying assumptions. In principle, there is also neither any theoretical basis to justify the system that defines feedbacks in terms of global-time-mean changes in surface temperature nor is there any compelling empirical evidence to do so. The lack of maturity of feedback analysis methods also suggests that progress in understanding climate feedback will require development of alternative methods of analysis.It has been argued that, in view of the complex nature of the climate system, and the cumbersome problems encountered in diagnosing feedbacks, understanding cloud feedback will be gleaned neither from observations nor proved from simple theoretical argument alone. The blueprint for progress must follow a more arduous path that requires a carefully orchestrated and systematic combination of model and observations. Models provide the tool for diagnosing processes and quantifying feedbacks while observations provide the essential test of the model's credibility in representing these processes. While GCM climate and NWP models represent the most complete description of all the interactions between the processes that presumably establish the main cloud feedbacks, the weak link in the use of these models lies in the cloud parameterization imbedded in them. Aspects of these parameterizations remain worrisome, containing levels of empiricism and assumptions that are hard to evaluate with current global observations. Clearly observationally based methods for evaluating cloud parameterizations are an important element in the road map to progress.Although progress in understanding the cloud feedback problem has been slow and confused by past analysis, there are legitimate reasons outlined in the paper that give hope for real progress in the future.

Proceedings of the 1991 Symposium on Systems Analysis in Forest Resources

Treesearch

[Compiler

1991-01-01

Forest Service, university, forest industry, and private consulting representatives presented 65 papers. General topic areas include: land management planning, multicriteria optimization, timber harvest scheduling, geographic information systems, sawmill simulation, timber supply analysis, and climate simulation.

The Coordinated Ocean Wave Climate Project

NASA Astrophysics Data System (ADS)

Hemer, Mark; Dobrynin, Mikhail; Erikson, Li; Lionello, Piero; Mori, Nobuhito; Semedo, Alvaro; Wang, Xiaolan

2016-04-01

Future 21st Century changes in wind-wave climate have broad implications for marine and coastal infrastructure and ecosystems. Atmosphere-ocean general circulation models (GCM) are now routinely used for assessing and providing future projections of climatological parameters such as temperature and precipitation, but generally these provide no information on ocean wind-waves. To fill this information gap a growing number of studies are using GCM outputs and independently producing global and regional scale wind-wave climate projections. Furthermore, additional studies are actively coupling wind-wave dependent atmosphere-ocean exchanges into GCMs, to improve physical representation and quantify the impact of waves in the coupled climate system, and can also deliver wave characteristics as another variable in the climate system. To consolidate these efforts, understand the sources of variance between projections generated by different methodologies and International groups, and ultimately provide a robust picture of the role of wind-waves in the climate system and their projected changes, we present outcomes of the JCOMM supported Coordinated Ocean Wave Climate Project (COWCLIP). The objective of COWCLIP is twofold: to make community based ensembles of wave climate projections openly accessible, to provide the necessary information to support diligent marine and coastal impacts of climate change studies; and to understand the effects and feedback influences of wind-waves in the coupled ocean-atmosphere climate system. We will present the current status of COWCLIP, providing an overview of the objectives, analysis and results of the initial phase - now complete - and the progress of ongoing phases of the project.

Climate Risk Informed Decision Analysis: A Hypothetical Application to the Waas Region

NASA Astrophysics Data System (ADS)

Gilroy, Kristin; Mens, Marjolein; Haasnoot, Marjolijn; Jeuken, Ad

2016-04-01

More frequent and intense hydrologic events under climate change are expected to enhance water security and flood risk management challenges worldwide. Traditional planning approaches must be adapted to address climate change and develop solutions with an appropriate level of robustness and flexibility. The Climate Risk Informed Decision Analysis (CRIDA) method is a novel planning approach embodying a suite of complementary methods, including decision scaling and adaptation pathways. Decision scaling offers a bottom-up approach to assess risk and tailors the complexity of the analysis to the problem at hand and the available capacity. Through adaptation pathway,s an array of future strategies towards climate robustness are developed, ranging in flexibility and immediacy of investments. Flexible pathways include transfer points to other strategies to ensure that the system can be adapted if future conditions vary from those expected. CRIDA combines these two approaches in a stakeholder driven process which guides decision makers through the planning and decision process, taking into account how the confidence in the available science, the consequences in the system, and the capacity of institutions should influence strategy selection. In this presentation, we will explain the CRIDA method and compare it to existing planning processes, such as the US Army Corps of Engineers Principles and Guidelines as well as Integrated Water Resources Management Planning. Then, we will apply the approach to a hypothetical case study for the Waas Region, a large downstream river basin facing rapid development threatened by increased flood risks. Through the case study, we will demonstrate how a stakeholder driven process can be used to evaluate system robustness to climate change; develop adaptation pathways for multiple objectives and criteria; and illustrate how varying levels of confidence, consequences, and capacity would play a role in the decision making process, specifically in regards to the level of robustness and flexibility in the selected strategy. This work will equip practitioners and decision makers with an example of a structured process for decision making under climate uncertainty that can be scaled as needed to the problem at hand. This presentation builds further on another submitted abstract "Climate Risk Informed Decision Analysis (CRIDA): A novel practical guidance for Climate Resilient Investments and Planning" by Jeuken et al.

A Hybrid Evaluation System Framework (Shell & Web) with Standardized Access to Climate Model Data and Verification Tools for a Clear Climate Science Infrastructure on Big Data High Performance Computers

NASA Astrophysics Data System (ADS)

Kadow, C.; Illing, S.; Kunst, O.; Cubasch, U.

2014-12-01

The project 'Integrated Data and Evaluation System for Decadal Scale Prediction' (INTEGRATION) as part of the German decadal prediction project MiKlip develops a central evaluation system. The fully operational hybrid features a HPC shell access and an user friendly web-interface. It employs one common system with a variety of verification tools and validation data from different projects in- and outside of MiKlip. The evaluation system is located at the German Climate Computing Centre (DKRZ) and has direct access to the bulk of its ESGF node including millions of climate model data sets, e.g. from CMIP5 and CORDEX. The database is organized by the international CMOR standard using the meta information of the self-describing model, reanalysis and observational data sets. Apache Solr is used for indexing the different data projects into one common search environment. This implemented meta data system with its advanced but easy to handle search tool supports users, developers and their tools to retrieve the required information. A generic application programming interface (API) allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language used. Users of the evaluation techniques benefit from the common interface of the evaluation system without any need to understand the different scripting languages. Facilitating the provision and usage of tools and climate data increases automatically the number of scientists working with the data sets and identify discrepancies. Additionally, the history and configuration sub-system stores every analysis performed with the evaluation system in a MySQL database. Configurations and results of the tools can be shared among scientists via shell or web-system. Therefore, plugged-in tools gain automatically from transparency and reproducibility. Furthermore, when configurations match while starting a evaluation tool, the system suggests to use results already produced by other users-saving CPU time, I/O and disk space. This study presents the different techniques and advantages of such a hybrid evaluation system making use of a Big Data HPC in climate science. website: www-miklip.dkrz.de visitor-login: guest password: miklip

A Hybrid Evaluation System Framework (Shell & Web) with Standardized Access to Climate Model Data and Verification Tools for a Clear Climate Science Infrastructure on Big Data High Performance Computers

NASA Astrophysics Data System (ADS)

Kadow, Christopher; Illing, Sebastian; Kunst, Oliver; Ulbrich, Uwe; Cubasch, Ulrich

2015-04-01

The project 'Integrated Data and Evaluation System for Decadal Scale Prediction' (INTEGRATION) as part of the German decadal prediction project MiKlip develops a central evaluation system. The fully operational hybrid features a HPC shell access and an user friendly web-interface. It employs one common system with a variety of verification tools and validation data from different projects in- and outside of MiKlip. The evaluation system is located at the German Climate Computing Centre (DKRZ) and has direct access to the bulk of its ESGF node including millions of climate model data sets, e.g. from CMIP5 and CORDEX. The database is organized by the international CMOR standard using the meta information of the self-describing model, reanalysis and observational data sets. Apache Solr is used for indexing the different data projects into one common search environment. This implemented meta data system with its advanced but easy to handle search tool supports users, developers and their tools to retrieve the required information. A generic application programming interface (API) allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language used. Users of the evaluation techniques benefit from the common interface of the evaluation system without any need to understand the different scripting languages. Facilitating the provision and usage of tools and climate data increases automatically the number of scientists working with the data sets and identify discrepancies. Additionally, the history and configuration sub-system stores every analysis performed with the evaluation system in a MySQL database. Configurations and results of the tools can be shared among scientists via shell or web-system. Therefore, plugged-in tools gain automatically from transparency and reproducibility. Furthermore, when configurations match while starting a evaluation tool, the system suggests to use results already produced by other users-saving CPU time, I/O and disk space. This study presents the different techniques and advantages of such a hybrid evaluation system making use of a Big Data HPC in climate science. website: www-miklip.dkrz.de visitor-login: click on "Guest"

Modeling Climate Dynamically

ERIC Educational Resources Information Center

Walsh, Jim; McGehee, Richard

2013-01-01

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

Risk Assessment in Relation to the Effect of Climate Change on Water Shortage in the Taichung Area

NASA Astrophysics Data System (ADS)

Hsiao, J.; Chang, L.; Ho, C.; Niu, M.

2010-12-01

Rapid economic development has stimulated a worldwide greenhouse effect and induced global climate change. Global climate change has increased the range of variation in the quantity of regional river flows between wet and dry seasons, which effects the management of regional water resources. Consequently, the influence of climate change has become an important issue in the management of regional water resources. In this study, the Monte Carlo simulation method was applied to risk analysis of shortage of water supply in the Taichung area. This study proposed a simulation model that integrated three models: weather generator model, surface runoff model, and water distribution model. The proposed model was used to evaluate the efficiency of the current water supply system and the potential effectiveness of two additional plans for water supply: the “artificial lakes” plan and the “cross-basin water transport” plan. A first-order Markov Chain method and two probability distribution models, exponential distribution and normal distribution, were used in the weather generator model. In the surface runoff model, researchers selected the Generalized Watershed Loading Function model (GWLF) to simulate the relationship between quantity of rainfall and basin outflow. A system dynamics model (SD) was applied to the water distribution model. Results of the simulation indicated that climate change could increase the annual quantity of river flow in the Dachia River and Daan River basins. However, climate change could also increase the difference in the quantity of river flow between wet and dry seasons. Simulation results showed that in current system case or in the additional plan cases, shortage status of water for both public and agricultural uses with conditions of climate change will be mostly worse than that without conditions of climate change except for the shortage status for the public use in the current system case. With or without considering the effect of climate change, the additional plans, especially the “cross-basin water transport” plan, for water supply could significantly increase the supply of water for public use. The proposed simulation model and results of analysis in this study could provide valuable reference for decision-makers in regards to risk analysis of regional water supply.

Development and application of earth system models.

PubMed

Prinn, Ronald G

2013-02-26

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

Sea surface temperature predictions using a multi-ocean analysis ensemble scheme

NASA Astrophysics Data System (ADS)

Zhang, Ying; Zhu, Jieshun; Li, Zhongxian; Chen, Haishan; Zeng, Gang

2017-08-01

This study examined the global sea surface temperature (SST) predictions by a so-called multiple-ocean analysis ensemble (MAE) initialization method which was applied in the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2). Different from most operational climate prediction practices which are initialized by a specific ocean analysis system, the MAE method is based on multiple ocean analyses. In the paper, the MAE method was first justified by analyzing the ocean temperature variability in four ocean analyses which all are/were applied for operational climate predictions either at the European Centre for Medium-range Weather Forecasts or at NCEP. It was found that these systems exhibit substantial uncertainties in estimating the ocean states, especially at the deep layers. Further, a set of MAE hindcasts was conducted based on the four ocean analyses with CFSv2, starting from each April during 1982-2007. The MAE hindcasts were verified against a subset of hindcasts from the NCEP CFS Reanalysis and Reforecast (CFSRR) Project. Comparisons suggested that MAE shows better SST predictions than CFSRR over most regions where ocean dynamics plays a vital role in SST evolutions, such as the El Niño and Atlantic Niño regions. Furthermore, significant improvements were also found in summer precipitation predictions over the equatorial eastern Pacific and Atlantic oceans, for which the local SST prediction improvements should be responsible. The prediction improvements by MAE imply a problem for most current climate predictions which are based on a specific ocean analysis system. That is, their predictions would drift towards states biased by errors inherent in their ocean initialization system, and thus have large prediction errors. In contrast, MAE arguably has an advantage by sampling such structural uncertainties, and could efficiently cancel these errors out in their predictions.

Life-cycle assessment of a biogas power plant with application of different climate metrics and inclusion of near-term climate forcers.

PubMed

Iordan, Cristina; Lausselet, Carine; Cherubini, Francesco

2016-12-15

This study assesses the environmental sustainability of electricity production through anaerobic co-digestion of sewage sludge and organic wastes. The analysis relies on primary data from a biogas plant, supplemented with data from the literature. The climate impact assessment includes emissions of near-term climate forcers (NTCFs) like ozone precursors and aerosols, which are frequently overlooked in Life Cycle Assessment (LCA), and the application of a suite of different emission metrics, based on either the Global Warming Potential (GWP) or the Global Temperature change Potential (GTP) with a time horizon (TH) of 20 or 100 years. The environmental performances of the biogas system are benchmarked against a conventional fossil fuel system. We also investigate the sensitivity of the system to critical parameters and provide five different scenarios in a sensitivity analysis. Hotspots are the management of the digestate (mainly due to the open storage) and methane (CH 4 ) losses during the anaerobic co-digestion. Results are sensitive to the type of climate metric used. The impacts range from 52 up to 116 g CO 2 -eq./MJ electricity when using GTP100 and GWP20, respectively. This difference is mostly due to the varying contribution from CH 4 emissions. The influence of NTCFs is about 6% for GWP100 (worst case), and grows up to 31% for GWP20 (best case). The biogas system has a lower performance than the fossil reference system for the acidification and particulate matter formation potentials. We argue for an active consideration of NTCFs in LCA and a critical reflection over the climate metrics to be used, as these aspects can significantly affect the final outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Spatial variability of the response to climate change in regional groundwater systems -- examples from simulations in the Deschutes Basin, Oregon

USGS Publications Warehouse

Waibel, Michael S.; Gannett, Marshall W.; Chang, Heejun; Hulbe, Christina L.

2013-01-01

We examine the spatial variability of the response of aquifer systems to climate change in and adjacent to the Cascade Range volcanic arc in the Deschutes Basin, Oregon using downscaled global climate model projections to drive surface hydrologic process and groundwater flow models. Projected warming over the 21st century is anticipated to shift the phase of precipitation toward more rain and less snow in mountainous areas in the Pacific Northwest, resulting in smaller winter snowpack and in a shift in the timing of runoff to earlier in the year. This will be accompanied by spatially variable changes in the timing of groundwater recharge. Analysis of historic climate and hydrologic data and modeling studies show that groundwater plays a key role in determining the response of stream systems to climate change. The spatial variability in the response of groundwater systems to climate change, particularly with regard to flow-system scale, however, has generally not been addressed in the literature. Here we simulate the hydrologic response to projected future climate to show that the response of groundwater systems can vary depending on the location and spatial scale of the flow systems and their aquifer characteristics. Mean annual recharge averaged over the basin does not change significantly between the 1980s and 2080s climate periods given the ensemble of global climate models and emission scenarios evaluated. There are, however, changes in the seasonality of groundwater recharge within the basin. Simulation results show that short-flow-path groundwater systems, such as those providing baseflow to many headwater streams, will likely have substantial changes in the timing of discharge in response changes in seasonality of recharge. Regional-scale aquifer systems with flow paths on the order of many tens of kilometers, in contrast, are much less affected by changes in seasonality of recharge. Flow systems at all spatial scales, however, are likely to reflect interannual changes in total recharge. These results provide insights into the possible impacts of climate change to other regional aquifer systems, and the streams they support, where discharge points represent a range of flow system scales.

A Nonlinear Model for Interactive Data Analysis and Visualization and an Implementation Using Progressive Computation for Massive Remote Climate Data Ensembles

NASA Astrophysics Data System (ADS)

Christensen, C.; Liu, S.; Scorzelli, G.; Lee, J. W.; Bremer, P. T.; Summa, B.; Pascucci, V.

2017-12-01

The creation, distribution, analysis, and visualization of large spatiotemporal datasets is a growing challenge for the study of climate and weather phenomena in which increasingly massive domains are utilized to resolve finer features, resulting in datasets that are simply too large to be effectively shared. Existing workflows typically consist of pipelines of independent processes that preclude many possible optimizations. As data sizes increase, these pipelines are difficult or impossible to execute interactively and instead simply run as large offline batch processes. Rather than limiting our conceptualization of such systems to pipelines (or dataflows), we propose a new model for interactive data analysis and visualization systems in which we comprehensively consider the processes involved from data inception through analysis and visualization in order to describe systems composed of these processes in a manner that facilitates interactive implementations of the entire system rather than of only a particular component. We demonstrate the application of this new model with the implementation of an interactive system that supports progressive execution of arbitrary user scripts for the analysis and visualization of massive, disparately located climate data ensembles. It is currently in operation as part of the Earth System Grid Federation server running at Lawrence Livermore National Lab, and accessible through both web-based and desktop clients. Our system facilitates interactive analysis and visualization of massive remote datasets up to petabytes in size, such as the 3.5 PB 7km NASA GEOS-5 Nature Run simulation, previously only possible offline or at reduced resolution. To support the community, we have enabled general distribution of our application using public frameworks including Docker and Anaconda.

Hands-on Approach to Prepare Specialists in Climate Changes Modeling and Analysis Using an Information-Computational Web-GIS Portal "Climate"

NASA Astrophysics Data System (ADS)

Shulgina, T. M.; Gordova, Y. E.; Martynova, Y. V.

2014-12-01

A problem of making education relevant to the workplace tasks is a key problem of higher education in the professional field of environmental sciences. To answer this challenge several new courses for students of "Climatology" and "Meteorology" specialties were developed and implemented at the Tomsk State University, which comprises theoretical knowledge from up-to-date environmental sciences with computational tasks. To organize the educational process we use an open-source course management system Moodle (www.moodle.org). It gave us an opportunity to combine text and multimedia in a theoretical part of educational courses. The hands-on approach is realized through development of innovative trainings which are performed within the information-computational web GIS platform "Climate" (http://climate.scert.ru/). The platform has a set of tools and data bases allowing a researcher to perform climate changes analysis on the selected territory. The tools are also used for students' trainings, which contain practical tasks on climate modeling and climate changes assessment and analysis. Laboratory exercises are covering three topics: "Analysis of regional climate changes"; "Analysis of climate extreme indices on the regional scale"; and "Analysis of future climate". They designed to consolidate students' knowledge of discipline, to instill in them the skills to work independently with large amounts of geophysical data using modern processing and analysis tools of web-GIS platform "Climate" and to train them to present results obtained on laboratory work as reports with the statement of the problem, the results of calculations and logically justified conclusion. Thus, students are engaged in n the use of modern tools of the geophysical data analysis and it cultivates dynamic of their professional learning. The approach can help us to fill in this gap because it is the only approach that offers experience, increases students involvement, advance the use of modern information and communication tools. Financial support for this research from the RFBR (13-05-12034, 14-05-00502), SB RAS project VIII.80.2.1 and grant of the President of RF (№ 181) is acknowledged.

A probabilistic framework for assessing vulnerability to climate variability and change: The case of the US water supply system

Treesearch

Romano Foti; Jorge A. Ramirez; Thomas C. Brown

2014-01-01

We introduce a probabilistic framework for vulnerability analysis and use it to quantify current and future vulnerability of the US water supply system. We also determine the contributions of hydro-climatic and socio-economic drivers to the changes in projected vulnerability. For all scenarios and global climatemodels examined, the US Southwest including California and...

Analysis of Climatic and Environmental Changes Using CLEARS Web-GIS Information-Computational System: Siberia Case Study

NASA Astrophysics Data System (ADS)

Titov, A. G.; Gordov, E. P.; Okladnikov, I.; Shulgina, T. M.

2011-12-01

Analysis of recent climatic and environmental changes in Siberia performed on the basis of the CLEARS (CLimate and Environment Analysis and Research System) information-computational system is presented. The system was developed using the specialized software framework for rapid development of thematic information-computational systems based on Web-GIS technologies. It comprises structured environmental datasets, computational kernel, specialized web portal implementing web mapping application logic, and graphical user interface. Functional capabilities of the system include a number of procedures for mathematical and statistical analysis, data processing and visualization. At present a number of georeferenced datasets is available for processing including two editions of NCEP/NCAR Reanalysis, JMA/CRIEPI JRA-25 Reanalysis, ECMWF ERA-40 and ERA Interim Reanalysis, meteorological observation data for the territory of the former USSR, and others. Firstly, using functionality of the computational kernel employing approved statistical methods it was shown that the most reliable spatio-temporal characteristics of surface temperature and precipitation in Siberia in the second half of 20th and beginning of 21st centuries are provided by ERA-40/ERA Interim Reanalysis and APHRODITE JMA Reanalysis, respectively. Namely those Reanalyses are statistically consistent with reliable in situ meteorological observations. Analysis of surface temperature and precipitation dynamics for the territory of Siberia performed on the base of the developed information-computational system reveals fine spatial and temporal details in heterogeneous patterns obtained for the region earlier. Dynamics of bioclimatic indices determining climate change impact on structure and functioning of regional vegetation cover was investigated as well. Analysis shows significant positive trends of growing season length accompanied by statistically significant increase of sum of growing degree days and total annual precipitation over the south of Western Siberia. In particular, we conclude that analysis of trends of growing season length, sum of growing degree-days and total precipitation during the growing season reveals a tendency to an increase of vegetation ecosystems productivity across the south of Western Siberia (55°-60°N, 59°-84°E) in the past several decades. The developed system functionality providing instruments for comparison of modeling and observational data and for reliable climatological analysis allowed us to obtain new results characterizing regional manifestations of global change. It should be added that each analysis performed using the system leads also to generation of the archive of spatio-temporal data fields ready for subsequent usage by other specialists. In particular, the archive of bioclimatic indices obtained will allow performing further detailed studies of interrelations between local climate and vegetation cover changes, including changes of carbon uptake related to variations of types and amount of vegetation and spatial shift of vegetation zones. This work is partially supported by RFBR grants #10-07-00547 and #11-05-01190-a, SB RAS Basic Program Projects 4.31.1.5 and 4.31.2.7.

Palynology in coal systems analysis-The key to floras, climate, and stratigraphy of coal-forming environments

USGS Publications Warehouse

Nichols, D.J.

2005-01-01

Palynology can be effectively used in coal systems analysis to understand the nature of ancient coal-forming peat mires. Pollen and spores preserved in coal effectively reveal the floristic composition of mires, which differed substantially through geologic time, and contribute to determination of depositional environment and paleo- climate. Such applications are most effective when integrated with paleobotanical and coal-petrographic data. Examples of previous studies of Miocene, Carboniferous, and Paleogene coal beds illustrate the methods and results. Palynological age determinations and correlations of deposits are also important in coal systems analysis to establish stratigraphic setting. Application to studies of coalbed methane generation shows potential because certain kinds of pollen are associated with gas-prone lithotypes. ??2005 Geological Society of America.

European monitoring systems and data for assessing environmental and climate impacts on human infectious diseases.

PubMed

Nichols, Gordon L; Andersson, Yvonne; Lindgren, Elisabet; Devaux, Isabelle; Semenza, Jan C

2014-04-09

Surveillance is critical to understanding the epidemiology and control of infectious diseases. The growing concern over climate and other drivers that may increase infectious disease threats to future generations has stimulated a review of the surveillance systems and environmental data sources that might be used to assess future health impacts from climate change in Europe. We present an overview of organizations, agencies and institutions that are responsible for infectious disease surveillance in Europe. We describe the surveillance systems, tracking tools, communication channels, information exchange and outputs in light of environmental and climatic drivers of infectious diseases. We discuss environmental and climatic data sets that lend themselves to epidemiological analysis. Many of the environmental data sets have a relatively uniform quality across EU Member States because they are based on satellite measurements or EU funded FP6 or FP7 projects with full EU coverage. Case-reporting systems for surveillance of infectious diseases should include clear and consistent case definitions and reporting formats that are geo-located at an appropriate resolution. This will allow linkage to environmental, social and climatic sources that will enable risk assessments, future threat evaluations, outbreak management and interventions to reduce disease burden.

European Monitoring Systems and Data for Assessing Environmental and Climate Impacts on Human Infectious Diseases

PubMed Central

Nichols, Gordon L.; Andersson, Yvonne; Lindgren, Elisabet; Devaux, Isabelle; Semenza, Jan C.

2014-01-01

Surveillance is critical to understanding the epidemiology and control of infectious diseases. The growing concern over climate and other drivers that may increase infectious disease threats to future generations has stimulated a review of the surveillance systems and environmental data sources that might be used to assess future health impacts from climate change in Europe. We present an overview of organizations, agencies and institutions that are responsible for infectious disease surveillance in Europe. We describe the surveillance systems, tracking tools, communication channels, information exchange and outputs in light of environmental and climatic drivers of infectious diseases. We discuss environmental and climatic data sets that lend themselves to epidemiological analysis. Many of the environmental data sets have a relatively uniform quality across EU Member States because they are based on satellite measurements or EU funded FP6 or FP7 projects with full EU coverage. Case-reporting systems for surveillance of infectious diseases should include clear and consistent case definitions and reporting formats that are geo-located at an appropriate resolution. This will allow linkage to environmental, social and climatic sources that will enable risk assessments, future threat evaluations, outbreak management and interventions to reduce disease burden. PMID:24722542

Data-Driven Synthesis for Investigating Food Systems Resilience to Climate Change

NASA Astrophysics Data System (ADS)

Magliocca, N. R.; Hart, D.; Hondula, K. L.; Munoz, I.; Shelley, M.; Smorul, M.

2014-12-01

The production, supply, and distribution of our food involves a complex set of interactions between farmers, rural communities, governments, and global commodity markets that link important issues such as environmental quality, agricultural science and technology, health and nutrition, rural livelihoods, and social institutions and equality - all of which will be affected by climate change. The production of actionable science is thus urgently needed to inform and prepare the public for the consequences of climate change for local and global food systems. Access to data that spans multiple sectors/domains and spatial and temporal scales is key to beginning to tackle such complex issues. As part of the White House's Climate Data Initiative, the USDA and the National Socio-Environmental Synthesis Center (SESYNC) are launching a new collaboration to catalyze data-driven research to enhance food systems resilience to climate change. To support this collaboration, SESYNC is developing a new "Data to Motivate Synthesis" program designed to engage early career scholars in a highly interactive and dynamic process of real-time data discovery, analysis, and visualization to catalyze new research questions and analyses that would not have otherwise been possible and/or apparent. This program will be supported by an integrated, spatially-enabled cyberinfrastructure that enables the management, intersection, and analysis of large heterogeneous datasets relevant to food systems resilience to climate change. Our approach is to create a series of geospatial abstraction data structures and visualization services that can be used to accelerate analysis and visualization across various socio-economic and environmental datasets (e.g., reconcile census data with remote sensing raster datasets). We describe the application of this approach with a pilot workshop of socio-environmental scholars that will lay the groundwork for the larger SESYNC-USDA collaboration. We discuss the particular challenges of supporting an integrated, repeatable workflow for socio-environmental data synthesis, and the advantages and limitations to using data as a launching point for interdisciplinary research projects.

Global water cycle

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Christy, John R.; Goodman, Steven J.; Miller, Tim L.; Fitzjarrald, Dan; Lapenta, Bill; Wang, Shouping

1991-01-01

The primary objective is to determine the scope and interactions of the global water cycle with all components of the Earth system and to understand how it stimulates and regulates changes on both global and regional scales. The following subject areas are covered: (1) water vapor variability; (2) multi-phase water analysis; (3) diabatic heating; (4) MSU (Microwave Sounding Unit) temperature analysis; (5) Optimal precipitation and streamflow analysis; (6) CCM (Community Climate Model) hydrological cycle; (7) CCM1 climate sensitivity to lower boundary forcing; and (8) mesoscale modeling of atmosphere/surface interaction.

The influence of authentic leadership on safety climate in nursing.

PubMed

Dirik, Hasan Fehmi; Seren Intepeler, Seyda

2017-07-01

This study analysed nurses' perceptions of authentic leadership and safety climate and examined the contribution of authentic leadership to the safety climate. It has been suggested and emphasised that authentic leadership should be used as a guidance to ensure quality care and the safety of patients and health-care personnel. This predictive study was conducted with 350 nurses in three Turkish hospitals. The data were collected using the Authentic Leadership Questionnaire and the Safety Climate Survey and analysed using hierarchical regression analysis. The mean authentic leadership perception and the safety climate scores of the nurses were 2.92 and 3.50, respectively. The percentage of problematic responses was found to be less than 10% for only four safety climate items. Hierarchical regression analysis revealed that authentic leadership significantly predicted the safety climate. Procedural and political improvements are required in terms of the safety climate in institutions, where the study was conducted, and authentic leadership increases positive perceptions of safety climate. Exhibiting the characteristics of authentic leadership, or improving them and reflecting them on to personnel can enhance the safety climate. Planning information sharing meetings to raise the personnel's awareness of safety climate and systemic improvements can contribute to creating safe care climates. © 2017 John Wiley & Sons Ltd.

Network-based approaches to climate knowledge discovery

NASA Astrophysics Data System (ADS)

Budich, Reinhard; Nyberg, Per; Weigel, Tobias

2011-11-01

Climate Knowledge Discovery Workshop; Hamburg, Germany, 30 March to 1 April 2011 Do complex networks combined with semantic Web technologies offer the next generation of solutions in climate science? To address this question, a first Climate Knowledge Discovery (CKD) Workshop, hosted by the German Climate Computing Center (Deutsches Klimarechenzentrum (DKRZ)), brought together climate and computer scientists from major American and European laboratories, data centers, and universities, as well as representatives from industry, the broader academic community, and the semantic Web communities. The participants, representing six countries, were concerned with large-scale Earth system modeling and computational data analysis. The motivation for the meeting was the growing problem that climate scientists generate data faster than it can be interpreted and the need to prepare for further exponential data increases. Current analysis approaches are focused primarily on traditional methods, which are best suited for large-scale phenomena and coarse-resolution data sets. The workshop focused on the open discussion of ideas and technologies to provide the next generation of solutions to cope with the increasing data volumes in climate science.

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

PubMed

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

2015-11-01

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

The integrated effects of future climate and hydrologic uncertainty on sustainable flood risk management

NASA Astrophysics Data System (ADS)

Steinschneider, S.; Wi, S.; Brown, C. M.

2013-12-01

Flood risk management performance is investigated within the context of integrated climate and hydrologic modeling uncertainty to explore system robustness. The research question investigated is whether structural and hydrologic parameterization uncertainties are significant relative to other uncertainties such as climate change when considering water resources system performance. Two hydrologic models are considered, a conceptual, lumped parameter model that preserves the water balance and a physically-based model that preserves both water and energy balances. In the conceptual model, parameter and structural uncertainties are quantified and propagated through the analysis using a Bayesian modeling framework with an innovative error model. Mean climate changes and internal climate variability are explored using an ensemble of simulations from a stochastic weather generator. The approach presented can be used to quantify the sensitivity of flood protection adequacy to different sources of uncertainty in the climate and hydrologic system, enabling the identification of robust projects that maintain adequate performance despite the uncertainties. The method is demonstrated in a case study for the Coralville Reservoir on the Iowa River, where increased flooding over the past several decades has raised questions about potential impacts of climate change on flood protection adequacy.

Past, present, and future design of urban drainage systems with focus on Danish experiences.

PubMed

Arnbjerg-Nielsen, K

2011-01-01

Climate change will influence the water cycle substantially, and extreme precipitation will become more frequent in many regions in the years to come. How should this fact be incorporated into design of urban drainage systems, if at all? And how important is climate change compared to other changes over time? Based on an analysis of the underlying key drivers of changes that are expected to affect urban drainage systems the current problems and their predicted development over time are presented. One key issue is management of risk and uncertainties and therefore a framework for design and analysis of urban structures in light of present and future uncertainties is presented.

Report of the international workshop on quality control of monthly climate data

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

Not Available

1993-12-31

The National Climatic Data Center (NCDC), the US Department of Energy`s Carbon Dioxide Information Analysis Center, and the World Meteorological Organization (WMO) cosponsored an international quality control workshop for monthly climate data, October 5--6, 1993, at NCDC. About 40 scientists from around the world participated. The purpose of the meeting was to discuss and compare various quality control methods and to draft recommendations concerning the most successful systems. The near-term goal to improve quality control of CLIMAT messages for the NCDC/WMO publication Monthly Climatic Data for the World was sucessfully met. An electronic bulletin board was established to post errorsmore » and corrections. Improved communications among Global Telecommunication System hubs will be implemented. Advanced quality control algorithms were discussed and improvements were suggested. Further data exchanges were arranged.« less

Separation of spatial-temporal patterns ('climatic modes') by combined analysis of really measured and generated numerically vector time series

NASA Astrophysics Data System (ADS)

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

2013-12-01

The new method of decomposition of the Earth's climate system into well separated spatial-temporal patterns ('climatic modes') is discussed. The method is based on: (i) generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding vector (space-distributed) time series in basis of spatial-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points; (ii) expanding both real SST data, and longer by several times SST data generated numerically, in STEOF basis; (iii) use of the numerically produced STEOF basis for exclusion of 'too slow' (and thus not represented correctly) processes from real data. The application of the method allows by means of vector time series generated numerically by the INM RAS Coupled Climate Model [2] to separate from real SST anomalies data [3] two climatic modes possessing by noticeably different time scales: 3-5 and 9-11 years. Relations of separated modes to ENSO and PDO are investigated. Possible applications of spatial-temporal climatic patterns concept to prognosis of climate system evolution is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm 3. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Architecture of a spatial data service system for statistical analysis and visualization of regional climate changes

NASA Astrophysics Data System (ADS)

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

2017-11-01

The use of large geospatial datasets in climate change studies requires the development of a set of Spatial Data Infrastructure (SDI) elements, including geoprocessing and cartographical visualization web services. This paper presents the architecture of a geospatial OGC web service system as an integral part of a virtual research environment (VRE) general architecture for statistical processing and visualization of meteorological and climatic data. The architecture is a set of interconnected standalone SDI nodes with corresponding data storage systems. Each node runs a specialized software, such as a geoportal, cartographical web services (WMS/WFS), a metadata catalog, and a MySQL database of technical metadata describing geospatial datasets available for the node. It also contains geospatial data processing services (WPS) based on a modular computing backend realizing statistical processing functionality and, thus, providing analysis of large datasets with the results of visualization and export into files of standard formats (XML, binary, etc.). Some cartographical web services have been developed in a system’s prototype to provide capabilities to work with raster and vector geospatial data based on OGC web services. The distributed architecture presented allows easy addition of new nodes, computing and data storage systems, and provides a solid computational infrastructure for regional climate change studies based on modern Web and GIS technologies.

Public Perception of Uncertainties Within Climate Change Science.

PubMed

Visschers, Vivianne H M

2018-01-01

Climate change is a complex, multifaceted problem involving various interacting systems and actors. Therefore, the intensities, locations, and timeframes of the consequences of climate change are hard to predict and cause uncertainties. Relatively little is known about how the public perceives this scientific uncertainty and how this relates to their concern about climate change. In this article, an online survey among 306 Swiss people is reported that investigated whether people differentiate between different types of uncertainty in climate change research. Also examined was the way in which the perception of uncertainty is related to people's concern about climate change, their trust in science, their knowledge about climate change, and their political attitude. The results of a principal component analysis showed that respondents differentiated between perceived ambiguity in climate research, measurement uncertainty, and uncertainty about the future impact of climate change. Using structural equation modeling, it was found that only perceived ambiguity was directly related to concern about climate change, whereas measurement uncertainty and future uncertainty were not. Trust in climate science was strongly associated with each type of uncertainty perception and was indirectly associated with concern about climate change. Also, more knowledge about climate change was related to less strong perceptions of each type of climate science uncertainty. Hence, it is suggested that to increase public concern about climate change, it may be especially important to consider the perceived ambiguity about climate research. Efforts that foster trust in climate science also appear highly worthwhile. © 2017 Society for Risk Analysis.

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

USGS Publications Warehouse

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

2013-01-01

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

Agricultural Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Tam, A.; Jain, M.

2016-12-01

This research includes two projects pertaining to agricultural systems' adaption to climate change. The first research project focuses on the wheat yielding regions of India. Wheat is a major staple crop and many rural households and smallholder farmers rely on crop yields for survival. We examine the impacts of weather variability and groundwater depletion on agricultural systems, using geospatial analysis and satellite-based analysis and household-based and census data sets. We use these methods to estimate the crop yields and identify what factors are associated with low versus high yielding regions. This can help identify strategies that should be further promoted to increase crop yields. The second research project is a literature review. We conduct a meta-analysis and synthetic review on literature about agricultural adaptation to climate change. We sort through numerous articles to identify and examine articles that associate socio-economic, biophysical, and perceptional factors to farmers' adaption to climate change. Our preliminary results show that researchers tend to associate few factors to a farmers' vulnerability and adaptive capacity, and most of the research conducted is concentrated in North America, whereas tropical regions that are highly vulnerable to weather variability are underrepresented by literature. There are no conclusive results in both research projects as of so far.

Development and application of earth system models

PubMed Central

Prinn, Ronald G.

2013-01-01

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

Advanced spectral methods for climatic time series

USGS Publications Warehouse

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

2002-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-09-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing numbers of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis relating the multiple visualisation challenges to a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Review: visual analytics of climate networks

NASA Astrophysics Data System (ADS)

Nocke, T.; Buschmann, S.; Donges, J. F.; Marwan, N.; Schulz, H.-J.; Tominski, C.

2015-04-01

Network analysis has become an important approach in studying complex spatiotemporal behaviour within geophysical observation and simulation data. This new field produces increasing amounts of large geo-referenced networks to be analysed. Particular focus lies currently on the network analysis of the complex statistical interrelationship structure within climatological fields. The standard procedure for such network analyses is the extraction of network measures in combination with static standard visualisation methods. Existing interactive visualisation methods and tools for geo-referenced network exploration are often either not known to the analyst or their potential is not fully exploited. To fill this gap, we illustrate how interactive visual analytics methods in combination with geovisualisation can be tailored for visual climate network investigation. Therefore, the paper provides a problem analysis, relating the multiple visualisation challenges with a survey undertaken with network analysts from the research fields of climate and complex systems science. Then, as an overview for the interested practitioner, we review the state-of-the-art in climate network visualisation and provide an overview of existing tools. As a further contribution, we introduce the visual network analytics tools CGV and GTX, providing tailored solutions for climate network analysis, including alternative geographic projections, edge bundling, and 3-D network support. Using these tools, the paper illustrates the application potentials of visual analytics for climate networks based on several use cases including examples from global, regional, and multi-layered climate networks.

Distributed Research Center for Analysis of Regional Climatic Changes and Their Impacts on Environment

NASA Astrophysics Data System (ADS)

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

2016-12-01

Presented is a collaborative project carrying out by joint team of researchers from the Institute of Monitoring of Climatic and Ecological Systems, Russia and Earth Systems Research Center, University of New Hampshire, USA. Its main objective is development of a hardware and software prototype of Distributed Research Center (DRC) for monitoring and projecting of regional climatic and and their impacts on the environment over the Northern extratropical areas. In the framework of the project new approaches to "cloud" processing and analysis of large geospatial datasets (big geospatial data) are being developed. It will be deployed on technical platforms of both institutions and applied in research of climate change and its consequences. Datasets available at NCEI and IMCES include multidimensional arrays of climatic, environmental, demographic, and socio-economic characteristics. The project is aimed at solving several major research and engineering tasks: 1) structure analysis of huge heterogeneous climate and environmental geospatial datasets used in the project, their preprocessing and unification; 2) development of a new distributed storage and processing model based on a "shared nothing" paradigm; 3) development of a dedicated database of metadata describing geospatial datasets used in the project; 4) development of a dedicated geoportal and a high-end graphical frontend providing intuitive user interface, internet-accessible online tools for analysis of geospatial data and web services for interoperability with other geoprocessing software packages. DRC will operate as a single access point to distributed archives of spatial data and online tools for their processing. Flexible modular computational engine running verified data processing routines will provide solid results of geospatial data analysis. "Cloud" data analysis and visualization approach will guarantee access to the DRC online tools and data from all over the world. Additionally, exporting of data processing results through WMS and WFS services will be used to provide their interoperability. Financial support of this activity by the RF Ministry of Education and Science under Agreement 14.613.21.0037 (RFMEFI61315X0037) and by the Iola Hubbard Climate Change Endowment is acknowledged.

The climate change-infectious disease nexus: is it time for climate change syndemics?

PubMed

Heffernan, Claire

2013-12-01

Conceptualizing climate as a distinct variable limits our understanding of the synergies and interactions between climate change and the range of abiotic and biotic factors, which influence animal health. Frameworks such as eco-epidemiology and the epi-systems approach, while more holistic, view climate and climate change as one of many discreet drivers of disease. Here, I argue for a new paradigmatic framework: climate-change syndemics. Climate-change syndemics begins from the assumption that climate change is one of many potential influences on infectious disease processes, but crucially is unlikely to act independently or in isolation; and as such, it is the inter-relationship between factors that take primacy in explorations of infectious disease and climate change. Equally importantly, as climate change will impact a wide range of diseases, the frame of analysis is at the collective rather than individual level (for both human and animal infectious disease) across populations.

Towards the construction of a Drought Early Warning System in México

NASA Astrophysics Data System (ADS)

Neri, C.; Magaña, V. O.

2011-12-01

Droughts in Mexico are related to severe impacts in agricultural and livestock activities, water management and with the occurrence of wildfire. Droughts are recurrent, on time scales from years to decades. The impacts however, depend on the vulnerability. The negative impacts may be reduced by studying and monitoring the dynamical evolution of meteorological drought, and by identifying the factors that result in vulnerability, in the context of risk management. Considering the analysis of the vulnerability in the northern of Mexico, a semiarid region highly vulnerable to drought, a Drought Early Warning System was created based on the use of climate information. The first step was to identify the capacity to provide useful climate information to develop prevention actions. Results confirm that the drought in northern Mexico is a well-diagnosed phenomenon from the point of view of impacts in various sectors. However, the use of climate information is still very limited resulting in response to mitigate drought impacts rather than preparing for drought. Part of the problem is the limited capacity to interpret probabilistic forecasts to define actions. Therefore, a key element in a Drought Early Warning System is the development of reliable climate information and the use of indicators to determine of the onset, maximum intensity and duration of the event. The occurrence and severity of drought may be estimated using climate diagnosis and forecast. A preventive response to drought may be defined if the severity and duration surpass a threshold value after which a decision action should be made. In order to establish the relevance of indicators for drought risk management, retroactive analyses have been developed considering the case of northwestern Mexico. After a vulnerability analysis that considers the institutional capacity to make use of climate information, a Drought Early warning System has been designed that considers a number of actions that may be put forward in order to reduce the impacts of such climatic hazard. The potential impact of such system is examined considering a number of actions that may be implemented in the water, agricultural and cattle ranching sectors. We conclude that there are great opportunities to reduce the negative impacts of drought if climate information is used.

Multiscale complex network analysis: An approach to study spatiotemporal rainfall pattern in south Germany

NASA Astrophysics Data System (ADS)

Agarwal, Ankit; Marwan, Norbert; Rathinasamy, Maheswaran; Oeztuerk, Ugur; Merz, Bruno; Kurths, Jürgen

2017-04-01

Understanding of the climate sytems has been of tremendous importance to different branches such as agriculture, flood, drought and water resources management etc. In this regard, complex networks analysis and time series analysis attracted considerable attention, owing to their potential role in understanding the climate system through characteristic properties. One of the basic requirements in studying climate network dynamics is to identify connections in space or time or space-time, depending upon the purpose. Although a wide variety of approaches have been developed and applied to identify and analyse spatio-temporal relationships by climate networks, there is still further need for improvements in particular when considering precipitation time series or interactions on different scales. In this regard, recent developments in the area of network theory, especially complex networks, offer new avenues, both for their generality about systems and for their holistic perspective about spatio-temporal relationships. The present study has made an attempt to apply the ideas developed in the field of complex networks to examine connections in regional climate networks with particular focus on multiscale spatiotemporal connections. This paper proposes a novel multiscale understanding of regional climate networks using wavelets. The proposed approach is applied to daily precipitation records observed at 543 selected stations from south Germany for a period of 110 years (1901-2010). Further, multiscale community mining is performed on the same study region to shed more light on the underlying processes at different time scales. Various network measure and tools so far employed provide micro-level (individual station) and macro-level (community structure) information of the network. It is interesting to investigate how the result of this study can be useful for future climate predictions and for evaluating climate models on their implementation regarding heavy precipitation. Keywords: Complex network, event synchronization, wavelet, regional climate network, multiscale community mining

Adapting to Uncertainty: Comparing Methodological Approaches to Climate Adaptation and Mitigation Policy

NASA Astrophysics Data System (ADS)

Huda, J.; Kauneckis, D. L.

2013-12-01

Climate change adaptation represents a number of unique policy-making challenges. Foremost among these is dealing with the range of future climate impacts to a wide scope of inter-related natural systems, their interaction with social and economic systems, and uncertainty resulting from the variety of downscaled climate model scenarios and climate science projections. These cascades of uncertainty have led to a number of new approaches as well as a reexamination of traditional methods for evaluating risk and uncertainty in policy-making. Policy makers are required to make decisions and formulate policy irrespective of the level of uncertainty involved and while a debate continues regarding the level of scientific certainty required in order to make a decision, incremental change in the climate policy continues at multiple governance levels. This project conducts a comparative analysis of the range of methodological approaches that are evolving to address uncertainty in climate change policy. It defines 'methodologies' to include a variety of quantitative and qualitative approaches involving both top-down and bottom-up policy processes that attempt to enable policymakers to synthesize climate information into the policy process. The analysis examines methodological approaches to decision-making in climate policy based on criteria such as sources of policy choice information, sectors to which the methodology has been applied, sources from which climate projections were derived, quantitative and qualitative methods used to deal with uncertainty, and the benefits and limitations of each. A typology is developed to better categorize the variety of approaches and methods, examine the scope of policy activities they are best suited for, and highlight areas for future research and development.

The Application of Climate Risk Informed Decision Analysis to the Ioland Water Treatment Plant in Lusaka, Zambia

NASA Astrophysics Data System (ADS)

Kucharski, John; Tkach, Mark; Olszewski, Jennifer; Chaudhry, Rabia; Mendoza, Guillermo

2016-04-01

This presentation demonstrates the application of Climate Risk Informed Decision Analysis (CRIDA) at Zambia's principal water treatment facility, The Iolanda Water Treatment Plant. The water treatment plant is prone to unacceptable failures during periods of low hydropower production at the Kafue Gorge Dam Hydroelectric Power Plant. The case study explores approaches of increasing the water treatment plant's ability to deliver acceptable levels of service under the range of current and potential future climate states. The objective of the study is to investigate alternative investments to build system resilience that might have been informed by the CRIDA process, and to evaluate the extra resource requirements by a bilateral donor agency to implement the CRIDA process. The case study begins with an assessment of the water treatment plant's vulnerability to climate change. It does so by following general principals described in "Confronting Climate Uncertainty in Water Resource Planning and Project Design: the Decision Tree Framework". By utilizing relatively simple bootstrapping methods a range of possible future climate states is generated while avoiding the use of more complex and costly downscaling methodologies; that are beyond the budget and technical capacity of many teams. The resulting climate vulnerabilities and uncertainty in the climate states that produce them are analyzed as part of a "Level of Concern" analysis. CRIDA principals are then applied to this Level of Concern analysis in order to arrive at a set of actionable water management decisions. The principal goals of water resource management is to transform variable, uncertain hydrology into dependable services (e.g. water supply, flood risk reduction, ecosystem benefits, hydropower production, etc…). Traditional approaches to climate adaptation require the generation of predicted future climate states but do little guide decision makers how this information should impact decision making. In this context it is not surprising that the increased hydrologic variability and uncertainty produced by many climate risk analyses bedevil water resource decision making. The Climate Risk Informed Decision Analysis (CRIDA) approach builds on work found in "Confronting Climate Uncertainty in Water Resource Planning and Project Design: the Decision Tree Framework" which provide guidance of vulnerability assessments. It guides practitioners through a "Level of Concern" analysis where climate vulnerabilities are analyzed to produce actionable alternatives and decisions.

A Bayesian approach for temporally scaling climate for modeling ecological systems

USGS Publications Warehouse

Post van der Burg, Max; Anteau, Michael J.; McCauley, Lisa A.; Wiltermuth, Mark T.

2016-01-01

With climate change becoming more of concern, many ecologists are including climate variables in their system and statistical models. The Standardized Precipitation Evapotranspiration Index (SPEI) is a drought index that has potential advantages in modeling ecological response variables, including a flexible computation of the index over different timescales. However, little development has been made in terms of the choice of timescale for SPEI. We developed a Bayesian modeling approach for estimating the timescale for SPEI and demonstrated its use in modeling wetland hydrologic dynamics in two different eras (i.e., historical [pre-1970] and contemporary [post-2003]). Our goal was to determine whether differences in climate between the two eras could explain changes in the amount of water in wetlands. Our results showed that wetland water surface areas tended to be larger in wetter conditions, but also changed less in response to climate fluctuations in the contemporary era. We also found that the average timescale parameter was greater in the historical period, compared with the contemporary period. We were not able to determine whether this shift in timescale was due to a change in the timing of wet–dry periods or whether it was due to changes in the way wetlands responded to climate. Our results suggest that perhaps some interaction between climate and hydrologic response may be at work, and further analysis is needed to determine which has a stronger influence. Despite this, we suggest that our modeling approach enabled us to estimate the relevant timescale for SPEI and make inferences from those estimates. Likewise, our approach provides a mechanism for using prior information with future data to assess whether these patterns may continue over time. We suggest that ecologists consider using temporally scalable climate indices in conjunction with Bayesian analysis for assessing the role of climate in ecological systems.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Regional Analysis of Energy, Water, Land and Climate Interactions

NASA Astrophysics Data System (ADS)

Tidwell, V. C.; Averyt, K.; Harriss, R. C.; Hibbard, K. A.; Newmark, R. L.; Rose, S. K.; Shevliakova, E.; Wilson, T.

2014-12-01

Energy, water, and land systems interact in many ways and are impacted by management and climate change. These systems and their interactions often differ in significant ways from region-to-region. To explore the coupled energy-water-land system and its relation to climate change and management a simple conceptual model of demand, endowment and technology (DET) is proposed. A consistent and comparable analysis framework is needed as climate change and resource management practices have the potential to impact each DET element, resource, and region differently. These linkages are further complicated by policy and trade agreements where endowments of one region are used to meet demands in another. This paper reviews the unique DET characteristics of land, energy and water resources across the United States. Analyses are conducted according to the eight geographic regions defined in the 2014 National Climate Assessment. Evident from the analyses are regional differences in resources endowments in land (strong East-West gradient in forest, cropland and desert), water (similar East-West gradient), and energy. Demands likewise vary regionally reflecting differences in population density and endowment (e.g., higher water use in West reflecting insufficient precipitation to support dryland farming). The effect of technology and policy are particularly evident in differences in the energy portfolios across the eight regions. Integrated analyses that account for the various spatial and temporal differences in regional energy, water and land systems are critical to informing effective policy requirements for future energy, climate and resource management. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Solar heating and cooling technical data and systems analysis

NASA Technical Reports Server (NTRS)

Christensen, D. L.

1977-01-01

The research activities described herein were concentrated on the areas of economics, heating and cooling systems, architectural design, materials characteristics, climatic conditions, educational information packages, and evaluation of solar energy systems and components.

Anthropology is missing: on the World Development Report 2010: Development and Climate Change.

PubMed

Trostle, James

2010-07-01

When the World Bank publishes a report on climate change, the world takes notice. What are its diagnoses and treatments, and how present is anthropology in this analysis? The 2010 World Development Report on climate change provides few new diagnostic tools and no clear Bank policy revisions. It often fails to harmonize neoliberal development rhetoric with new climate-change imperatives. It nods to the importance of social context and risk perception yet refers primarily to behavioral economics and psychological constructs. Although anthropologists are documenting the local effects and human responses to larger-scale, climate-driven processes, our work is absent in the report. To play a role at global scale we would do well to learn more about concepts like nonlinearity and emergence, systems analysis, modeling, and disease dynamics. Our adroitness in developing metaphors and methods for crossing scale will make our efforts more visible and applicable.

Modeling and Analysis Compute Environments, Utilizing Virtualization Technology in the Climate and Earth Systems Science domain

NASA Astrophysics Data System (ADS)

Michaelis, A.; Nemani, R. R.; Wang, W.; Votava, P.; Hashimoto, H.

2010-12-01

Given the increasing complexity of climate modeling and analysis tools, it is often difficult and expensive to build or recreate an exact replica of the software compute environment used in past experiments. With the recent development of new technologies for hardware virtualization, an opportunity exists to create full modeling, analysis and compute environments that are “archiveable”, transferable and may be easily shared amongst a scientific community or presented to a bureaucratic body if the need arises. By encapsulating and entire modeling and analysis environment in a virtual machine image, others may quickly gain access to the fully built system used in past experiments, potentially easing the task and reducing the costs of reproducing and verify past results produced by other researchers. Moreover, these virtual machine images may be used as a pedagogical tool for others that are interested in performing an academic exercise but don't yet possess the broad expertise required. We built two virtual machine images, one with the Community Earth System Model (CESM) and one with Weather Research Forecast Model (WRF), then ran several small experiments to assess the feasibility, performance overheads costs, reusability, and transferability. We present a list of the pros and cons as well as lessoned learned from utilizing virtualization technology in the climate and earth systems modeling domain.

Albedo impact on the suitability of biochar systems to mitigate global warming.

PubMed

Meyer, Sebastian; Bright, Ryan M; Fischer, Daniel; Schulz, Hardy; Glaser, Bruno

2012-11-20

Biochar application to agricultural soils can change the surface albedo which could counteract the climate mitigation benefit of biochar systems. However, the size of this impact has not yet been quantified. Based on empirical albedo measurements and literature data of arable soils mixed with biochar, a model for annual vegetation cover development based on satellite data and an assessment of the annual development of surface humidity, an average mean annual albedo reduction of 0.05 has been calculated for applying 30-32 Mg ha(-1) biochar on a test field near Bayreuth, Germany. The impact of biochar production and application on the carbon cycle and on the soil albedo was integrated into the greenhouse gas (GHG) balance of a modeled pyrolysis based biochar system via the computation of global warming potential (GWP) characterization factors. The analysis resulted in a reduction of the overall climate mitigation benefit of biochar systems by 13-22% due to the albedo change as compared to an analysis which disregards the albedo effect. Comparing the use of the same quantity of biomass in a biochar system to a bioenergy district heating system which replaces natural gas combustion, bioenergy heating systems achieve 99-119% of the climate benefit of biochar systems according to the model calculation.

Post-processing Seasonal Precipitation Forecasts via Integrating Climate Indices and the Analog Approach

NASA Astrophysics Data System (ADS)

Liu, Y.; Zhang, Y.; Wood, A.; Lee, H. S.; Wu, L.; Schaake, J. C.

2016-12-01

Seasonal precipitation forecasts are a primary driver for seasonal streamflow prediction that is critical for a range of water resources applications, such as reservoir operations and drought management. However, it is well known that seasonal precipitation forecasts from climate models are often biased and also too coarse in spatial resolution for hydrologic applications. Therefore, post-processing procedures such as downscaling and bias correction are often needed. In this presentation, we discuss results from a recent study that applies a two-step methodology to downscale and correct the ensemble mean precipitation forecasts from the Climate Forecast System (CFS). First, CFS forecasts are downscaled and bias corrected using monthly reforecast analogs: we identify past precipitation forecasts that are similar to the current forecast, and then use the finer-scale observational analysis fields from the corresponding dates to represent the post-processed ensemble forecasts. Second, we construct the posterior distribution of forecast precipitation from the post-processed ensemble by integrating climate indices: a correlation analysis is performed to identify dominant climate indices for the study region, which are then used to weight the analysis analogs selected in the first step using a Bayesian approach. The methodology is applied to the California Nevada River Forecast Center (CNRFC) and the Middle Atlantic River Forecast Center (MARFC) regions for 1982-2015, using the North American Land Data Assimilation System (NLDAS-2) precipitation as the analysis. The results from cross validation show that the post-processed CFS precipitation forecast are considerably more skillful than the raw CFS with the analog approach only. Integrating climate indices can further improve the skill if the number of ensemble members considered is large enough; however, the improvement is generally limited to the first couple of months when compared against climatology. Impacts of various factors such as ensemble size, lead time, and choice of climate indices will also be discussed.

Urban Flood Management with Integrated Inland-River System in Seoul

NASA Astrophysics Data System (ADS)

Moon, Y. I.; Kim, J. S.; Yuk, J. M.

2015-12-01

Global warming and climate change have caused significant damage and loss of life worldwide. The pattern of natural disasters has gradually diversified and their frequency is increasing. The impact of climate change on flood risk in urban rivers is of particular interest because these areas are typically densely populated. The occurrence of urban river flooding due to climate change not only causes significant loss of life and property but also causes health and social problems. It is therefore necessary to develop a scientific urban flood management system to cope with and reduce the impacts of climate change, including flood damage. In this study, we are going to introduce Integrated Inland-River Flood Analysis System in Seoul to conduct predictions on flash rain or short-term rainfall by using radar and satellite information and perform prompt and accurate prediction on the inland flooded areas. In addition, this urban flood management system can be used as a tool for decision making of systematic disaster prevention through real-time monitoring.

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

NASA Astrophysics Data System (ADS)

Bandoc, Georgeta; Pravalie, Remus

2015-04-01

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

Structuring injustice: partisan politics in the making and unmaking of James Madison University's equal opportunity policy.

PubMed

Robinson, Christine M; Spivey, Sue E

2011-01-01

This analysis contributes to LGBT campus climate research on the quality of campus life in higher education in the United States. We argue that public education institutions in different states face divergent impediments to improving campus climate, and that more research is needed identifying structural factors affecting campus climate. Using a social systems analysis of policymaking at one university as a case study, we illustrate how partisan politics and state regulation make Virginia colleges and universities more vulnerable to political scrutiny and control. Finally, we propose a social justice-oriented policy agenda to address structural inequalities.

Enhancing the usability of seasonal to decadal (S2D) climate information - an evidence-based framework for the identification and assessment of sector-specific vulnerabilities

NASA Astrophysics Data System (ADS)

Funk, Daniel

2016-04-01

The successful provision of from seasonal to decadal (S2D) climate service products to sector-specific users is dependent on specific problem characteristics and individual user needs and decision-making processes. Climate information requires an impact on decision making to have any value (Rodwell and Doblas-Reyes, 2006). For that reason the knowledge of sector-specific vulnerabilities to S2D climate variability is very valuable information for both, climate service producers and users. In this context a concept for a vulnerability assessment framework was developed to (i) identify climate events (and especially their temporal scales) critical for sector-specific problems to assess the basic requirements for an appropriate climate-service product development; and to (ii) assess the potential impact or value of related climate information for decision-makers. The concept was developed within the EUPORIAS project (European Provision of Regional Impacts Assessments on Seasonal and Decadal Timescales) based on ten project-related case-studies from different sectors all over Europe. In the prevalent stage the framework may be useful as preliminary assessment or 'quick-scan' of the vulnerability of specific systems to climate variability in the context of S2D climate service provision. The assessment strategy of the framework is user-focused, using predominantly a bottom-up approach (vulnerability as state) but also a top-down approach (vulnerability as outcome) generally based on qualitative data (surveys, interviews, etc.) and literature research for system understanding. The starting point of analysis is a climate-sensitive 'critical situation' of the considered system which requires a decision and is defined by the user. From this basis the related 'critical climate conditions' are assessed and 'climate information needs' are derived. This mainly refers to the critical period of time of the climate event or sequence of events. The relevant period of time of problem-specific critical climate conditions may be assessed by the resilience of the system of concern, the response time of an interconnected system (i.e. top-down approach using a bottom-up methodology) or alternatively, by the critical time-frame of decision-making processes (bottom-up approach). This approach counters the challenges for a vulnerability assessment of economic sectors to S2D climate events which originate from the inherent role of climate for economic sectors: climate may affect economic sectors as hazard, resource, production- or regulation factor. This implies, that climate dependencies are often indirect and nonlinear. Consequently, climate events which are critical for affected systems do not necessarily correlate with common climatological extremes. One important output of the framework is a classification system of 'climate-impact types' which classifies sector-specific problems in a systemic way. This system proves to be promising because (i) it reflects and thus differentiates the cause for the climate relevance of a specific problem (compositions of buffer factors); (ii) it integrates decision-making processes which proved to be a significant factor; (iii) it indicates a potential usability of S2D climate service products and thus integrates coping options, and (vi) it is a systemic approach which goes beyond the established 'snap-shot' of vulnerability assessments.

Climate change likely to favor shift toward warmer climate states of the Pliocene and Eocene

NASA Astrophysics Data System (ADS)

Burke, K. D.; Williams, J. W.

2017-12-01

As the world warms due to rising greenhouse gas concentrations, the climate system is moving toward a state without precedent in the historical record. Various past climate states have been proposed as potential analogues or model systems for the coming decades, including the early to middle Holocene, the last interglacial, the middle Pliocene, and the early Eocene. However, until now, such comparisons have been qualitative. To compare these time periods to the projected climate states for the 21st and 22nd centuries, we conduct a climate similarity analysis using the standardized Euclidean distance metric (SED) and seasonal means of surface air temperature and precipitation. We make this future-to-past comparison using 30-year mean climatologies, for every decade between 2020 and 2280 AD (27 total comparisons). The list of past earth system states includes the historical period (1940-1970 AD), a pre-industrial control (ca. 1850), the middle Holocene (ca. 6 ka), the last glacial maximum (ca. 21 ka), the last interglacial (ca. 125 ka), the middle Pliocene (ca. 3 Ma), and the early Eocene (ca. 50-55 Ma). To reduce uncertainties resulting from choice of earth system model, analyses are based on simulations from three earth system models (HadCM, CCSM, NASA/GISS Model-E), using in part experiments from PMIP2, PMIP3/CMIP5, EoMIP, and PlioMIP. Results are presented for two representative concentration pathways (RCP's 4.5, 8.5). By 2050 AD, the most common past climate analogue is sourced from the Pliocene for RCP 8.5, while by 2190 AD, the Eocene becomes the source of the most common past climate analogue. For RCP 4.5, in which radiative forcings stabilize this century, the Pliocene becomes the most important past climate analogue by 2100 AD. Low latitude climates are the first to most closely resemble these past earth warm periods. The mid-latitudes then follow this pattern by the end of the 22nd century. Although no past state of the earth system is a perfect analogue for the Anthropocene, these analyses clarify the similarities between the expected climates of the future and the geological climates of the past.

A Web Geographic Information System to share data and explorative analysis tools: The application to West Nile disease in the Mediterranean basin.

PubMed

Savini, Lara; Tora, Susanna; Di Lorenzo, Alessio; Cioci, Daniela; Monaco, Federica; Polci, Andrea; Orsini, Massimiliano; Calistri, Paolo; Conte, Annamaria

2018-01-01

In the last decades an increasing number of West Nile Disease cases was observed in equines and humans in the Mediterranean basin and surveillance systems are set up in numerous countries to manage and control the disease. The collection, storage and distribution of information on the spread of the disease becomes important for a shared intervention and control strategy. To this end, a Web Geographic Information System has been developed and disease data, climatic and environmental remote sensed data, full genome sequences of selected isolated strains are made available. This paper describes the Disease Monitoring Dashboard (DMD) web system application, the tools available for the preliminary analysis on climatic and environmental factors and the other interactive tools for epidemiological analysis. WNV occurrence data are collected from multiple official and unofficial sources. Whole genome sequences and metadata of WNV strains are retrieved from public databases or generated in the framework of the Italian surveillance activities. Climatic and environmental data are provided by NASA website. The Geographical Information System is composed by Oracle 10g Database and ESRI ArcGIS Server 10.03; the web mapping client application is developed with the ArcGIS API for Javascript and Phylocanvas library to facilitate and optimize the mash-up approach. ESRI ArcSDE 10.1 has been used to store spatial data. The DMD application is accessible through a generic web browser at https://netmed.izs.it/networkMediterraneo/. The system collects data through on-line forms and automated procedures and visualizes data as interactive graphs, maps and tables. The spatial and temporal dynamic visualization of disease events is managed by a time slider that returns results on both map and epidemiological curve. Climatic and environmental data can be associated to cases through python procedures and downloaded as Excel files. The system compiles multiple datasets through user-friendly web tools; it integrates entomological, veterinary and human surveillance, molecular information on pathogens and environmental and climatic data. The principal result of the DMD development is the transfer and dissemination of knowledge and technologies to develop strategies for integrated prevention and control measures of animal and human diseases.

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

Regional climate projections for the MENA-CORDEX domain: analysis of projected temperature and precipitation changes

NASA Astrophysics Data System (ADS)

Hänsler, Andreas; Weber, Torsten; Eggert, Bastian; Saeed, Fahad; Jacob, Daniela

2014-05-01

Within the CORDEX initiative a multi-model suite of regionalized climate change information will be made available for several regions of the world. The German Climate Service Center (CSC) is taking part in this initiative by applying the regional climate model REMO to downscale global climate projections of different coupled general circulation models (GCMs) for several CORDEX domains. Also for the MENA-CORDEX domain, a set of regional climate change projections has been established at the CSC by downscaling CMIP5 projections of the Max-Planck-Institute Earth System Model (MPI-ESM) for the scenarios RCP4.5 and RCP8.5 with the regional model REMO for the time period from 1950 to 2100 to a horizontal resolution of 0.44 degree. In this study we investigate projected changes in future climate conditions over the domain towards the end of the 21st century. Focus in the analysis is given to projected changes in the temperature and rainfall characteristics and their differences for the two scenarios will be highlighted.

Can We Consume Our Way Out of Climate Change? A Call for Analysis

PubMed Central

Grant, Lyle K

2011-01-01

The problem of climate change is analyzed as a manifestation of economic growth, and the steady-state economy of ecological economics is proposed as a system-wide solution. Four classes of more specific solutions are described. In the absence of analysis, cultural inertia will bias solutions in favor of green consumption as a generalized solution strategy. By itself, green consumption is a flawed solution to climate change because it perpetuates or even accelerates economic growth that is incompatible with a sustainable culture. Addressing climate change requires an integration of regulatory, energy efficiency, skill-based, and dissemination solutions. Behavioral scientists are encouraged to work with others in ecological economics and other social sciences who recognize cultural reinvention as a means of achieving sustainability. PMID:22532747

TECA: Petascale pattern recognition for climate science

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

Prabhat, .; Byna, Surendra; Vishwanath, Venkatram

Climate Change is one of the most pressing challenges facing humanity in the 21st century. Climate simulations provide us with a unique opportunity to examine effects of anthropogenic emissions. Highresolution climate simulations produce “Big Data”: contemporary climate archives are ≈ 5PB in size and we expect future archives to measure on the order of Exa-Bytes. In this work, we present the successful application of TECA (Toolkit for Extreme Climate Analysis) framework, for extracting extreme weather patterns such as Tropical Cyclones, Atmospheric Rivers and Extra-Tropical Cyclones from TB-sized simulation datasets. TECA has been run at full-scale on Cray XE6 and IBMmore » BG/Q systems, and has reduced the runtime for pattern detection tasks from years to hours. TECA has been utilized to evaluate the performance of various computational models in reproducing the statistics of extreme weather events, and for characterizing the change in frequency of storm systems in the future.« less

Response of the groundwater system in the Guanzhong Basin (central China) to climate change and human activities

NASA Astrophysics Data System (ADS)

Wang, Wenke; Zhang, Zaiyong; Duan, Lei; Wang, Zhoufeng; Zhao, Yaqian; Zhang, Qian; Dai, Meiling; Liu, Huizhong; Zheng, Xiaoyan; Sun, Yibo

2018-03-01

The Guanzhong Basin in central China features a booming economy and has suffered severe drought, resulting in serious groundwater depletion in the last 30 years. As a major water resource, groundwater plays a significant role in water supply. The combined impact of climate change and intensive human activities has caused a substantial decline in groundwater recharge and groundwater levels, as well as degradation of groundwater quality and associated changes in the ecosystems. Based on observational data, an integrated approach was used to assess the impact of climate change and human activities on the groundwater system and the base flow of the river basin. Methods included: river runoff records and a multivariate statistical analysis of data including historical groundwater levels and climate; hydro-chemical investigation and trend analysis of the historical hydro-chemical data; wavelet analysis of climate data; and the base flow index. The analyses indicate a clear warming trend and a decreasing trend in rainfall since the 1960s, in addition to increased human activities since the 1970s. The reduction of groundwater recharge in the past 30 years has led to a continuous depletion of groundwater levels, complex changes of the hydro-chemical environment, localized salinization, and a strong decline of the base flow to the river. It is expected that the results will contribute to a more comprehensive management plan for groundwater and the related eco-environment in the face of growing pressures from intensive human activities superimposed on climate change in this region.

Some Good Practices for Integration and Outreach and their Implementation in the Community Integrated Assessment System (CIAS) and its associated web portal CLIMASCOPE

NASA Astrophysics Data System (ADS)

Warren, R. F.; Price, J. T.; Goswami, S.

2010-12-01

Successful communication of knowledge to climate change policy makers requires the careful integration of scientific knowledge in an integrated assessment that can be clearly communicated to stakeholders, and which encapsulates the uncertainties in the analysis and conveys the need for using a risk assessment approach. It is important that (i) the system is co-designed with the users (ii) relevant disciplines are included (iii) assumptions made are clear (iv) the robustness of outputs to uncertainties is demonstrated (v) the system is flexible so that it can keep up with changing stakeholder needs and (vi) the results are communicated clearly and are readily accessible. The “Community Integrated Assessment System” (CIAS) is a unique multi-institutional, modular, and flexible integrated assessment system for modeling climate change which fulfils the above six criteria. It differs from other integrated models in being a flexible system allowing various combinations of component modules, to be connected together into alternative integrated assessment models. These modules may be written at different institutions in different computer languages and/or based on different operating systems. Scientists are able determine which particular CIAS coupled model they wish to use through a web portal. This includes the facility to implement Latin hypercube experimental design facilitating formal uncertainty analysis. Further exploration of robustness is possible through the ability to select, for example, alternative hyrdrological or climate models to address the same questions. It has been applied to study future scenarios of climate change mitigation, through for example the AVOIDing dangerous climate change project for DEFRA, in which the avoided impacts (benefits) of alternative climate policies were compared to no-policy baselines. These highlight the potential for mitigation to remove a substantial fraction of the climate change impacts that would otherwise occur; but also show that is not possible to avoid all the impacts, and hence that adaptation will still be required. For example, this has been shown for projections of future European drought. CIAS has also been used for analyses used in the IPCC 4AR and the Stern review. Recent applications include a study of the role of avoided deforestation in climate mitigation, and a study of the impacts of climate change on biodiversity. A second web portal, CLIMASCOPE, is being developed for use by stakeholders, currently focusing on the needs of adaptation planners. This will benefit communication by allowing a wide range of users free access to regional climate change projections in simple manner, yet one which encourages risk assessment through encapsulation of the uncertainties in climate change projection. Examples of CLIMASCOPE output that is being made available to stakeholders will be shown.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Understanding the Reach of Agricultural Impacts from Climate Extremes in the Agricultural Model Intercomparison and Improvement Project (AgMIP)

NASA Astrophysics Data System (ADS)

Ruane, A. C.

2016-12-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has been working since 2010 to build a modeling framework capable of representing the complexities of agriculture, its dependence on climate, and the many elements of society that depend on food systems. AgMIP's 30+ activities explore the interconnected nature of climate, crop, livestock, economics, food security, and nutrition, using common protocols to systematically evaluate the components of agricultural assessment and allow multi-model, multi-scale, and multi-method analysis of intertwining changes in socioeconomic development, environmental change, and technological adaptation. AgMIP is now launching Coordinated Global and Regional Assessments (CGRA) with a particular focus on unforeseen consequences of development strategies, interactions between global and local systems, and the resilience of agricultural systems to extreme climate events. Climate extremes shock the agricultural system through local, direct impacts (e.g., droughts, heat waves, floods, severe storms) and also through teleconnections propagated through international trade. As the climate changes, the nature of climate extremes affecting agriculture is also likely to change, leading to shifting intensity, duration, frequency, and geographic extents of extremes. AgMIP researchers are developing new scenario methodologies to represent near-term extreme droughts in a probabilistic manner, field experiments that impose heat wave conditions on crops, increased resolution to differentiate sub-national drought impacts, new behavioral functions that mimic the response of market actors faced with production shortfalls, analysis of impacts from simultaneous failures of multiple breadbasket regions, and more detailed mapping of food and socioeconomic indicators into food security and nutrition metrics that describe the human impact in diverse populations. Agricultural models illustrate the challenges facing agriculture, allowing resilience planning even as precise prediction of extremes remains difficult. Increased research is necessary to understand hazards, vulnerability, and exposure of populations to characterize the risk of shocks and mechanisms by which unexpected losses drive land-use transitions.

Is There a Temperate Bias in Our Understanding of How Climate Change Will Alter Plant-Herbivore Interactions? A Meta-analysis of Experimental Studies.

PubMed

Mundim, Fabiane M; Bruna, Emilio M

2016-09-01

Climate change can drive major shifts in community composition and interactions between resident species. However, the magnitude of these changes depends on the type of interactions and the biome in which they take place. We review the existing conceptual framework for how climate change will influence tropical plant-herbivore interactions and formalize a similar framework for the temperate zone. We then conduct the first biome-specific tests of how plant-herbivore interactions change in response to climate-driven changes in temperature, precipitation, ambient CO2, and ozone. We used quantitative meta-analysis to compare predicted and observed changes in experimental studies. Empirical studies were heavily biased toward temperate systems, so testing predicted changes in tropical plant-herbivore interactions was virtually impossible. Furthermore, most studies investigated the effects of CO2 with limited plant and herbivore species. Irrespective of location, most studies manipulated only one climate change factor despite the fact that different factors can act in synergy to alter responses of plants and herbivores. Finally, studies of belowground plant-herbivore interactions were also rare; those conducted suggest that climate change could have major effects on belowground subsystems. Our results suggest that there is a disconnection between the growing literature proposing how climate change will influence plant-herbivore interactions and the studies testing these predictions. General conclusions will also be hampered without better integration of above- and belowground systems, assessing the effects of multiple climate change factors simultaneously, and using greater diversity of species in experiments.

Simulation skill of APCC set of global climate models for Asian summer monsoon rainfall variability

NASA Astrophysics Data System (ADS)

Singh, U. K.; Singh, G. P.; Singh, Vikas

2015-04-01

The performance of 11 Asia-Pacific Economic Cooperation Climate Center (APCC) global climate models (coupled and uncoupled both) in simulating the seasonal summer (June-August) monsoon rainfall variability over Asia (especially over India and East Asia) has been evaluated in detail using hind-cast data (3 months advance) generated from APCC which provides the regional climate information product services based on multi-model ensemble dynamical seasonal prediction systems. The skill of each global climate model over Asia was tested separately in detail for the period of 21 years (1983-2003), and simulated Asian summer monsoon rainfall (ASMR) has been verified using various statistical measures for Indian and East Asian land masses separately. The analysis found a large variation in spatial ASMR simulated with uncoupled model compared to coupled models (like Predictive Ocean Atmosphere Model for Australia, National Centers for Environmental Prediction and Japan Meteorological Agency). The simulated ASMR in coupled model was closer to Climate Prediction Centre Merged Analysis of Precipitation (CMAP) compared to uncoupled models although the amount of ASMR was underestimated in both models. Analysis also found a high spread in simulated ASMR among the ensemble members (suggesting that the model's performance is highly dependent on its initial conditions). The correlation analysis between sea surface temperature (SST) and ASMR shows that that the coupled models are strongly associated with ASMR compared to the uncoupled models (suggesting that air-sea interaction is well cared in coupled models). The analysis of rainfall using various statistical measures suggests that the multi-model ensemble (MME) performed better compared to individual model and also separate study indicate that Indian and East Asian land masses are more useful compared to Asia monsoon rainfall as a whole. The results of various statistical measures like skill of multi-model ensemble, large spread among the ensemble members of individual model, strong teleconnection (correlation analysis) with SST, coefficient of variation, inter-annual variability, analysis of Taylor diagram, etc. suggest that there is a need to improve coupled model instead of uncoupled model for the development of a better dynamical seasonal forecast system.

Probabilistic seasonal Forecasts to deterministic Farm Leve Decisions: Innovative Approach

NASA Astrophysics Data System (ADS)

Mwangi, M. W.

2015-12-01

Climate change and vulnerability are major challenges in ensuring household food security. Climate information services have the potential to cushion rural households from extreme climate risks. However, most the probabilistic nature of climate information products is not easily understood by majority of smallholder farmers. Despite the probabilistic nature, climate information have proved to be a valuable climate risk adaptation strategy at the farm level. This calls for innovative ways to help farmers understand and apply climate information services to inform their farm level decisions. The study endeavored to co-design and test appropriate innovation systems for climate information services uptake and scale up necessary for achieving climate risk development. In addition it also determined the conditions necessary to support the effective performance of the proposed innovation system. Data and information sources included systematic literature review, secondary sources, government statistics, focused group discussions, household surveys and semi-structured interviews. Data wasanalyzed using both quantitative and qualitative data analysis techniques. Quantitative data was analyzed using the Statistical Package for Social Sciences (SPSS) software. Qualitative data was analyzed using qualitative techniques, which involved establishing the categories and themes, relationships/patterns and conclusions in line with the study objectives. Sustainable livelihood, reduced household poverty and climate change resilience were the impact that resulted from the study.

Using Web GIS "Climate" for Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Gordova, Yulia; Martynova, Yulia; Shulgina, Tamara

2015-04-01

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

Climate Drivers of Alaska Summer Stream Temperature

NASA Astrophysics Data System (ADS)

Bieniek, P.; Bhatt, U. S.; Plumb, E. W.; Thoman, R.; Trammell, E. J.

2016-12-01

The temperature of the water in lakes, rivers and streams has wide ranging impacts from local water quality and fish habitats to global climate change. Salmon fisheries in Alaska, a critical source of food in many subsistence communities, are sensitive to large-scale climate variability and river and stream temperatures have also been linked with salmon production in Alaska. Given current and projected climate change, understanding the mechanisms that link the large-scale climate and river and stream temperatures is essential to better understand the changes that may occur with aquatic life in Alaska's waterways on which subsistence users depend. An analysis of Alaska stream temperatures in the context of reanalysis, downscaled, station and other climate data is undertaken in this study to fill that need. Preliminary analysis identified eight stream observation sites with sufficiently long (>15 years) data available for climate-scale analysis in Alaska with one station, Terror Creek in Kodiak, having a 30-year record. Cross-correlation of summer (June-August) water temperatures between the stations are generally high even though they are spread over a large geographic region. Correlation analysis of the Terror Creek summer observations with seasonal sea surface temperatures (SSTs) in the North Pacific broadly resembles the SST anomaly fields typically associated with the Pacific Decadal Oscillation (PDO). A similar result was found for the remaining stations and in both cases PDO-like correlation patterns also occurred in the preceding spring. These preliminary results demonstrate that there is potential to diagnose the mechanisms that link the large-scale climate system and Alaska stream temperatures.

Detecting hydrological changes through conceptual model

NASA Astrophysics Data System (ADS)

Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo

2015-04-01

Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General Circulation Models (GCMs) for the future scenarios 2046-2065 and 2081-2100. Land use changes (i.e., changes in the fraction of impervious area due to increasing urbanization) are explicitly simulated, while the reference hydrological responses are assessed by the spatially distributed, process-based hydrological model tRIBS, the TIN-based Real-time Integrated Basin Simulator. Several scenarios have been created, describing hypothetical centuries with steady conditions, climate change conditions, land use change conditions and finally complex conditions involving both transient climatic modifications and gradual land use changes. A conceptual lumped model, the EHSM (EcoHydrological Streamflow Model) is calibrated for the above mentioned scenarios with regard to different time-windows. The calibrated parameters show high sensitivity to anthropic variations in land use and/or climatic variability. Land use changes are clearly visible from parameters evolution especially when steady climatic conditions are considered. When the increase in urbanization is coupled with rainfall reduction the ability to detect human interventions through the analysis of conceptual model parameters is weakened.

Toward a Continental-Scale Mesonet: USDA National Resources Conservation Service SCAN and SNOTEL System

NASA Astrophysics Data System (ADS)

Schaffer, G.; Marks, D.

2004-12-01

Since 1978 snow deposition and SWE in the inter-mountain western US have been monitored by the NRCS SNOTEL (SNOwpack TELemetry) system. This revolutionary network utilizes Meteorburst technology to telemeter data back to a central location in near real-time. With a pilot program starting in 1991, NRCS introduced SCAN (Soil Climate and Analysis Network) adding a focus on soil moisture and climate in regions outside the intermountain west. In the mid-1990's SNOTEL sites began to be augmented to match the full climate instrumentation (air temperature, humidity, solar radiation, wind, and soil moisture and temperature in addition to precipitation, snow depth and SWE) of the SCAN system. At present there are nearly 700 SNOTEL sites in 12 states in the western US and Alaska, and over 100 SCAN sites in 40 states, Puerto Rico, and several foreign countries. Though SNOTEL was originally a western snow-monitoring network, differences between SCAN and SNOTEL have largely disappeared. The combined SNOTEL/SCAN system provides a continental-scale mesonet to support river basin to continental scale hydro-climatic analysis. The system is flexible and based on off-the-shelf data recording technology, allowing instrumentation, sampling and averaging intervals to be specified by site conditions, issues, or scientific questions. Because of the NRCS data management structure, all sites have active telemetery and provide near real-time access to data through the internet. An ongoing research program is directed to improved instrumentation for measuring precipitation, snow depth and SWE, and soil moisture and temperature. Future directions include expansion of the network to be more comprehensive, and to develop focused monitoring efforts to more effectively observe elevational and regional gradients, and to capture high intensity hydro-climatic events such as potential flooding from convective storms and rain-on-snow.

Precision diet formulation to improve performance and profitability across various climates: Modeling the implications of increasing the formulation frequency of dairy cattle diets.

PubMed

White, Robin R; Capper, Judith L

2014-03-01

The objective of this study was to use a precision nutrition model to simulate the relationship between diet formulation frequency and dairy cattle performance across various climates. Agricultural Modeling and Training Systems (AMTS) CattlePro diet-balancing software (Cornell Research Foundation, Ithaca, NY) was used to compare 3 diet formulation frequencies (weekly, monthly, or seasonal) and 3 levels of climate variability (hot, cold, or variable). Predicted daily milk yield (MY), metabolizable energy (ME) balance, and dry matter intake (DMI) were recorded for each frequency-variability combination. Economic analysis was conducted to calculate the predicted revenue over feed and labor costs. Diet formulation frequency affected ME balance and MY but did not affect DMI. Climate variability affected ME balance and DMI but not MY. The interaction between climate variability and formulation frequency did not affect ME balance, MY, or DMI. Formulating diets more frequently increased MY, DMI, and ME balance. Economic analysis showed that formulating diets weekly rather than seasonally could improve returns over variable costs by $25,000 per year for a moderate-sized (300-cow) operation. To achieve this increase in returns, an entire feeding system margin of error of <1% was required. Formulating monthly, rather than seasonally, may be a more feasible alternative as this requires a margin of error of only 2.5% for the entire feeding system. Feeding systems with a low margin of error must be developed to better take advantage of the benefits of precision nutrition. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Seasonal Prediction of Taiwan's Streamflow Using Teleconnection Patterns

NASA Astrophysics Data System (ADS)

Chen, Chia-Jeng; Lee, Tsung-Yu

2017-04-01

Seasonal streamflow as an integrated response to complex hydro-climatic processes can be subject to activity of prevailing weather systems potentially modulated by large-scale climate oscillations (e.g., El Niño-Southern Oscillation, ENSO). To develop a seamless seasonal forecasting system in Taiwan, this study assesses how significant Taiwan's precipitation and streamflow in different seasons correlate with selected teleconnection patterns. Long-term precipitation and streamflow data in three major precipitation seasons, namely the spring rains (February to April), Mei-Yu (May and June), and typhoon (July to September) seasons, are derived at 28 upstream and 13 downstream catchments in Taiwan. The three seasons depict a complete wet period of Taiwan as well as many regions bearing similar climatic conditions in East Asia. Lagged correlation analysis is then performed to investigate how the precipitation and streamflow data correlate with predominant teleconnection indices at varied lead times. Teleconnection indices are selected only if they show certain linkage with weather systems and activity in the three seasons based on previous literature. For instance, the ENSO and Quasi-Biennial Oscillation, proven to influence East Asian climate across seasons and summer typhoon activity, respectively, are included in the list of climate indices for correlation analysis. Significant correlations found between Taiwan's precipitation and streamflow and teleconnection indices are further examined by a climate regime shift (CRS) test to identify any abrupt changes in the correlations. The understanding of existing CRS is useful for informing the forecasting system of the changes in the predictor-predictand relationship. To evaluate prediction skill in the three seasons and skill differences between precipitation and streamflow, hindcasting experiments of precipitation and streamflow are conducted using stepwise linear regression models. Discussion and suggestions for coping with extreme events in empirical seasonal predictions are also carried out. Findings from this work will contribute to the development of an integrated water resources planning and management system.

Web-GIS approach for integrated analysis of heterogeneous georeferenced data

NASA Astrophysics Data System (ADS)

Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander; Shulgina, Tamara

2014-05-01

Georeferenced datasets are currently actively used for modeling, interpretation and forecasting of climatic and ecosystem changes on different spatial and temporal scales [1]. Due to inherent heterogeneity of environmental datasets as well as their huge size (up to tens terabytes for a single dataset) a special software supporting studies in the climate and environmental change areas is required [2]. Dedicated information-computational system for integrated analysis of heterogeneous georeferenced climatological and meteorological data is presented. It is based on combination of Web and GIS technologies according to Open Geospatial Consortium (OGC) standards, and involves many modern solutions such as object-oriented programming model, modular composition, and JavaScript libraries based on GeoExt library (http://www.geoext.org), ExtJS Framework (http://www.sencha.com/products/extjs) and OpenLayers software (http://openlayers.org). The main advantage of the system lies in it's capability to perform integrated analysis of time series of georeferenced data obtained from different sources (in-situ observations, model results, remote sensing data) and to combine the results in a single map [3, 4] as WMS and WFS layers in a web-GIS application. Also analysis results are available for downloading as binary files from the graphical user interface or can be directly accessed through web mapping (WMS) and web feature (WFS) services for a further processing by the user. Data processing is performed on geographically distributed computational cluster comprising data storage systems and corresponding computational nodes. Several geophysical datasets represented by NCEP/NCAR Reanalysis II, JMA/CRIEPI JRA-25 Reanalysis, ECMWF ERA-40 Reanalysis, ECMWF ERA Interim Reanalysis, MRI/JMA APHRODITE's Water Resources Project Reanalysis, DWD Global Precipitation Climatology Centre's data, GMAO Modern Era-Retrospective analysis for Research and Applications, reanalysis of Monitoring atmospheric composition and climate (MACC) Collaborated Project, NOAA-CIRES Twentieth Century Global Reanalysis Version II, NCEP Climate Forecast System Reanalysis (CFSR), meteorological observational data for the territory of the former USSR for the 20th century, results of modeling by global and regional climatological models, and others are available for processing by the system. The Web-GIS information-computational system for heterogeneous geophysical data analysis provides specialists involved into multidisciplinary research projects with reliable and practical instruments for integrated research of climate and ecosystems changes on global and regional scales. With its help even an unskilled in programming user is able to process and visualize multidimensional observational and model data through unified web-interface using a common graphical web-browser. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grant #13-05-12034, grant #14-05-00502, and integrated project SB RAS #131. References 1. Gordov E.P., Lykosov V.N., Krupchatnikov V.N., Okladnikov I.G., Titov A.G., Shulgina T.M. Computational and information technologies for monitoring and modeling of climate changes and their consequences. - Novosibirsk: Nauka, Siberian branch, 2013. - 195 p. (in Russian) 2. Felice Frankel, Rosalind Reid. Big data: Distilling meaning from data // Nature. Vol. 455. N. 7209. P. 30. 3. T.M. Shulgina, E.P. Gordov, I.G. Okladnikov, A.G., Titov, E.Yu. Genina, N.P. Gorbatenko, I.V. Kuzhevskaya, A.S. Akhmetshina. Software complex for a regional climate change analysis. // Vestnik NGU. Series: Information technologies. 2013. Vol. 11. Issue 1. P. 124-131 (in Russian). 4. I.G. Okladnikov, A.G. Titov, T.M. Shulgina, E.P. Gordov, V.Yu. Bogomolov, Yu.V. Martynova, S.P. Suschenko, A.V. Skvortsov. Software for analysis and visualization of climate change monitoring and forecasting data // Numerical methods and programming, 2013. Vol. 14. P. 123-131 (in Russian).

Quantification of physical and economic impacts of climate change on public infrastructure in Alaska and benefits of global greenhouse gas mitigation

NASA Astrophysics Data System (ADS)

Melvin, A. M.; Larsen, P.; Boehlert, B.; Martinich, J.; Neumann, J.; Chinowsky, P.; Schweikert, A.; Strzepek, K.

2015-12-01

Climate change poses many risks and challenges for the Arctic and sub-Arctic, including threats to infrastructure. The safety and stability of infrastructure in this region can be impacted by many factors including increased thawing of permafrost soils, reduced coastline protection due to declining arctic sea ice, and changes in inland flooding. The U.S. Environmental Protection Agency (EPA) is coordinating an effort to quantify physical and economic impacts of climate change on public infrastructure across the state of Alaska and estimate how global greenhouse gas (GHG) mitigation may avoid or reduce these impacts. This research builds on the Climate Change Impacts and Risk Analysis (CIRA) project developed for the contiguous U.S., which is described in an EPA report released in June 2015. We are using a multi-model analysis focused primarily on the impacts of changing permafrost, coastal erosion, and inland flooding on a range of infrastructure types, including transportation (e.g. roads, airports), buildings and harbors, energy sources and transmission, sewer and water systems, and others. This analysis considers multiple global GHG emission scenarios ranging from a business as usual future to significant global action. These scenarios drive climate projections through 2100 spanning a range of outcomes to capture variability amongst climate models. Projections are being combined with a recently developed public infrastructure database and integrated into a version of the Infrastructure Planning Support System (IPSS) we are modifying for use in the Arctic and sub-Arctic region. The IPSS tool allows for consideration of both adaptation and reactive responses to climate change. Results of this work will address a gap in our understanding of climate change impacts in Alaska, provide estimates of the physical and economic damages we may expect with and without global GHG mitigation, and produce important insights about infrastructure vulnerabilities in response to warming at northern latitudes.

An analysis of simulated and observed storm characteristics

NASA Astrophysics Data System (ADS)

Benestad, R. E.

2010-09-01

A calculus-based cyclone identification (CCI) method has been applied to the most recent re-analysis (ERAINT) from the European Centre for Medium-range Weather Forecasts and results from regional climate model (RCM) simulations. The storm frequency for events with central pressure below a threshold value of 960-990hPa were examined, and the gradient wind from the simulated storm systems were compared with corresponding estimates from the re-analysis. The analysis also yielded estimates for the spatial extent of the storm systems, which was also included in the regional climate model cyclone evaluation. A comparison is presented between a number of RCMs and the ERAINT re-analysis in terms of their description of the gradient winds, number of cyclones, and spatial extent. Furthermore, a comparison between geostrophic wind estimated though triangules of interpolated or station measurements of SLP is presented. Wind still represents one of the more challenging variables to model realistically.

Droughts and governance impacts on water scarcity: an~analysis in the Brazilian semi-arid

NASA Astrophysics Data System (ADS)

Silva, A. C. S.; Galvão, C. O.; Silva, G. N. S.

2015-06-01

Extreme events are part of climate variability. Dealing with variability is still a challenge that might be increased due to climate change. However, impacts of extreme events are not only dependent on their variability, but also on management and governance. In Brazil, its semi-arid region is vulnerable to extreme events, especially droughts, for centuries. Actually, other Brazilian regions that have been mostly concerned with floods are currently also experiencing droughts. This article evaluates how a combination between climate variability and water governance might affect water scarcity and increase the impacts of extreme events on some regions. For this evaluation, Ostrom's framework for analyzing social-ecological systems (SES) was applied. Ostrom's framework is useful for understanding interactions between resource systems, governance systems and resource users. This study focuses on social-ecological systems located in a drought-prone region of Brazil. Two extreme events were selected, one in 1997-2000, when Brazil's new water policy was very young, and the other one in 2012-2015. The analysis of SES considering Ostrom's principle "Clearly defined boundaries" showed that deficiencies in water management cause the intensification of drought's impacts for the water users. The reasons are more related to water management and governance problems than to drought event magnitude or climate change. This is a problem that holdup advances in dealing with extreme events.

Climate change impacts on rainfall extremes and urban drainage: state-of-the-art review

NASA Astrophysics Data System (ADS)

Willems, Patrick; Olsson, Jonas; Arnbjerg-Nielsen, Karsten; Beecham, Simon; Pathirana, Assela; Bülow Gregersen, Ida; Madsen, Henrik; Nguyen, Van-Thanh-Van

2013-04-01

Under the umbrella of the IWA/IAHR Joint Committee on Urban Drainage, the International Working Group on Urban Rainfall (IGUR) has reviewed existing methodologies for the analysis of long-term historical and future trends in urban rainfall extremes and their effects on urban drainage systems, due to anthropogenic climate change. Current practises have several limitations and pitfalls, which are important to be considered by trend or climate change impact modellers and users of trend/impact results. The review considers the following aspects: Analysis of long-term historical trends due to anthropogenic climate change: influence of data limitation, instrumental or environmental changes, interannual variations and longer term climate oscillations on trend testing results. Analysis of long-term future trends due to anthropogenic climate change: by complementing empirical historical data with the results from physically-based climate models, dynamic downscaling to the urban scale by means of Limited Area Models (LAMs) including explicitly small-scale cloud processes; validation of RCM/GCM results for local conditions accounting for natural variability, limited length of the available time series, difference in spatial scales, and influence of climate oscillations; statistical downscaling methods combined with bias correction; uncertainties associated with the climate forcing scenarios, the climate models, the initial states and the statistical downscaling step; uncertainties in the impact models (e.g. runoff peak flows, flood or surcharge frequencies, and CSO frequencies and volumes), including the impacts of more extreme conditions than considered during impact model calibration and validation. Implications for urban drainage infrastructure design and management: upgrading of the urban drainage system as part of a program of routine and scheduled replacement and renewal of aging infrastructure; how to account for the uncertainties; flexible and sustainable solutions; adaptive approach that provides inherent flexibility and reversibility and avoids closing off options; importance of active learning. References: Willems, P., Olsson, J., Arnbjerg-Nielsen, K., Beecham, S., Pathirana, A., Bülow Gregersen, I., Madsen, H., Nguyen, V-T-V. (2012). Impacts of climate change on rainfall extremes and urban drainage. IWA Publishing, 252 p., Paperback Print ISBN 9781780401256; Ebook ISBN 9781780401263 Willems, P., Arnbjerg-Nielsen, K., Olsson, J., Nguyen, V.T.V. (2012), 'Climate change impact assessment on urban rainfall extremes and urban drainage: methods and shortcomings', Atmospheric Research, 103, 106-118

Climate Change Impacts on Hydrology and Water Management of the San Juan Basin

NASA Astrophysics Data System (ADS)

Rich, P. M.; Weintraub, L. H.; Chen, L.; Herr, J.

2005-12-01

Recent climatic events, including regional drought and increased storm severity, have accentuated concerns that climatic extremes may be increasing in frequency and intensity due to global climate change. As part of the ZeroNet Water-Energy Initiative, the San Juan Decision Support System includes a basin-scale modeling tool to evaluate effects of climate change on water budgets under different climate and management scenarios. The existing Watershed Analysis Risk Management Framework (WARMF) was enhanced with iterative modeling capabilities to enable construction of climate scenarios based on historical and projected data. We applied WARMF to 42,000 km2 (16,000 mi2) of the San Juan Basin (CO, NM) to assess impacts of extended drought and increased temperature on surface water balance. Simulations showed that drought and increased temperature impact water availability for all sectors (agriculture, energy, municipal, industry), and lead to increased frequency of critical shortages. Implementation of potential management alternatives such as "shortage sharing" or degraded water usage during critical years helps improve available water supply. In the face of growing concern over climate change, limited water resources, and competing demands, integrative modeling tools can enable better understanding of complex interconnected systems, and enable better decisions.

Toward server-side, high performance climate change data analytics in the Earth System Grid Federation (ESGF) eco-system

NASA Astrophysics Data System (ADS)

Fiore, Sandro; Williams, Dean; Aloisio, Giovanni

2016-04-01

In many scientific domains such as climate, data is often n-dimensional and requires tools that support specialized data types and primitives to be properly stored, accessed, analysed and visualized. Moreover, new challenges arise in large-scale scenarios and eco-systems where petabytes (PB) of data can be available and data can be distributed and/or replicated (e.g., the Earth System Grid Federation (ESGF) serving the Coupled Model Intercomparison Project, Phase 5 (CMIP5) experiment, providing access to 2.5PB of data for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5). Most of the tools currently available for scientific data analysis in the climate domain fail at large scale since they: (1) are desktop based and need the data locally; (2) are sequential, so do not benefit from available multicore/parallel machines; (3) do not provide declarative languages to express scientific data analysis tasks; (4) are domain-specific, which ties their adoption to a specific domain; and (5) do not provide a workflow support, to enable the definition of complex "experiments". The Ophidia project aims at facing most of the challenges highlighted above by providing a big data analytics framework for eScience. Ophidia provides declarative, server-side, and parallel data analysis, jointly with an internal storage model able to efficiently deal with multidimensional data and a hierarchical data organization to manage large data volumes ("datacubes"). The project relies on a strong background of high performance database management and OLAP systems to manage large scientific data sets. It also provides a native workflow management support, to define processing chains and workflows with tens to hundreds of data analytics operators to build real scientific use cases. With regard to interoperability aspects, the talk will present the contribution provided both to the RDA Working Group on Array Databases, and the Earth System Grid Federation (ESGF) Compute Working Team. Also highlighted will be the results of large scale climate model intercomparison data analysis experiments, for example: (1) defined in the context of the EU H2020 INDIGO-DataCloud project; (2) implemented in a real geographically distributed environment involving CMCC (Italy) and LLNL (US) sites; (3) exploiting Ophidia as server-side, parallel analytics engine; and (4) applied on real CMIP5 data sets available through ESGF.

Varying geospatial analyses to assess climate risk and adaptive capacity in a hotter, drier Southwestern United States

NASA Astrophysics Data System (ADS)

Elias, E.; Reyes, J. J.; Steele, C. M.; Rango, A.

2017-12-01

Assessing vulnerability of agricultural systems to climate variability and change is vital in securing food systems and sustaining rural livelihoods. Farmers, ranchers, and forest landowners rely on science-based, decision-relevant, and localized information to maintain production, ecological viability, and economic returns. This contribution synthesizes a collection of research on the future of agricultural production in the American Southwest (SW). Research was based on a variety of geospatial methodologies and datasets to assess the vulnerability of rangelands and livestock, field crops, specialty crops, and forests in the SW to climate-risk and change. This collection emerged from the development of regional vulnerability assessments for agricultural climate-risk by the U.S. Department of Agriculture (USDA) Climate Hub Network, established to deliver science-based information and technologies to enable climate-informed decision-making. Authors defined vulnerability differently based on their agricultural system of interest, although each primarily focuses on biophysical systems. We found that an inconsistent framework for vulnerability and climate risk was necessary to adequately capture the diversity, variability, and heterogeneity of SW landscapes, peoples, and agriculture. Through the diversity of research questions and methodologies, this collection of articles provides valuable information on various aspects of SW vulnerability. All articles relied on geographic information systems technology, with highly variable levels of complexity. Agricultural articles used National Agricultural Statistics Service data, either as tabular county level summaries or through the CropScape cropland raster datasets. Most relied on modeled historic and future climate information, but with differing assumptions regarding spatial resolution and temporal framework. We assert that it is essential to evaluate climate risk using a variety of complementary methodologies and perspectives. In addition, we found that spatial analysis supports informed adaptation, within and outside the SW United States. The persistence and adaptive capacity of agriculture in the water-limited Southwest serves as an instructive example and may offer solutions to reduce future climate risk.

Simulation of Transcritical CO2 Refrigeration System with Booster Hot Gas Bypass in Tropical Climate

NASA Astrophysics Data System (ADS)

Santosa, I. D. M. C.; Sudirman; Waisnawa, IGNS; Sunu, PW; Temaja, IW

2018-01-01

A Simulation computer becomes significant important for performance analysis since there is high cost and time allocation to build an experimental rig, especially for CO2 refrigeration system. Besides, to modify the rig also need additional cos and time. One of computer program simulation that is very eligible to refrigeration system is Engineering Equation System (EES). In term of CO2 refrigeration system, environmental issues becomes priority on the refrigeration system development since the Carbon dioxide (CO2) is natural and clean refrigerant. This study aims is to analysis the EES simulation effectiveness to perform CO2 transcritical refrigeration system with booster hot gas bypass in high outdoor temperature. The research was carried out by theoretical study and numerical analysis of the refrigeration system using the EES program. Data input and simulation validation were obtained from experimental and secondary data. The result showed that the coefficient of performance (COP) decreased gradually with the outdoor temperature variation increasing. The results show the program can calculate the performance of the refrigeration system with quick running time and accurate. So, it will be significant important for the preliminary reference to improve the CO2 refrigeration system design for the hot climate temperature.

Environmental and economic risks assessment under climate changes for three land uses scenarios analysis across Teshio watershed, northernmost of Japan.

PubMed

Fan, Min; Shibata, Hideaki; Chen, Li

2017-12-01

Land use and climate changes affect on the economy and environment with different patterns and magnitudes in the watershed. This study used risk analysis model stochastic efficiency with respect to a function (SERF) to evaluate economic and environmental risks caused by four climate change scenarios (baseline, small-, mid- and large changes) and three land uses (paddy dominated, paddy-farmland mixture and farmland dominated for agriculture) in Teshio watershed in northern Hokkaido, Japan. Under the baseline climate conditions, the lower ranking of economic income of crop yield and higher ranking of pollutant load from agricultural land were both predicted in paddy dominated for agriculture, suggesting that the paddy dominated system caused higher risks of economic and environmental variables compared to other two land uses. Increase of temperature and precipitation increased crop yields under all three climate changes which resulted in increase of the ranking of economic income, indicating that those climate changes could reduce economic risk. The increased temperature and precipitation also accelerated mineralization of organic nutrient and nutrient leaching to river course of Teshio which resulted in increase of the ranking of pollutant load, suggesting that those climate changes could lead to more environmental risk. The rankings of economic income in mid- and large changes of climate were lower than that in small change of climate under paddy-farmland mixture and farmland dominated systems due to decrease of crop yield, suggesting that climate change led to more economic risk. In summary, the results suggested that increase in temperature and precipitation caused higher risks of both economic and environmental perspectives, and the impacts was higher than those of land use changes in the studied watershed. Those findings would help producers and watershed managers to measure the tradeoffs between environmental protection and agricultural economic development for making decision under land use and climate changes. Copyright © 2017 Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Kolokolov, Yury; Monovskaya, Anna

2016-06-01

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

Variation in Estimated Ozone-Related Health Impacts of Climate Change due to Modeling Choices and Assumptions

PubMed Central

Post, Ellen S.; Grambsch, Anne; Weaver, Chris; Morefield, Philip; Leung, Lai-Yung; Nolte, Christopher G.; Adams, Peter; Liang, Xin-Zhong; Zhu, Jin-Hong; Mahoney, Hardee

2012-01-01

Background: Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices. Objectives: Our goal was to assess the sensitivity of estimated ozone-related human health impacts of climate change to key modeling choices. Methods: Our analysis included seven modeling systems in which a climate change model is linked to an air quality model, five population projections, and multiple concentration–response functions. Using the U.S. Environmental Protection Agency’s (EPA’s) Environmental Benefits Mapping and Analysis Program (BenMAP), we estimated future ozone (O3)-related health effects in the United States attributable to simulated climate change between the years 2000 and approximately 2050, given each combination of modeling choices. Health effects and concentration–response functions were chosen to match those used in the U.S. EPA’s 2008 Regulatory Impact Analysis of the National Ambient Air Quality Standards for O3. Results: Different combinations of methodological choices produced a range of estimates of national O3-related mortality from roughly 600 deaths avoided as a result of climate change to 2,500 deaths attributable to climate change (although the large majority produced increases in mortality). The choice of the climate change and the air quality model reflected the greatest source of uncertainty, with the other modeling choices having lesser but still substantial effects. Conclusions: Our results highlight the need to use an ensemble approach, instead of relying on any one set of modeling choices, to assess the potential risks associated with O3-related human health effects resulting from climate change. PMID:22796531

Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots.

PubMed

Wang, Junpeng; Liu, Xiaotong; Shen, Han-Wei; Lin, Guang

2017-01-01

Due to the uncertain nature of weather prediction, climate simulations are usually performed multiple times with different spatial resolutions. The outputs of simulations are multi-resolution spatial temporal ensembles. Each simulation run uses a unique set of values for multiple convective parameters. Distinct parameter settings from different simulation runs in different resolutions constitute a multi-resolution high-dimensional parameter space. Understanding the correlation between the different convective parameters, and establishing a connection between the parameter settings and the ensemble outputs are crucial to domain scientists. The multi-resolution high-dimensional parameter space, however, presents a unique challenge to the existing correlation visualization techniques. We present Nested Parallel Coordinates Plot (NPCP), a new type of parallel coordinates plots that enables visualization of intra-resolution and inter-resolution parameter correlations. With flexible user control, NPCP integrates superimposition, juxtaposition and explicit encodings in a single view for comparative data visualization and analysis. We develop an integrated visual analytics system to help domain scientists understand the connection between multi-resolution convective parameters and the large spatial temporal ensembles. Our system presents intricate climate ensembles with a comprehensive overview and on-demand geographic details. We demonstrate NPCP, along with the climate ensemble visualization system, based on real-world use-cases from our collaborators in computational and predictive science.

Monitoring Building Energy Systems at NASA Centers Using NASA Earth Science data, CMIP5 climate data products and RETScreen Expert Clean Energy Tool

NASA Astrophysics Data System (ADS)

Stackhouse, P. W., Jr.; Ganoe, R. E.; Westberg, D. J.; Leng, G. J.; Teets, E.; Hughes, J. M.; De Young, R.; Carroll, M.; Liou, L. C.; Iraci, L. T.; Podolske, J. R.; Stefanov, W. L.; Chandler, W.

2016-12-01

The NASA Climate Adaptation Science Investigator team is devoted to building linkages between NASA Earth Science and those within NASA responsible for infrastructure assessment, upgrades and planning. One of the focus areas is assessing NASA center infrastructure for energy efficiency, planning to meet new energy portfolio standards, and assessing future energy needs. These topics intersect at the provision of current and predicted future weather and climate data. This presentation provides an overview of the multi-center effort to access current building energy usage using Earth science observations, including those from in situ measurements, satellite measurement analysis, and global model data products as inputs to the RETScreen Expert, a clean energy decision support tool. RETScreen® Expert, sponsored by Natural Resources Canada (NRCan), is a tool dedicated to developing and providing clean energy project analysis software for the feasibility design and assessment of a wide range of building projects that incorporate renewable energy technologies. RETScreen Expert requires daily average meteorological and solar parameters that are available within less than a month of real-time. A special temporal collection of meteorological parameters was compiled from near-by surface in situ measurements. These together with NASA data from the NASA CERES (Clouds and Earth's Radiance Energy System)/FLASHFlux (Fast Longwave and SHortwave radiative Fluxes) provides solar fluxes and the NASA GMAO (Global Modeling and Assimilation Office) GEOS (Goddard Earth Observing System) operational meteorological analysis are directly used for meteorological input parameters. Examples of energy analysis for a few select buildings at various NASA centers are presented in terms of the energy usage relationship that these buildings have with changes in their meteorological environment. The energy requirements of potential future climates are then surveyed for a range of changes using the most recent CMIP5 global climate model data output.

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.

Climate change impacts utilizing regional models for agriculture, hydrology and natural ecosystems

NASA Astrophysics Data System (ADS)

Kafatos, M.; Asrar, G. R.; El-Askary, H. M.; Hatzopoulos, N.; Kim, J.; Kim, S.; Medvigy, D.; Prasad, A. K.; Smith, E.; Stack, D. H.; Tremback, C.; Walko, R. L.

2012-12-01

Climate change impacts the entire Earth but with crucial and often catastrophic impacts at local and regional levels. Extreme phenomena such as fires, dust storms, droughts and other natural hazards present immediate risks and challenges. Such phenomena will become more extreme as climate change and anthropogenic activities accelerate in the future. We describe a major project funded by NIFA (Grant # 2011-67004-30224), under the joint NSF-DOE-USDA Earth System Models (EaSM) program, to investigate the impacts of climate variability and change on the agricultural and natural (i.e. rangeland) ecosystems in the Southwest USA using a combination of historical and present observations together with climate, and ecosystem models, both in hind-cast and forecast modes. The applicability of the methodology to other regions is relevant (for similar geographic regions as well as other parts of the world with different agriculture and ecosystems) and should advance the state of knowledge for regional impacts of climate change. A combination of multi-model global climate projections from the decadal predictability simulations, to downscale dynamically these projections using three regional climate models, combined with remote sensing MODIS and other data, in order to obtain high-resolution climate data that can be used with hydrological and ecosystem models for impacts analysis, is described in this presentation. Such analysis is needed to assess the future risks and potential impacts of projected changes on these natural and managed ecosystems. The results from our analysis can be used by scientists to assist extended communities to determine agricultural coping strategies, and is, therefore, of interest to wide communities of stakeholders. In future work we will be including surface hydrologic modeling and water resources, extend modeling to higher resolutions and include significantly more crops and geographical regions with different weather and climate conditions. Specifics of the importance of the scientific methodology e.g. RCM ensemble modeling (using OLAM, RAMS and WRF); combining RCM runs with agriculture modeling system (specifically APSIM); bringing different RCM setups to as close as possible common framework, etc., and important science results (e.g. the significance of Gulf of CA SST for precipitation over dry regions; the AR landfall impacts on precipitation; etc.) are described in our work. We emphasize that the methodology is significant in order to advance the state of the art climate change impacts at regional levels; and to implement our methodology for realistic impact analysis on the natural and managed (agriculture) ecosystems, beyond the SW US.

Self-organization of the climate system: Synchronized polar and oceanic teleconnections

NASA Astrophysics Data System (ADS)

Reischmann, Elizabeth Piccard

Synchronization is a widespread phenomenon in nonlinear, physical systems. It describes the phenomena of two or more weakly interacting, nonlinear oscillators adjust their natural frequencies until they come into phase and frequency lock. This behavior has been observed in biological, chemical and electronic systems, including neurons, fireflies, and computers, but has not been widely studied in climate. This thesis presents a study of several major examples of synchronized climatic systems, starting with ice age timings seemingly caused by the global climate's gradual synchronization to the Earth's 413kyr orbital eccentricity band, which may be responsible for the shift of ice age timings and amplitudes at the Mid-Pleistocene transition. The focus of the thesis, however, is centered the second major example of stable synchronization in the climate system: the continuous, 90 degree phase relationship of the polar climate signals for the entirety of the available ice record. The existence of a relationship between polar climates has been widely observed since ice core proxies became available in both Greenland and Antarctica. However, my work focuses on refining this phase relationship, utilizing it's linear nature to apply deconvolution and establish an energy transfer function. This transfer function shows a distinctly singular frequency, suggesting that climate signal is predominately communicated north to south with a period of 1.6kyrs. This narrows down possible mechanisms of polar connection dramatically, and is further investigated via a collection of intermediate proxy datasets and a set of more contemporary, synchronized, sea surface temperature dipoles. While the former fails to show any strong indication of the nature of the polar signal due in part to the overwhelming uncertainties present on the centennial and millennial scales, the latter demonstrates a large set of synchronized climate oscillations exist, communicate in a variety of networks, and have a direct connection to larger climate patterns (in this case, precipitation anomalies). Overall, this thesis represents a clear advance in our understanding of global climate dynamics, presents a new method of climate time series analysis, evidence of 16, stable, synchronized sea surface temperature dipoles, and provides a detailed sediment core database with explanations of age model limitations for future investigation.

Edge states in the climate system: exploring global instabilities and critical transitions

NASA Astrophysics Data System (ADS)

Lucarini, Valerio; Bódai, Tamás

2017-07-01

Multistability is a ubiquitous feature in systems of geophysical relevance and provides key challenges for our ability to predict a system’s response to perturbations. Near critical transitions small causes can lead to large effects and—for all practical purposes—irreversible changes in the properties of the system. As is well known, the Earth climate is multistable: present astronomical and astrophysical conditions support two stable regimes, the warm climate we live in, and a snowball climate characterized by global glaciation. We first provide an overview of methods and ideas relevant for studying the climate response to forcings and focus on the properties of critical transitions in the context of both stochastic and deterministic dynamics, and assess strengths and weaknesses of simplified approaches to the problem. Following an idea developed by Eckhardt and collaborators for the investigation of multistable turbulent fluid dynamical systems, we study the global instability giving rise to the snowball/warm multistability in the climate system by identifying the climatic edge state, a saddle embedded in the boundary between the two basins of attraction of the stable climates. The edge state attracts initial conditions belonging to such a boundary and, while being defined by the deterministic dynamics, is the gate facilitating noise-induced transitions between competing attractors. We use a simplified yet Earth-like intermediate complexity climate model constructed by coupling a primitive equations model of the atmosphere with a simple diffusive ocean. We refer to the climatic edge states as Melancholia states and provide an extensive analysis of their features. We study their dynamics, their symmetry properties, and we follow a complex set of bifurcations. We find situations where the Melancholia state has chaotic dynamics. In these cases, we have that the basin boundary between the two basins of attraction is a strange geometric set with a nearly zero codimension, and relate this feature to the time scale separation between instabilities occurring on weather and climatic time scales. We also discover a new stable climatic state that is similar to a Melancholia state and is characterized by non-trivial symmetry properties.

Guiding climate change adaptation within vulnerable natural resource management systems.

PubMed

Bardsley, Douglas K; Sweeney, Susan M

2010-05-01

Climate change has the potential to compromise the sustainability of natural resources in Mediterranean climatic systems, such that short-term reactive responses will increasingly be insufficient to ensure effective management. There is a simultaneous need for both the clear articulation of the vulnerabilities of specific management systems to climate risk, and the development of appropriate short- and long-term strategic planning responses that anticipate environmental change or allow for sustainable adaptive management in response to trends in resource condition. Governments are developing climate change adaptation policy frameworks, but without the recognition of the importance of responding strategically, regional stakeholders will struggle to manage future climate risk. In a partnership between the South Australian Government, the Adelaide and Mt Lofty Ranges Natural Resource Management Board and the regional community, a range of available research approaches to support regional climate change adaptation decision-making, were applied and critically examined, including: scenario modelling; applied and participatory Geographical Information Systems modelling; environmental risk analysis; and participatory action learning. As managers apply ideas for adaptation within their own biophysical and socio-cultural contexts, there would be both successes and failures, but a learning orientation to societal change will enable improvements over time. A base-line target for regional responses to climate change is the ownership of the issue by stakeholders, which leads to an acceptance that effective actions to adapt are now both possible and vitally important. Beyond such baseline knowledge, the research suggests that there is a range of tools from the social and physical sciences available to guide adaptation decision-making.

Quantifying Impacts of Land-use and Land Cover Change in a Changing Climate at the Regional Scale using an Integrated Earth System Modeling Approach

NASA Astrophysics Data System (ADS)

Huang, M.

2016-12-01

Earth System models (ESMs) are effective tools for investigating the water-energy-food system interactions under climate change. In this presentation, I will introduce research efforts at the Pacific Northwest National Laboratory towards quantifying impacts of LULCC on the water-energy-food nexus in a changing climate using an integrated regional Earth system modeling framework: the Platform for Regional Integrated Modeling and Analysis (PRIMA). Two studies will be discussed to showcase the capability of PRIMA: (1) quantifying changes in terrestrial hydrology over the Conterminous US (CONUS) from 2005 to 2095 using the Community Land Model (CLM) driven by high-resolution downscaled climate and land cover products from PRIMA, which was designed for assessing the impacts of and potential responses to climate and anthropogenic changes at regional scales; (2) applying CLM over the CONUS to provide the first county-scale model validation in simulating crop yields and assessing associated impacts on the water and energy budgets using CLM. The studies demonstrate the benefits of incorporating and coupling human activities into complex ESMs, and critical needs to account for the biogeophysical and biogeochemical effects of LULCC in climate impacts studies, and in designing mitigation and adaptation strategies at a scale meaningful for decision-making. Future directions in quantifying LULCC impacts on the water-energy-food nexus under a changing climate, as well as feedbacks among climate, energy production and consumption, and natural/managed ecosystems using an Integrated Multi-scale, Multi-sector Modeling framework will also be discussed.

Guiding Climate Change Adaptation Within Vulnerable Natural Resource Management Systems

NASA Astrophysics Data System (ADS)

Bardsley, Douglas K.; Sweeney, Susan M.

2010-05-01

Climate change has the potential to compromise the sustainability of natural resources in Mediterranean climatic systems, such that short-term reactive responses will increasingly be insufficient to ensure effective management. There is a simultaneous need for both the clear articulation of the vulnerabilities of specific management systems to climate risk, and the development of appropriate short- and long-term strategic planning responses that anticipate environmental change or allow for sustainable adaptive management in response to trends in resource condition. Governments are developing climate change adaptation policy frameworks, but without the recognition of the importance of responding strategically, regional stakeholders will struggle to manage future climate risk. In a partnership between the South Australian Government, the Adelaide and Mt Lofty Ranges Natural Resource Management Board and the regional community, a range of available research approaches to support regional climate change adaptation decision-making, were applied and critically examined, including: scenario modelling; applied and participatory Geographical Information Systems modelling; environmental risk analysis; and participatory action learning. As managers apply ideas for adaptation within their own biophysical and socio-cultural contexts, there would be both successes and failures, but a learning orientation to societal change will enable improvements over time. A base-line target for regional responses to climate change is the ownership of the issue by stakeholders, which leads to an acceptance that effective actions to adapt are now both possible and vitally important. Beyond such baseline knowledge, the research suggests that there is a range of tools from the social and physical sciences available to guide adaptation decision-making.

Climate change impacts on food system

NASA Astrophysics Data System (ADS)

Zhang, X.; Cai, X.; Zhu, T.

2014-12-01

Food system includes biophysical factors (climate, land and water), human environments (production technologies and food consumption, distribution and marketing), as well as the dynamic interactions within them. Climate change affects agriculture and food systems in various ways. Agricultural production can be influenced directly by climatic factors such as mean temperature rising, change in rainfall patterns, and more frequent extreme events. Eventually, climate change could cause shift of arable land, alteration of water availability, abnormal fluctuation of food prices, and increase of people at risk of malnutrition. This work aims to evaluate how climate change would affect agricultural production biophysically and how these effects would propagate to social factors at the global level. In order to model the complex interactions between the natural and social components, a Global Optimization model of Agricultural Land and Water resources (GOALW) is applied to the analysis. GOALW includes various demands of human society (food, feed, other), explicit production module, and irrigation water availability constraint. The objective of GOALW is to maximize global social welfare (consumers' surplus and producers' surplus).Crop-wise irrigation water use in different regions around the world are determined by the model; marginal value of water (MVW) can be obtained from the model, which implies how much additional welfare benefit could be gained with one unit increase in local water availability. Using GOALW, we will analyze two questions in this presentation: 1) how climate change will alter irrigation requirements and how the social system would buffer that by price/demand adjustment; 2) how will the MVW be affected by climate change and what are the controlling factors. These results facilitate meaningful insights for investment and adaptation strategies in sustaining world's food security under climate change.

Evaluating the Impacts of Climate Change on the Operations and Future Development of the U.S. Electricity System

NASA Astrophysics Data System (ADS)

Newmark, R. L.; Cohen, S. M.; Averyt, K.; Macknick, J.; Meldrum, J.; Sullivan, P.

2014-12-01

Climate change has the potential to exacerbate reliability concerns for the power sector through changes in water availability and air temperatures. The power sector is responsible for 41% of U.S. freshwater withdrawals, primarily for power plant cooling needs, and any changes in the water available for the power sector, given increasing competition among water users, could affect decisions about new power plant builds and reliable operations for existing generators. Similarly, increases in air temperatures can reduce power plant efficiencies, which in turn increases fuel consumption as well as water withdrawal and consumption rates. This analysis describes an initial link between climate, water, and electricity systems using the National Renewable Energy Laboratory's (NREL) Regional Energy Deployment System (ReEDS) electricity system capacity expansion model. Average surface water runoff projections from Coupled Model Intercomparison Project 5 (CMIP5) data are applied to surface water available to generating capacity in ReEDS, and electric sector growth is compared with and without climate-influenced water availability for the 134 electricity balancing regions in the ReEDS model. In addition, air temperature changes are considered for their impacts on electricity load, transmission capacity, and power plant efficiencies and water use rates. Mean climate projections have only a small impact on national or regional capacity growth and water use because most regions have sufficient unappropriated or previously retired water access to offset climate impacts. Climate impacts are notable in southwestern states, which experience reduced water access purchases and a greater share of water acquired from wastewater and other higher-cost water resources. The electric sector climate impacts demonstrated herein establish a methodology to be later exercised with more extreme climate scenarios and a more rigorous representation of legal and physical water availability.

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.

Analysis of Energy Intensive Enterprises under EU Emission Trading System in Latvia

NASA Astrophysics Data System (ADS)

Zahare, Dace; Rosa, Marika

2011-01-01

Climate change and global warming has become one of the main topics worldwide. The European Union Emission Trading System (EU ETS) was established to limit climate change, providing regulations which encourage companies to invest in cleaner production and more energy efficient production. Latvian energy intensive enterprises are operating under the EU ETS from the year 2005. The main goal of this paper is to provide an analysis of energy intensive installations in terms of their energy efficiency. Additionally, an analysis of EU ETS phase III which will start to operate in 2013 under new, more stringent rules has been conducted by modelling three Latvian energy intensive enterprise operations under this phase and estimating the barriers to meet the goal of the EU ETS phase III.

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

PubMed

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

2013-12-01

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

Railway safety climate: a study on organizational development.

PubMed

Cheng, Yung-Hsiang

2017-09-07

The safety climate of an organization is considered a leading indicator of potential risk for railway organizations. This study adopts the perceptual measurement-individual attribute approach to investigate the safety climate of a railway organization. The railway safety climate attributes are evaluated from the perspective of railway system staff. We identify four safety climate dimensions from exploratory factor analysis, namely safety communication, safety training, safety management and subjectively evaluated safety performance. Analytical results indicate that the safety climate differs at vertical and horizontal organizational levels. This study contributes to the literature by providing empirical evidence of the multilevel safety climate in a railway organization, presents possible causes of the differences under various cultural contexts and differentiates between safety climate scales for diverse workgroups within the railway organization. This information can be used to improve the safety sustainability of railway organizations and to conduct safety supervisions for the government.

Climate and society in 20th century Mexico

NASA Technical Reports Server (NTRS)

Liverman, Diana M.

1991-01-01

Mexican agriculture has been greatly transformed by the widespread introduction of 'Green Revolution' technologies (irrigation, chemical fertilizers, and improved seeds), through land reform, and by land use policies oriented to export crops and grain production. Drought prone Mexico provides an excellent case to study how technological and social changes alter the impact of drought on food and agricultural system. A goal is to document and understand how relationships between climate and agriculture in Mexico have changed in the last fifty years. The results for several locations will be interpreted in light of the prospects of regional climate change due to global warming. This analysis will be complimented by four case studies of vulnerability to drought which will use local records and interviews to try and show how environmental, technological, and social changes may have altered the impacts of climate on local agricultural systems.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Big Data Challenges in Climate Science: Improving the Next-Generation Cyberinfrastructure

NASA Technical Reports Server (NTRS)

Schnase, John L.; Lee, Tsengdar J.; Mattmann, Chris A.; Lynnes, Christopher S.; Cinquini, Luca; Ramirez, Paul M.; Hart, Andre F.; Williams, Dean N.; Waliser, Duane; Rinsland, Pamela;

Incorporating climate-system and carbon-cycle uncertainties in integrated assessments of climate change. (Invited)

NASA Astrophysics Data System (ADS)

Rogelj, J.; McCollum, D. L.; Reisinger, A.; Knutti, R.; Riahi, K.; Meinshausen, M.

2013-12-01

The field of integrated assessment draws from a large body of knowledge across a range of disciplines to gain robust insights about possible interactions, trade-offs, and synergies. Integrated assessment of climate change, for example, uses knowledge from the fields of energy system science, economics, geophysics, demography, climate change impacts, and many others. Each of these fields comes with its associated caveats and uncertainties, which should be taken into account when assessing any results. The geophysical system and its associated uncertainties are often represented by models of reduced complexity in integrated assessment modelling frameworks. Such models include simple representations of the carbon-cycle and climate system, and are often based on the global energy balance equation. A prominent example of such model is the 'Model for the Assessment of Greenhouse Gas Induced Climate Change', MAGICC. Here we show how a model like MAGICC can be used for the representation of geophysical uncertainties. Its strengths, weaknesses, and limitations are discussed and illustrated by means of an analysis which attempts to integrate socio-economic and geophysical uncertainties. These uncertainties in the geophysical response of the Earth system to greenhouse gases remains key for estimating the cost of greenhouse gas emission mitigation scenarios. We look at uncertainties in four dimensions: geophysical, technological, social and political. Our results indicate that while geophysical uncertainties are an important factor influencing projections of mitigation costs, political choices that delay mitigation by one or two decades a much more pronounced effect.

A decision science approach for integrating social science in climate and energy solutions

NASA Astrophysics Data System (ADS)

Wong-Parodi, Gabrielle; Krishnamurti, Tamar; Davis, Alex; Schwartz, Daniel; Fischhoff, Baruch

2016-06-01

The social and behavioural sciences are critical for informing climate- and energy-related policies. We describe a decision science approach to applying those sciences. It has three stages: formal analysis of decisions, characterizing how well-informed actors should view them; descriptive research, examining how people actually behave in such circumstances; and interventions, informed by formal analysis and descriptive research, designed to create attractive options and help decision-makers choose among them. Each stage requires collaboration with technical experts (for example, climate scientists, geologists, power systems engineers and regulatory analysts), as well as continuing engagement with decision-makers. We illustrate the approach with examples from our own research in three domains related to mitigating climate change or adapting to its effects: preparing for sea-level rise, adopting smart grid technologies in homes, and investing in energy efficiency for office buildings. The decision science approach can facilitate creating climate- and energy-related policies that are behaviourally informed, realistic and respectful of the people whom they seek to aid.

Computational Environments and Analysis methods available on the NCI High Performance Computing (HPC) and High Performance Data (HPD) Platform

NASA Astrophysics Data System (ADS)

Evans, B. J. K.; Foster, C.; Minchin, S. A.; Pugh, T.; Lewis, A.; Wyborn, L. A.; Evans, B. J.; Uhlherr, A.

2014-12-01

The National Computational Infrastructure (NCI) has established a powerful in-situ computational environment to enable both high performance computing and data-intensive science across a wide spectrum of national environmental data collections - in particular climate, observational data and geoscientific assets. This paper examines 1) the computational environments that supports the modelling and data processing pipelines, 2) the analysis environments and methods to support data analysis, and 3) the progress in addressing harmonisation of the underlying data collections for future transdisciplinary research that enable accurate climate projections. NCI makes available 10+ PB major data collections from both the government and research sectors based on six themes: 1) weather, climate, and earth system science model simulations, 2) marine and earth observations, 3) geosciences, 4) terrestrial ecosystems, 5) water and hydrology, and 6) astronomy, social and biosciences. Collectively they span the lithosphere, crust, biosphere, hydrosphere, troposphere, and stratosphere. The data is largely sourced from NCI's partners (which include the custodians of many of the national scientific records), major research communities, and collaborating overseas organisations. The data is accessible within an integrated HPC-HPD environment - a 1.2 PFlop supercomputer (Raijin), a HPC class 3000 core OpenStack cloud system and several highly connected large scale and high-bandwidth Lustre filesystems. This computational environment supports a catalogue of integrated reusable software and workflows from earth system and ecosystem modelling, weather research, satellite and other observed data processing and analysis. To enable transdisciplinary research on this scale, data needs to be harmonised so that researchers can readily apply techniques and software across the corpus of data available and not be constrained to work within artificial disciplinary boundaries. Future challenges will involve the further integration and analysis of this data across the social sciences to facilitate the impacts across the societal domain, including timely analysis to more accurately predict and forecast future climate and environmental state.

NASA Center for Climate Simulation (NCCS) Presentation

NASA Technical Reports Server (NTRS)

Webster, William P.

2012-01-01

The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.

Hydrological resiliency in the Western Boreal Plains: classification of hydrological responses using wavelet analysis to assess landscape resilience

NASA Astrophysics Data System (ADS)

Probert, Samantha; Kettridge, Nicholas; Devito, Kevin; Hannah, David; Parkin, Geoff

2017-04-01

The Boreal represents a system of substantial resilience to climate change, with minimal ecological change over the past 6000 years. However, unprecedented climatic warming, coupled with catchment disturbances could exceed thresholds of hydrological function in the Western Boreal Plains. Knowledge of ecohydrological and climatic feedbacks that shape the resilience of boreal forests has advanced significantly in recent years, but this knowledge is yet to be applied and understood at landscape scales. Hydrological modelling at the landscape scale is challenging in the WBP due to diverse, non-topographically driven hydrology across the mosaic of terrestrial and aquatic ecosystems. This study functionally divides the geologic and ecological components of the landscape into Hydrologic Response Areas (HRAs) and wetland, forestland, interface and pond Hydrologic Units (HUs) to accurately characterise water storage and infer transmission at multiple spatial and temporal scales. Wavelet analysis is applied to pond and groundwater levels to describe the patterns of water storage in response to climate signals; to isolate dominant controls on hydrological responses and to assess the relative importance of physical controls between wet and dry climates. This identifies which components of the landscape exhibit greater magnitude and frequency of variability to wetting and drying trends, further to testing the hierarchical framework for hydrological storage controls of: climate, bedrock geology, surficial geology, soil, vegetation, and topography. Classifying HRA and HU hydrological function is essential to understand and predict water storage and redistribution through drought cycles and wet periods. This work recognises which landscape components are most sensitive under climate change and disturbance and also creates scope for hydrological resiliency research in Boreal systems by recognising critical landscape components and their role in landscape collapse or catastrophic shift in ecosystem function under future climatic scenarios.

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

NASA Astrophysics Data System (ADS)

Turner, Sean; Galelli, Stefano; Wilcox, Karen

2015-04-01

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

In Brief: Geoengineering draft statement

NASA Astrophysics Data System (ADS)

Showstack, Randy

2009-04-01

The American Meteorological Society (AMS) has prepared a draft policy statement on geoengineering the climate system, which the AMS Council is considering for approval. The statement notes, “Geoengineering will not substitute for either aggressive mitigation or proactive adaptation. It could contribute to a comprehensive risk management strategy to slow climate change and alleviate its negative impacts, but the potential for adverse and unintended consequences implies a need for adequate research, appropriate regulation, and transparent consideration.” The statement, if adopted, indicates that AMS recommends enhanced research on the scientific and technological potential for geoengineering the climate system; additional study of the historical, ethical, legal, political, and societal aspects of the geoengineering issues; and the development and analysis of policy options to promote transparency and international cooperation in exploring geoengineering options along with restrictions on reckless efforts to manipulate the climate system. AMS is accepting comments on the draft statement until 23 April. For more information, visit http://ametsoc.org/policy/draftstatements/index.html#draft.

Next-Generation Climate Modeling Science Challenges for Simulation, Workflow and Analysis Systems

NASA Astrophysics Data System (ADS)

Koch, D. M.; Anantharaj, V. G.; Bader, D. C.; Krishnan, H.; Leung, L. R.; Ringler, T.; Taylor, M.; Wehner, M. F.; Williams, D. N.

2016-12-01

We will present two examples of current and future high-resolution climate-modeling research that are challenging existing simulation run-time I/O, model-data movement, storage and publishing, and analysis. In each case, we will consider lessons learned as current workflow systems are broken by these large-data science challenges, as well as strategies to repair or rebuild the systems. First we consider the science and workflow challenges to be posed by the CMIP6 multi-model HighResMIP, involving around a dozen modeling groups performing quarter-degree simulations, in 3-member ensembles for 100 years, with high-frequency (1-6 hourly) diagnostics, which is expected to generate over 4PB of data. An example of science derived from these experiments will be to study how resolution affects the ability of models to capture extreme-events such as hurricanes or atmospheric rivers. Expected methods to transfer (using parallel Globus) and analyze (using parallel "TECA" software tools) HighResMIP data for such feature-tracking by the DOE CASCADE project will be presented. A second example will be from the Accelerated Climate Modeling for Energy (ACME) project, which is currently addressing challenges involving multiple century-scale coupled high resolution (quarter-degree) climate simulations on DOE Leadership Class computers. ACME is anticipating production of over 5PB of data during the next 2 years of simulations, in order to investigate the drivers of water cycle changes, sea-level-rise, and carbon cycle evolution. The ACME workflow, from simulation to data transfer, storage, analysis and publication will be presented. Current and planned methods to accelerate the workflow, including implementing run-time diagnostics, and implementing server-side analysis to avoid moving large datasets will be presented.

Analysis of selected photovoltaic systems and storage options for residential applications in hot, humid climates

NASA Astrophysics Data System (ADS)

Lau, A. S.; Hill, J. M.; Ball, D. E.

1982-08-01

The relationship is studied between photovoltaic (PV) generated power and its on-site use as a function of total array size for an energy-efficient house in the hot, humid climates of Miami and Houston. Options in addition to be the full-roof system using a direct current (dc) to alternating current (ac) inverter are studied in an effort to identify applications which are less expensive and which rely less on utility sellback. The results show that common residential loads in this climate lead to high on-site utilization. For the various PV applications studied, array sizes are identified which can be fully potential is identified both in the house structure and the domestic water heater. Using projected 1986 costs, the economics of selected systems were studied for Miami. Only one of the system sizes was found to be marginally competitive with utility supplied power.

Atmospheric and oceanographic research review, 1979

NASA Technical Reports Server (NTRS)

1980-01-01

Papers generated by atmospheric, oceanographic, and climatological research performed during 1979 at the Goddard Laboratory for Atmospheric Sciences are presented. The GARP/global weather research is aimed at developing techniques for the utilization and analysis of the FGGE data sets. Observing system studies were aimed at developing a GLAS TIROS N sounding retrieval system and preparing for the joint NOAA/NASA AMTS simulation study. The climate research objective is to support the development and effective utilization of space acquired data systems by developing the GLAS GCM for short range climate predictions, studies of the sensitivity of climate to boundary conditions, and predictability studies. Ocean/air interaction studies concentrated on the development of models for the prediction of upper ocean currents, temperatures, sea state, mixed layer depths, and upwelling zones, and on studies of the interactions of the atmospheric and oceanic circulation systems on time scales of a month or more.

State Wildlife Action Plans as Tools for Adapting to a Continuously Changing Climate

NASA Astrophysics Data System (ADS)

Metivier, D. W.; Yocum, H.; Ray, A. J.

2015-12-01

Public land management plans are potentially powerful policies for building sustainability and adaptive capacity. Land managers are recognizing the need to respond to numerous climate change impacts on natural and human systems. For the first time, in 2015, the federal government required each state to incorporate climate change into their State Wildlife Action Plans (SWAP) as a condition for funding. As important land management tools, SWAPs have the potential to guide state agencies in shaping and implementing practices for climate change adaptation. Intended to be revised every ten years, SWAPs can change as conditions and understanding of climate change evolves. This study asks what practices are states using to integrate climate change, and how does this vary between states? To answer this question, we conducted a broad analysis among seven states (CO, MT, NE, ND, SD, UT, WY) and a more in-depth analysis of four states (CO, ND, SD, WY). We use seven key factors that represent best practices for incorporating climate change identified in the literature. These best practices are species prioritization, key habitats, threats, monitoring, partnerships and participation, identification of management options, and implementation of management options. The in-depth analysis focuses on how states are using climate change information for specific habitats addressed in the plans. We find that states are integrating climate change in many different ways, showing varying degrees of sophistication and preparedness. We summarize different practices and highlight opportunities to improve the effectiveness of plans through: communication tools across state lines and stakeholders, explicit targeting of key habitats, enforcement and monitoring progress and success, and conducting vulnerability analyses that incorporate topics beyond climate and include other drivers, trajectories, and implications of historic and future land-use change.

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

NASA Astrophysics Data System (ADS)

Liberato, M. L. R.

2017-12-01

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

Internal Variability-Generated Uncertainty in East Asian Climate Projections Estimated with 40 CCSM3 Ensembles.

PubMed

Yao, Shuai-Lei; Luo, Jing-Jia; Huang, Gang

2016-01-01

Regional climate projections are challenging because of large uncertainty particularly stemming from unpredictable, internal variability of the climate system. Here, we examine the internal variability-induced uncertainty in precipitation and surface air temperature (SAT) trends during 2005-2055 over East Asia based on 40 member ensemble projections of the Community Climate System Model Version 3 (CCSM3). The model ensembles are generated from a suite of different atmospheric initial conditions using the same SRES A1B greenhouse gas scenario. We find that projected precipitation trends are subject to considerably larger internal uncertainty and hence have lower confidence, compared to the projected SAT trends in both the boreal winter and summer. Projected SAT trends in winter have relatively higher uncertainty than those in summer. Besides, the lower-level atmospheric circulation has larger uncertainty than that in the mid-level. Based on k-means cluster analysis, we demonstrate that a substantial portion of internally-induced precipitation and SAT trends arises from internal large-scale atmospheric circulation variability. These results highlight the importance of internal climate variability in affecting regional climate projections on multi-decadal timescales.

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

Carbon-Temperature-Water Change Analysis for Peanut Production Under Climate Change: A Prototype for the AgMIP Coordinated Climate-Crop Modeling Project (C3MP)

NASA Technical Reports Server (NTRS)

Ruane, Alex C.; McDermid, Sonali; Rosenzweig, Cynthia; Baigorria, Guillermo A.; Jones, James W.; Romero, Consuelo C.; Cecil, L. DeWayne

2014-01-01

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

A new statistical tool for NOAA local climate studies

NASA Astrophysics Data System (ADS)

Timofeyeva, M. M.; Meyers, J. C.; Hollingshead, A.

2011-12-01

The National Weather Services (NWS) Local Climate Analysis Tool (LCAT) is evolving out of a need to support and enhance the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) field offices' ability to efficiently access, manipulate, and interpret local climate data and characterize climate variability and change impacts. LCAT will enable NOAA's staff to conduct regional and local climate studies using state-of-the-art station and reanalysis gridded data and various statistical techniques for climate analysis. The analysis results will be used for climate services to guide local decision makers in weather and climate sensitive actions and to deliver information to the general public. LCAT will augment current climate reference materials with information pertinent to the local and regional levels as they apply to diverse variables appropriate to each locality. The LCAT main emphasis is to enable studies of extreme meteorological and hydrological events such as tornadoes, flood, drought, severe storms, etc. LCAT will close a very critical gap in NWS local climate services because it will allow addressing climate variables beyond average temperature and total precipitation. NWS external partners and government agencies will benefit from the LCAT outputs that could be easily incorporated into their own analysis and/or delivery systems. Presently we identified five existing requirements for local climate: (1) Local impacts of climate change; (2) Local impacts of climate variability; (3) Drought studies; (4) Attribution of severe meteorological and hydrological events; and (5) Climate studies for water resources. The methodologies for the first three requirements will be included in the LCAT first phase implementation. Local rate of climate change is defined as a slope of the mean trend estimated from the ensemble of three trend techniques: (1) hinge, (2) Optimal Climate Normals (running mean for optimal time periods), (3) exponentially-weighted moving average. Root mean squared error is used to determine the best fit of trend to the observations with the least error. The studies of climate variability impacts on local extremes use composite techniques applied to various definitions of local variables: from specified percentiles to critical thresholds. Drought studies combine visual capabilities of Google maps with statistical estimates of drought severity indices. The process of development will be linked to local office interactions with users to ensure the tool will meet their needs as well as provide adequate training. A rigorous internal and tiered peer-review process will be implemented to ensure the studies are scientifically-sound that will be published and submitted to the local studies catalog (database) and eventually to external sources, such as the Climate Portal.

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

NASA Astrophysics Data System (ADS)

Rodó, Xavier; Rodríguez-Arias, Miquel-Àngel

2006-10-01

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

The NASA Modern Era Reanalysis for Research and Applications, Version-2 (MERRA-2)

NASA Astrophysics Data System (ADS)

Gelaro, R.; McCarty, W.; Molod, A.; Suarez, M.; Takacs, L.; Todling, R.

2014-12-01

The NASA Modern Era Reanalysis for Research Applications Version-2 (MERRA-2) is a reanalysis for the satellite era using an updated version of the Goddard Earth Observing System Data Assimilation System Version-5 (GEOS-5) produced by the Global Modeling and Assimilation Office (GMAO). MERRA-2 will assimilate meteorological and aerosol observations not available to MERRA and includes improvements to the GEOS-5 model and analysis scheme so as to provide an ongoing climate analysis beyond MERRA's terminus. MERRA-2 will also serve as a development milestone for a future GMAO coupled Earth system analysis. Production of MERRA-2 began in June 2014 in four processing streams, with convergence to a single near-real time climate analysis expected by early 2015. This talk provides an overview of the MERRA-2 system developments and key science results. For example, compared with MERRA, MERRA-2 exhibits a well-balanced relationship between global precipitation and evaporation, with significantly reduced sensitivity to changes in the global observing system through time. Other notable improvements include reduced biases in the tropical middle- and upper-tropospheric wind and near-surface temperature over continents.

Scientific workflow and support for high resolution global climate modeling at the Oak Ridge Leadership Computing Facility

NASA Astrophysics Data System (ADS)

Anantharaj, V.; Mayer, B.; Wang, F.; Hack, J.; McKenna, D.; Hartman-Baker, R.

2012-04-01

The Oak Ridge Leadership Computing Facility (OLCF) facilitates the execution of computational experiments that require tens of millions of CPU hours (typically using thousands of processors simultaneously) while generating hundreds of terabytes of data. A set of ultra high resolution climate experiments in progress, using the Community Earth System Model (CESM), will produce over 35,000 files, ranging in sizes from 21 MB to 110 GB each. The execution of the experiments will require nearly 70 Million CPU hours on the Jaguar and Titan supercomputers at OLCF. The total volume of the output from these climate modeling experiments will be in excess of 300 TB. This model output must then be archived, analyzed, distributed to the project partners in a timely manner, and also made available more broadly. Meeting this challenge would require efficient movement of the data, staging the simulation output to a large and fast file system that provides high volume access to other computational systems used to analyze the data and synthesize results. This file system also needs to be accessible via high speed networks to an archival system that can provide long term reliable storage. Ideally this archival system is itself directly available to other systems that can be used to host services making the data and analysis available to the participants in the distributed research project and to the broader climate community. The various resources available at the OLCF now support this workflow. The available systems include the new Jaguar Cray XK6 2.63 petaflops (estimated) supercomputer, the 10 PB Spider center-wide parallel file system, the Lens/EVEREST analysis and visualization system, the HPSS archival storage system, the Earth System Grid (ESG), and the ORNL Climate Data Server (CDS). The ESG features federated services, search & discovery, extensive data handling capabilities, deep storage access, and Live Access Server (LAS) integration. The scientific workflow enabled on these systems, and developed as part of the Ultra-High Resolution Climate Modeling Project, allows users of OLCF resources to efficiently share simulated data, often multi-terabyte in volume, as well as the results from the modeling experiments and various synthesized products derived from these simulations. The final objective in the exercise is to ensure that the simulation results and the enhanced understanding will serve the needs of a diverse group of stakeholders across the world, including our research partners in U.S. Department of Energy laboratories & universities, domain scientists, students (K-12 as well as higher education), resource managers, decision makers, and the general public.

Crossing the Threshold: From Climate to its Human Dimensions

NASA Astrophysics Data System (ADS)

Cornejo, P.

2007-05-01

It is very easy to say we could deliver applications from our ocean science research that are useful and usable by other researchers in applied sciences or by the end-users. However, it is very difficult to do so, and the fact remains that most of the variables that we need to handle do not only depend on our sampling or analysis strategies but on credibility, trust and policy decisions. I will present two cases, of how we use our climate knowledge to forecast its impact on economic resources in Ecuador (from Aquaculture and Agriculture), and how policy implementation and unforeseen events forces us to rethink and re-do the forecast process. The Ecuadorian shrimp aquaculture started at the beginning of the seventies with few hundred Has., and expanded into a 150,000Has. crop area by the end of 1997. Time series analysis revealed that climate variability - from seasonal to interannual - played an important role in production, 35% being accounted for. A three-month phase lag relationship was found between wild shrimp larvae availability (the price of hatchery rear larvae was used as a proxy), and the El Niño 3 index. This relationship was used for forecasting climate variability impact upon the sector and a local oceanographic station was established in 1990 in the area where most of the larvae supply was found to monitor the in situ conditions and its relationships with the El Niño indices. However, after the 1997-1998 ENSO record yields, a disease (white spot virus syndrome) appeared along with the 1999-2000 La Niña, which not only wiped out most of the shrimp production, but together with the political crisis set up the stage for major job losses of the 8% of the economic active population that worked for this sector. Afterwards, a banned in catching wild shrimp larvae was imposed to prevent more spreading of the disease and the relationship developed to forecast climate variability impact on shrimp aquaculture was useless. Hence, a new approach was developed, and the forecast system turned into an alert and management system using a GIS, with the pre- and post-disease shrimp variables inserted into a production index, calculated from and for each individual shrimp pond. The shrimp and climate analysis is a service in place for the Gulf of Guayaquil area at www.saema.espol.edu.ec. For the agriculture case, we are working in a small river basin, in an integrated approach, applying the principles of the UNESCO-HELP program: hydrology for the environment, life and policy. Climate forecast is one its components. A climate virtual application expert system was developed. In this first phase, we are using a crossover between "weather and climate". The application is for banana farmers, and the system has knowledge of the seasonal forecast and the input from the farm meteorological station (daily data). The information feeds the system and the expert knowledge from agriculture engineers, which is already embedded in the system gives the users recommendations on irrigation, fertilization and other parameters important to maintain and/or improve banana yield. The system is still underdevelopment and has other compartments, which involved a decision system for preserving the required water quantity for its services within the basin.

Inferring LGM sedimentary and climatic changes in the southern Eastern Alps foreland through the analysis of a 14C ages database (Brenta megafan, Italy)

NASA Astrophysics Data System (ADS)

Rossato, Sandro; Mozzi, Paolo

2016-09-01

The analysis of a database of radiocarbon ages is proposed as a tool for investigating major glaciofluvial systems of the Last Glacial Maximum (LGM) in the Alpine foreland, and their relations with glacier dynamics and climatic fluctuations. Our research concerns the Brenta megafan (NE Italy), where 110 radiocarbon dates integrate a robust regional stratigraphic and palaeoclimatic framework. Age-depth models allowed us to calculate sedimentation rates, while the time distribution of peat layers, which recurrently formed in this region during the LGM, were estimated through meta-analysis. The reliability of statistical results was carefully evaluated using Pearson and Spearman coefficients. Sedimentation rates in the Brenta megafan markedly fluctuated during LGM: ≈1.8 m/ka between 40 and 26.7 ka cal BP; ≈3 m/ka between 26.7 and 23.8 ka cal BP and ≈1.4 m/ka from 23.8 to 17.5 ka cal BP, when the distributary system deactivated due to fan-head trenching. This is evidence that sediment input and routing in the glaciofluvial distributary system was particularly efficient during the central part of LGM, when glaciers were stable at their outermost position. Meta-analysis indicates an increase in peat formation in correspondence with global (Heinrich Event 3 and/or the Greenland Interstadial 5.1 and 4 for the 30.5, 29.6 and 28.8 ka cal BP peaks) and regional (23.5 ka cal BP) wet events. Other peaks at 22.2, 21.8, 20.2 and 19 ka cal BP correlate with fluctuations of south-eastern Alpine glaciers. Significant peat formation continued until ≈18 ka cal BP, when the last peak occurred. A marked decrease in peat formation is recorded concomitantly with the onset of Heinrich Event 2 (i.e. the 26 ka cal BP trough). The good correspondence of sedimentary events in the Brenta glaciofluvial system with the dynamics of glaciers and glaciofluvial and lacustrine systems in the southern Eastern Alps suggests a common climatic forcing on the whole region during the LGM. Peat layer formation in the floodplain fens increased significantly in correspondence with glacier withdrawals and/or wetter climatic episodes, constituting a good proxy for climatic fluctuations during glacial periods. It also allows correlations across different continental environments and regions in the northern hemisphere.

Energy Efficiency and Environmental Impact Analyses of Supermarket Refrigeration Systems

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

Fricke, Brian A; Bansal, Pradeep; Zha, Shitong

This paper presents energy and life cycle climate performance (LCCP) analyses of a variety of supermarket refrigeration systems to identify designs that exhibit low environmental impact and high energy efficiency. EnergyPlus was used to model refrigeration systems in a variety of climate zones across the United States. The refrigeration systems that were modeled include the traditional multiplex DX system, cascade systems with secondary loops and the transcritical CO2 system. Furthermore, a variety of refrigerants were investigated, including R-32, R-134a, R-404A, R-1234yf, R-717, and R-744. LCCP analysis was used to determine the direct and indirect carbon dioxide emissions resulting from themore » operation of the various refrigeration systems over their lifetimes. Our analysis revealed that high-efficiency supermarket refrigeration systems may result in up to 44% less energy consumption and 78% reduced carbon dioxide emissions compared to the baseline multiplex DX system. This is an encouraging result for legislators, policy makers and supermarket owners to select low emission, high-efficiency commercial refrigeration system designs for future retrofit and new projects.« less

NASA's Modern Era Retrospective-Analysis for Research and Applications (MERRA): Early Results and Future Directions

NASA Technical Reports Server (NTRS)

Schubert, Siegfried

2008-01-01

This talk will review the status and progress of the NASA/Global Modeling and Assimilation Office (GMAO) atmospheric global reanalysis project called the Modern Era Retrospective-Analysis for Research and Applications (MERRA). An overview of NASA's emerging capabilities for assimilating a variety of other Earth Science observations of the land, ocean, and atmospheric constituents will also be presented. MERRA supports NASA Earth science by synthesizing the current suite of research satellite observations in a climate data context (covering the period 1979-present), and by providing the science and applications communities with of a broad range of weather and climate data with an emphasis on improved estimates of the hydrological cycle. MERRA is based on a major new version of the Goddard Earth Observing System Data Assimilation System (GEOS-5), that includes the Earth System Modeling Framework (ESMF)-based GEOS-5 atmospheric general circulation model and the new NOAA National Centers for Environmental Prediction (NCEP) unified grid-point statistical interpolation (GST) analysis scheme developed as a collaborative effort between NCEP and the GMAO. In addition to MERRA, the GMAO is developing new capabilities in aerosol and constituent assimilation, ocean, ocean biology, and land surface assimilation. This includes the development of an assimilation capability for tropospheric air quality monitoring and prediction, the development of a carbon-cycle modeling and assimilation system, and an ocean data assimilation system for use in coupled short-term climate forecasting.

Technical Report Series on Global Modeling and Data Assimilation, Volume 43. MERRA-2; Initial Evaluation of the Climate

NASA Technical Reports Server (NTRS)

Koster, Randal D. (Editor); Bosilovich, Michael G.; Akella, Santha; Lawrence, Coy; Cullather, Richard; Draper, Clara; Gelaro, Ronald; Kovach, Robin; Liu, Qing; Molod, Andrea;

Climate Data Guide - Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)

NASA Technical Reports Server (NTRS)

Cullather, Richard; Bosilovich, Michael

2017-01-01

The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) is a global atmospheric reanalysis produced by the NASA Global Modeling and Assimilation Office (GMAO). It spans the satellite observing era from 1980 to the present. The goals of MERRA-2 are to provide a regularly-gridded, homogeneous record of the global atmosphere, and to incorporate additional aspects of the climate system including trace gas constituents (stratospheric ozone), and improved land surface representation, and cryospheric processes. MERRA-2 is also the first satellite-era global reanalysis to assimilate space-based observations of aerosols and represent their interactions with other physical processes in the climate system. The inclusion of these additional components are consistent with the overall objectives of an Integrated Earth System Analysis (IESA). MERRA-2 is intended to replace the original MERRA product, and reflects recent advances in atmospheric modeling and data assimilation. Modern hyperspectral radiance and microwave observations, along with GPS-Radio Occultation and NASA ozone datasets are now assimilated in MERRA-2. Much of the structure of the data files remains the same in MERRA-2. While the original MERRA data format was HDF-EOS, the MERRA-2 supplied binary data format is now NetCDF4 (with lossy compression to save space).

Sensitivities of marine carbon fluxes to ocean change.

PubMed

Riebesell, Ulf; Körtzinger, Arne; Oschlies, Andreas

2009-12-08

Throughout Earth's history, the oceans have played a dominant role in the climate system through the storage and transport of heat and the exchange of water and climate-relevant gases with the atmosphere. The ocean's heat capacity is approximately 1,000 times larger than that of the atmosphere, its content of reactive carbon more than 60 times larger. Through a variety of physical, chemical, and biological processes, the ocean acts as a driver of climate variability on time scales ranging from seasonal to interannual to decadal to glacial-interglacial. The same processes will also be involved in future responses of the ocean to global change. Here we assess the responses of the seawater carbonate system and of the ocean's physical and biological carbon pumps to (i) ocean warming and the associated changes in vertical mixing and overturning circulation, and (ii) ocean acidification and carbonation. Our analysis underscores that many of these responses have the potential for significant feedback to the climate system. Because several of the underlying processes are interlinked and nonlinear, the sign and magnitude of the ocean's carbon cycle feedback to climate change is yet unknown. Understanding these processes and their sensitivities to global change will be crucial to our ability to project future climate change.

Visualization and Analysis of Climate Simulation Performance Data

NASA Astrophysics Data System (ADS)

Röber, Niklas; Adamidis, Panagiotis; Behrens, Jörg

2015-04-01

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

Predictability Analysis of PM10 Concentrations in Budapest

NASA Astrophysics Data System (ADS)

Ferenczi, Zita

2013-04-01

Climate, weather and air quality may have harmful effects on human health and environment. Over the past few hundred years we had to face the changes in climate in parallel with the changes in air quality. These observed changes in climate, weather and air quality continuously interact with each other: pollutants are changing the climate, thus changing the weather, but climate also has impacts on air quality. The increasing number of extreme weather situations may be a result of climate change, which could create favourable conditions for rising of pollutant concentrations. Air quality in Budapest is determined by domestic and traffic emissions combined with the meteorological conditions. In some cases, the effect of long-range transport could also be essential. While the time variability of the industrial and traffic emissions is not significant, the domestic emissions increase in winter season. In recent years, PM10 episodes have caused the most critical air quality problems in Budapest, especially in winter. In Budapest, an air quality network of 11 stations detects the concentration values of different pollutants hourly. The Hungarian Meteorological Service has developed an air quality prediction model system for the area of Budapest. The system forecasts the concentration of air pollutants (PM10, NO2, SO2 and O3) for two days in advance. In this work we used meteorological parameters and PM10 data detected by the stations of the air quality network, as well as the forecasted PM10 values of the air quality prediction model system. In this work we present the evaluation of PM10 predictions in the last two years and the most important meteorological parameters affecting PM10 concentration. The results of this analysis determine the effect of the meteorological parameters and the emission of aerosol particles on the PM10 concentration values as well as the limits of this prediction system.

Climate impact on airborne particulate matter concentrations in California using seven year analysis periods

NASA Astrophysics Data System (ADS)

Mahmud, A.; Hixson, M.; Hu, J.; Zhao, Z.; Chen, S.-H.; Kleeman, M. J.

2010-11-01

The effect of global climate change on the annual average concentration of fine particulate matter (PM2.5) in California was studied using a climate-air quality modeling system composed of global through regional models. Output from the NCAR/DOE Parallel Climate Model (PCM) generated under the "business as usual" global emissions scenario was downscaled using the Weather Research and Forecasting (WRF) model followed by air quality simulations using the UCD/CIT airshed model. The system represents major atmospheric processes acting on gas and particle phase species including meteorological effects on emissions, advection, dispersion, chemical reaction rates, gas-particle conversion, and dry/wet deposition. The air quality simulations were carried out for the entire state of California with a resolution of 8-km for the years 2000-2006 (present climate with present emissions) and 2047-2053 (future climate with present emissions). Each of these 7-year analysis periods was analyzed using a total of 1008 simulated days to span a climatologically relevant time period with a practical computational burden. The 7-year windows were chosen to properly account for annual variability with the added benefit that the air quality predictions under the present climate could be compared to actual measurements. The climate-air quality modeling system successfully predicted the spatial pattern of present climate PM2.5 concentrations in California but the absolute magnitude of the annual average PM2.5 concentrations were under-predicted by ~4-39% in the major air basins. The majority of this under-prediction was caused by excess ventilation predicted by PCM-WRF that should be present to the same degree in the current and future time periods so that the net bias introduced into the comparison is minimized. Surface temperature, relative humidity (RH), rain rate, and wind speed were predicted to increase in the future climate while the ultra violet (UV) radiation was predicted to decrease in major urban areas in the San Joaquin Valley (SJV) and South Coast Air Basin (SoCAB). These changes lead to a predicted decrease in PM2.5 mass concentrations of ~0.3-0.7 μg m-3 in the southern portion of the SJV and ~0.3-1.1 μg m-3 along coastal regions of California including the heavily populated San Francisco Bay Area and the SoCAB surrounding Los Angeles. Annual average PM2.5 concentrations were predicted to increase at certain locations within the SJV and the Sacramento Valley (SV) due to the effects of climate change, but a corresponding analysis of the annual variability showed that these predictions are not statistically significant (i.e. the choice of a different 7-year period could produce a different outcome for these regions). Overall, virtually no region in California outside of coastal + central Los Angeles, and a small region around the port of Oakland in the San Francisco Bay Area experienced a statistically significant change in annual average PM2.5 concentrations due to the effects of climate change in the present~study. The present study employs the highest spatial resolution (8 km) and the longest analysis windows (7 years) of any climate-air quality analysis conducted for California to date, but the results still have some degree of uncertainty. Most significantly, GCM calculations have inherent uncertainty that is not fully represented in the current study since a single GCM was used as the starting point for all calculations. The PCM results used in the current study predicted greater wintertime increases in air temperature over the Pacific Ocean than over land, further motivating comparison to other GCM results. Ensembles of GCM results are usually employed to build confidence in climate calculations. The current results provide a first data-point for the climate-air quality analysis that simultaneously employ the fine spatial resolution and long time scales needed to capture the behavior of climate-PM2.5 interactions in California. Future downscaling studies should follow up with a full ensemble of GCMs as their starting point, and include aerosol feedback effects on local meteorology.

Identifying tectonic and climatic drivers for deep-marine siliciclastic systems: Middle Eocene, Spanish Pyrenees

NASA Astrophysics Data System (ADS)

Pickering, K. T.; Scotchman, J. I.; Robinson, S. A.

2009-12-01

Analysis of the sedimentary record in deep time requires the deconvolution of tectonic and climatic drivers. The deep-marine siliciclastic systems in the Middle Eocene Ainsa-Jaca basin, Spanish Pyrenees, with their excellent outcrops and good temporal resolution, provide an opportunity to identify the relative importance of tectonic and climatic drivers on deposition over ~10 Myr at a time when the Earth’s climate was shifting from a greenhouse to icehouse conditions. The cumulative ~4 km of stratigraphy contains 8 sandy systems with a total of ~25 discrete channelized sandbodies that accumulated in water depths of ~400-800 m, and that were controlled by the ~400-kyr Milkankovitch frequency with modes, at ~100 kyr and ~41 kyr (possibly stacked ~23-kyr) influencing bottom-water conditions, causing periodic stratification in the water column across a submarine sill within the eastern, more proximal depositional systems in the Ainsa basin. We also identify a range of sub-Milankovitch millennial-scale cycles (Scotchman et al. 2009). In the Ainsa basin, the interplay of basin-bounding growth anticlines defined and controlled the position and stacking patterns of the sandy systems and their constituent channelized sandbodies, in a process of seesaw tectonics by: (i) Westward lateral offset-stacking of channelized sandbodies due to growth of the eastern anticline (Mediano), and (ii) Eastward (orogenwards) back-stepping of the depositional axis of each sandy system, due to phases of relative uplift of the opposing Boltaña growth anticline. The first-order control on accommodation, and the flow paths, for deep-marine sedimentation were tectonic, with the pacing of the supply of coarse siliciclastics being driven by global climatic processes, particularly Milankovitch-type frequencies. The dominance of eccentricity and obliquity is similar to results from the continental lacustrine Eocene Green River Formation, and the observations from ODP Site 1258 that the early to middle Eocene climatic record is characterized by eccentricity-modulated precession cycles (Westerhold & Rohl 2009), The age model for the Ainsa basin yields an average sediment accumulation rate of ~40 cm kyr-1, that is consistent with that inferred from the spectral analysis on bioturbation intensity for fine-grained sedimentation (~30 cm kyr-1). References Scotchman, J.I., Pickering, K.T. & Robinson, S.A. 2009. Sub-Milankovitch millennial-scale climate variability in Middle Eocene deep-marine sediments. AGU Fall Meeting San Francisco 2009. Westerhold, T. & Rohl, U. 2009. High resolution cyclostratigraphy of the early Eocene - new insights into the origin of the Cenozoic cooling trend. Climate of the Past, 5, 309-327.

Recovery Migration After Hurricanes Katrina and Rita: Spatial Concentration and Intensification in the Migration System.

PubMed

Curtis, Katherine J; Fussell, Elizabeth; DeWaard, Jack

2015-08-01

Changes in the human migration systems of the Gulf of Mexico coastline counties affected by Hurricanes Katrina and Rita provide an example of how climate change may affect coastal populations. Crude climate change models predict a mass migration of "climate refugees," but an emerging literature on environmental migration suggests that most migration will be short-distance and short-duration within existing migration systems, with implications for the population recovery of disaster-stricken places. In this research, we derive a series of hypotheses on recovery migration predicting how the migration system of hurricane-affected coastline counties in the Gulf of Mexico was likely to have changed between the pre-disaster and the recovery periods. We test these hypotheses using data from the Internal Revenue Service on annual county-level migration flows, comparing the recovery period migration system (2007-2009) with the pre-disaster period (1999-2004). By observing county-to-county ties and flows, we find that recovery migration was strong: the migration system of the disaster-affected coastline counties became more spatially concentrated, while flows within it intensified and became more urbanized. Our analysis demonstrates how migration systems are likely to be affected by the more intense and frequent storms anticipated by climate change scenarios, with implications for the population recovery of disaster-affected places.

Assessing climate change impact by integrated hydrological modelling

NASA Astrophysics Data System (ADS)

Lajer Hojberg, Anker; Jørgen Henriksen, Hans; Olsen, Martin; der Keur Peter, van; Seaby, Lauren Paige; Troldborg, Lars; Sonnenborg, Torben; Refsgaard, Jens Christian

2013-04-01

Future climate may have a profound effect on the freshwater cycle, which must be taken into consideration by water management for future planning. Developments in the future climate are nevertheless uncertain, thus adding to the challenge of managing an uncertain system. To support the water managers at various levels in Denmark, the national water resources model (DK-model) (Højberg et al., 2012; Stisen et al., 2012) was used to propagate future climate to hydrological response under considerations of the main sources of uncertainty. The DK-model is a physically based and fully distributed model constructed on the basis of the MIKE SHE/MIKE11 model system describing groundwater and surface water systems and the interaction between the domains. The model has been constructed for the entire 43.000 km2 land area of Denmark only excluding minor islands. Future climate from General Circulation Models (GCM) was downscaled by Regional Climate Models (RCM) by a distribution-based scaling method (Seaby et al., 2012). The same dataset was used to train all combinations of GCM-RCMs and they were found to represent the mean and variance at the seasonal basis equally well. Changes in hydrological response were computed by comparing the short term development from the period 1990 - 2010 to 2021 - 2050, which is the time span relevant for water management. To account for uncertainty in future climate predictions, hydrological response from the DK-model using nine combinations of GCMs and RCMs was analysed for two catchments representing the various hydrogeological conditions in Denmark. Three GCM-RCM combinations displaying high, mean and low future impacts were selected as representative climate models for which climate impact studies were carried out for the entire country. Parameter uncertainty was addressed by sensitivity analysis and was generally found to be of less importance compared to the uncertainty spanned by the GCM-RCM combinations. Analysis of the simulations showed some unexpected results, where climate models predicting the largest increase in net precipitation did not result in the largest increase in groundwater heads. This was found to be the result of different initial conditions (1990 - 2010) for the various climate models. In some areas a combination of a high initial groundwater head and an increase in precipitation towards 2021 - 2050 resulted in a groundwater head raise that reached the drainage or the surface water system. This will increase the exchange from the groundwater to the surface water system, but reduce the raise in groundwater heads. An alternative climate model, with a lower initial head can thus predict a higher increase in the groundwater head, although the increase in precipitation is lower. This illustrates an extra dimension in the uncertainty assessment, namely the climate models capability of simulating the current climatic conditions in a way that can reproduce the observed hydrological response. Højberg, AL, Troldborg, L, Stisen, S, et al. (2012) Stakeholder driven update and improvement of a national water resources model - http://www.sciencedirect.com/science/article/pii/S1364815212002423 Seaby, LP, Refsgaard, JC, Sonnenborg, TO, et al. (2012) Assessment of robustness and significance of climate change signals for an ensemble of distribution-based scaled climate projections (submitted) Journal of Hydrology Stisen, S, Højberg, AL, Troldborg, L et al., (2012): On the importance of appropriate rain-gauge catch correction for hydrological modelling at mid to high latitudes - http://www.hydrol-earth-syst-sci.net/16/4157/2012/

Development of Representative Rainfall Periods for Green Infrastructure Design: Connecting the Dots Between Climate, Urban Hydrology and Resilience

NASA Astrophysics Data System (ADS)

Albright, C. M.; Traver, R.; Wadzuk, B.

2017-12-01

Analysis of local-to-regional climate data is critical in understanding how changing patterns in rainfall and other atmospheric conditions can affect urban hydrology. Urbanization has caused hydrologic and ecologic modifications to our land surfaces, and altered the dynamics of urban water cycle in complex ways. Green infrastructure (GI) systems, in their simplest form, reduce runoff and flooding, prevent combined sewer overflows and improve quality of receiving waters. However, when viewed through a more holistic lens, GI systems sit at the nexus of hydrology, climate and energy, yet are rarely designed to account for the impacts of these intersections. We must assess urban hydrologic systems beyond their response to a single event or design storm, incorporating multiple temporal scales and all hydrologic processes. This is of utmost importance to design and characterization of urban GI systems because the resilience of these systems will be dictated by their ability to adapt to future behavior of extreme weather patterns and climate. In this study, we characterize long-term hydrologic conditions in Philadelphia to identify periods of record that are most representative of regional climate characteristics, including a representative rainfall year and longer representative periods. Utility of these datasets will be demonstrated by showing that GI systems are able to sustain effective performance for most expected annual precipitation events. Connections between atmospheric (precipitation and temperature) patterns, GI systems and potential removal mechanisms in the urban hydrologic cycle will be presented for Philadelphia and cities with similar climate characteristics. Establishing such connections is critically needed to not only validate what is already known about urban GI, but more importantly, to advance theory and practice by linking the hydrologic benefits of urban GI to broader concepts such as risk, mitigation of extreme events and sustainable communities.

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers

PubMed Central

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell’Aquila, Alessandro

2014-01-01

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests. PMID:24706833

Fine-scale ecological and economic assessment of climate change on olive in the Mediterranean Basin reveals winners and losers.

PubMed

Ponti, Luigi; Gutierrez, Andrew Paul; Ruti, Paolo Michele; Dell'Aquila, Alessandro

2014-04-15

The Mediterranean Basin is a climate and biodiversity hot spot, and climate change threatens agro-ecosystems such as olive, an ancient drought-tolerant crop of considerable ecological and socioeconomic importance. Climate change will impact the interactions of olive and the obligate olive fruit fly (Bactrocera oleae), and alter the economics of olive culture across the Basin. We estimate the effects of climate change on the dynamics and interaction of olive and the fly using physiologically based demographic models in a geographic information system context as driven by daily climate change scenario weather. A regional climate model that includes fine-scale representation of the effects of topography and the influence of the Mediterranean Sea on regional climate was used to scale the global climate data. The system model for olive/olive fly was used as the production function in our economic analysis, replacing the commonly used production-damage control function. Climate warming will affect olive yield and fly infestation levels across the Basin, resulting in economic winners and losers at the local and regional scales. At the local scale, profitability of small olive farms in many marginal areas of Europe and elsewhere in the Basin will decrease, leading to increased abandonment. These marginal farms are critical to conserving soil, maintaining biodiversity, and reducing fire risk in these areas. Our fine-scale bioeconomic approach provides a realistic prototype for assessing climate change impacts in other Mediterranean agro-ecosystems facing extant and new invasive pests.

Climatically driven loss of calcium in steppe soil as a sink for atmospheric carbon

Treesearch

A.G. Lapenis; G.B. Lawrence; S.W. Bailey; B.F. Aparin; A.I. Shiklomanov; N.A. Speranskaya; M.S. Torn; M. Calef

2008-01-01

During the last several thousand years the semi-arid, cold climate of the Russian steppe formed highly fertile soils rich in organic carbon and calcium (classified as Chernozems in the Russian system). Analysis of archived soil samples collected in Kemannaya Steppe Preserve in 1920, 1947, 1970, and fresh samples collected in 1998 indicated that the native steppe...

Forest Health Monitoring and Forest Inventory Analysis programs monitor climate change effects in forest ecosystems

Treesearch

Kenneth W. Stolte

2001-01-01

The Forest Health Monitoring (FHM) and Forest Inventory and Analyses (FIA) programs are integrated bilogical monitoring systems that use nationally standardized methods to evaluate and report on the health and sustainability of forest ecosystems in the United States. Many of the anticipated changes in forest ecosystems from climate change were also issues addressed in...

How well do simulated last glacial maximum tropical temperatures constrain equilibrium climate sensitivity?

NASA Astrophysics Data System (ADS)

Hopcroft, Peter O.; Valdes, Paul J.

2015-07-01

Previous work demonstrated a significant correlation between tropical surface air temperature and equilibrium climate sensitivity (ECS) in PMIP (Paleoclimate Modelling Intercomparison Project) phase 2 model simulations of the last glacial maximum (LGM). This implies that reconstructed LGM cooling in this region could provide information about the climate system ECS value. We analyze results from new simulations of the LGM performed as part of Coupled Model Intercomparison Project (CMIP5) and PMIP phase 3. These results show no consistent relationship between the LGM tropical cooling and ECS. A radiative forcing and feedback analysis shows that a number of factors are responsible for this decoupling, some of which are related to vegetation and aerosol feedbacks. While several of the processes identified are LGM specific and do not impact on elevated CO2 simulations, this analysis demonstrates one area where the newer CMIP5 models behave in a qualitatively different manner compared with the older ensemble. The results imply that so-called Earth System components such as vegetation and aerosols can have a significant impact on the climate response in LGM simulations, and this should be taken into account in future analyses.

Shallow Horizontal GCHP Effectiveness in Arid Climate Soils

NASA Astrophysics Data System (ADS)

North, Timothy James

Ground coupled heat pumps (GCHPs) have been used successfully in many environments to improve the heating and cooling efficiency of both small and large scale buildings. In arid climate regions, such as the Phoenix, Arizona metropolitan area, where the air condi-tioning load is dominated by cooling in the summer, GCHPs are difficult to install and operate. This is because the nature of soils in arid climate regions, in that they are both dry and hot, renders them particularly ineffective at dissipating heat. The first part of this thesis addresses applying the SVHeat finite element modeling soft-ware to create a model of a GCHP system. Using real-world data from a prototype solar-water heating system coupled with a ground-source heat exchanger installed in Menlo Park, California, a relatively accurate model was created to represent a novel GCHP panel system installed in a shallow vertical trench. A sensitivity analysis was performed to evaluate the accuracy of the calibrated model. The second part of the thesis involved adapting the calibrated model to represent an ap-proximation of soil conditions in arid climate regions, using a range of thermal properties for dry soils. The effectiveness of the GCHP in the arid climate region model was then evaluated by comparing the thermal flux from the panel into the subsurface profile to that of the prototype GCHP. It was shown that soils in arid climate regions are particularly inefficient at heat dissipation, but that it is highly dependent on the thermal conductivity inputted into the model. This demonstrates the importance of proper site characterization in arid climate regions. Finally, several soil improvement methods were researched to evaluate their potential for use in improving the effectiveness of shallow horizontal GCHP systems in arid climate regions.

Adaptation of rainfed agriculture to climatic variability in the Mixteca Alta Region of Oaxaca, Mexico

NASA Astrophysics Data System (ADS)

Rogé, P.; Friedman, A. R.; Astier, M.; Altieri, M.

2015-12-01

The traditional management systems of the Mixteca Alta Region of Oaxaca, Mexico offer historical lessons about resilience to climatic variability. We interviewed small farmers to inquire about the dynamics of abandonment and persistence of a traditional management systems. We interpret farmers' narratives from a perspective of general agroecological resilience. In addition, we facilitated workshops in small farmers described their adaptation to past climate challenges and identified 14 indicators that they subsequently used to evaluate the condition of their agroecosystems. The most recent years presented increasingly extreme climatic and socioeconomic hardships: increased temperatures, delayed rainy seasons, reduced capacity of soils to retain soil moisture, changing cultural norms, and reduced rural labor. Farmers reported that their cropping systems were changing for multiple reasons: more drought, later rainfall onset, decreased rural labor, and introduced labor-saving technologies. Examination of climate data found that farmers' climate narratives were largely consistent with the observational record. There have been increases in temperature and rainfall intensity, and an increase in rainfall seasonality that may be perceived as later rainfall onset. Farmers ranked landscape-scale indicators as more marginal than farmer management or soil quality indicators. From this analysis, farmers proposed strategies to improve the ability of their agroecosystems to cope with climatic variability. Notably, they recognized that social organizing and education are required for landscape-level indicators to be improved. Transformative change is required to develop novel cropping systems and complementary activities to agriculture that will allow for farming to be sustained in the face of these challenges. Climate change adaptation by small farmers involves much more than just a set of farming practices, but also community action to tackle collective problems.

Regional analysis of drought and heat impacts on forests: current and future science directions.

PubMed

Law, Beverly E

2014-12-01

Accurate assessments of forest response to current and future climate and human actions are needed at regional scales. Predicting future impacts on forests will require improved analysis of species-level adaptation, resilience, and vulnerability to mortality. Land system models can be enhanced by creating trait-based groupings of species that better represent climate sensitivity, such as risk of hydraulic failure from drought. This emphasizes the need for more coordinated in situ and remote sensing observations to track changes in ecosystem function, and to improve model inputs, spatio-temporal diagnosis, and predictions of future conditions, including implications of actions to mitigate climate change. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Status and Plans for Reanalysis at NASA/GMAO

NASA Technical Reports Server (NTRS)

Gelaro, Ron

2017-01-01

Reanalysis plays a critical role in GMAOs goal to enhance NASA's program of Earth observations, providing vital data sets for climate research and the development of future missions. As the breadth of NASAs observations expands to include multiple components of the Earth system, so does the need to assimilate observations from currently uncoupled components of the system in a more physically consistent manner. GMAOs most recent reanalysis of the satellite era, MERRA-2, has completed the period 1980-present, and is now running as a continuing global climate analysis with two- to three-week latency. MERRA-2 assimilates meteorological and aerosol observations as a weakly coupled assimilation system as a first step toward GMAOs longer term goal of developing an integrated Earth system analysis (IESA) capability that will couple assimilation systems for the atmosphere, ocean, land and chemistry. The GMAO strategy is to progress incrementally toward an IESA through an evolving combination of coupled systems and offline component reanalyses driven by, for example, MERRA-2 atmospheric forcing. Most recently, the GMAO has implemented a weakly coupled assimilation scheme for analyzing ocean skin temperature within the existing atmospheric analysis. The scheme uses background fields from a near-surface ocean diurnal layer model to assimilate surface-sensitive radiances plus in-situ observations along with all other observations in the atmospheric assimilation system. In addition, MERRA-2-driven simulations of the ocean (plus sea ice) and atmospheric chemistry (for the EOS period) are currently underway, as is the development of a coupled atmosphere-ocean assimilation system. This talk will describe the status of these ongoing efforts and the planned steps toward an IESA capability for climate research.

Linking research, education and public engagement in geoscience: Leadership and strategic partnerships (invited)

NASA Astrophysics Data System (ADS)

Harcourt, P.

2017-12-01

Addressing the urgent issue of climate change requires mitigation and adaptation actions on individual to global scales, and appropriate action must be based upon geoscience literacy across population sectors. The NSF-funded MADE CLEAR (Maryland and Delaware Climate Change Education, Assessment, and Research) project provides a coordinated approach to embed climate change into education programs at the university level, in formal K12 classrooms, and among informal educators. We have worked with state agencies, university systems, non-profit organizations, and community groups to establish and support research-based education about climate change. In this panel I will describe how MADE CLEAR approached the task of infusing climate change education across sectors in the highly diverse states of Delaware and Maryland. I will share the characteristics of our strongest alliances, an analysis of significant barriers to climate change education, and our perspective on the outlook for the future of climate change education.

Integrated web system of geospatial data services for climate research

NASA Astrophysics Data System (ADS)

Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander

2016-04-01

Georeferenced datasets are currently actively used for modeling, interpretation and forecasting of climatic and ecosystem changes on different spatial and temporal scales. Due to inherent heterogeneity of environmental datasets as well as their huge size (up to tens terabytes for a single dataset) a special software supporting studies in the climate and environmental change areas is required. An approach for integrated analysis of georefernced climatological data sets based on combination of web and GIS technologies in the framework of spatial data infrastructure paradigm is presented. According to this approach a dedicated data-processing web system for integrated analysis of heterogeneous georeferenced climatological and meteorological data is being developed. It is based on Open Geospatial Consortium (OGC) standards and involves many modern solutions such as object-oriented programming model, modular composition, and JavaScript libraries based on GeoExt library, ExtJS Framework and OpenLayers software. This work is supported by the Ministry of Education and Science of the Russian Federation, Agreement #14.613.21.0037.

How can a climate change perspective be integrated into public health surveillance?

PubMed

Pascal, M; Viso, A C; Medina, S; Delmas, M C; Beaudeau, P

2012-08-01

Climate change may be considered as a key factor for environmental change, exposure to health risks and pathogens, consequently impairing the state of health among populations. Efficient health surveillance systems are required to support adaptation to climate change. However, despite a growing awareness, the public health surveillance sector has had very little involvement in the drafting of adaptation plans. This paper proposes a method to raise awareness about climate change in the public health community, to identify possible health risks and to assess the needs for reinforced health surveillance systems. A working group was set up comprising surveillance experts in the following fields: environmental health; chronic diseases and; infectious diseases. Their goal was to define common objectives, to propose a framework for risk analysis, and to apply it to relevant health risks in France. The framework created helped to organize available information on climate-sensitive health risks, making a distinction between three main determinants as follows: (1) environment; (2) individual and social behaviours; and (3) demography and health status. The process is illustrated using two examples: heatwaves and airborne allergens. Health surveillance systems can be used to trigger early warning systems, to create databases which improve scientific knowledge about the health impacts of climate change, to identify and prioritize needs for intervention and adaptation measures, and to evaluate these measures. Adaptation requires public health professionals to consider climate change as a concrete input parameter in their studies and to create partnerships with professionals from other disciplines. Copyright © 2012 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Vulnerability of Agriculture to Climate Change as Revealed by Relationships between Simulated Crop Yield and Climate Change Indices

NASA Astrophysics Data System (ADS)

King, A. W.; Absar, S. M.; Nair, S.; Preston, B. L.

2012-12-01

The vulnerability of agriculture is among the leading concerns surrounding climate change. Agricultural production is influenced by drought and other extremes in weather and climate. In regions of subsistence farming, worst case reductions in yield lead to malnutrition and famine. Reduced surplus contributes to poverty in agrarian economies. In more economically diverse and industrialized regions, variations in agricultural yield can influence the regional economy through market mechanisms. The latter grows in importance as agriculture increasingly services the energy market in addition to markets for food and fiber. Agriculture is historically a highly adaptive enterprise and will respond to future changes in climate with a variety of adaptive mechanisms. Nonetheless, the risk, if not expectation, of increases in climate extremes and hazards exceeding historical experience motivates scientifically based anticipatory assessment of the vulnerability of agriculture to climate change. We investigate the sensitivity component of that vulnerability using EPIC, a well established field-scale model of cropping systems that includes the simulation of economic yield. The core of our analysis is the relationship between simulated yield and various indices of climate change, including the CCI/CLIVAR/JCOM ETCCDI indices, calculated from weather inputs to the model. We complement this core with analysis using the DSSAT cropping system model and exploration of relationships between historical yield statistics and climate indices calculated from weather records. Our analyses are for sites in the Southeast/Gulf Coast region of the United States. We do find "tight" monotonic relationships between annual yield and climate for some indices, especially those associated with available water. More commonly, however, we find an increase in the variability of yield as the index value becomes more extreme. Our findings contribute to understanding the sensitivity of crop yield as part of vulnerability analysis. They also contribute to considerations of adaptation, focusing attention on adapting to increased variability in yield rather than just reductions in yield. For example, in the face of increased variability or reduced reliability, hedging and risk spreading strategies may be more important than technological innovations such as drought-resistant crops or other optimization strategies. Our findings also have implications for the choice and application of climate extreme indices, demands on models used to project climate change and the development of next generation integrated assessment models (IAM) that incorporate the agricultural sector, and especially adaption within that sector, in energy and broader more general markets.

Modeling Urban Energy Savings Scenarios Using Earth System Microclimate and Urban Morphology

NASA Astrophysics Data System (ADS)

Allen, M. R.; Rose, A.; New, J. R.; Yuan, J.; Omitaomu, O.; Sylvester, L.; Branstetter, M. L.; Carvalhaes, T. M.; Seals, M.; Berres, A.

2017-12-01

We analyze and quantify the relationships among climatic conditions, urban morphology, population, land cover, and energy use so that these relationships can be used to inform energy-efficient urban development and planning. We integrate different approaches across three research areas: earth system modeling; impacts, adaptation and vulnerability; and urban planning in order to address three major gaps in the existing capability in these areas: i) neighborhood resolution modeling and simulation of urban micrometeorological processes and their effect on and from regional climate; ii) projections for future energy use under urbanization and climate change scenarios identifying best strategies for urban morphological development and energy savings; iii) analysis and visualization tools to help planners optimally use these projections.

Underlying influence of perception of management leadership on patient safety climate in healthcare organizations - A mediation analysis approach.

PubMed

Weng, Shao-Jen; Kim, Seung-Hwan; Wu, Chieh-Liang

2017-02-01

We aim to draw insights on how medical staff's perception of management leadership affects safety climate with key safety related dimensions-teamwork climate, job satisfaction and working conditions. A cross-sectional survey using Safety Attitude Questionnaire (SAQ) was performed in a medical center in Taichung City, Taiwan. The relationships among the dimensions in SAQ were then analyzed by structural equation modeling with a mediation analysis. 2205 physicians and nurses of the medical center participated in the survey. Because not all questions in the survey are suitable for entire hospital staff, only the valid responses (n = 1596, response rate of 72%) were extracted for analysis. Key measures are the direct and indirect effects of teamwork climate, job satisfaction, perception of management leadership, and working conditions on safety climate. Outcomes show that effect of perception of management leadership on safety climate is significant (standardized indirect effect of 0.892 with P-value 0.002) and fully mediated by other dimensions, where 66.9% is mediated through teamwork climate, 24.1% through working conditions and 9.0% through job satisfaction. Our findings point to the importance of management leadership and the mechanism of its influence on safety climate. To improve safety climate, the implication is that commitment by management on leading safety improvement needs to be demonstrated when it implements daily supportive actions for other safety dimensions. For future improvement, development of a management system that can facilitate two-way trust between management and staff over the long term is recommended. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Growth response of conifers in Adirondack plantations to changing environment: Model approaches based on stem-analysis

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

Pan, Y.

1993-01-01

Based on model approaches, three conifer species, red pine, Norway spruce and Scots pine grown in plantations at Pack Demonstration Forest, in the southeastern Adirondack mountains of New York, were chosen to study growth response to different environmental changes, including silvicultural treatments and changes in climate and chemical environment. Detailed stem analysis data provided a basis for constructing tree growth models. These models were organized into three groups: morphological, dynamic and predictive. The morphological model was designed to evaluate relationship between tree attributes and interactive influences of intrinsic and extrinsic factors on the annual increments. Three types of morphological patternsmore » have been characterized: space-time patterns of whole-stem rings, intrinsic wood deposition pattern along the tree-stem, and bolewood allocation ratio patterns along the tree-stem. The dynamic model reflects the growth process as a system which responds to extrinsic signal inputs, including fertilization pulses, spacing effects and climatic disturbance, as well as intrinsic feedback. Growth signals indicative of climatic effects were used to construct growth-climate models using both multivariate analysis and Kalman filter methods. The predictive model utilized GCMs and growth-climate relationships to forecast tree growth responses in relation to future scenarios of CO[sub 2]-induced climate change. Prediction results indicate that different conifer species have individualistic growth response to future climatic change and suggest possible changes in future growth and distribution of naturally occurring conifers in this region.« less

2016 International Land Model Benchmarking (ILAMB) Workshop Report

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

Hoffman, Forrest M.; Koven, Charles D.; Keppel-Aleks, Gretchen

As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

Climate change induced transformations of agricultural systems: insights from a global model

NASA Astrophysics Data System (ADS)

Leclère, D.; Havlík, P.; Fuss, S.; Schmid, E.; Mosnier, A.; Walsh, B.; Valin, H.; Herrero, M.; Khabarov, N.; Obersteiner, M.

2014-12-01

Climate change might impact crop yields considerably and anticipated transformations of agricultural systems are needed in the coming decades to sustain affordable food provision. However, decision-making on transformational shifts in agricultural systems is plagued by uncertainties concerning the nature and geography of climate change, its impacts, and adequate responses. Locking agricultural systems into inadequate transformations costly to adjust is a significant risk and this acts as an incentive to delay action. It is crucial to gain insight into how much transformation is required from agricultural systems, how robust such strategies are, and how we can defuse the associated challenge for decision-making. While implementing a definition related to large changes in resource use into a global impact assessment modelling framework, we find transformational adaptations to be required of agricultural systems in most regions by 2050s in order to cope with climate change. However, these transformations widely differ across climate change scenarios: uncertainties in large-scale development of irrigation span in all continents from 2030s on, and affect two-thirds of regions by 2050s. Meanwhile, significant but uncertain reduction of major agricultural areas affects the Northern Hemisphere’s temperate latitudes, while increases to non-agricultural zones could be large but uncertain in one-third of regions. To help reducing the associated challenge for decision-making, we propose a methodology exploring which, when, where and why transformations could be required and uncertain, by means of scenario analysis.

Organic farming enhances soil microbial abundance and activity—A meta-analysis and meta-regression

PubMed Central

Symnaczik, Sarah; Mäder, Paul; De Deyn, Gerlinde; Gattinger, Andreas

2017-01-01

Population growth and climate change challenge our food and farming systems and provide arguments for an increased intensification of agriculture. A promising option is eco-functional intensification through organic farming, an approach based on using and enhancing internal natural resources and processes to secure and improve agricultural productivity, while minimizing negative environmental impacts. In this concept an active soil microbiota plays an important role for various soil based ecosystem services such as nutrient cycling, erosion control and pest and disease regulation. Several studies have reported a positive effect of organic farming on soil health and quality including microbial community traits. However, so far no systematic quantification of whether organic farming systems comprise larger and more active soil microbial communities compared to conventional farming systems was performed on a global scale. Therefore, we conducted a meta-analysis on current literature to quantify possible differences in key indicators for soil microbial abundance and activity in organic and conventional cropping systems. All together we integrated data from 56 mainly peer-reviewed papers into our analysis, including 149 pairwise comparisons originating from different climatic zones and experimental duration ranging from 3 to more than 100 years. Overall, we found that organic systems had 32% to 84% greater microbial biomass carbon, microbial biomass nitrogen, total phospholipid fatty-acids, and dehydrogenase, urease and protease activities than conventional systems. Exclusively the metabolic quotient as an indicator for stresses on microbial communities remained unaffected by the farming systems. Categorical subgroup analysis revealed that crop rotation, the inclusion of legumes in the crop rotation and organic inputs are important farming practices affecting soil microbial community size and activity. Furthermore, we show that differences in microbial size and activity between organic and conventional farming systems vary as a function of land use (arable, orchards, and grassland), plant life cycle (annual and perennial) and climatic zone. In summary, this study shows that overall organic farming enhances total microbial abundance and activity in agricultural soils on a global scale. PMID:28700609

Interdisciplinary research in climate and energy sciences

DOE PAGES

Xu, Xiaofeng; Goswami, Santonu; Gulledge, Jay; ...

2015-09-12

Due to the complex nature of climate change, interdisciplinary research approaches involving knowledge and skills from a broad range of disciplines have been adopted for studying changes in the climate system as well as strategies for mitigating climate change (i.e., greenhouse gas emissions reductions) and adapting to its impacts on society and natural systems. Harnessing of renewable energy sources to replace fossil fuels is widely regarded as a long-term mitigation strategy that requires the synthesis of knowledge from engineering, technology, and natural and social sciences. In this study, we examine how the adoption of interdisciplinary approaches has evolved over timemore » and in different geographic regions. We conducted a comprehensive literature survey using an evaluation matrix of keywords, in combination with a word cloud analysis, to evaluate the spatiotemporal dynamics of scholarly discourse about interdisciplinary approaches to climate change and renewable energy research and development (R&D). Publications that discuss interdisciplinary approaches to climate change and renewable energy have substantially increased over the last 60 years; it appears, however, that the nature, timing, and focus of these publications vary across countries and through time. Over the most recent three decades, the country-level contribution to interdisciplinary research for climate change has become more evenly distributed, but this was not true for renewable energy research, which remained dominated by the United Sates and a few other major economies. The research topics have also evolved: Water resource management was emphasized from 1990s to 2000s, policy and adaptation were emphasized from the 2000s to 2010 – 2013, while vulnerability became prominent during the most recent years (2010 – 2013). Lastly, our analysis indicates that the rate of growth of interdisciplinary research for renewable energy lags behind that for climate change, possibly because knowledge emanating from climate change science has motivated the subsequent upswing in renewable energy R&D.« less

Climate Services Information System Activities in Support of The Global Framework for Climate Services Implementation

NASA Astrophysics Data System (ADS)

Timofeyeva-Livezey, M. M.; Horsfall, F. M. C.; Pulwarty, R. S.; Klein-Tank, A.; Kolli, R. K.; Hechler, P.; Dilley, M.; Ceron, J. P.; Goodess, C.

2017-12-01

The WMO Commission on Climatology (CCl) supports the implementation of the Global Framework for Climate Services (GFCS) with a particular focus on the Climate Services Information System (CSIS), which is the core operational component of GFCS at the global, regional, and national level. CSIS is designed for producing, packaging and operationally delivering authoritative climate information data and products through appropriate operational systems, practices, data exchange, technical standards, authentication, communication, and product delivery. Its functions include climate analysis and monitoring, assessment and attribution, prediction (monthly, seasonal, decadal), and projection (centennial scale) as well as tailoring the associated products tUEAo suit user requirements. A central, enabling piece of implementation of CSIS is a Climate Services Toolkit (CST). In its development phase, CST exists as a prototype (www.wmo.int/cst) as a compilation of tools for generating tailored data and products for decision-making, with a special focus on national requirements in developing countries. WMO provides a server to house the CST prototype as well as support operations and maintenance. WMO members provide technical expertise and other in-kind support, including leadership of the CSIS development team. Several recent WMO events have helped with the deployment of CST within the eight countries that have been recognized by GFCS as illustrative for developing their climate services at national levels. Currently these countries are developing climate services projects focusing service development and delivery for selected economic sectors, such as for health, agriculture, energy, water resources, and hydrometeorological disaster risk reduction. These countries are working together with their respective WMO Regional Climate Centers (RCCs), which provide technical assistance with implementation of climate services projects at the country level and facilitate development of regional climate products, starting with the CST. The paper will introduce the CST prototype to the wider meteorological, hydrological, and climatological communities and provide details of its implementation in the context of the global framework.

Research Review, 1984

NASA Technical Reports Server (NTRS)

1986-01-01

A variety of topics relevant to global modeling and simulation are presented. Areas of interest include: (1) analysis and forecast studies; (2) satellite observing systems; (3) analysis and forecast model development; (4) atmospheric dynamics and diagnostic studies; (5) climate/ocean-air interactions; and notes from lectures.

Climate Science Program at California State University, Northridge

NASA Astrophysics Data System (ADS)

Steele Cox, H.; Klein, D.; Cadavid, A. C.; Foley, B.

2012-12-01

Due to its interdisciplinary nature, climate science poses wide-ranging challenges for science and mathematics students seeking careers in this field. There is a compelling need for universities to provide coherent programs in climate science in order to train future climate scientists. With funding from NASA Innovations in Climate Education (NICE), California State University, Northridge (CSUN), is creating the CSUN Climate Science Program. An interdisciplinary team of faculty members is working in collaboration with UCLA, Santa Monica College and NASA/JPL partners to create a new curriculum in climate science. The resulting sequence of climate science courses, or Pathway for studying the Mathematics of Climate Change (PMCC), is integrated into a Bachelor of Science degree program in the Applied Mathematical Sciences offered by the Mathematics Department at CSUN. The PMCC consists of courses offered by the departments of Mathematics, Physics, and Geography and is designed to prepare students for Ph.D. programs in technical fields relevant to global climate change and related careers. The students who choose to follow this program will be guided to enroll in the following sequence of courses for their 12 units of upper division electives: 1) A newly created course junior level course, Math 396CL, in applied mathematics which will introduce students to applications of vector calculus and differential equations to the study of thermodynamics and atmospheric dynamics. 2) An already existing course, Math 483, with new content on mathematical modeling specialized for this program; 3) An improved version of Phys 595CL on the mathematics and physics of climate change with emphasis on Radiative Transfer; 4) A choice of Geog 407 on Remote Sensing or Geog 416 on Climate Change with updated content to train the students in the analysis of satellite data obtained with the NASA Earth Observing System and instruction in the analysis of data obtained within a Geographical Information System (GIS). In addition the Geography department will similarly update the corresponding graduate courses on Remote Sensing, Geog 690D, and Climate Change Geog 620F, and there will be a reciprocal curriculum and data sharing collaboration with the Earth and Environmental Sciences program at Santa Monica College. Throughout the academic year a seminar series offers the students the opportunity to learn about ongoing work on Atmospheric Sciences and Climate and during the summer they have access to research experiences at NASA's Jet Propulsion Laboratory.

Detecting the Spectrum of the Atlantic's Thermo-haline Circulation: Deconvolved Climate Proxies Show How Polar Climates Communicate

NASA Astrophysics Data System (ADS)

Reischmann, Elizabeth; Yang, Xiao; Rial, José

2014-05-01

Deconvolution is widely used in a wide variety of scientific fields, including its significant use in seismology, as a tool to recover real input from a system's impulse response and output. Our research uses spectral division deconvolution in the context of studying the impulse response of the possible relationship between the nonlinear climates of the Polar Regions by using select δ18O ice cores from both poles. This is feasible in spite of the fact that the records may be the result of nonlinear processes because the two polar climates are synchronized for the period studied, forming a Hilbert transform pair. In order to perform this analysis, the age models of three Greenland and four Antarctica records have been matched using a Monte Carlo method with the methane-matched pair GRIP and BYRD as a basis of calculations. For all of the twelve resulting pairs, various deconvolutions schemes (Weiner, Damped Least Squares, Tikhonov, Truncated Singular Value Decomposition) give consistent, quasi-periodic, impulse responses of the system. Multitaper analysis then demonstrates strong, millennia scale, quasi-periodic oscillations in these system responses with a range of 2,500 to 1,000 years. However, these results are directionally dependent, with the transfer function from north to south differing from that of south north. High amplitude power peaks at 5,000 to 1,7000 years characterize the former, while the latter contains peaks at 2,500 to 1,700 years. These predominant periodicities are also found in the data, some of which have been identified as solar forcing, but others of which may indicate internal oscillations of the climate system (1.6-1.4ky). The approximately 1,500 year period transfer function, which does not have a corresponding solar forcing, may indicate one of these internal periodicities of the system, perhaps even indicating the long-term presence of the Deep Water circulation, also known as the thermo-haline circulation (THC). Simplified models of the polar climate fluctuations are shown to support these findings.

Identification of reliable gridded reference data for statistical downscaling methods in Alberta

NASA Astrophysics Data System (ADS)

Eum, H. I.; Gupta, A.

2017-12-01

Climate models provide essential information to assess impacts of climate change at regional and global scales. However, statistical downscaling methods have been applied to prepare climate model data for various applications such as hydrologic and ecologic modelling at a watershed scale. As the reliability and (spatial and temporal) resolution of statistically downscaled climate data mainly depend on a reference data, identifying the most reliable reference data is crucial for statistical downscaling. A growing number of gridded climate products are available for key climate variables which are main input data to regional modelling systems. However, inconsistencies in these climate products, for example, different combinations of climate variables, varying data domains and data lengths and data accuracy varying with physiographic characteristics of the landscape, have caused significant challenges in selecting the most suitable reference climate data for various environmental studies and modelling. Employing various observation-based daily gridded climate products available in public domain, i.e. thin plate spline regression products (ANUSPLIN and TPS), inverse distance method (Alberta Townships), and numerical climate model (North American Regional Reanalysis) and an optimum interpolation technique (Canadian Precipitation Analysis), this study evaluates the accuracy of the climate products at each grid point by comparing with the Adjusted and Homogenized Canadian Climate Data (AHCCD) observations for precipitation, minimum and maximum temperature over the province of Alberta. Based on the performance of climate products at AHCCD stations, we ranked the reliability of these publically available climate products corresponding to the elevations of stations discretized into several classes. According to the rank of climate products for each elevation class, we identified the most reliable climate products based on the elevation of target points. A web-based system was developed to allow users to easily select the most reliable reference climate data at each target point based on the elevation of grid cell. By constructing the best combination of reference data for the study domain, the accurate and reliable statistically downscaled climate projections could be significantly improved.

An Analysis of Home Energy Score and REM/Rate Energy Simulation Results for Homes in Three Climates

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

Merket, Noel D

Energy ratings and scores for homes attempt to give homeowners a understandable metric to compare the energy efficiency of homes. Two rating systems in the marketplace include RESNET's Home Energy Rating System (HERS) and DOE's Home Energy Score (HEScore) and include differing energy calculation methodologies. This report compares the energy predictions from both REM/Rate and Home Energy Score for populations of real homes in three climates and determines some features of homes that lead to the greatest differences between energy predictions.

Educator Uses of Data-Enhanced Investigations for Climate Change Education (DICCE), An Online System for Accessing a Vast Portal of NASA Earth System Data Known As the Goddard Interactive Online Visualization and Analysis Infrastructure (GIOVANNI)

NASA Astrophysics Data System (ADS)

Zalles, D. R.; Acker, J. G.

2015-12-01

Data-enhanced Investigations for Climate Change Education (DICCE) has made it easier and more technologically feasible for secondary and post-secondary instructors and students to study climate change and related Earth system phenomena using data products from the Goddard Interactive Online Visualization and Analysis Infrastructure (GIOVANNI), a powerful portal of Earth observation data that provides access to numerous data products on Earth system phenomena representing the land biosphere, physical land, ocean biosphere, physical ocean, physical atmosphere, atmospheric gases, and energy and radiation system. These data products are derived from remote-sensing instruments on satellites, ground stations, and data assimilation models. Instructors and students can query the GIOVANNI data archive, then save the results as map images, time series plots, vertical profiles of the atmosphere, and data tables. Any part of the world can be selected for analysis. The project has also produced a tool for instructors to author and adapt standards-based lesson plans, student data investigation activities, and presentations around visualizations they make available to their students via DICCE-G. Supports are provided to students and teachers about how to interpret trends in data products of their choice at the regional level and a schema has been developed to help them understand how those data products fit into current scientific thinking about the certainties and uncertainties of climate change. The presentation will (1) describe the features of DICCE, (2) examples of curricula developed to make use of DICCE in classrooms, (3) how these curricula align to Next Generation Science Standards, and (4) how they align to science education research literature about how to make school science more engaging. Recently-analyzed teacher and student outcomes from DICCE use will also be reported.

Climate change and livestock system in mountain: Understanding from Gandaki River basin of Nepal Himalaya.

NASA Astrophysics Data System (ADS)

Dahal, P.; Shrestha, N. S.; Krakauer, N.; Lakhankar, T.; Panthi, J., Sr.; Pradhanang, S.; Jha, A. K.; Shrestha, M.; Sharma, M.

2015-12-01

In recent years climate change has emerged as a source of vulnerability for agro-livestock smallholders in Nepal where people are mostly dependent on rain-fed agriculture and livestock farming for their livelihoods. There is a need to understand and predict the potential impacts of climate change on agro-livestock farmer to develop effective mitigation and adaptation strategies. To understand dynamics of this vulnerability, we assess the farmers' perceptions of climate change, analysis of historical and future projections of climatic parameters and try to understand impact of climate change on livestock system in Gandaki River Basin of Central Nepal. During the period of 1981-2012, as reported by the mountain communities, the most serious hazards for livestock system and agriculture are the increasing trend of temperature, erratic rainfall patterns and increase in drought. Poor households without irrigated land are facing greater risks and stresses than well-off people. Analysis of historical climate data also supports the farmer perception. Result shows that there is increasing trend of temperature but no consistent trend in precipitation but a notable finding is that wet areas are getting wetter and dry areas getting drier. Besides that, there is increase in percentage of warm days and nights with decrease in the cool nights and days. The magnitude of the trend is found to be higher in high altitude. Trend of wet days has found to be increasing with decreasing in rainy days. Most areas are characterized by increases in both severity and frequency of drought and are more evident in recent years. The summers of 2004/05/06/09 and winters of 2006/08/09 were the worst widespread droughts and have a serious impact on livestock since 1981. Future projected change in temperature and precipitation obtained from downscaling the data global model by regional climate model shows that precipitation in central Nepal will change by -8% to 12% and temperature will change by 1.9 0C to 3 0C in 2031-2060 compared to the baseline period 1970-2000. Since there will be an increase in temperature and most of the area will experience decreasing rainfall we can predict that there will be increasing vulnerability on livestock system in central Nepal in future which is already facing a serious impact.

Implementation of a Time Series Analysis for the Assessment of the Role of Climate Variability in a Post-Disturbance Savanna System

NASA Astrophysics Data System (ADS)

Gibbes, C.; Southworth, J.; Waylen, P. R.

2013-05-01

How do climate variability and climate change influence vegetation cover and vegetation change in savannas? A landscape scale investigation of the effect of changes in precipitation on vegetation is undertaken through the employment of a time series analysis. The multi-national study region is located within the Kavango-Zambezi region, and is delineated by the Okavango, Kwando, and Zambezi watersheds. A mean-variance time-series analysis quantifies vegetation dynamics and characterizes vegetation response to climate. The spatially explicit approach used to quantify the persistence of vegetation productivity permits the extraction of information regarding long term climate-landscape dynamics. Results show a pattern of reduced mean annual precipitation and increased precipitation variability across key social and ecological areas within the study region. Despite decreased mean annual precipitation since the mid to late 1970's vegetation trends predominantly indicate increasing biomass. The limited areas which have diminished vegetative cover relate to specific vegetation types, and are associated with declines in precipitation variability. Results indicate that in addition to short term changes in vegetation cover, long term trends in productive biomass are apparent, relate to spatial differences in precipitation variability, and potentially represent shifts vegetation composition. This work highlights the importance of time-series analyses for examining climate-vegetation linkages in a spatially explicit manner within a highly vulnerable region of the world.

Climate Data Provenance Tracking for Just-In-Time Computation

NASA Astrophysics Data System (ADS)

Fries, S.; Nadeau, D.; Doutriaux, C.; Williams, D. N.

2016-12-01

The "Climate Data Management System" (CDMS) was created in 1996 as part of the Climate Data Analysis Tools suite of software. It provides a simple interface into a wide variety of climate data formats, and creates NetCDF CF-Compliant files. It leverages the NumPy framework for high performance computation, and is an all-in-one IO and computation package. CDMS has been extended to track manipulations of data, and trace that data all the way to the original raw data. This extension tracks provenance about data, and enables just-in-time (JIT) computation. The provenance for each variable is packaged as part of the variable's metadata, and can be used to validate data processing and computations (by repeating the analysis on the original data). It also allows for an alternate solution for sharing analyzed data; if the bandwidth for a transfer is prohibitively expensive, the provenance serialization can be passed in a much more compact format and the analysis rerun on the input data. Data provenance tracking in CDMS enables far-reaching and impactful functionalities, permitting implementation of many analytical paradigms.

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.

Sediment color and reflectance record from Ocean Drilling Program Hole 625B, Gulf of Mexico (marine isotope stage 5 interval)

USGS Publications Warehouse

Dowsett, Harry J.

1999-01-01

Analysis of climate indicators from the North Atlantic, California Margin, and ice cores from Greenland suggest millennial scale climate variability is a component of earth's climate system during the last interglacial period (marine oxygen isotope stage 5). The USGS is involved in a survey of high resolution marine records covering the last interglacial period (MIS 5) to further document the variability of climate and assess the rate at which climate can change during warm intervals. The Gulf of Mexico (GOM) is an attractive area for analysis of climate variability and rapid change. Changes in the Mississippi River Basin presumably are translated to the GOM via the river and its effect on sediment distribution and type. Likewise, the summer monsoon in the southwestern US is driven by strong southerly winds. These winds may produce upwelling in the GOM which will be recorded in the sedimentary record. Several areas of high accumulation rate have been identified in the GOM. Ocean Drilling Program (ODP) Site 625 appears to meet the criteria of having a well preserved carbonate record and accumulation rate capable of discerning millennial scale changes.

Energy loss, range, and bremsstrahlung yield for 10-keV to 100-MeV electrons in various elements and chemical compounds

NASA Astrophysics Data System (ADS)

Pages, Lucien; Bertel, Evelyne; Joffre, Henri; Sklavenitis, Laodamas

2012-12-01

Even though the United States lacks a national climate policy, significant action has occurred at the local and regional levels. Some of the most aggressive climate change policies have occurred at the state and local levels and in interagency cooperation on specific management issues. While there is a long history of partnerships in dealing with a wide variety of policy issues, the uncertainty and the political debate surrounding climate change has generated new challenges to establishing effective policy networks. This paper investigates the formation of climate policy networks in the State of Nevada. It presents a methodology based on social network analysis for assessing the structure and function of local policy networks across a range of substantive climate impacted resources (water, landscape management, conservation, forestry and others). It draws from an emerging literature on federalism and climate policy, public sector innovation, and institutional analysis in socio-ecological systems. Comparisons across different policy issue networks in the state are used to highlight the influence of network structure, connectivity, bridging across vertical and horizontal organizational units, organizational diversity, and flows between organizational nodes.

Research | Argonne National Laboratory

Science.gov Websites

, and Decision Analytics Energy Systems Analysis Engines and Fuels Friction, Wear, and Lubrication Vehicle Technologies Buildings and Climate-Environment Energy, Power, and Decision Analytics Energy

Integrating Climate and Risk-Informed Science to Support Critical Decisions

ScienceCinema

None

2018-01-16

The PNNL Environmental Health and Remediation Sector stewards several decision support capabilities to integrate climate- and risk-informed science to support critical decisions. Utilizing our expertise in risk and decision analysis, integrated Earth systems modeling, and remote sensing and geoinformatics, PNNL is influencing the way science informs high level decisions at national, regional and local scales to protect and preserve our most critical assets.

Communicating Coastal Risk Analysis in an Age of Climate Change

DTIC Science & Technology

2011-10-01

extratropical storm systems); the geometry and geomorphology of the area (regional and local bathymetry and topography, including rivers, marshes, and...at risk from coastal hazards including storm surge inundation, precipitation driven flooding, waves, and coastal erosion. This population segment...will likely be exposed to increased risk as impacts of a changing climate are felt through elevated sea levels and potentially increased storm

Integrating Climate and Risk-Informed Science to Support Critical Decisions

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

None

2016-07-27

The PNNL Environmental Health and Remediation Sector stewards several decision support capabilities to integrate climate- and risk-informed science to support critical decisions. Utilizing our expertise in risk and decision analysis, integrated Earth systems modeling, and remote sensing and geoinformatics, PNNL is influencing the way science informs high level decisions at national, regional and local scales to protect and preserve our most critical assets.

A Comparative Study on the Environmental Impact of CO2 Supermarket Refrigeration Systems

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

Beshr, Mohamed; Aute, Vikrant; Sharma, Vishaldeep

Supermarket refrigeration systems have high environmental impact due to their large refrigerant charge and high leak rates. Accordingly, the interest in using natural refrigerants, such as carbon dioxide (CO2), and new refrigerant blends with low GWP in such systems is increasing. In this paper, an open-source Life Cycle Climate Performance (LCCP) framework is presented and used to compare the environmental impact of three supermarket refrigeration systems. These systems include a transcritical CO2 booster system, a cascade CO2/N-40 system, and a baseline R-404A multiplex direct expansion system. The study is performed for cities representing different climates within the USA using EnergyPlusmore » to simulate the systems' hourly performance. Finally, a parametric analysis is performed to study the impact of annual leak rate on the systems' LCCP.« less

A method for physically based model analysis of conjunctive use in response to potential climate changes

USGS Publications Warehouse

Hanson, R.T.; Flint, L.E.; Flint, A.L.; Dettinger, M.D.; Faunt, C.C.; Cayan, D.; Schmid, W.

2012-01-01

Potential climate change effects on aspects of conjunctive management of water resources can be evaluated by linking climate models with fully integrated groundwater-surface water models. The objective of this study is to develop a modeling system that links global climate models with regional hydrologic models, using the California Central Valley as a case study. The new method is a supply and demand modeling framework that can be used to simulate and analyze potential climate change and conjunctive use. Supply-constrained and demand-driven linkages in the water system in the Central Valley are represented with the linked climate models, precipitation-runoff models, agricultural and native vegetation water use, and hydrologic flow models to demonstrate the feasibility of this method. Simulated precipitation and temperature were used from the GFDL-A2 climate change scenario through the 21st century to drive a regional water balance mountain hydrologic watershed model (MHWM) for the surrounding watersheds in combination with a regional integrated hydrologic model of the Central Valley (CVHM). Application of this method demonstrates the potential transition from predominantly surface water to groundwater supply for agriculture with secondary effects that may limit this transition of conjunctive use. The particular scenario considered includes intermittent climatic droughts in the first half of the 21st century followed by severe persistent droughts in the second half of the 21st century. These climatic droughts do not yield a valley-wide operational drought but do cause reduced surface water deliveries and increased groundwater abstractions that may cause additional land subsidence, reduced water for riparian habitat, or changes in flows at the Sacramento-San Joaquin River Delta. The method developed here can be used to explore conjunctive use adaptation options and hydrologic risk assessments in regional hydrologic systems throughout the world.

Improving Assimilated Global Data Sets using TMI Rainfall and Columnar Moisture Observations

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.; Zhang, Sara Q.; daSilva, Arlindo M.; Olson, William S.

1999-01-01

A global analysis that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data products contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. In this study, we show that assimilating precipitation and total precipitable water (TPW) retrievals derived from the TRMM Microwave Imager (TMI) improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the large-scale circulation produced by the Goddard Earth Observing System (GEOS) data assimilation system (DAS). In particular, assimilating TMI rain improves clouds and radiation in areas of active convection, as well as the latent heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW heating distribution and the large-scale motion field in the tropics, while assimilating TMI TPW retrievals leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. The improved analysis also improves short-range forecasts in the tropics. Ensemble forecasts initialized with the GEOS analysis incorporating TMI rain rates and TPW yield smaller biases in tropical precipitation forecasts beyond 1 day and better 500 hPa geopotential height forecasts up to 5 days. Results of this study demonstrate the potential of using high-quality space-borne rainfall and moisture observations to improve the quality of assimilated global data for climate analysis and weather forecasting applications

Incorporating Parallel Computing into the Goddard Earth Observing System Data Assimilation System (GEOS DAS)

NASA Technical Reports Server (NTRS)

Larson, Jay W.

1998-01-01

Atmospheric data assimilation is a method of combining actual observations with model forecasts to produce a more accurate description of the earth system than the observations or forecast alone can provide. The output of data assimilation, sometimes called the analysis, are regular, gridded datasets of observed and unobserved variables. Analysis plays a key role in numerical weather prediction and is becoming increasingly important for climate research. These applications, and the need for timely validation of scientific enhancements to the data assimilation system pose computational demands that are best met by distributed parallel software. The mission of the NASA Data Assimilation Office (DAO) is to provide datasets for climate research and to support NASA satellite and aircraft missions. The system used to create these datasets is the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The core components of the the GEOS DAS are: the GEOS General Circulation Model (GCM), the Physical-space Statistical Analysis System (PSAS), the Observer, the on-line Quality Control (QC) system, the Coupler (which feeds analysis increments back to the GCM), and an I/O package for processing the large amounts of data the system produces (which will be described in another presentation in this session). The discussion will center on the following issues: the computational complexity for the whole GEOS DAS, assessment of the performance of the individual elements of GEOS DAS, and parallelization strategy for some of the components of the system.

Sensitivity of the Tropical Atmosphere Energy Balance to ENSO-Related SST Changes: How Well Can We Quantify Hydrologic and Radiative Responses?

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Fitzjarrald, Dan; Sohn, Byung-Ju; Arnold, James E. (Technical Monitor)

2001-01-01

The continuing debate over feedback mechanisms governing tropical sea surface temperatures (SSTs) and tropical climate in general has highlighted the diversity of potential checks and balances within the climate system. Competing feedbacks due to changes in surface evaporation, water vapor, and cloud long- and shortwave radiative properties each may serve critical roles in stabilizing or destabilizing the climate system. It is also intriguing that even those climate variations having origins internal to the climate system-- changes in ocean heat transport for example, apparently require complementary equilibrating effects by changes in atmospheric energy fluxes. Perhaps the best observational evidence of this is the relatively invariant nature of tropically averaged net radiation exiting the top-of-atmosphere (TOA) as measured by broadband satellite sensors over the past two decades. Thus, analyzing how these feedback mechanisms are operating within the context of current interannual variability may offer considerable insight for anticipating future climate change. In this paper we focus on how fresh water and radiative fluxes over the tropical oceans change during ENSO warm and cold events and how these changes affect the tropical energy balance. At present, ENSO remains the most prominent known mode of natural variability at interannual time scales. Although great advances have been made in understanding this phenomenon and realizing prediction skill over the past decade, our ability to document the coupled water and energy changes observationally and to represent them in climate models seems far from settled (Soden, 2000 J Climate). Our analysis makes use a number of data bases, principally those derived from space-based measurements, to explore systematic changes in rainfall, evaporation, and surface and top-of-atmosphere (TOA) radiative fluxes, A reexamination of the Langley 8-Year Surface Radiation Budget data set reveals errors in the surface longwave emission due to use of biased SSTs. Subsequent correction allows subsequent use of this data set along with ERBE TOA fluxes to infer net atmospheric radiative beating. Further analysis of recent rainfall algorithms provides new estimates for precipitation variability in line with interannual evaporation changes inferred from the da Silva, Young, Levitus COADS analysis. The overall results from our analysis suggest an increase (decrease) of the hydrologic cycle during ENSO warm (cold) events at the rate of about 5 Wm-2 per K of SST change. This rate is slightly less than that which would be expected for constant relative humidity over the tropical oceans. Corresponding radiative fluxes seem systematically smaller resulting in a enhanced (suppressed) export of energy from the tropical ocean regions during warm (cold) SST events. Discussion of likely errors due to sampling and measurement strategies are discussed along with their impacts on our conclusions.

An Enhanced Engineering Perspective of Global Climate Systems and Statistical Formulation of Terrestrial CO2 Exchanges

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

Dai, Yuanshun; Baek, Seung H.; Garcia-Diza, Alberto

2012-01-01

This paper designs a comprehensive approach based on the engineering machine/system concept, to model, analyze, and assess the level of CO2 exchange between the atmosphere and terrestrial ecosystems, which is an important factor in understanding changes in global climate. The focus of this article is on spatial patterns and on the correlation between levels of CO2 fluxes and a variety of influencing factors in eco-environments. The engineering/machine concept used is a system protocol that includes the sequential activities of design, test, observe, and model. This concept is applied to explicitly include various influencing factors and interactions associated with CO2 fluxes.more » To formulate effective models of a large and complex climate system, this article introduces a modeling technique that will be referred to as Stochastic Filtering Analysis of Variance (SFANOVA). The CO2 flux data observed from some sites of AmeriFlux are used to illustrate and validate the analysis, prediction and globalization capabilities of the proposed engineering approach and the SF-ANOVA technology. The SF-ANOVA modeling approach was compared to stepwise regression, ridge regression, and neural networks. The comparison indicated that the proposed approach is a valid and effective tool with similar accuracy and less complexity than the other procedures.« less

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.

NCA-LDAS: A Terrestrial Water Analysis System Enabling Sustained Assessment and Dissemination of National Climate Indicators

NASA Astrophysics Data System (ADS)

Jasinski, M. F.; Kumar, S.; Peters-Lidard, C. D.; Arsenault, K. R.; Beaudoing, H. K.; Bolten, J. D.; Borak, J.; Kempler, S.; Li, B.; Mocko, D. M.; Rodell, M.; Rui, H.; Silberstein, D. S.; Teng, W. L.; Vollmer, B.

2016-12-01

The National Climate Assessment - Land Data Assimilation System, or NCA-LDAS, is an integrated terrestrial water analysis system created as an end-to-end enabling tool for sustained assessment and dissemination of terrestrial hydrologic indicators in support of the NCA. The primary features are i) gridded, daily time series of over forty hydrologic variables including terrestrial water and energy balance stores, states and fluxes over the continental U.S. derived from land surface modeling with multivariate satellite data record assimilation (1979-2015), ii) estimated trends of the principal water balance components over a wide range of scales and locations, and iii) public dissemination of all NCA-LDAS model forcings, and input and output data products through dedicated NCA-LDAS and NASA GES-DISC websites. NCA-LDAS supports sustained assessment of our national terrestrial hydrologic climate for improved scientific understanding, and the adaptation and management of water resources and related energy sectors. This presentation provides an overview of the NCA-LDAS system together with an evaluation of the initial release of NCA-LDAS data products and trends using two land surface models; Noah Ver. 3.3 and Catchment Ver. Fortuna 2.5, and a listing of several available pathways for public access and visualization of NCA-LDAS background information and data products.

A coupled human-natural systems analysis of irrigated agriculture under changing climate

NASA Astrophysics Data System (ADS)

Giuliani, M.; Li, Y.; Castelletti, A.; Gandolfi, C.

2016-09-01

Exponentially growing water demands and increasingly uncertain hydrologic regimes due to changes in climate and land use are challenging the sustainability of agricultural water systems. Farmers must adapt their management strategies in order to secure food production and avoid crop failures. Investigating the potential for adaptation policies in agricultural systems requires accounting for their natural and human components, along with their reciprocal interactions. Yet this feedback is generally overlooked in the water resources systems literature. In this work, we contribute a novel modeling approach to study the coevolution of irrigated agriculture under changing climate, advancing the representation of the human component within agricultural systems by using normative meta-models to describe the behaviors of groups of farmers or institutional decisions. These behavioral models, validated against observational data, are then integrated into a coupled human-natural system simulation model to better represent both systems and their coevolution under future changing climate conditions, assuming the adoption of different policy adaptation options, such as cultivating less water demanding crops. The application to the pilot study of the Adda River basin in northern Italy shows that the dynamic coadaptation of water supply and demand allows farmers to avoid estimated potential losses of more than 10 M€/yr under projected climate changes, while unilateral adaptation of either the water supply or the demand are both demonstrated to be less effective. Results also show that the impact of the different policy options varies as function of drought intensity, with water demand adaptation outperforming water supply adaptation when drought conditions become more severe.

The Hydrological Response of Snowmelt Dominated Catchments to Climate Change

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Ontological and Epistemological Issues Regarding Climate Models and Computer Experiments

NASA Astrophysics Data System (ADS)

Vezer, M. A.

2010-12-01

Recent philosophical discussions (Parker 2009; Frigg and Reiss 2009; Winsberg, 2009; Morgon 2002, 2003, 2005; Gula 2002) about the ontology of computer simulation experiments and the epistemology of inferences drawn from them are of particular relevance to climate science as computer modeling and analysis are instrumental in understanding climatic systems. How do computer simulation experiments compare with traditional experiments? Is there an ontological difference between these two methods of inquiry? Are there epistemological considerations that result in one type of inference being more reliable than the other? What are the implications of these questions with respect to climate studies that rely on computer simulation analysis? In this paper, I examine these philosophical questions within the context of climate science, instantiating concerns in the philosophical literature with examples found in analysis of global climate change. I concentrate on Wendy Parker’s (2009) account of computer simulation studies, which offers a treatment of these and other questions relevant to investigations of climate change involving such modelling. Two theses at the center of Parker’s account will be the focus of this paper. The first is that computer simulation experiments ought to be regarded as straightforward material experiments; which is to say, there is no significant ontological difference between computer and traditional experimentation. Parker’s second thesis is that some of the emphasis on the epistemological importance of materiality has been misplaced. I examine both of these claims. First, I inquire as to whether viewing computer and traditional experiments as ontologically similar in the way she does implies that there is no proper distinction between abstract experiments (such as ‘thought experiments’ as well as computer experiments) and traditional ‘concrete’ ones. Second, I examine the notion of materiality (i.e., the material commonality between object and target systems) and some arguments for the claim that materiality entails some inferential advantage to traditional experimentation. I maintain that Parker’s account of the ontology of computer simulations has some interesting though potentially problematic implications regarding conventional distinctions between abstract and concrete methods of inquiry. With respect to her account of materiality, I outline and defend an alternative account, posited by Mary Morgan (2002, 2003, 2005), which holds that ontological similarity between target and object systems confers some epistemological advantage to traditional forms of experimental inquiry.

The relationship between organizational climate and quality of chronic disease management.

PubMed

Benzer, Justin K; Young, Gary; Stolzmann, Kelly; Osatuke, Katerine; Meterko, Mark; Caso, Allison; White, Bert; Mohr, David C

2011-06-01

To test the utility of a two-dimensional model of organizational climate for explaining variation in diabetes care between primary care clinics. Secondary data were obtained from 223 primary care clinics in the Department of Veterans Affairs health care system. Organizational climate was defined using the dimensions of task and relational climate. The association between primary care organizational climate and diabetes processes and intermediate outcomes were estimated for 4,539 patients in a cross-sectional study. All data were collected from administrative datasets. The climate data were drawn from the 2007 VA All Employee Survey, and the outcomes data were collected as part of the VA External Peer Review Program. Climate data were aggregated to the facility level of analysis and merged with patient-level data. Relational climate was related to an increased likelihood of diabetes care process adherence, with significant but small effects for adherence to intermediate outcomes. Task climate was generally not shown to be related to adherence. The role of relational climate in predicting the quality of chronic care was supported. Future research should examine the mediators and moderators of relational climate and further investigate task climate. © Health Research and Educational Trust.

Impacts of Rising Air Temperatures and Emissions Mitigation on Electricity Demand and Supply in the United States. A Multi-Model Comparison

DOE PAGES

McFarland, James; Zhou, Yuyu; Clarke, Leon; ...

2015-06-10

The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Fewer studies have explored the physical impacts of climate change on the power sector. Our present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effectsmore » of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. Moreover, the increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.« less

A Case Study: Climate Change Decision Support for the Apalachicola, Chattahoochee, Flint Basins

NASA Astrophysics Data System (ADS)

Day, G. N.; McMahon, G.; Friesen, N.; Carney, S.

2011-12-01

Riverside Technology, inc. has developed a Climate Change Decision Support System (DSS) to provide water managers with a tool to explore a range of current Global Climate Model (GCM) projections to evaluate their potential impacts on streamflow and the reliability of future water supplies. The system was developed as part of a National Oceanic and Atmospheric Administration (NOAA) Small Business Innovation Research (SBIR) project. The DSS uses downscaled GCM data as input to small-scale watershed models to produce time series of projected undepleted streamflow for various emission scenarios and GCM simulations. Until recently, water managers relied on historical streamflow data for water resources planning. In many parts of the country, great effort has been put into estimating long-term historical undepleted streamflow accounting for regulation, diversions, and return flows to support planning and water rights administration. In some cases, longer flow records have been constructed using paleohydrologic data in an attempt to capture climate variability beyond what is evident during the observed historical record. Now, many water managers are recognizing that historical data may not be representative of an uncertain climate future, and they have begun to explore the use of climate projections in their water resources planning. The Climate Change DSS was developed to support water managers in planning by accounting for both climate variability and potential climate change. In order to use the information for impact analysis, the projected streamflow time series can be exported and substituted for the historical streamflow data traditionally applied in their system operations models for water supply planning. This paper presents a case study in which climate-adjusted flows are coupled with the U.S. Army Corps of Engineers (USACE) ResSim model for the Apalachicola, Chattahoochee, and Flint (ACF) River basins. The study demonstrates how climate scenarios can be used with existing or proposed operating rules to explore the range of potential climate impacts on lake levels, drought trigger frequency, hydropower generation, and low-flow statistics. Initial system implementation of the Climate Change DSS was focused in the State of Colorado working with water supply agencies in the Front Range to assess local water supply vulnerability to climate change. To facilitate national implementation, the system capitalizes on National Weather Service (NWS) watershed models currently used for operational river forecasting. These models are well calibrated and available for the entire country. The system has been extended to include the ACF and the Sacramento River basins because of the importance of the water resources in these basins. Plans are now being made to expand coverage to include the Baltimore-Washington, D.C. water supply area. The DSS is operational and publicly available (www.climatechangedss.com).

Diarrheal Diseases and Climate Change in Cambodia.

PubMed

McIver, Lachlan J; Imai, Chisato; Buettner, Petra G; Gager, Paul; Chan, Vibol S; Hashizume, Masahiro; Iddings, Steven N; Kol, Hero; Raingsey, Piseth P; Lyne, K

2016-10-01

The DRIP-SWICCH (Developing Research and Innovative Policies Specific to the Water-related Impacts of Climate Change on Health) project aimed to increase the resilience of Cambodian communities to the health risks posed by climate change-related impacts on water. This article follows a review of climate change and water-related diseases in Cambodia and presents the results of a time series analysis of monthly weather and diarrheal disease data for 11 provinces. In addition, correlations of diarrheal disease incidence with selected demographic, socioeconomic, and water and sanitation indicators are described, with results suggesting education and literacy may be most protective against disease. The potential impact of climate change on the burden of diarrheal disease in Cambodia is considered, along with the implications of these findings for health systems adaptation.

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.

Are abrupt climate changes predictable?

NASA Astrophysics Data System (ADS)

Ditlevsen, Peter

2013-04-01

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

Large-scale, high-performance and cloud-enabled multi-model analytics experiments in the context of the Earth System Grid Federation

NASA Astrophysics Data System (ADS)

Fiore, S.; Płóciennik, M.; Doutriaux, C.; Blanquer, I.; Barbera, R.; Williams, D. N.; Anantharaj, V. G.; Evans, B. J. K.; Salomoni, D.; Aloisio, G.

2017-12-01

The increased models resolution in the development of comprehensive Earth System Models is rapidly leading to very large climate simulations output that pose significant scientific data management challenges in terms of data sharing, processing, analysis, visualization, preservation, curation, and archiving.Large scale global experiments for Climate Model Intercomparison Projects (CMIP) have led to the development of the Earth System Grid Federation (ESGF), a federated data infrastructure which has been serving the CMIP5 experiment, providing access to 2PB of data for the IPCC Assessment Reports. In such a context, running a multi-model data analysis experiment is very challenging, as it requires the availability of a large amount of data related to multiple climate models simulations and scientific data management tools for large-scale data analytics. To address these challenges, a case study on climate models intercomparison data analysis has been defined and implemented in the context of the EU H2020 INDIGO-DataCloud project. The case study has been tested and validated on CMIP5 datasets, in the context of a large scale, international testbed involving several ESGF sites (LLNL, ORNL and CMCC), one orchestrator site (PSNC) and one more hosting INDIGO PaaS services (UPV). Additional ESGF sites, such as NCI (Australia) and a couple more in Europe, are also joining the testbed. The added value of the proposed solution is summarized in the following: it implements a server-side paradigm which limits data movement; it relies on a High-Performance Data Analytics (HPDA) stack to address performance; it exploits the INDIGO PaaS layer to support flexible, dynamic and automated deployment of software components; it provides user-friendly web access based on the INDIGO Future Gateway; and finally it integrates, complements and extends the support currently available through ESGF. Overall it provides a new "tool" for climate scientists to run multi-model experiments. At the time this contribution is being written, the proposed testbed represents the first implementation of a distributed large-scale, multi-model experiment in the ESGF/CMIP context, joining together server-side approaches for scientific data analysis, HPDA frameworks, end-to-end workflow management, and cloud computing.

The public health impacts of climate change in the former Yugoslav Republic of Macedonia.

PubMed

Kendrovski, Vladimir; Spasenovska, Margarita; Menne, Bettina

2014-06-05

Projected climatic changes for the former Yugoslav Republic of Macedonia for the period 2025-2100 will be most intense in the warmest period of the year with more frequent and more intense heat-waves, droughts and flood events compared with the period 1961-1990. The country has examined their vulnerabilities to climate change and many public health impacts have been projected. A variety of qualitative and quantitative methodologies were used in the assessment: literature reviews, interviews, focus groups, time series and regression analysis, damage and adaptation cost estimation, and scenario-based assessment. Policies and interventions to minimize the risks and development of long-term adaptation strategies have been explored. The generation of a robust evidence base and the development of stakeholder engagement have been used to support the development of an adaptation strategy and to promote adaptive capacity by improving the resilience of public health systems to climate change. Climate change adaptation has been established as a priority within existing national policy instruments. The lessons learnt from the process are applicable to countries considering how best to improve adaptive capacity and resilience of health systems to climate variability and its associated impacts.

Challenges in Incorporating Climate Change Adaptation into Integrated Water Resources Management

NASA Astrophysics Data System (ADS)

Kirshen, P. H.; Cardwell, H.; Kartez, J.; Merrill, S.

2011-12-01

Over the last few decades, integrated water resources management (IWRM), under various names, has become the accepted philosophy for water management in the USA. While much is still to be learned about how to actually carry it out, implementation is slowly moving forward - spurred by both legislation and the demands of stakeholders. New challenges to IWRM have arisen because of climate change. Climate change has placed increased demands on the creativities of planners and engineers because they now must design systems that will function over decades of hydrologic uncertainties that dwarf any previous hydrologic or other uncertainties. Climate and socio-economic monitoring systems must also now be established to determine when the future climate has changed sufficiently to warrant undertaking adaptation. The requirements for taking some actions now and preserving options for future actions as well as the increased risk of social inequities in climate change impacts and adaptation are challenging experts in stakeholder participation. To meet these challenges, an integrated methodology is essential that builds upon scenario analysis, risk assessment, statistical decision theory, participatory planning, and consensus building. This integration will create cross-disciplinary boundaries for these disciplines to overcome.

Energy feedbacks of northern high-latitude ecosystems to the climate system due to reduced snow cover during 20th century warming

USGS Publications Warehouse

Euskirchen, E.S.; McGuire, A.D.; Chapin, F.S.

2007-01-01

The warming associated with changes in snow cover in northern high-latitude terrestrial regions represents an important energy feedback to the climate system. Here, we simulate snow cover-climate feedbacks (i.e. changes in snow cover on atmospheric heating) across the Pan-arctic over two distinct warming periods during the 20th century, 1910-1940 and 1970-2000. We offer evidence that increases in snow cover-climate feedbacks during 1970-2000 were nearly three times larger than during 1910-1940 because the recent snow-cover change occurred in spring, when radiation load is highest, rather than in autumn. Based on linear regression analysis, we also detected a greater sensitivity of snow cover-climate feedbacks to temperature trends during the more recent time period. Pan-arctic vegetation types differed substantially in snow cover-climate feedbacks. Those with a high seasonal contrast in albedo, such as tundra, showed much larger changes in atmospheric heating than did those with a low seasonal contrast in albedo, such as forests, even if the changes in snow-cover duration were similar across the vegetation types. These changes in energy exchange warrant careful consideration in studies of climate change, particularly with respect to associated shifts in vegetation between forests, grasslands, and tundra. ?? 2007 Blackwell Publishing Ltd.

Easier surveillance of climate-related health vulnerabilities through a Web-based spatial OLAP application.

PubMed

Bernier, Eveline; Gosselin, Pierre; Badard, Thierry; Bédard, Yvan

2009-04-03

Climate change has a significant impact on population health. Population vulnerabilities depend on several determinants of different types, including biological, psychological, environmental, social and economic ones. Surveillance of climate-related health vulnerabilities must take into account these different factors, their interdependence, as well as their inherent spatial and temporal aspects on several scales, for informed analyses. Currently used technology includes commercial off-the-shelf Geographic Information Systems (GIS) and Database Management Systems with spatial extensions. It has been widely recognized that such OLTP (On-Line Transaction Processing) systems were not designed to support complex, multi-temporal and multi-scale analysis as required above. On-Line Analytical Processing (OLAP) is central to the field known as BI (Business Intelligence), a key field for such decision-support systems. In the last few years, we have seen a few projects that combine OLAP and GIS to improve spatio-temporal analysis and geographic knowledge discovery. This has given rise to SOLAP (Spatial OLAP) and a new research area. This paper presents how SOLAP and climate-related health vulnerability data were investigated and combined to facilitate surveillance. Based on recent spatial decision-support technologies, this paper presents a spatio-temporal web-based application that goes beyond GIS applications with regard to speed, ease of use, and interactive analysis capabilities. It supports the multi-scale exploration and analysis of integrated socio-economic, health and environmental geospatial data over several periods. This project was meant to validate the potential of recent technologies to contribute to a better understanding of the interactions between public health and climate change, and to facilitate future decision-making by public health agencies and municipalities in Canada and elsewhere. The project also aimed at integrating an initial collection of geo-referenced multi-scale indicators that were identified by Canadian specialists and end-users as relevant for the surveillance of the public health impacts of climate change. This system was developed in a multidisciplinary context involving researchers, policy makers and practitioners, using BI and web-mapping concepts (more particularly SOLAP technologies), while exploring new solutions for frequent automatic updating of data and for providing contextual warnings for users (to minimize the risk of data misinterpretation). According to the project participants, the final system succeeds in facilitating surveillance activities in a way not achievable with today's GIS. Regarding the experiments on frequent automatic updating and contextual user warnings, the results obtained indicate that these are meaningful and achievable goals but they still require research and development for their successful implementation in the context of surveillance and multiple organizations. Surveillance of climate-related health vulnerabilities may be more efficiently supported using a combination of BI and GIS concepts, and more specifically, SOLAP technologies (in that it facilitates and accelerates multi-scale spatial and temporal analysis to a point where a user can maintain an uninterrupted train of thought by focussing on "what" she/he wants (not on "how" to get it) and always obtain instant answers, including to the most complex queries that take minutes or hours with OLTP systems (e.g., aggregated, temporal, comparative)). The developed system respects Newell's cognitive band of 10 seconds when performing knowledge discovery (exploring data, looking for hypotheses, validating models). The developed system provides new operators for easily and rapidly exploring multidimensional data at different levels of granularity, for different regions and epochs, and for visualizing the results in synchronized maps, tables and charts. It is naturally adapted to deal with multiscale indicators such as those used in the surveillance community, as confirmed by this project's end-users.

A Global Assessment on Climate Research Engaging Indigenous Knowledge Systems and Recommendations for Quality Standards of Research Practice in Indigenous Communities

NASA Astrophysics Data System (ADS)

Davíd-Chavez, D. M.; Gavin, M. C.

2017-12-01

Indigenous communities worldwide have maintained their own knowledge systems for millennia informed through careful observation of dynamics of environmental changes. Withstanding centuries of challenges to their rights to maintain and practice these knowledge systems, Indigenous peoples continually speak to a need for quality standards for research in their communities. Although, international and Indigenous peoples' working groups emphasize Indigenous knowledge systems and the communities who hold them as critical resources for understanding and adapting to climate change, there has yet to be a comprehensive, evidence based analysis into how diverse knowledge systems are integrated in scientific studies. Do current research practices challenge or support Indigenous communities in their efforts to maintain and appropriately apply their knowledge systems? This study addresses this question using a systematic literature review and meta-analysis assessing levels of Indigenous community participation and decision-making in all stages of the research process (initiation, design, implementation, analysis, dissemination). Assessment is based on reported quality indicators such as: outputs that serve the community, ethical guidelines in practice (free, prior, and informed consent and intellectual property rights), and community access to findings. These indicators serve to identify patterns between levels of community participation and quality standards in practice. Meta-analysis indicates most climate studies practice an extractive model in which Indigenous knowledge systems are co-opted with minimal participation or decision-making authority from communities who hold them. Few studies report outputs that directly serve Indigenous communities, ethical guidelines in practice, or community access to findings. Studies reporting the most quality indicators were initiated in mutual agreement between Indigenous communities and outside researchers or by communities themselves. This study also draws from the researcher's experiences as an Indigenous scientist and includes recommendations for quality research practice. This global assessment provides an evidence base to inform our understanding of broader impacts related to research design.

An early warning system for high climate sensitivity? (Invited)

NASA Astrophysics Data System (ADS)

Pierrehumbert, R.

2010-12-01

The scientific case for the clear and present danger of global warming has been unassailable at least since the release of the Charney Report more than thirty years ago, if not longer. While prompt action to begin decarbonizing energy systems could still head off much of the potential warming, it is distinctly possible that emissions will continue unabated in the coming decades, leading to a doubling or more of pre-industrial carbon dioxide concentrations. At present, we are in the unenviable position of not even knowing how bad things will get if this scenario comes to pass, because of the uncertainty in climate sensitivity. If climate sensitivity is high, then the consequences will be dire, perhaps even catastrophic. As the world continues to warm in response to continued carbon dioxide emissions, will we at least be able to monitor the climate and provide an early warning that the planet is on a high-sensitivity track, if such turns out to be the case? At what point will we actually know the climate sensitivity? It has long been recognized that the prime contributor to uncertainty in climate sensitivity is uncertainty in cloud feedbacks. Study of paleoclimate and climate of the past century has not been able to resolve which models do cloud feedback most correctly, because of uncertainties in radiative forcing. In this talk, I will discuss monitoring requirements, and analysis techniques, that might have the potential to determine which climate models most faithfully represent climate feedbacks, and thus determine which models provide the best estimate of climate sensitivity. The endeavor is complicated by the distinction between transient climate response and equilibrium climate sensitivity. I will discuss the particular challenges posed by this issue, particularly in light of recent indications that the pattern of ocean heat storage may lead to different cloud feedbacks in the transient warming stage than apply once the system has reached equilibrium. Apart from this problem, the transient nature of climate response driven by increasing CO2 requires careful monitoring of ocean heat storage as well as top-of-atmosphere radiative budgets, if climate sensitivity is to be estimated. Water vapor feedback is not considered as uncertain as cloud feedback, but there is still a considerable potential for surprises. I will discuss microwave monitoring requirements for tracking water vapor feedback. At the other extreme, the longer term feedbacks that contribute to Earth System Sensitivity are even more uncertain than cloud feedbacks, particularly with regard to the terrestrial carbon cycle. Prospects for obtaining an early warning of a PETM-type organic carbon release seem bleak. Finally, I will discuss the particular challenge of obtaining an early warning of high climate sensitivity in the case that the climate system has a bifurcation.

Assessing Current State Science Teaching and Learning Standards for Ability to Achieve Climate Science Literacy

NASA Astrophysics Data System (ADS)

Busch, K. C.

2012-12-01

Even though there exists a high degree of consensus among scientists about climate change, doubt has actually increased over the last five years within the general U.S. public. In 2006, 79% of those polled agreed that there is evidence for global warming, while only 59% agreed in 2010 (Pew Research Center, 2010). The source for this doubt can be partially attributed to lack of knowledge. Formal education is one mechanism that potentially can address inadequate public understanding as school is the primary place where students - and future citizens - learn about the climate. In a joint effort, several governmental agencies, non-governmental organizations, scientists and educators have created a framework called The Essential Principles of Climate Science Literacy, detailing seven concepts that are deemed vital for individuals and communities to understand Earth's climate system (USGCRP, 2009). Can students reach climate literacy - as defined by these 7 concepts - if they are taught using a curriculum based on the current state standards? To answer this question, the K-12 state science teaching and learning standards for Texas and California - two states that heavily influence nation-wide textbook creation - were compared against the Essential Principles. The data analysis consisted of two stages, looking for: 1) direct reference to "climate" and "climate change" and 2) indirect reference to the 7 Essential Principles through axial coding. The word "climate" appears in the California K-12 science standards 4 times and in the Texas standards 7 times. The word "climate change" appears in the California and Texas standards only 3 times each. Indirect references to the 7 Essential Principles of climate science literacy were more numerous. Broadly, California covered 6 of the principles while Texas covered all 7. In looking at the 7 principles, the second one "Climate is regulated by complex interactions among component of the Earth system" was the most substantively addressed. Least covered were number 6 "Human activities are impacting the climate system" and number 7 "Climate change will have consequences for the Earth system and human lives." Most references, either direct or indirect, occurred in the high school standards for earth science, a class not required for graduation in either state. This research points to the gaps between what the 7 Essential Principles of Climate Literacy defines as essential knowledge and what students may learn in their K-12 science classes. Thus, the formal system does not seem to offer an experience which can potentially develop a more knowledgeable citizenry who will be able to make wise personal and policy decisions about climate change, falling short of the ultimate goal of achieving widespread climate literacy. Especially troubling was the sparse attention to the principles addressing the human connection to the climate - principles number 6 and 7. If climate literate citizens are to make "wise personal and policy decisions" (USGCRP, 2009), these two principles especially are vital. This research, therefore, has been valuable for identifying current shortcomings in state standards.

Web-based Visual Analytics for Extreme Scale Climate Science

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

Steed, Chad A; Evans, Katherine J; Harney, John F

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less

Assessing Flood Risk at Nuclear Power Plants with an Uncertain Climate

NASA Astrophysics Data System (ADS)

Wigmosta, M. S.; Vail, L. W.

2011-12-01

In 2010 a tsunami severely damaged the Fukushima Dai-ichi Nuclear Power Plant in Japan. As a result, the U.S. Nuclear Regulatory Commission directed that a systematic and methodical review of Commission processes and regulations be performed to determine whether the agency should make additional improvements to its regulatory system and to make recommendations to the Commission. Two of the recommendations of the Task Force created to inform the Commission were: establish a logical, systematic, and coherent regulatory framework for adequate protection that appropriately balances defense-in-depth and risk considerations and that the NRC require licensees to reevaluate and upgrade as necessary the design-basis flooding protection of structures, systems, and components for each operating reactor. These recommendations came at the same time as technical discussions about updating approaches to evaluate flood hazard were underway. These discussions included: consideration of climate nonstationarity in flood assessments; transitioning from PMP/PMF assessments to probabilistic flood analyses to better align with risk-informed decision making; and systematic consideration of combined events in flood risk analysis. There is no scientific basis to assume that shifts in long-term mean precipitation and temperature (such as is commonly derived from climate models) relate to flood probability. Flood mechanisms are often more complex and reflect climate pattern anomalies more than mean annual shifts. Instead of discounting historical data due to climatic nonstationarity, it is important to better understand the climate patterns that have triggered floods in the past and to look to climate forecasts to understand the likely changes in the frequency of those historical climate patterns with climate change. It is equally important to have a better understanding of whether climate change will result in flood-generating climate systems heretofore unknown in the particular locale. This presentation will provide a roadmap to ensuring that the flood hazards of existing and future nuclear power plants are well defined.

Recovery Migration after Hurricanes Katrina and Rita: Spatial Concentration and Intensification in the Migration System

PubMed Central

Fussell, Elizabeth; DeWaard, Jack

2015-01-01

Changes in the human migration systems of Hurricane Katrina- and Rita-affected Gulf of Mexico coastline counties provide an example of how climate change may affect coastal populations. Crude climate change models predict a mass migration of “climate refugees,” but an emerging literature on environmental migration suggests most migration will be short-distance and short-duration within existing migration systems, with implications for the population recovery of disaster-struck places. In this research, we derive a series of hypotheses on recovery migration predicting how the migration system of hurricane-affected coastline counties in the Gulf of Mexico was likely to have changed between the pre-disaster and the recovery periods. We test these hypotheses using data from the Internal Revenue Service on annual county-level migration flows, comparing the recovery period migration system (2007–2009) to the pre-disaster period (1999–2004). By observing county-to-county ties and flows we find that recovery migration was strong, as the migration system of the disaster-affected coastline counties became more spatially concentrated while flows within it intensified and became more urbanized. Our analysis demonstrates how migration systems are likely to be affected by the more intense and frequent storms anticipated by climate change scenarios with implications for the population recovery of disaster-affected places. PMID:26084982

Reducing uncertainty in Climate Response Time Scale by Bayesian Analysis of the 8.2 ka event

NASA Astrophysics Data System (ADS)

Lorenz, A.; Held, H.; Bauer, E.; Schneider von Deimling, T.

2009-04-01

We analyze the possibility of uncertainty reduction in Climate Response Time Scale by utilizing Greenland ice-core data that contain the 8.2 ka event within a Bayesian model-data intercomparison with the Earth system model of intermediate complexity, CLIMBER-2.3. Within a stochastic version of the model it has been possible to mimic the 8.2 ka event within a plausible experimental setting and with relatively good accuracy considering the timing of the event in comparison to other modeling exercises [1]. The simulation of the centennial cold event is effectively determined by the oceanic cooling rate which depends largely on the ocean diffusivity described by diffusion coefficients of relatively wide uncertainty ranges. The idea now is to discriminate between the different values of diffusivities according to their likelihood to rightly represent the duration of the 8.2 ka event and thus to exploit the paleo data to constrain uncertainty in model parameters in analogue to [2]. Implementing this inverse Bayesian Analysis with this model the technical difficulty arises to establish the related likelihood numerically in addition to the uncertain model parameters: While mainstream uncertainty analyses can assume a quasi-Gaussian shape of likelihood, with weather fluctuating around a long term mean, the 8.2 ka event as a highly nonlinear effect precludes such an a priori assumption. As a result of this study [3] the Bayesian Analysis showed a reduction of uncertainty in vertical ocean diffusivity parameters of factor 2 compared to prior knowledge. This learning effect on the model parameters is propagated to other model outputs of interest; e.g. the inverse ocean heat capacity, which is important for the dominant time scale of climate response to anthropogenic forcing which, in combination with climate sensitivity, strongly influences the climate systems reaction for the near- and medium-term future. 1 References [1] E. Bauer, A. Ganopolski, M. Montoya: Simulation of the cold climate event 8200 years ago by meltwater outburst from lake Agassiz. Paleoceanography 19:PA3014, (2004) [2] T. Schneider von Deimling, H. Held, A. Ganopolski, S. Rahmstorf, Climate sensitivity estimated from ensemble simulations of glacial climates, Climate Dynamics 27, 149-163, DOI 10.1007/s00382-006-0126-8 (2006). [3] A. Lorenz, Diploma Thesis, U Potsdam (2007).

Forest management under climatic and social uncertainty: trade-offs between reducing climate change impacts and fostering adaptive capacity.

PubMed

Seidl, Rupert; Lexer, Manfred J

2013-01-15

The unabated continuation of anthropogenic greenhouse gas emissions and the lack of an international consensus on a stringent climate change mitigation policy underscore the importance of adaptation for coping with the all but inevitable changes in the climate system. Adaptation measures in forestry have particularly long lead times. A timely implementation is thus crucial for reducing the considerable climate vulnerability of forest ecosystems. However, since future environmental conditions as well as future societal demands on forests are inherently uncertain, a core requirement for adaptation is robustness to a wide variety of possible futures. Here we explicitly address the roles of climatic and social uncertainty in forest management, and tackle the question of robustness of adaptation measures in the context of multi-objective sustainable forest management (SFM). We used the Austrian Federal Forests (AFF) as a case study, and employed a comprehensive vulnerability assessment framework based on ecosystem modeling, multi-criteria decision analysis, and practitioner participation. We explicitly considered climate uncertainty by means of three climate change scenarios, and accounted for uncertainty in future social demands by means of three societal preference scenarios regarding SFM indicators. We found that the effects of climatic and social uncertainty on the projected performance of management were in the same order of magnitude, underlining the notion that climate change adaptation requires an integrated social-ecological perspective. Furthermore, our analysis of adaptation measures revealed considerable trade-offs between reducing adverse impacts of climate change and facilitating adaptive capacity. This finding implies that prioritization between these two general aims of adaptation is necessary in management planning, which we suggest can draw on uncertainty analysis: Where the variation induced by social-ecological uncertainty renders measures aiming to reduce climate change impacts statistically insignificant (i.e., for approximately one third of the investigated management units of the AFF case study), fostering adaptive capacity is suggested as the preferred pathway for adaptation. We conclude that climate change adaptation needs to balance between anticipating expected future conditions and building the capacity to address unknowns and surprises. Copyright © 2012 Elsevier Ltd. All rights reserved.

Opportunities and Examples for Integration of Socio-environmental Approaches to Support Climate-informed Decisions

NASA Astrophysics Data System (ADS)

Kenney, M. A.

2014-12-01

Climate and environmental decisions require science that couples human and natural systems to quantify or articulate the observed physical, natural, and societal changes or likely consequences of different decision options. Despite the need for such policy-relevant research, multidisciplinary collaborations can be wrought with challenges of data integration, model interoperability, and communication across disciplinary divides. In this talk, I will present several examples where I have collaborated with colleagues from the physical, natural, and social sciences to develop novel, actionable science to inform decision-making. Specifically, I will discuss a cost analysis of water and sediment diversions to optimize land building in the Mississippi River delta (winner of American Geophysical Union Water Resources Research Editor's Choice Award 2014) and the development of a National Climate Indicator System that uses knowledge across the physical, natural, and social sciences to establish an end-to-end indicator system of climate changes, impacts, vulnerabilities, and responses. The latter project is in the process of moving from research to operations, an additional challenge and opportunity, as we work with the U.S. Global Change Research Program and their affiliated Federal agencies to establish it beyond the research prototype. Using these examples, I will provide some lessons learned that would have general applicability to socio-environmental research collaborations and integration of data, models, and information systems to support climate and environmental decision-making.

Scenario Analysis With Economic-Energy Systems Models Coupled to Simple Climate Models

NASA Astrophysics Data System (ADS)

Hanson, D. A.; Kotamarthi, V. R.; Foster, I. T.; Franklin, M.; Zhu, E.; Patel, D. M.

2008-12-01

Here, we compare two scenarios based on Stanford University's Energy Modeling Forum Study 22 on global cooperative and non-cooperative climate policies. In the former, efficient transition paths are implemented including technology Research and Development effort, energy conservation programs, and price signals for greenhouse gas (GHG) emissions. In the non-cooperative case, some countries try to relax their regulations and be free riders. Total emissions and costs are higher in the non-cooperative scenario. The simulations, including climate impacts, run to the year 2100. We use the Argonne AMIGA-MARS economic-energy systems model, the Texas AM University's Forest and Agricultural Sector Optimization Model (FASOM), and the University of Illinois's Integrated Science Assessment Model (ISAM), with offline coupling between the FASOM and AMIGA-MARS and an online coupling between AMIGA-MARS and ISAM. This set of models captures the interaction of terrestrial systems, land use, crops and forests, climate change, human activity, and energy systems. Our scenario simulations represent dynamic paths over which all the climate, terrestrial, economic, and energy technology equations are solved simultaneously Special attention is paid to biofuels and how they interact with conventional gasoline/diesel fuel markets. Possible low-carbon penetration paths are based on estimated costs for new technologies, including cellulosic biomass, coal-to-liquids, plug-in electric vehicles, solar and nuclear energy. We explicitly explore key uncertainties that affect mitigation and adaptation scenarios.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

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

PubMed

Elliott, Grant P

2012-07-01

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

Progress, decline, and the public uptake of climate science.

PubMed

Rudiak-Gould, Peter

2014-02-01

Previous research has sought to explain public perception of climate change science in terms of individuals' "prior commitment" to such ideological stances as just-world belief, system justification, and liberalism/conservatism. One type of prior commitment that has received little formal attention in the literature is narratives of the moral trajectory of society. A theory of climate science uptake based on beliefs in societal progress or decline is more easily portable to non-Western settings; in a case study of global warming attitudes in the Marshall Islands, trajectory narratives indeed account for public belief, concern, blame, and response more aptly than existing theories, and accord well with qualitative analysis of Marshallese climate change discourse. In Western settings, progress/decline narratives may explain much of the variation in climate change attitudes previously accounted for by other ideological variables, promising a more penetrating explanation for the divergence of climate change attitudes within and between societies.

A platform to integrate climate information and rural telemedicine in Malawi

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

Water and Power Systems Co-optimization under a High Performance Computing Framework

NASA Astrophysics Data System (ADS)

Xuan, Y.; Arumugam, S.; DeCarolis, J.; Mahinthakumar, K.

2016-12-01

Water and energy systems optimizations are traditionally being treated as two separate processes, despite their intrinsic interconnections (e.g., water is used for hydropower generation, and thermoelectric cooling requires a large amount of water withdrawal). Given the challenges of urbanization, technology uncertainty and resource constraints, and the imminent threat of climate change, a cyberinfrastructure is needed to facilitate and expedite research into the complex management of these two systems. To address these issues, we developed a High Performance Computing (HPC) framework for stochastic co-optimization of water and energy resources to inform water allocation and electricity demand. The project aims to improve conjunctive management of water and power systems under climate change by incorporating improved ensemble forecast models of streamflow and power demand. First, by downscaling and spatio-temporally disaggregating multimodel climate forecasts from General Circulation Models (GCMs), temperature and precipitation forecasts are obtained and input into multi-reservoir and power systems models. Extended from Optimus (Optimization Methods for Universal Simulators), the framework drives the multi-reservoir model and power system model, Temoa (Tools for Energy Model Optimization and Analysis), and uses Particle Swarm Optimization (PSO) algorithm to solve high dimensional stochastic problems. The utility of climate forecasts on the cost of water and power systems operations is assessed and quantified based on different forecast scenarios (i.e., no-forecast, multimodel forecast and perfect forecast). Analysis of risk management actions and renewable energy deployments will be investigated for the Catawba River basin, an area with adequate hydroclimate predicting skill and a critical basin with 11 reservoirs that supplies water and generates power for both North and South Carolina. Further research using this scalable decision supporting framework will provide understanding and elucidate the intricate and interdependent relationship between water and energy systems and enhance the security of these two critical public infrastructures.

Network access to PCDS (SPAN, ESN, SESNET, ARPANET)

NASA Technical Reports Server (NTRS)

Green, J.

1986-01-01

One of the major goals of the National Space Science Data Center is to increase access to NASA data systems by enhancing networking activities. The activities are centered around three basic networking systems: the Space Physics Analysis Network (SPAN); the Earth Science Network (ESN); and the NASA Packet Switched System (NPSS). Each system is described, linkages among systems are explained, and future plans are announced. The inclusion of several new climate nodes on SPAN or ESN are also mentioned. Presently, the Pilot Climate Data System is accessible through SPAN and will be accessible through NPSS by summer and ESN by the end of 1986. Ambitious plans for implementation are underway. The implementation of these plans will represent a major advance in the utilization and accessibility of data worldwide.

Integrated Information Systems Across the Weather-Climate Continuum

NASA Astrophysics Data System (ADS)

Pulwarty, R. S.; Higgins, W.; Nierenberg, C.; Trtanj, J.

2015-12-01

The increasing demand for well-organized (integrated) end-to-end research-based information has been highlighted in several National Academy studies, in IPCC Reports (such as the SREX and Fifth Assessment) and by public and private constituents. Such information constitutes a significant component of the "environmental intelligence" needed to address myriad societal needs for early warning and resilience across the weather-climate continuum. The next generation of climate research in service to the nation requires an even more visible, authoritative and robust commitment to scientific integration in support of adaptive information systems that address emergent risks and inform longer-term resilience strategies. A proven mechanism for resourcing such requirements is to demonstrate vision, purpose, support, connection to constituencies, and prototypes of desired capabilities. In this presentation we will discuss efforts at NOAA, and elsewhere, that: Improve information on how changes in extremes in key phenomena such as drought, floods, and heat stress impact management decisions for resource planning and disaster risk reduction Develop regional integrated information systems to address these emergent challenges, that integrate observations, monitoring and prediction, impacts assessments and scenarios, preparedness and adaptation, and coordination and capacity-building. Such systems, as illustrated through efforts such as NIDIS, have strengthened the integration across the foundational research enterprise (through for instance, RISAs, Modeling Analysis Predictions and Projections) by increasing agility for responding to emergent risks. The recently- initiated Climate Services Information System, in support of the WMO Global Framework for Climate Services draws on the above models and will be introduced during the presentation.

The climate4impact platform: Providing, tailoring and facilitating climate model data access

NASA Astrophysics Data System (ADS)

Pagé, Christian; Pagani, Andrea; Plieger, Maarten; Som de Cerff, Wim; Mihajlovski, Andrej; de Vreede, Ernst; Spinuso, Alessandro; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Vega, Manuel; Cofiño, Antonio; d'Anca, Alessandro; Fiore, Sandro; Kolax, Michael

2017-04-01

One of the main objectives of climate4impact is to provide standardized web services and tools that are reusable in other portals. These services include web processing services, web coverage services and web mapping services (WPS, WCS and WMS). Tailored portals can be targeted to specific communities and/or countries/regions while making use of those services. Easier access to climate data is very important for the climate change impact communities. To fulfill this objective, the climate4impact (http://climate4impact.eu/) web portal and services has been developed, targeting climate change impact modellers, impact and adaptation consultants, as well as other experts using climate change data. It provides to users harmonized access to climate model data through tailored services. It features static and dynamic documentation, Use Cases and best practice examples, an advanced search interface, an integrated authentication and authorization system with the Earth System Grid Federation (ESGF), a visualization interface with ADAGUC web mapping tools. In the latest version, statistical downscaling services, provided by the Santander Meteorology Group Downscaling Portal, were integrated. An innovative interface to integrate statistical downscaling services will be released in the upcoming version. The latter will be a big step in bridging the gap between climate scientists and the climate change impact communities. The climate4impact portal builds on the infrastructure of an international distributed database that has been set to disseminate the results from the global climate model results of the Coupled Model Intercomparison project Phase 5 (CMIP5). This database, the ESGF, is an international collaboration that develops, deploys and maintains software infrastructure for the management, dissemination, and analysis of climate model data. The European FP7 project IS-ENES, Infrastructure for the European Network for Earth System modelling, supports the European contribution to ESGF and contributes to the ESGF open source effort, notably through the development of search, monitoring, quality control, and metadata services. In its second phase, IS-ENES2 supports the implementation of regional climate model results from the international Coordinated Regional Downscaling Experiments (CORDEX). These services were extended within the European FP7 Climate Information Portal for Copernicus (CLIPC) project, and some could be later integrated into the European Copernicus platform.

Desert dust and anthropogenic aerosol interactions in the Community Climate System Model coupled-carbon-climate model

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

Mahowald, Natalie; Rothenberg, D.; Lindsay, Keith

2011-02-01

Coupled-carbon-climate simulations are an essential tool for predicting the impact of human activity onto the climate and biogeochemistry. Here we incorporate prognostic desert dust and anthropogenic aerosols into the CCSM3.1 coupled carbon-climate model and explore the resulting interactions with climate and biogeochemical dynamics through a series of transient anthropogenic simulations (20th and 21st centuries) and sensitivity studies. The inclusion of prognostic aerosols into this model has a small net global cooling effect on climate but does not significantly impact the globally averaged carbon cycle; we argue that this is likely to be because the CCSM3.1 model has a small climatemore » feedback onto the carbon cycle. We propose a mechanism for including desert dust and anthropogenic aerosols into a simple carbon-climate feedback analysis to explain the results of our and previous studies. Inclusion of aerosols has statistically significant impacts on regional climate and biogeochemistry, in particular through the effects on the ocean nitrogen cycle and primary productivity of altered iron inputs from desert dust deposition.« less

The underestimated potential of solar energy to mitigate climate change

NASA Astrophysics Data System (ADS)

Creutzig, Felix; Agoston, Peter; Goldschmidt, Jan Christoph; Luderer, Gunnar; Nemet, Gregory; Pietzcker, Robert C.

2017-09-01

The Intergovernmental Panel on Climate Change's fifth assessment report emphasizes the importance of bioenergy and carbon capture and storage for achieving climate goals, but it does not identify solar energy as a strategically important technology option. That is surprising given the strong growth, large resource, and low environmental footprint of photovoltaics (PV). Here we explore how models have consistently underestimated PV deployment and identify the reasons for underlying bias in models. Our analysis reveals that rapid technological learning and technology-specific policy support were crucial to PV deployment in the past, but that future success will depend on adequate financing instruments and the management of system integration. We propose that with coordinated advances in multiple components of the energy system, PV could supply 30-50% of electricity in competitive markets.

Recent climatic events controlling the hydrological and the aquifer dynamics at arid areas: The case of Huasco River watershed, northern Chile.

PubMed

Salas, I; Herrera, C; Luque, J A; Delgado, J; Urrutia, J; Jordan, T

2016-11-15

The investigation assesses the influence of recent climatic events in the water resources and the aquifer dynamics in the Huasco watershed by means of the analysis of precipitation, streamflow and piezometric levels during the last 50years. These hydrological and hydrogeological parameters were evaluated by an exploratory geostatistical analysis (semivariogram) and a spectral analysis (periodogram). Specifically, the hydrological and hydrogeological data analyses are organized according to three sub-basins, the Del Carmen River (Section I), the El Tránsito River (Section II), and the Huasco River (Section III). Data ranges for rainfall are from 1961 to 2015, for streamflow from 1964 to 2015, and for groundwater levels from 1969 to 2014, available from Water Authority of Chile. The analyses allowed the identification of cycles in the hydrological and hydrogeological records. The study area is located in a transient climatic fringe where the convergence of several climatic systems can be identified in the hydrological and hydrogeological records. Results indicate that the nival areas and the small glaciers are especially important to the recharge processes in the Huasco watershed during the spring-summer snowmelting. Water reservoirs in the main aquifer (Section III) and in the Santa Juana dam are highly sensitive to ENSO oscillation climatic patterns. The main climatic events that control this record are the El Niño and La Niña events. In addition, the climatic influence of the westerlies and the SE extratropical moisture were also identified. Spectral analysis identified the presence of a 22.9-yearcycle in piezometric levels of the alluvial aquifer of the Huasco River. This cycle is consistent with the 22-year Hale solar cycle, suggesting the existence of a solar forcing controlling the ENSO oscillations. Moreover, semivariogram and spectral analysis identified a 10.65-yearcycle and a 9.2-yearcycle in groundwater, respectively, which were attributed to the strong mode of ENSO oscillations. Copyright © 2016 Elsevier B.V. All rights reserved.

The Ophidia framework: toward cloud-based data analytics for climate change

NASA Astrophysics Data System (ADS)

Fiore, Sandro; D'Anca, Alessandro; Elia, Donatello; Mancini, Marco; Mariello, Andrea; Mirto, Maria; Palazzo, Cosimo; Aloisio, Giovanni

2015-04-01

The Ophidia project is a research effort on big data analytics facing scientific data analysis challenges in the climate change domain. It provides parallel (server-side) data analysis, an internal storage model and a hierarchical data organization to manage large amount of multidimensional scientific data. The Ophidia analytics platform provides several MPI-based parallel operators to manipulate large datasets (data cubes) and array-based primitives to perform data analysis on large arrays of scientific data. The most relevant data analytics use cases implemented in national and international projects target fire danger prevention (OFIDIA), interactions between climate change and biodiversity (EUBrazilCC), climate indicators and remote data analysis (CLIP-C), sea situational awareness (TESSA), large scale data analytics on CMIP5 data in NetCDF format, Climate and Forecast (CF) convention compliant (ExArch). Two use cases regarding the EU FP7 EUBrazil Cloud Connect and the INTERREG OFIDIA projects will be presented during the talk. In the former case (EUBrazilCC) the Ophidia framework is being extended to integrate scalable VM-based solutions for the management of large volumes of scientific data (both climate and satellite data) in a cloud-based environment to study how climate change affects biodiversity. In the latter one (OFIDIA) the data analytics framework is being exploited to provide operational support regarding processing chains devoted to fire danger prevention. To tackle the project challenges, data analytics workflows consisting of about 130 operators perform, among the others, parallel data analysis, metadata management, virtual file system tasks, maps generation, rolling of datasets, import/export of datasets in NetCDF format. Finally, the entire Ophidia software stack has been deployed at CMCC on 24-nodes (16-cores/node) of the Athena HPC cluster. Moreover, a cloud-based release tested with OpenNebula is also available and running in the private cloud infrastructure of the CMCC Supercomputing Centre.

Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT)

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

Williams, Dean N.; Silva, Claudio

2013-09-30

For the past three years, a large analysis and visualization effort—funded by the Department of Energy’s Office of Biological and Environmental Research (BER), the National Aeronautics and Space Administration (NASA), and the National Oceanic and Atmospheric Administration (NOAA)—has brought together a wide variety of industry-standard scientific computing libraries and applications to create Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT) to serve the global climate simulation and observational research communities. To support interactive analysis and visualization, all components connect through a provenance application–programming interface to capture meaningful history and workflow. Components can be loosely coupled into the framework for fast integrationmore » or tightly coupled for greater system functionality and communication with other components. The overarching goal of UV-CDAT is to provide a new paradigm for access to and analysis of massive, distributed scientific data collections by leveraging distributed data architectures located throughout the world. The UV-CDAT framework addresses challenges in analysis and visualization and incorporates new opportunities, including parallelism for better efficiency, higher speed, and more accurate scientific inferences. Today, it provides more than 600 users access to more analysis and visualization products than any other single source.« less

Analyzing the Response of Climate Perturbations to (Tropical) Cyclones using the WRF Model

NASA Astrophysics Data System (ADS)

Tewari, M.; Mittal, R.; Radhakrishnan, C.; Cipriani, J.; Watson, C.

2015-12-01

An analysis of global climate models shows considerable changes in the intensity and characteristics of future, warm climate cyclones. At regional scales, deviations in cyclone characteristics are often derived using idealized perturbations in the humidity, temperature and surface conditions. In this work, a more realistic approach is adopted by applying climate perturbations from the Community Climate System Model (CCSM4) to ERA-interim data to generate the initial and boundary conditions for future climate simulations. The climate signal perturbations are generated from the differences in 21 years of mean data from CCSM4 with representative concentration pathways (RCP8.5) for the periods: (a) 2070-2090 (future climate), (b) 2025-2045 (near-future climate) and (c) 1985-2005 (current climate). Four individual cyclone cases are simulated with and without climate perturbations using the Weather Research and Forecasting model with a nested configuration. Each cyclone is characterized by variations in intensity, landfall location, precipitation and societal damage. To calculate societal damage, we use the recently introduced Cyclone Damage Potential (CDP) index evolved from the Willis Hurricane Index (WHI). As CDP has been developed for general societal applications, this work should provide useful insights for resilience analyses and industry (e.g., re-insurance).

Linking Climate Risk, Policy Networks and Adaptation Planning in Public Lands

NASA Astrophysics Data System (ADS)

Lubell, M.; Schwartz, M.; Peters, C.

2014-12-01

Federal public land management agencies in the United States have engaged a variety of planning efforts to address climate adaptation. A major goal of these efforts is to build policy networks that enable land managers to access information and expertise needed for responding to local climate risks. This paper investigates whether the perceived and modeled climate risk faced by different land managers is leading to larger networks or more participating in climate adaptation. In theory, the benefits of climate planning networks are larger when land managers are facing more potential changes. The basic hypothesis is tested with a survey of public land managers from hundreds of local and regional public lands management units in the Southwestern United States, as well as other stakeholders involved with climate adaptation planning. All survey respondents report their perceptions of climate risk along a variety of dimensions, as well as their participation in climate adaptation planning and information sharing networks. For a subset of respondents, we have spatially explicity GIS data about their location, which will be linked with downscaled climate model data. With the focus on climate change, the analysis is a subset of the overall idea of linking social and ecological systems.

Modeling the Near-Term Risk of Climate Uncertainty: Interdependencies among the U.S. States

NASA Astrophysics Data System (ADS)

Lowry, T. S.; Backus, G.; Warren, D.

2010-12-01

Decisions made to address climate change must start with an understanding of the risk of an uncertain future to human systems, which in turn means understanding both the consequence as well as the probability of a climate induced impact occurring. In other words, addressing climate change is an exercise in risk-informed policy making, which implies that there is no single correct answer or even a way to be certain about a single answer; the uncertainty in future climate conditions will always be present and must be taken as a working-condition for decision making. In order to better understand the implications of uncertainty on risk and to provide a near-term rationale for policy interventions, this study estimates the impacts from responses to climate change on U.S. state- and national-level economic activity by employing a risk-assessment methodology for evaluating uncertain future climatic conditions. Using the results from the Intergovernmental Panel on Climate Change’s (IPCC) Fourth Assessment Report (AR4) as a proxy for climate uncertainty, changes in hydrology over the next 40 years were mapped and then modeled to determine the physical consequences on economic activity and to perform a detailed 70-industry analysis of the economic impacts among the interacting lower-48 states. The analysis determines industry-level effects, employment impacts at the state level, interstate population migration, consequences to personal income, and ramifications for the U.S. trade balance. The conclusions show that the average risk of damage to the U.S. economy from climate change is on the order of $1 trillion over the next 40 years, with losses in employment equivalent to nearly 7 million full-time jobs. Further analysis shows that an increase in uncertainty raises this risk. This paper will present the methodology behind the approach, a summary of the underlying models, as well as the path forward for improving the approach.

Hands-on approach to teaching Earth system sciences using a information-computational web-GIS portal "Climate"

NASA Astrophysics Data System (ADS)

Gordova, Yulia; Gorbatenko, Valentina; Martynova, Yulia; Shulgina, Tamara

2014-05-01

A problem of making education relevant to the workplace tasks is a key problem of higher education because old-school training programs are not keeping pace with the rapidly changing situation in the professional field of environmental sciences. A joint group of specialists from Tomsk State University and Siberian center for Environmental research and Training/IMCES SB RAS developed several new courses for students of "Climatology" and "Meteorology" specialties, which comprises theoretical knowledge from up-to-date environmental sciences with practical tasks. To organize the educational process we use an open-source course management system Moodle (www.moodle.org). It gave us an opportunity to combine text and multimedia in a theoretical part of educational courses. The hands-on approach is realized through development of innovative trainings which are performed within the information-computational platform "Climate" (http://climate.scert.ru/) using web GIS tools. These trainings contain practical tasks on climate modeling and climate changes assessment and analysis and should be performed using typical tools which are usually used by scientists performing such kind of research. Thus, students are engaged in n the use of modern tools of the geophysical data analysis and it cultivates dynamic of their professional learning. The hands-on approach can help us to fill in this gap because it is the only approach that offers experience, increases students involvement, advance the use of modern information and communication tools. The courses are implemented at Tomsk State University and help forming modern curriculum in Earth system science area. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grants numbers 13-05-12034 and 14-05-00502.

Fuel cell on-site integrated energy system parametric analysis of a residential complex

NASA Technical Reports Server (NTRS)

Simons, S. N.

1977-01-01

A parametric energy-use analysis was performed for a large apartment complex served by a fuel cell on-site integrated energy system (OS/IES). The variables parameterized include operating characteristics for four phosphoric acid fuel cells, eight OS/IES energy recovery systems, and four climatic locations. The annual fuel consumption for selected parametric combinations are presented and a breakeven economic analysis is presented for one parametric combination. The results show fuel cell electrical efficiency and system component choice have the greatest effect on annual fuel consumption; fuel cell thermal efficiency and geographic location have less of an effect.

The role of country-to-region assignments in global integrated modeling of energy, agriculture, land use, and climate

NASA Astrophysics Data System (ADS)

Kyle, P.; Patel, P.; Calvin, K. V.

2014-12-01

Global integrated assessment models used for understanding the linkages between the future energy, agriculture, and climate systems typically represent between 8 and 30 geopolitical macro-regions, balancing the benefits of geographic resolution with the costs of additional data collection, processing, analysis, and computing resources. As these models are continually being improved and updated in order to address new questions for the research and policy communities, it is worth examining the consequences of the country-to-region mapping schemes used for model results. This study presents an application of a data processing system built for the GCAM integrated assessment model that allows any country-to-region assignments, with a minimum of four geopolitical regions and a maximum of 185. We test ten different mapping schemes, including the specific mappings used in existing major integrated assessment models. We also explore the impacts of clustering nations into regions according to the similarity of the structure of each nation's energy and agricultural sectors, as indicated by multivariate analysis. Scenarios examined include a reference scenario, a low-emissions scenario, and scenarios with agricultural and buildings sector climate change impacts. We find that at the global level, the major output variables (primary energy, agricultural land use) are surprisingly similar regardless of regional assignments, but at finer geographic scales, differences are pronounced. We suggest that enhancing geographic resolution is advantageous for analysis of climate impacts on the buildings and agricultural sectors, due to the spatial heterogeneity of these drivers.

The analysis and assessment of the climate conditions of China in 1959-1961: the three-year difficult period

NASA Astrophysics Data System (ADS)

Zhang, Haidong; Sun, Zhao bo; Luo, Yong; Zhang, Shangyin; Li, Qingxiang

2006-08-01

China is in the fragile climate area and is one of the most serious countries that suffered serious natural disaster in the world. This text had analyzing the climate conditions of China for the three-year difficult period of 1959-1961 scientifically, and told us about the number of the disaster (20, 29, 26 times) that occurred in the main natural areas by analyzing meteorological factors in 1951-1961, and the result is serious. The disasters of these years are mainly drought and typhoon, other natural disasters such as flood, hail are mainly in some areas in China. On the basis of analyze the three years' meteorological materials from the whole country (670 observation stations at national level and national basis, 4/24 times a day) year by year, and do the comparative analysis according to a common way (considered the average value of climate conditions in 1961-1990 as the standard value), analyze the impact of the natural disasters on national economy objectively with specific and accurate materials at that time, and give us suggestions on how to organize the deference of climate emergency system, etc. According to analysis, during 1959 - 1961, China's climate characteristic was lack of precipitation, especially in 1960, the space and time for the precipitation was not fair. As a whole, the weather and climate conditions are very disadvantageous to China's agricultural production during those years, especially 1960. According to loss caused by the disasters, the year 1960 was much more serious than 1959 and 1961.

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

NASA Astrophysics Data System (ADS)

Ravindranath, A.; Devineni, N.

2017-12-01

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

The Ophidia Stack: Toward Large Scale, Big Data Analytics Experiments for Climate Change

NASA Astrophysics Data System (ADS)

Fiore, S.; Williams, D. N.; D'Anca, A.; Nassisi, P.; Aloisio, G.

2015-12-01

The Ophidia project is a research effort on big data analytics facing scientific data analysis challenges in multiple domains (e.g. climate change). It provides a "datacube-oriented" framework responsible for atomically processing and manipulating scientific datasets, by providing a common way to run distributive tasks on large set of data fragments (chunks). Ophidia provides declarative, server-side, and parallel data analysis, jointly with an internal storage model able to efficiently deal with multidimensional data and a hierarchical data organization to manage large data volumes. The project relies on a strong background on high performance database management and On-Line Analytical Processing (OLAP) systems to manage large scientific datasets. The Ophidia analytics platform provides several data operators to manipulate datacubes (about 50), and array-based primitives (more than 100) to perform data analysis on large scientific data arrays. To address interoperability, Ophidia provides multiple server interfaces (e.g. OGC-WPS). From a client standpoint, a Python interface enables the exploitation of the framework into Python-based eco-systems/applications (e.g. IPython) and the straightforward adoption of a strong set of related libraries (e.g. SciPy, NumPy). The talk will highlight a key feature of the Ophidia framework stack: the "Analytics Workflow Management System" (AWfMS). The Ophidia AWfMS coordinates, orchestrates, optimises and monitors the execution of multiple scientific data analytics and visualization tasks, thus supporting "complex analytics experiments". Some real use cases related to the CMIP5 experiment will be discussed. In particular, with regard to the "Climate models intercomparison data analysis" case study proposed in the EU H2020 INDIGO-DataCloud project, workflows related to (i) anomalies, (ii) trend, and (iii) climate change signal analysis will be presented. Such workflows will be distributed across multiple sites - according to the datasets distribution - and will include intercomparison, ensemble, and outlier analysis. The two-level workflow solution envisioned in INDIGO (coarse grain for distributed tasks orchestration, and fine grain, at the level of a single data analytics cluster instance) will be presented and discussed.

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

DOE PAGES

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

2016-02-11

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

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

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

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

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

Proactive pavement asset management with climate change aspects

NASA Astrophysics Data System (ADS)

Zofka, Adam

2018-05-01

Pavement Asset Management System is a systematic and objective tool to manage pavement network based on the rational, engineering and economic principles. Once implemented and mature Pavement Asset Management System serves the entire range of users starting with the maintenance engineers and ending with the decision-makers. Such a system is necessary to coordinate agency management strategy including proactive maintenance. Basic inputs in the majority of existing Pavement Asset Management System approaches comprise the actual pavement inventory with associated construction history and condition, traffic information as well as various economical parameters. Some Pavement Management System approaches include also weather aspects which is of particular importance considering ongoing climate changes. This paper presents challenges in implementing the Pavement Asset Management System for those National Road Administrations that manage their pavement assets using more traditional strategies, e.g. worse-first approach. Special considerations are given to weather-related inputs and associated analysis to demonstrate the effects of climate change in a short- and long-term range. Based on the presented examples this paper concludes that National Road Administrations should account for the weather-related factors in their Pavement Management Systems as this has a significant impact on the system outcomes from the safety and economical perspective.

International Land Model Benchmarking (ILAMB) Workshop Report, Technical Report DOE/SC-0186

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

Hoffman, Forrest M.; Koven, Charles D.; Kappel-Aleks, Gretchen

2016-11-01

As Earth system models become increasingly complex, there is a growing need for comprehensive and multi-faceted evaluation of model projections. To advance understanding of biogeochemical processes and their interactions with hydrology and climate under conditions of increasing atmospheric carbon dioxide, new analysis methods are required that use observations to constrain model predictions, inform model development, and identify needed measurements and field experiments. Better representations of biogeochemistry–climate feedbacks and ecosystem processes in these models are essential for reducing uncertainties associated with projections of climate change during the remainder of the 21st century.

The NASA NEESPI Data Portal: Products, Information, and Services

NASA Technical Reports Server (NTRS)

Shen, Suhung; Leptoukh, Gregory; Loboda, Tatiana; Csiszar, Ivan; Romanov, Peter; Gerasimov, Irina

2008-01-01

Studies have indicated that land cover and use changes in Northern Eurasia influence global climate system. However, the procedures are not fully understood and it is challenging to understand the interactions between the land changes in this region and the global climate. Having integrated data collections form multiple disciplines are important for studies of climate and environmental changes. Remote sensed and model data are particularly important die to sparse in situ measurements in many Eurasia regions especially in Siberia. The NASA GES DISC (Goddard Earth Sciences Data and Information Services Center) NEESPI data portal has generated infrastructure to provide satellite remote sensing and numerical model data for atmospheric, land surface, and cryosphere. Data searching, subsetting, and downloading functions are available. ONe useful tool is the Web-based online data analysis and visualization system, Giovanni (Goddard Interactive Online Visualization ANd aNalysis Infrastructure), which allows scientists to assess easily the state and dynamics of terrestrial ecosystems in Northern Eurasia and their interactions with global climate system. Recently, we have created a metadata database prototype to expand the NASA NEESPI data portal for providing a venue for NEESPI scientists fo find the desired data easily and leveraging data sharing within NEESPI projects. The database provides product level information. The desired data can be found through navigation and free text search and narrowed down by filtering with a number of constraints. In addition, we have developed a Web Map Service (WMS) prototype to allow access data and images from difference data resources.

Atmospheric and oceanographic research review, 1978. [global weather, ocean/air interactions, and climate

NASA Technical Reports Server (NTRS)

1978-01-01

Research activities related to global weather, ocean/air interactions, and climate are reported. The global weather research is aimed at improving the assimilation of satellite-derived data in weather forecast models, developing analysis/forecast models that can more fully utilize satellite data, and developing new measures of forecast skill to properly assess the impact of satellite data on weather forecasting. The oceanographic research goal is to understand and model the processes that determine the general circulation of the oceans, focusing on those processes that affect sea surface temperature and oceanic heat storage, which are the oceanographic variables with the greatest influence on climate. The climate research objective is to support the development and effective utilization of space-acquired data systems in climate forecast models and to conduct sensitivity studies to determine the affect of lower boundary conditions on climate and predictability studies to determine which global climate features can be modeled either deterministically or statistically.

Documenting Climate Models and Their Simulations

DOE PAGES

Guilyardi, Eric; Balaji, V.; Lawrence, Bryan; ...

2013-05-01

The results of climate models are of increasing and widespread importance. No longer is climate model output of sole interest to climate scientists and researchers in the climate change impacts and adaptation fields. Now nonspecialists such as government officials, policy makers, and the general public all have an increasing need to access climate model output and understand its implications. For this host of users, accurate and complete metadata (i.e., information about how and why the data were produced) is required to document the climate modeling results. We describe a pilot community initiative to collect and make available documentation of climatemore » models and their simulations. In an initial application, a metadata repository is being established to provide information of this kind for a major internationally coordinated modeling activity known as CMIP5 (Coupled Model Intercomparison Project, Phase 5). We expected that for a wide range of stakeholders, this and similar community-managed metadata repositories will spur development of analysis tools that facilitate discovery and exploitation of Earth system simulations.« less

CO2 Supermarket Refrigeration Systems for Southeast Asia and the USA

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

Sharma, Vishaldeep; Fricke, Brian A; Bansal, Pradeep

This paper presents a comparative analysis of the annual energy consumption of these refrigeration systems in eighty eight cities from all climate zones in Southeast Asia. Also, the performance of the CO2 refrigeration systems is compared to the baseline R404A multiplex direct expansion (DX) system. Finally, the overall performance of the CO2 refrigeration systems in various climatic conditions in Southeast Asia is compared to that in the United States. For the refrigeration systems investigated, it was found that the Transcritical Booster System with Bypass Compressor (TBS-BC) performs better or equivalent to the R404A multiplex DX system in the northern regionsmore » of Southeast Asia (China and Japan). In the southern regions of Southeast Asia (India, Bangladesh, Burma), the R404A multiplex DX system and the Combined Secondary Cascade (CSC) system performs better than the TBS-BC.« less

Climatic Data Integration and Analysis - Regional Approaches to Climate Change for Pacific Northwest Agriculture (REACCH PNA)

NASA Astrophysics Data System (ADS)

Seamon, E.; Gessler, P. E.; Flathers, E.; Sheneman, L.; Gollberg, G.

2013-12-01

The Regional Approaches to Climate Change for Pacific Northwest Agriculture (REACCH PNA) is a five-year USDA/NIFA-funded coordinated agriculture project to examine the sustainability of cereal crop production systems in the Pacific Northwest, in relationship to ongoing climate change. As part of this effort, an extensive data management system has been developed to enable researchers, students, and the public, to upload, manage, and analyze various data. The REACCH PNA data management team has developed three core systems to encompass cyberinfrastructure and data management needs: 1) the reacchpna.org portal (https://www.reacchpna.org) is the entry point for all public and secure information, with secure access by REACCH PNA members for data analysis, uploading, and informational review; 2) the REACCH PNA Data Repository is a replicated, redundant database server environment that allows for file and database storage and access to all core data; and 3) the REACCH PNA Libraries which are functional groupings of data for REACCH PNA members and the public, based on their access level. These libraries are accessible thru our https://www.reacchpna.org portal. The developed system is structured in a virtual server environment (data, applications, web) that includes a geospatial database/geospatial web server for web mapping services (ArcGIS Server), use of ESRI's Geoportal Server for data discovery and metadata management (under the ISO 19115-2 standard), Thematic Realtime Environmental Distributed Data Services (THREDDS) for data cataloging, and Interactive Python notebook server (IPython) technology for data analysis. REACCH systems are housed and maintained by the Northwest Knowledge Network project (www.northwestknowledge.net), which provides data management services to support research. Initial project data harvesting and meta-tagging efforts have resulted in the interrogation and loading of over 10 terabytes of climate model output, regional entomological data, agricultural and atmospheric information, as well as imagery, publications, videos, and other soft content. In addition, the outlined data management approach has focused on the integration and interconnection of hard data (raw data output) with associated publications, presentations, or other narrative documentation - through metadata lineage associations. This harvest-and-consume data management methodology could additionally be applied to other research team environments that involve large and divergent data.

A survey of urban climate change experiments in 100 cities

PubMed Central

Castán Broto, Vanesa; Bulkeley, Harriet

2013-01-01

Cities are key sites where climate change is being addressed. Previous research has largely overlooked the multiplicity of climate change responses emerging outside formal contexts of decision-making and led by actors other than municipal governments. Moreover, existing research has largely focused on case studies of climate change mitigation in developed economies. The objective of this paper is to uncover the heterogeneous mix of actors, settings, governance arrangements and technologies involved in the governance of climate change in cities in different parts of the world. The paper focuses on urban climate change governance as a process of experimentation. Climate change experiments are presented here as interventions to try out new ideas and methods in the context of future uncertainties. They serve to understand how interventions work in practice, in new contexts where they are thought of as innovative. To study experimentation, the paper presents evidence from the analysis of a database of 627 urban climate change experiments in a sample of 100 global cities. The analysis suggests that, since 2005, experimentation is a feature of urban responses to climate change across different world regions and multiple sectors. Although experimentation does not appear to be related to particular kinds of urban economic and social conditions, some of its core features are visible. For example, experimentation tends to focus on energy. Also, both social and technical forms of experimentation are visible, but technical experimentation is more common in urban infrastructure systems. While municipal governments have a critical role in climate change experimentation, they often act alongside other actors and in a variety of forms of partnership. These findings point at experimentation as a key tool to open up new political spaces for governing climate change in the city. PMID:23805029

Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

NASA Astrophysics Data System (ADS)

Quetin, G. R.; Swann, A. L. S.

2017-12-01

Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models.

Evaluating Domestic Hot Water Distribution System Options With Validated Analysis Models

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

Weitzel, E.; Hoeschele, M.

2014-09-01

A developing body of work is forming that collects data on domestic hot water consumption, water use behaviors, and energy efficiency of various distribution systems. A full distribution system developed in TRNSYS has been validated using field monitoring data and then exercised in a number of climates to understand climate impact on performance. This study builds upon previous analysis modelling work to evaluate differing distribution systems and the sensitivities of water heating energy and water use efficiency to variations of climate, load, distribution type, insulation and compact plumbing practices. Overall 124 different TRNSYS models were simulated. Of the configurations evaluated,more » distribution losses account for 13-29% of the total water heating energy use and water use efficiency ranges from 11-22%. The base case, an uninsulated trunk and branch system sees the most improvement in energy consumption by insulating and locating the water heater central to all fixtures. Demand recirculation systems are not projected to provide significant energy savings and in some cases increase energy consumption. Water use is most efficient with demand recirculation systems, followed by the insulated trunk and branch system with a central water heater. Compact plumbing practices and insulation have the most impact on energy consumption (2-6% for insulation and 3-4% per 10 gallons of enclosed volume reduced). The results of this work are useful in informing future development of water heating best practices guides as well as more accurate (and simulation time efficient) distribution models for annual whole house simulation programs.« less

Water erosion and climate change in a small alpine catchment

NASA Astrophysics Data System (ADS)

Berteni, Francesca; Grossi, Giovanna

2017-04-01

WATER EROSION AND CLIMATE CHANGE IN A SMALL ALPINE CATCHMENT Francesca Berteni, Giovanna Grossi A change in the mean and variability of some variables of the climate system is expected to affect the sediment yield of mountainous areas in several ways: for example through soil temperature and precipitation peak intensity change, permafrost thawing, snow- and ice-melt time shifting. Water erosion, sediment transport and yield and the effects of climate change on these physical phenomena are the focus of this work. The study area is a small mountainous basin, the Guerna creek watershed, located in the Central Southern Alps. The sensitivity of sediment yield estimates to a change of condition of the climate system may be investigated through the application of different models, each characterized by its own features and limits. In this preliminary analysis two different empirical mathematical models are considered: RUSLE (Revised Universal Soil Loss Equation; Renard et al., 1991) and EPM (Erosion Potential Method; Gavrilovic, 1988). These models are implemented in a Geographical Information System (GIS) supporting the management of the territorial database used to estimate relevant geomorphological parameters and to create different thematic maps. From one side the geographical and geomorphological information is required (land use, slope and hydrogeological instability, resistance to erosion, lithological characterization and granulometric composition). On the other side the knowledge of the weather-climate parameters (precipitation and temperature data) is fundamental as well to evaluate the intensity and variability of the erosive processes and estimate the sediment yield at the basin outlet. Therefore different climate change scenarios were considered in order to tentatively assess the impact on the water erosion and sediment yield at the small basin scale. Keywords: water erosion, sediment yield, climate change, empirical mathematical models, EPM, RUSLE, GIS, Guerna

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Contacts Change Log Events Calendar People Numerical Forecast Systems Ensemble and Post Processing Team

Quantitative assessment of resilience of a water supply system under rainfall reduction due to climate change

NASA Astrophysics Data System (ADS)

Amarasinghe, Pradeep; Liu, An; Egodawatta, Prasanna; Barnes, Paul; McGree, James; Goonetilleke, Ashantha

2016-09-01

A water supply system can be impacted by rainfall reduction due to climate change, thereby reducing its supply potential. This highlights the need to understand the system resilience, which refers to the ability to maintain service under various pressures (or disruptions). Currently, the concept of resilience has not yet been widely applied in managing water supply systems. This paper proposed three technical resilience indictors to assess the resilience of a water supply system. A case study analysis was undertaken of the Water Grid system of Queensland State, Australia, to showcase how the proposed indicators can be applied to assess resilience. The research outcomes confirmed that the use of resilience indicators is capable of identifying critical conditions in relation to the water supply system operation, such as the maximum allowable rainfall reduction for the system to maintain its operation without failure. Additionally, resilience indicators also provided useful insight regarding the sensitivity of the water supply system to a changing rainfall pattern in the context of climate change, which represents the system's stability when experiencing pressure. The study outcomes will help in the quantitative assessment of resilience and provide improved guidance to system operators to enhance the efficiency and reliability of a water supply system.

Climate Central World Weather Attribution (WWA) project: Real-time extreme weather event attribution analysis

NASA Astrophysics Data System (ADS)

Haustein, Karsten; Otto, Friederike; Uhe, Peter; Allen, Myles; Cullen, Heidi

2015-04-01

Extreme weather detection and attribution analysis has emerged as a core theme in climate science over the last decade or so. By using a combination of observational data and climate models it is possible to identify the role of climate change in certain types of extreme weather events such as sea level rise and its contribution to storm surges, extreme heat events and droughts or heavy rainfall and flood events. These analyses are usually carried out after an extreme event has occurred when reanalysis and observational data become available. The Climate Central WWA project will exploit the increasing forecast skill of seasonal forecast prediction systems such as the UK MetOffice GloSea5 (Global seasonal forecasting system) ensemble forecasting method. This way, the current weather can be fed into climate models to simulate large ensembles of possible weather scenarios before an event has fully emerged yet. This effort runs along parallel and intersecting tracks of science and communications that involve research, message development and testing, staged socialization of attribution science with key audiences, and dissemination. The method we employ uses a very large ensemble of simulations of regional climate models to run two different analyses: one to represent the current climate as it was observed, and one to represent the same events in the world that might have been without human-induced climate change. For the weather "as observed" experiment, the atmospheric model uses observed sea surface temperature (SST) data from GloSea5 (currently) and present-day atmospheric gas concentrations to simulate weather events that are possible given the observed climate conditions. The weather in the "world that might have been" experiments is obtained by removing the anthropogenic forcing from the observed SSTs, thereby simulating a counterfactual world without human activity. The anthropogenic forcing is obtained by comparing the CMIP5 historical and natural simulations from a variety of CMIP5 model ensembles. Here, we present results for the UK 2013/14 winter floods as proof of concept and we show validation and testing results that demonstrate the robustness of our method. We also revisit the record temperatures over Europe in 2014 and present a detailed analysis of this attribution exercise as it is one of the events to demonstrate that we can make a sensible statement of how the odds for such a year to occur have changed while it still unfolds.

The economics (or lack thereof) of aerosol geoengineering

NASA Astrophysics Data System (ADS)

Goes, M.; Keller, K.; Tuana, N.

2009-04-01

Anthropogenic greenhouse gas emissions are changing the Earth's climate and impose substantial risks for current and future generations. What are scientifically sound, economically viable, and ethically defendable strategies to manage these climate risks? Ratified international agreements call for a reduction of greenhouse gas emissions to avoid dangerous anthropogenic interference with the climate system. Recent proposals, however, call for the deployment of a different approach: to geoengineer climate by injecting aerosol precursors into the stratosphere. Published economic studies typically suggest that substituting aerosol geoengineering for abatement of carbon dioxide emissions results in large net monetary benefits. However, these studies neglect the risks of aerosol geoengineering due to (i) the potential for future geoengineering failures and (ii) the negative impacts associated with the aerosol forcing. Here we use a simple integrated assessment model of climate change to analyze potential economic impacts of aerosol geoengineering strategies over a wide range of uncertain parameters such as climate sensitivity, the economic damages due to climate change, and the economic damages due to aerosol geoengineering forcing. The simplicity of the model provides the advantages of parsimony and transparency, but it also imposes severe caveats on the interpretation of the results. For example, the analysis is based on a globally aggregated model and is hence silent on the question of intragenerational distribution of costs and benefits. In addition, the analysis neglects the effects of endogenous learning about the climate system. We show that the risks associated with a future geoengineering failure and negative impacts of aerosol forcings can cause geoenginering strategies to fail an economic cost-benefit test. One key to this finding is that a geoengineering failure would lead to dramatic and abrupt climatic changes. The monetary damages due to this failure can dominate the cost-benefit analysis because the monetary damages of climate change are expected to increase with the rate of change. Substituting aerosol geoengineering for greenhouse gas emission abatement might fail not only an economic cost-benefit test but also an ethical test of distributional justice. Substituting aerosol geoengineering for greenhouse gas emissions abatements constitutes a conscious risk transfer to future generations. Intergenerational justice demands distributional justice, namely that present generations may not create benefits for themselves in exchange for burdens on future generations. We use the economic model to quantify this risk transfer to better inform the judgment of whether substituting aerosol geoengineering for carbon dioxide emission abatement fails this ethical test.

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post streamline the interaction of analysis, forecast, and post-processing systems within NCEP. The NEMS Force, and will eventually provide support to the community through the Developmental Test Center (DTC

Analysis of Vegetation Index Variations and the Asian Monsoon Climate

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Implications of Projected Climate Change for Groundwater Recharge in the Western United States

NASA Technical Reports Server (NTRS)

Meixner, Thomas; Manning, Andrew H.; Stonestrom, David A.; Allen, Diana M.; Ajami, Hoori; Blasch, Kyle W.; Brookfield, Andrea E.; Castro, Christopher L.; Clark, Jordan F.; Gochis, David J.;

Implications of projected climate change for groundwater recharge in the western United States

USGS Publications Warehouse

Meixner, Thomas; Manning, Andrew H.; Stonestrom, David A.; Allen, Diana M.; Ajami, Hoori; Blasch, Kyle W.; Brookfield, Andrea E.; Castro, Christopher L.; Clark, Jordan F.; Gochis, David; Flint, Alan L.; Neff, Kirstin L.; Niraula, Rewati; Rodell, Matthew; Scanlon, Bridget R.; Singha, Kamini; Walvoord, Michelle Ann

2016-01-01

Existing studies on the impacts of climate change on groundwater recharge are either global or basin/location-specific. The global studies lack the specificity to inform decision making, while the local studies do little to clarify potential changes over large regions (major river basins, states, or groups of states), a scale often important in the development of water policy. An analysis of the potential impact of climate change on groundwater recharge across the western United States (west of 100° longitude) is presented synthesizing existing studies and applying current knowledge of recharge processes and amounts. Eight representative aquifers located across the region were evaluated. For each aquifer published recharge budget components were converted into four standard recharge mechanisms: diffuse, focused, irrigation, and mountain-systems recharge. Future changes in individual recharge mechanisms and total recharge were then estimated for each aquifer. Model-based studies of projected climate-change effects on recharge were available and utilized for half of the aquifers. For the remainder, forecasted changes in temperature and precipitation were logically propagated through each recharge mechanism producing qualitative estimates of direction of changes in recharge only (not magnitude). Several key patterns emerge from the analysis. First, the available estimates indicate average declines of 10–20% in total recharge across the southern aquifers, but with a wide range of uncertainty that includes no change. Second, the northern set of aquifers will likely incur little change to slight increases in total recharge. Third, mountain system recharge is expected to decline across much of the region due to decreased snowpack, with that impact lessening with higher elevation and latitude. Factors contributing the greatest uncertainty in the estimates include: (1) limited studies quantitatively coupling climate projections to recharge estimation methods using detailed, process-based numerical models; (2) a generally poor understanding of hydrologic flowpaths and processes in mountain systems; (3) difficulty predicting the response of focused recharge to potential changes in the frequency and intensity of extreme precipitation events; and (4) unconstrained feedbacks between climate, irrigation practices, and recharge in highly developed aquifer systems.

Implications of projected climate change for groundwater recharge in the western United States

NASA Astrophysics Data System (ADS)

Meixner, Thomas; Manning, Andrew H.; Stonestrom, David A.; Allen, Diana M.; Ajami, Hoori; Blasch, Kyle W.; Brookfield, Andrea E.; Castro, Christopher L.; Clark, Jordan F.; Gochis, David J.; Flint, Alan L.; Neff, Kirstin L.; Niraula, Rewati; Rodell, Matthew; Scanlon, Bridget R.; Singha, Kamini; Walvoord, Michelle A.

2016-03-01

Existing studies on the impacts of climate change on groundwater recharge are either global or basin/location-specific. The global studies lack the specificity to inform decision making, while the local studies do little to clarify potential changes over large regions (major river basins, states, or groups of states), a scale often important in the development of water policy. An analysis of the potential impact of climate change on groundwater recharge across the western United States (west of 100° longitude) is presented synthesizing existing studies and applying current knowledge of recharge processes and amounts. Eight representative aquifers located across the region were evaluated. For each aquifer published recharge budget components were converted into four standard recharge mechanisms: diffuse, focused, irrigation, and mountain-systems recharge. Future changes in individual recharge mechanisms and total recharge were then estimated for each aquifer. Model-based studies of projected climate-change effects on recharge were available and utilized for half of the aquifers. For the remainder, forecasted changes in temperature and precipitation were logically propagated through each recharge mechanism producing qualitative estimates of direction of changes in recharge only (not magnitude). Several key patterns emerge from the analysis. First, the available estimates indicate average declines of 10-20% in total recharge across the southern aquifers, but with a wide range of uncertainty that includes no change. Second, the northern set of aquifers will likely incur little change to slight increases in total recharge. Third, mountain system recharge is expected to decline across much of the region due to decreased snowpack, with that impact lessening with higher elevation and latitude. Factors contributing the greatest uncertainty in the estimates include: (1) limited studies quantitatively coupling climate projections to recharge estimation methods using detailed, process-based numerical models; (2) a generally poor understanding of hydrologic flowpaths and processes in mountain systems; (3) difficulty predicting the response of focused recharge to potential changes in the frequency and intensity of extreme precipitation events; and (4) unconstrained feedbacks between climate, irrigation practices, and recharge in highly developed aquifer systems.

HOW THE LEED VENTILATION CREDIT IMPACTS ENERGY CONSUMPTION OF GSHP SYSTEMS A CASE STUDY FOR PRIMARY SCHOOLS

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

Liu, Xiaobing

2011-01-01

This paper presents a study on the impacts of increased outdoor air (OA) ventilation on the performance of ground-source heat pump (GSHP) systems that heat and cool typical primary schools. Four locations Phoenix, Miami, Seattle, and Chicago are selected in this study to represent different climate zones in the United States. eQUEST, an integrated building and HVAC system energy analysis program, is used to simulate a typical primary school and the GSHP system at the four locations with minimum and 30% more than minimum OA ventilation. The simulation results show that, without an energy recovery ventilator, the 30% more OAmore » ventilation results in an 8.0 13.3% increase in total GSHP system energy consumption at the four locations. The peak heating and cooling loads increase by 20.2 30% and 14.9 18.4%, respectively, at the four locations. The load imbalance of the ground heat exchanger is increased in hot climates but reduced in mild and cold climates.« less

Integration of modern statistical tools for the analysis of climate extremes into the web-GIS “CLIMATE”

NASA Astrophysics Data System (ADS)

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

2017-11-01

The frequency of occurrence and magnitude of precipitation and temperature extreme events show positive trends in several geographical regions. These events must be analyzed and studied in order to better understand their impact on the environment, predict their occurrences, and mitigate their effects. For this purpose, we augmented web-GIS called “CLIMATE” to include a dedicated statistical package developed in the R language. The web-GIS “CLIMATE” is a software platform for cloud storage processing and visualization of distributed archives of spatial datasets. It is based on a combined use of web and GIS technologies with reliable procedures for searching, extracting, processing, and visualizing the spatial data archives. The system provides a set of thematic online tools for the complex analysis of current and future climate changes and their effects on the environment. The package includes new powerful methods of time-dependent statistics of extremes, quantile regression and copula approach for the detailed analysis of various climate extreme events. Specifically, the very promising copula approach allows obtaining the structural connections between the extremes and the various environmental characteristics. The new statistical methods integrated into the web-GIS “CLIMATE” can significantly facilitate and accelerate the complex analysis of climate extremes using only a desktop PC connected to the Internet.

Downscaled ice-ocean simulations for the Chukchi and Eastern Siberian Seas from an oceanic re-analysis product

NASA Astrophysics Data System (ADS)

Fujisaki-Manome, A.; Wang, J.

2016-12-01

Arctic summer sea ice has been declining at the rate that is much faster than any climate models predict. While the accelerated sea ice melting in the recent few decades could be attributed to several mechanisms such as the Arctic temperature amplification and the ice-albedo feedback, this does not necessarily explain why climate models underestimate the observed rate of summer sea ice loss. Clearly, an improved understanding is needed in what processes could be missed in climate models and could play roles in unprecedented loss of sea ice. This study evaluates contributions of sub-mesoscale processes in the ice edge (i.e. the boundary region between open water and ice covered area), which include eddies, ice bands, and the vertical mixing associated with ice bands, to the melting of sea ice and how they explain the underestimation of sea ice loss in the current state-of-art climate models. The focus area is in the pacific side of the Arctic Ocean. First, several oceanic re-analysis products including NCEP-Climate Forecast System Reanalysis (CFSR) and Modern-Era Retrospective Analysis for Research and Applications (MERRA) are evaluated in comparison with the in-situ observations from the Russian-American Long-term Census of the Arctic (RUSALCA) project. Second, the downscaled ice-ocean simulations are conducted for the Chukchi and East Siberian Seas with initial and open boundary conditions provided from a selected oceanic re-analysis product.

Analysis of Radiant Cooling System Configurations Integrated with Cooling Tower for Different Indian Climatic Zones

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

Mathur, Jyotirmay; Bhandari, Mahabir S; Jain, Robin

Radiant cooling system has proven to be a low energy consumption system for building cooling needs. This study describes the use of cooling tower in radiant cooling system to improve the overall system efficiency. A comprehensive simulation feasibility study of the application of cooling tower in radiant cooling system was performed for the fifteen cities in different climatic zones of India. It was found that in summer, the wet bulb temperature (WBT) of the different climatic zones except warm-humid is suitable for the integration of cooling tower with radiant cooling system. In these climates, cooling tower can provide on averagemore » 24 C to 27 C water In order to achieve the energy saving potential, three different configurations of radiant cooling system have been compared in terms of energy consumption. The different configurations of the radiant cooling system integrated with cooling tower are: (1) provide chilled water to the floor, wall and ceiling mounted tubular installation. (2) provide chilled water to the wall and ceiling mounted tabular installation. In this arrangement a separate chiller has also been used to provide chilled water at 16 C to the floor mounted tubular installation. (3) provide chilled water to the wall mounted tabular installation and a separate chiller is used to provide chilled water at 16 C to the floor and ceiling mounted tabular installation. A dedicated outdoor air system is also coupled for dehumidification and ventilation in all three configurations. A conventional all-air system was simulated as a baseline to compare these configurations for assessing the energy saving potential.« less

Indigenous Food Systems and Climate Change: Impacts of Climatic Shifts on the Production and Processing of Native and Traditional Crops in the Bolivian Andes.

PubMed

Keleman Saxena, Alder; Cadima Fuentes, Ximena; Gonzales Herbas, Rhimer; Humphries, Debbie L

2016-01-01

Inhabitants of the high-mountain Andes have already begun to experience changes in the timing, severity, and patterning of annual weather cycles. These changes have important implications for agriculture, for human health, and for the conservation of biodiversity in the region. This paper examines the implications of climate-driven changes for native and traditional crops in the municipality of Colomi, Cochabamba, Bolivia. Data were collected between 2012 and 2014 via mixed methods, qualitative fieldwork, including participatory workshops with female farmers and food preparers, semi-structured interviews with local agronomists, and participant observation. Drawing from this data, the paper describes (a) the observed impacts of changing weather patterns on agricultural production in the municipality of Colomi, Bolivia and (b) the role of local environmental resources and conditions, including clean running water, temperature, and humidity, in the household processing techniques used to conserve and sometimes detoxify native crop and animal species, including potato (Solanum sp.), oca (Oxalis tuberosa), tarwi (Lupinus mutabilis), papalisa (Ullucus tuberosus), and charke (llama or sheep jerky). Analysis suggests that the effects of climatic changes on agriculture go beyond reductions in yield, also influencing how farmers make choices about the timing of planting, soil management, and the use and spatial distribution of particular crop varieties. Furthermore, household processing techniques to preserve and detoxify native foods rely on key environmental and climatic resources, which may be vulnerable to climatic shifts. Although these findings are drawn from a single case study, we suggest that Colomi agriculture characterizes larger patterns in what might be termed, "indigenous food systems." Such systems are underrepresented in aggregate models of the impacts of climate change on world agriculture and may be under different, more direct, and more immediate threat from climate change. As such, the health of the food production and processing environments in such systems merits immediate attention in research and practice.

Indigenous Food Systems and Climate Change: Impacts of Climatic Shifts on the Production and Processing of Native and Traditional Crops in the Bolivian Andes

PubMed Central

Keleman Saxena, Alder; Cadima Fuentes, Ximena; Gonzales Herbas, Rhimer; Humphries, Debbie L.

2016-01-01

Inhabitants of the high-mountain Andes have already begun to experience changes in the timing, severity, and patterning of annual weather cycles. These changes have important implications for agriculture, for human health, and for the conservation of biodiversity in the region. This paper examines the implications of climate-driven changes for native and traditional crops in the municipality of Colomi, Cochabamba, Bolivia. Data were collected between 2012 and 2014 via mixed methods, qualitative fieldwork, including participatory workshops with female farmers and food preparers, semi-structured interviews with local agronomists, and participant observation. Drawing from this data, the paper describes (a) the observed impacts of changing weather patterns on agricultural production in the municipality of Colomi, Bolivia and (b) the role of local environmental resources and conditions, including clean running water, temperature, and humidity, in the household processing techniques used to conserve and sometimes detoxify native crop and animal species, including potato (Solanum sp.), oca (Oxalis tuberosa), tarwi (Lupinus mutabilis), papalisa (Ullucus tuberosus), and charke (llama or sheep jerky). Analysis suggests that the effects of climatic changes on agriculture go beyond reductions in yield, also influencing how farmers make choices about the timing of planting, soil management, and the use and spatial distribution of particular crop varieties. Furthermore, household processing techniques to preserve and detoxify native foods rely on key environmental and climatic resources, which may be vulnerable to climatic shifts. Although these findings are drawn from a single case study, we suggest that Colomi agriculture characterizes larger patterns in what might be termed, “indigenous food systems.” Such systems are underrepresented in aggregate models of the impacts of climate change on world agriculture and may be under different, more direct, and more immediate threat from climate change. As such, the health of the food production and processing environments in such systems merits immediate attention in research and practice. PMID:26973824

Influence of North Atlantic modes on European climate extremes

NASA Astrophysics Data System (ADS)

Proemmel, K.; Cubasch, U.

2017-12-01

It is well known that the North Atlantic strongly influences European climate. Only few studies exist that focus on its impact on climate extremes. We are interested in these extremes and the processes and mechanisms behind it. For the analysis of the North Atlantic Oscillation (NAO) we use simulations performed with the Max Planck Institute for Meteorology Earth System Model (MPI-ESM). The NAO has a strong impact especially on European winter and the changes in minimum temperature are even larger than in maximum temperature. The impact of the Atlantic Multi-decadal Variability (AMV) on climate extremes is analyzed in ECHAM6 simulations forced with AMV warm and AMV cold sea surface temperature patterns. We analyze different extreme indices and try to understand the processes.

Economic impact of climate on water management in Oklahoma

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

Eddy, A.

1981-08-01

Topics and authors are listed below: The Oklahoma Water Plan, Jim Schuelin; The Garber-Wellington Research Project, Odell Morgan; The Tulsa Urban Study, Howard Chalker; Some Civil Defense/Flood Warning Problems, Ron Hill; The Impact of Climate on Rural Water Management, Ellen Cooter; Economic Models for Water Resource and Climate Impact Applications, William S. Cooter; Flood Forecasting, Jack Bowman; Small Basin Rainfall Characteristics via Factor Analysis, John M. Harlin; Radar Clouds Over Oklahoma, Bernard N. Meisner; The Oklahoma Climatological Survey Data Bank, Amos Eddy; Derived Variables: Climatic and Hydrologic Data from Weather Station Records, Jayne M. Salisbury; Precipitation Estimates Using Radar, Kenmore » Wilk and David Zittel; and A Water Control Data System, Joe Z. Durham.« less

Energy Switching Threshold for Climatic Benefits

NASA Astrophysics Data System (ADS)

Zhang, X.; Cao, L.; Caldeira, K.

2013-12-01

Climate change is one of the great challenges facing humanity currently and in the future. Its most severe impacts may still be avoided if efforts are made to transform current energy systems (1). A transition from the global system of high Greenhouse Gas (GHG) emission electricity generation to low GHG emission energy technologies is required to mitigate climate change (2). Natural gas is increasingly seen as a choice for transitions to renewable sources. However, recent researches in energy and climate puzzled about the climate implications of relying more energy on natural gas. On one hand, a shift to natural gas is promoted as climate mitigation because it has lower carbon per unit energy than coal (3). On the other hand, the effect of switching to natural gas on nuclear-power and other renewable energies development may offset benefits from fuel-switching (4). Cheap natural gas is causing both coal plants and nuclear plants to close in the US. The objective of this study is to measure and evaluate the threshold of energy switching for climatic benefits. We hypothesized that the threshold ratio of energy switching for climatic benefits is related to GHGs emission factors of energy technologies, but the relation is not linear. A model was developed to study the fuel switching threshold for greenhouse gas emission reduction, and transition from coal and nuclear electricity generation to natural gas electricity generation was analyzed as a case study. The results showed that: (i) the threshold ratio of multi-energy switching for climatic benefits changes with GHGs emission factors of energy technologies. (ii)The mathematical relation between the threshold ratio of energy switching and GHGs emission factors of energies is a curved surface function. (iii) The analysis of energy switching threshold for climatic benefits can be used for energy and climate policy decision support.

A comparative review of multi-risk modelling methodologies for climate change adaptation in mountain regions

NASA Astrophysics Data System (ADS)

Terzi, Stefano; Torresan, Silvia; Schneiderbauer, Stefan

2017-04-01

Keywords: Climate change, mountain regions, multi-risk assessment, climate change adaptation. Climate change has already led to a wide range of impacts on the environment, the economy and society. Adaptation actions are needed to cope with the impacts that have already occurred (e.g. storms, glaciers melting, floods, droughts) and to prepare for future scenarios of climate change. Mountain environment is particularly vulnerable to the climate changes due to its exposure to recent climate warming (e.g. water regime changes, thawing of permafrost) and due to the high degree of specialization of both natural and human systems (e.g. alpine species, valley population density, tourism-based economy). As a consequence, the mountain local governments are encouraged to undertake territorial governance policies to climate change, considering multi-risks and opportunities for the mountain economy and identifying the best portfolio of adaptation strategies. This study aims to provide a literature review of available qualitative and quantitative tools, methodological guidelines and best practices to conduct multi-risk assessments in the mountain environment within the context of climate change. We analyzed multi-risk modelling and assessment methods applied in alpine regions (e.g. event trees, Bayesian Networks, Agent Based Models) in order to identify key concepts (exposure, resilience, vulnerability, risk, adaptive capacity), climatic drivers, cause-effect relationships and socio-ecological systems to be integrated in a comprehensive framework. The main outcomes of the review, including a comparison of existing techniques based on different criteria (e.g. scale of analysis, targeted questions, level of complexity) and a snapshot of the developed multi-risk framework for climate change adaptation will be here presented and discussed.

Can We Asses the Impact of Water Factor on Ecosystems and Agriculture under Future Climate Conditions? Case Study from Poland.

NASA Astrophysics Data System (ADS)

Okruszko, T.; O'Keeffe, J.; Marcinkowski, P.; Utratna, M.; Szcześniak, M.; Piniewski, M.

2016-12-01

This study presents a broad overview of climate change impacts on eco- and agro-systems in Poland using an index-based approach for the Vistula and Odra river basins in Poland. The issues of risks to biodiversity and agricultural productivity caused by climate change (CC) are explicitly addressed. The biodiversity issue is tackled by the analysis of two types of ecosystems: instream and wetland (both river-and groundwater fed). Agro-systems are analyzed using key crops (spring and winter grains, potatoes, corn and grasslands),including their regional differentiation and dominant soil types. The study was accomplished in the following steps: (1) development of historical climate dataset and its application for bias correction of climate projections, (2) modelling the hydrological system using the SWAT model for historical and future climate, (3) development of indices quantifying the impact of water factoron eco- and agro-systems based on the SWAT model results, (4) calculation and critical analysis of results for two emission scenarios (RCPs) and two time horizons. The 5-km resolution precipitation and temperature dataset (10.5194/essd-8-127-2016) was developed and applied for bias correction of the multi-model ensemble of 9 CORDEX RCMs under two RCPs 4.5 and 8.5. Comprehensive calibration/validation of SWAT showed overall good results across a range of catchment sizes in Poland. The ensemble median increase (relative to historical period) ranged between 6 and 16 % for precipitation and between 18 and 48 % for water yield simulated by SWAT, depending on the future time horizon and RCP. The Indicators of Hydrological Alteration (IHA) quantifying the natural flow regime were used as a proxy for quantifying the CC effect on instream biota (notably fish). Changes in frequency and magnitude of the identified flood events informed about the alteration to the water supply for riparian wetlands. Changes in groundwater recharge are used as a proxy for water conditions in mires. The SWAT output on water stress has proven to be a good indicator of agricultural drought. The results showed that developed indicators are highly sensitive to projected changes in water conditions under changing climate. It means that they can be used for agriculture adaptation programs and in conservation policy.

Revisiting the climate impacts of cool roofs around the globe using an Earth system model

NASA Astrophysics Data System (ADS)

Zhang, Jiachen; Zhang, Kai; Liu, Junfeng; Ban-Weiss, George

2016-08-01

Solar reflective ‘cool roofs’ absorb less sunlight than traditional dark roofs, reducing solar heat gain, and decreasing the amount of heat transferred to the atmosphere. Widespread adoption of cool roofs could therefore reduce temperatures in urban areas, partially mitigating the urban heat island effect, and contributing to reversing the local impacts of global climate change. The impacts of cool roofs on global climate remain debated by past research and are uncertain. Using a sophisticated Earth system model, the impacts of cool roofs on climate are investigated at urban, continental, and global scales. We find that global adoption of cool roofs in urban areas reduces urban heat islands everywhere, with an annual- and global-mean decrease from 1.6 to 1.2 K. Decreases are statistically significant, except for some areas in Africa and Mexico where urban fraction is low, and some high-latitude areas during wintertime. Analysis of the surface and TOA energy budget in urban regions at continental-scale shows cool roofs causing increases in solar radiation leaving the Earth-atmosphere system in most regions around the globe, though the presence of aerosols and clouds are found to partially offset increases in upward radiation. Aerosols dampen cool roof-induced increases in upward solar radiation, ranging from 4% in the United States to 18% in more polluted China. Adoption of cool roofs also causes statistically significant reductions in surface air temperatures in urbanized regions of China (-0.11 ± 0.10 K) and the United States (-0.14 ± 0.12 K); India and Europe show statistically insignificant changes. Though past research has disagreed on whether widespread adoption of cool roofs would cool or warm global climate, these studies have lacked analysis on the statistical significance of global temperature changes. The research presented here indicates that adoption of cool roofs around the globe would lead to statistically insignificant reductions in global mean air temperature (-0.0021 ± 0.026 K). Thus, we suggest that while cool roofs are an effective tool for reducing building energy use in hot climates, urban heat islands, and regional air temperatures, their influence on global climate is likely negligible.

Revisiting the Climate Impacts of Cool Roofs around the Globe Using an Earth System Model

NASA Astrophysics Data System (ADS)

Zhang, J.; Ban-Weiss, G. A.; Zhang, K.; Liu, J.

2016-12-01

Solar reflective "cool roofs" absorb less sunlight than traditional dark roofs, reducing solar heat gain, and decreasing the amount of heat transferred to the atmosphere. Widespread adoption of cool roofs could therefore reduce temperatures in urban areas, partially mitigating the urban heat island effect, and contributing to reversing the local impacts of global climate change. The impacts of cool roofs on global climate remain debated by past research and are uncertain. Using a sophisticated Earth system model, the impacts of cool roofs on climate are investigated at urban, continental, and global scales. We find that global adoption of cool roofs in urban areas reduces urban heat islands everywhere, with an annual- and global-mean decrease from 1.6 to 1.2 K. Decreases are statistically significant, except for some areas in Africa and Mexico where urban fraction is low, and some high-latitude areas during wintertime. Analysis of the surface and TOA energy budget in urban regions at continental-scale shows cool roofs causing increases in solar radiation leaving the Earth-atmosphere system in most regions around the globe, though the presence of aerosols and clouds are found to partially offset increases in upward radiation. Aerosols dampen cool roof-induced increases in upward solar radiation, ranging from 4% in the United States to 18% in more polluted China. Adoption of cool roofs also causes statistically significant reductions in surface air temperatures in urbanized regions of China (-0.11±0.10 K) and the United States (-0.14±0.12 K); India and Europe show statistically insignificant changes. Though past research has disagreed on whether widespread adoption of cool roofs would cool or warm global climate, these studies have lacked analysis on the statistical significance of global temperature changes. The research presented here indicates that adoption of cool roofs around the globe would lead to statistically insignificant reductions in global mean air temperature (-0.0021 ± 0.026 K). Thus, we suggest that while cool roofs are an effective tool for reducing building energy use in hot climates, urban heat islands, and regional air temperatures, their influence on global climate is likely negligible.

ParCAT: A Parallel Climate Analysis Toolkit

NASA Astrophysics Data System (ADS)

Haugen, B.; Smith, B.; Steed, C.; Ricciuto, D. M.; Thornton, P. E.; Shipman, G.

2012-12-01

Climate science has employed increasingly complex models and simulations to analyze the past and predict the future of our climate. The size and dimensionality of climate simulation data has been growing with the complexity of the models. This growth in data is creating a widening gap between the data being produced and the tools necessary to analyze large, high dimensional data sets. With single run data sets increasing into 10's, 100's and even 1000's of gigabytes, parallel computing tools are becoming a necessity in order to analyze and compare climate simulation data. The Parallel Climate Analysis Toolkit (ParCAT) provides basic tools that efficiently use parallel computing techniques to narrow the gap between data set size and analysis tools. ParCAT was created as a collaborative effort between climate scientists and computer scientists in order to provide efficient parallel implementations of the computing tools that are of use to climate scientists. Some of the basic functionalities included in the toolkit are the ability to compute spatio-temporal means and variances, differences between two runs and histograms of the values in a data set. ParCAT is designed to facilitate the "heavy lifting" that is required for large, multidimensional data sets. The toolkit does not focus on performing the final visualizations and presentation of results but rather, reducing large data sets to smaller, more manageable summaries. The output from ParCAT is provided in commonly used file formats (NetCDF, CSV, ASCII) to allow for simple integration with other tools. The toolkit is currently implemented as a command line utility, but will likely also provide a C library for developers interested in tighter software integration. Elements of the toolkit are already being incorporated into projects such as UV-CDAT and CMDX. There is also an effort underway to implement portions of the CCSM Land Model Diagnostics package using ParCAT in conjunction with Python and gnuplot. ParCAT is implemented in C to provide efficient file IO. The file IO operations in the toolkit use the parallel-netcdf library; this enables the code to use the parallel IO capabilities of modern HPC systems. Analysis that currently requires an estimated 12+ hours with the traditional CCSM Land Model Diagnostics Package can now be performed in as little as 30 minutes on a single desktop workstation and a few minutes for relatively small jobs completed on modern HPC systems such as ORNL's Jaguar.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

LCA and Cost Analysis of Membrane Bioreactor Systems: Influence of Scale, Population Density, Climate, and Methane Recovery

EPA Science Inventory

Future changes in drinking and waste water infrastructure need to incorporate a holistic view of the water service sustainability tradeoffs and potential benefits when considering shifts towards new treatment technology, decentralized systems, energy recovery and reuse of treated...

National Centers for Environmental Prediction

Science.gov Websites

Modeling Mesoscale Modeling Marine Modeling and Analysis Teams Climate Data Assimilation Ensembles and Post Ice group works on sea ice analysis from satellite, sea ice modeling, and ice-atmosphere-ocean / VISION | About EMC Analysis Drift Model KISS Model Numerical Forecast Systems The Polar and Great Lakes

Teaching Earth Signals Analysis Using the Java-DSP Earth Systems Edition: Modern and Past Climate Change

ERIC Educational Resources Information Center

Ramamurthy, Karthikeyan Natesan; Hinnov, Linda A.; Spanias, Andreas S.

2014-01-01

Modern data collection in the Earth Sciences has propelled the need for understanding signal processing and time-series analysis techniques. However, there is an educational disconnect in the lack of instruction of time-series analysis techniques in many Earth Science academic departments. Furthermore, there are no platform-independent freeware…

Statistical methods for the analysis of climate extremes

NASA Astrophysics Data System (ADS)

Naveau, Philippe; Nogaj, Marta; Ammann, Caspar; Yiou, Pascal; Cooley, Daniel; Jomelli, Vincent

2005-08-01

Currently there is an increasing research activity in the area of climate extremes because they represent a key manifestation of non-linear systems and an enormous impact on economic and social human activities. Our understanding of the mean behavior of climate and its 'normal' variability has been improving significantly during the last decades. In comparison, climate extreme events have been hard to study and even harder to predict because they are, by definition, rare and obey different statistical laws than averages. In this context, the motivation for this paper is twofold. Firstly, we recall the basic principles of Extreme Value Theory that is used on a regular basis in finance and hydrology, but it still does not have the same success in climate studies. More precisely, the theoretical distributions of maxima and large peaks are recalled. The parameters of such distributions are estimated with the maximum likelihood estimation procedure that offers the flexibility to take into account explanatory variables in our analysis. Secondly, we detail three case-studies to show that this theory can provide a solid statistical foundation, specially when assessing the uncertainty associated with extreme events in a wide range of applications linked to the study of our climate. To cite this article: P. Naveau et al., C. R. Geoscience 337 (2005).

Spatial diffusion of influenza outbreak-related climate factors in Chiang Mai Province, Thailand.

PubMed

Nakapan, Supachai; Tripathi, Nitin Kumar; Tipdecho, Taravudh; Souris, Marc

2012-10-24

Influenza is one of the most important leading causes of respiratory illness in the countries located in the tropical areas of South East Asia and Thailand. In this study the climate factors associated with influenza incidence in Chiang Mai Province, Northern Thailand, were investigated. Identification of factors responsible for influenza outbreaks and the mapping of potential risk areas in Chiang Mai are long overdue. This work examines the association between yearly climate patterns between 2001 and 2008 and influenza outbreaks in the Chiang Mai Province. The climatic factors included the amount of rainfall, percent of rainy days, relative humidity, maximum, minimum temperatures and temperature difference. The study develops a statistical analysis to quantitatively assess the relationship between climate and influenza outbreaks and then evaluate its suitability for predicting influenza outbreaks. A multiple linear regression technique was used to fit the statistical model. The Inverse Distance Weighted (IDW) interpolation and Geographic Information System (GIS) techniques were used in mapping the spatial diffusion of influenza risk zones. The results show that there is a significance correlation between influenza outbreaks and climate factors for the majority of the studied area. A statistical analysis was conducted to assess the validity of the model comparing model outputs and actual outbreaks.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Application of web-GIS approach for climate change study

NASA Astrophysics Data System (ADS)

Okladnikov, Igor; Gordov, Evgeny; Titov, Alexander; Bogomolov, Vasily; Martynova, Yuliya; Shulgina, Tamara

2013-04-01

Georeferenced datasets 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 huge 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 web-GIS information-computational system for analysis of georeferenced climatological and meteorological data has been created. It is based on OGC standards and involves many modern solutions such as object-oriented programming model, modular composition, and JavaScript libraries based on GeoExt library, ExtJS Framework and OpenLayers software. The main advantage of the system lies in a possibility to perform mathematical and statistical data analysis, graphical visualization of results with GIS-functionality, and to prepare binary output files with just only a modern graphical web-browser installed on a common desktop computer connected to Internet. Several geophysical datasets represented by 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, DWD Global Precipitation Climatology Centre's data, GMAO Modern Era-Retrospective analysis for Research and Applications, meteorological observational data for the territory of the former USSR for the 20th century, results of modeling by global and regional climatological models, and others are available for processing by the system. And this list is extending. Also a functionality to run WRF and "Planet simulator" models was implemented in the system. Due to many preset parameters and limited time and spatial ranges set in the system these models have low computational power requirements and could be used in educational workflow for better understanding of basic climatological and meteorological processes. The Web-GIS information-computational system for geophysical data analysis provides specialists involved into multidisciplinary research projects with reliable and practical instruments for complex analysis of climate and ecosystems changes on global and regional scales. Using it even unskilled user without specific knowledge can perform computational processing and visualization of large meteorological, climatological and satellite monitoring datasets through unified web-interface in a common graphical web-browser. 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.

The Relationship between Organizational Climate and Quality of Chronic Disease Management

PubMed Central

Benzer, Justin K; Young, Gary; Stolzmann, Kelly; Osatuke, Katerine; Meterko, Mark; Caso, Allison; White, Bert; Mohr, David C

2011-01-01

Objective To test the utility of a two-dimensional model of organizational climate for explaining variation in diabetes care between primary care clinics. Data Sources/Study Setting Secondary data were obtained from 223 primary care clinics in the Department of Veterans Affairs health care system. Study Design Organizational climate was defined using the dimensions of task and relational climate. The association between primary care organizational climate and diabetes processes and intermediate outcomes were estimated for 4,539 patients in a cross-sectional study. Data Collection/Extraction Methods All data were collected from administrative datasets. The climate data were drawn from the 2007 VA All Employee Survey, and the outcomes data were collected as part of the VA External Peer Review Program. Climate data were aggregated to the facility level of analysis and merged with patient-level data. Principal Findings Relational climate was related to an increased likelihood of diabetes care process adherence, with significant but small effects for adherence to intermediate outcomes. Task climate was generally not shown to be related to adherence. Conclusions The role of relational climate in predicting the quality of chronic care was supported. Future research should examine the mediators and moderators of relational climate and further investigate task climate. PMID:21210799

Advances in risk assessment for climate change adaptation policy.

PubMed

Adger, W Neil; Brown, Iain; Surminski, Swenja

2018-06-13

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts.This article is part of the theme issue 'Advances in risk assessment for climate change adaptation policy'. © 2018 The Author(s).

Advances in risk assessment for climate change adaptation policy

NASA Astrophysics Data System (ADS)

Adger, W. Neil; Brown, Iain; Surminski, Swenja

2018-06-01

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. This article is part of the theme issue `Advances in risk assessment for climate change adaptation policy'.

Advances in risk assessment for climate change adaptation policy

PubMed Central

Adger, W. Neil; Brown, Iain; Surminski, Swenja

2018-01-01

Climate change risk assessment involves formal analysis of the consequences, likelihoods and responses to the impacts of climate change and the options for addressing these under societal constraints. Conventional approaches to risk assessment are challenged by the significant temporal and spatial dynamics of climate change; by the amplification of risks through societal preferences and values; and through the interaction of multiple risk factors. This paper introduces the theme issue by reviewing the current practice and frontiers of climate change risk assessment, with specific emphasis on the development of adaptation policy that aims to manage those risks. These frontiers include integrated assessments, dealing with climate risks across borders and scales, addressing systemic risks, and innovative co-production methods to prioritize solutions to climate challenges with decision-makers. By reviewing recent developments in the use of large-scale risk assessment for adaptation policy-making, we suggest a forward-looking research agenda to meet ongoing strategic policy requirements in local, national and international contexts. This article is part of the theme issue ‘Advances in risk assessment for climate change adaptation policy’. PMID:29712800

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.

Sensitivity of the regional climate in the Middle East and North Africa to volcanic perturbations

NASA Astrophysics Data System (ADS)

Dogar, Muhammad Mubashar; Stenchikov, Georgiy; Osipov, Sergey; Wyman, Bruce; Zhao, Ming

2017-08-01

The Middle East and North Africa (MENA) regional climate appears to be extremely sensitive to volcanic eruptions. Winter cooling after the 1991 Pinatubo eruption far exceeded the mean hemispheric temperature anomaly, even causing snowfall in Israel. To better understand MENA climate variability, the climate responses to the El Chichón and Pinatubo volcanic eruptions are analyzed using observations, NOAA/National Centers for Environmental Prediction Climate Forecast System Reanalysis, and output from the Geophysical Fluid Dynamics Laboratory's High-Resolution Atmospheric Model. A multiple regression analysis both for the observations and the model output is performed on seasonal summer and winter composites to separate out the contributions from climate trends, El Niño-Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), Indian summer monsoon, and volcanic aerosols. Strong regional temperature and precipitation responses over the MENA region are found in both winter and summer. The model and the observations both show that a positive NAO amplifies the MENA volcanic winter cooling. In boreal summer, the patterns of changing temperature and precipitation suggest a weakening and southward shift of the Intertropical Convergence Zone, caused by volcanic surface cooling and weakening of the Indian and West African monsoons. The model captures the main features of the climate response; however, it underestimates the total cooling, especially in winter, and exhibits a different spatial pattern of the NAO climate response in MENA compared to the observations. The conducted analysis sheds light on the internal mechanisms of MENA climate variability and helps to selectively diagnose the model deficiencies.

LandCaRe DSS--an interactive decision support system for climate change impact assessment and the analysis of potential agricultural land use adaptation strategies.

PubMed

Wenkel, Karl-Otto; Berg, Michael; Mirschel, Wilfried; Wieland, Ralf; Nendel, Claas; Köstner, Barbara

2013-09-01

Decision support to develop viable climate change adaptation strategies for agriculture and regional land use management encompasses a wide range of options and issues. Up to now, only a few suitable tools and methods have existed for farmers and regional stakeholders that support the process of decision-making in this field. The interactive model-based spatial information and decision support system LandCaRe DSS attempts to close the existing methodical gap. This system supports interactive spatial scenario simulations, multi-ensemble and multi-model simulations at the regional scale, as well as the complex impact assessment of potential land use adaptation strategies at the local scale. The system is connected to a local geo-database and via the internet to a climate data server. LandCaRe DSS uses a multitude of scale-specific ecological impact models, which are linked in various ways. At the local scale (farm scale), biophysical models are directly coupled with a farm economy calculator. New or alternative simulation models can easily be added, thanks to the innovative architecture and design of the DSS. Scenario simulations can be conducted with a reasonable amount of effort. The interactive LandCaRe DSS prototype also offers a variety of data analysis and visualisation tools, a help system for users and a farmer information system for climate adaptation in agriculture. This paper presents the theoretical background, the conceptual framework, and the structure and methodology behind LandCaRe DSS. Scenario studies at the regional and local scale for the two Eastern German regions of Uckermark (dry lowlands, 2600 km(2)) and Weißeritz (humid mountain area, 400 km(2)) were conducted in close cooperation with stakeholders to test the functionality of the DSS prototype. The system is gradually being transformed into a web version (http://www.landcare-dss.de) to ensure the broadest possible distribution of LandCaRe DSS to the public. The system will be continuously developed, updated and used in different research projects and as a learning and knowledge-sharing tool for students. The main objective of LandCaRe DSS is to provide information on the complex long-term impacts of climate change and on potential management options for adaptation by answering "what-if" type questions. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

Holocene climate variability in the western Mediterranean through a multiproxy analysis from Padul peat bog (Sierra Nevada, Spain)

NASA Astrophysics Data System (ADS)

Ramos-Román, María J.; Jiménez-Moreno, Gonzalo; Camuera, Jon; García-Alix, Antonio; Anderson, R. Scott; Jiménez-Espejo, Francisco J.; Sachse, Dirk

2017-04-01

The Iberian Peninsula, located in the Mediterranean area, is an interesting location for paleoclimate studies due to its geographic situation between arid and humid climates. Sediments from peat bogs and lakes from Sierra Nevada, in southeastern Iberian Peninsula, have been very informative in terms of how vegetation and wetland environments were impacted by Holocene climate change. These studies are essential if we want to understand the past climate change in the area, which is the key to identify the possible environmental response of the Sierra Nevada ecosystems to future climate scenarios. Padul basin, located in the southwest of the Sierra Nevada mountain range, contains a ca. 100 m-thick peat bog sedimentary sequence that was deposited during the past 1 Ma making this area interesting for paleoenvironmental and paleoclimatic reconstructions. A new 43 m-long sedimentary record has recently been retrieved from the Padul peat bog. In this study we have developed a multiproxy analysis of the Holocene part of the Padul-15-05 core including pollen analysis, XRF-core scanner, magnetic susceptibility and organic geochemistry, supported by an age control based on AMS radiocarbon dates, providing with information about vegetation and climate variability during the past 9.9 cal ka BP. This multiproxy reconstruction of the Padul-15-05 evidences the Mediterranean as a sensitive area with respect to global-scale climate system, showing relevant climate episodes such as the ca. 8, 7.5, 6.5 and 5.5 cal ka BP events during the early and middle Holocene. The trend to aridification to the late Holocene is interrupted by more arid and humid periods as the Iberian Roman Humid Period (from ca. 3 to 1.6 cal ka BP), the Dark Ages (from ca. 1.5 to 1.1 cal ka BP), the Medieval Climate Anomaly (from ca. 1.1 to 1.3 cal ka BP) and the Little Ice Age period (from ca. 500 to 100 cal yr BP).

Impact of climate change on European weather extremes

NASA Astrophysics Data System (ADS)

Duchez, Aurelie; Forryan, Alex; Hirschi, Joel; Sinha, Bablu; New, Adrian; Freychet, Nicolas; Scaife, Adam; Graham, Tim

2015-04-01

An emerging science consensus is that global climate change will result in more extreme weather events with concomitant increasing financial losses. Key questions that arise are: Can an upward trend in natural extreme events be recognised and predicted at the European scale? What are the key drivers within the climate system that are changing and making extreme weather events more frequent, more intense, or both? Using state-of-the-art coupled climate simulations from the UK Met Office (HadGEM3-GC2, historical and future scenario runs) as well as reanalysis data, we highlight the potential of the currently most advanced forecasting systems to progress understanding of the causative drivers of European weather extremes, and assess future frequency and intensity of extreme weather under various climate change scenarios. We characterize European extremes in these simulations using a subset of the 27 core indices for temperature and precipitation from The Expert Team on Climate Change Detection and Indices (Tank et al., 2009). We focus on temperature and precipitation extremes (e.g. extremes in daily and monthly precipitation and temperatures) and relate them to the atmospheric modes of variability over Europe in order to establish the large-scale atmospheric circulation patterns that are conducive to the occurrence of extreme precipitation and temperature events. Klein Tank, Albert M.G., and Francis W. Zwiers. Guidelines on Analysis of Extremes in a Changing Climate in Support of Informed Decisions for Adaptation. WMO-TD No. 1500. Climate Data and Monitoring. World Meteorological Organization, 2009.

Climate-driven polar motion

NASA Astrophysics Data System (ADS)

Celaya, Michael A.; Wahr, John M.; Bryan, Frank O.

1999-06-01

The output of a coupled climate system model provides a synthetic climate record with temporal and spatial coverage not attainable with observational data, allowing evaluation of climatic excitation of polar motion on timescales of months to decades. Analysis of the geodetically inferred Chandler excitation power shows that it has fluctuated by up to 90% since 1900 and that it has characteristics representative of a stationary Gaussian process. Our model-predicted climate excitation of the Chandler wobble also exhibits variable power comparable to the observed. Ocean currents and bottom pressure shifts acting together can alone drive the 14-month wobble. The same is true of the excitation generated by the combined effects of barometric pressure and winds. The oceanic and atmospheric contributions are this large because of a relatively high degree of constructive interference between seafloor pressure and currents and between atmospheric pressure and winds. In contrast, excitation by the redistribution of water on land appears largely insignificant. Not surprisingly, the full climate effect is even more capable of driving the wobble than the effects of the oceans or atmosphere alone are. Our match to the observed annual excitation is also improved, by about 17%, over previous estimates made with historical climate data. Efforts to explain the 30-year Markowitz wobble meet with less success. Even so, at periods ranging from months to decades, excitation generated by a model of a coupled climate system makes a close approximation to the amplitude of what is geodetically observed.

Passive-solar homes for Texas

NASA Astrophysics Data System (ADS)

Garrison, M. L.

1982-06-01

Acceptance of passive solar technologies has been slow within the conventional building trades in Texas because it is a common misconception that solar is expensive, and data on local applications is severely limited or nonexistent. It is the purpose of this solar development to move passive solar design into the mainstream of public acceptance by helping to overcome and eliminate these barriers. Specifically, the goal is to develop a set of regional climatic building standards to help guide the conventional building trade toward the utilization of soft energy systems which will reduce overall consumption at a price and convenience most Texans can afford. To meet this objective, eight sample passive design structures are presented. These designs represent state of the art regional applications of passive solar space conditioning. The methodology used in the passive solar design process included: analysis of regional climatic data; analysis of historical regional building prototypes; determination of regional climatic design priorities and assets; prototypical design models for the discretionary housing market; quantitative thermal analysis of prototypical designs; and construction drawings of building prototypes.

El Niño$-$Southern Oscillation frequency cascade

DOE PAGES

Stuecker, Malte F.; Jin, Fei -Fei; Timmermann, Axel

2015-10-19

The El Niño$-$Southern Oscillation (ENSO) phenomenon, the most pronounced feature of internally generated climate variability, occurs on interannual timescales and impacts the global climate system through an interaction with the annual cycle. The tight coupling between ENSO and the annual cycle is particularly pronounced over the tropical Western Pacific. In this paper, we show that this nonlinear interaction results in a frequency cascade in the atmospheric circulation, which is characterized by deterministic high-frequency variability on near-annual and subannual timescales. Finally, through climate model experiments and observational analysis, it is documented that a substantial fraction of the anomalous Northwest Pacific anticyclonemore » variability, which is the main atmospheric link between ENSO and the East Asian Monsoon system, can be explained by these interactions and is thus deterministic and potentially predictable.« less

El Niño$-$Southern Oscillation frequency cascade

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

Stuecker, Malte F.; Jin, Fei -Fei; Timmermann, Axel

The El Niño$-$Southern Oscillation (ENSO) phenomenon, the most pronounced feature of internally generated climate variability, occurs on interannual timescales and impacts the global climate system through an interaction with the annual cycle. The tight coupling between ENSO and the annual cycle is particularly pronounced over the tropical Western Pacific. In this paper, we show that this nonlinear interaction results in a frequency cascade in the atmospheric circulation, which is characterized by deterministic high-frequency variability on near-annual and subannual timescales. Finally, through climate model experiments and observational analysis, it is documented that a substantial fraction of the anomalous Northwest Pacific anticyclonemore » variability, which is the main atmospheric link between ENSO and the East Asian Monsoon system, can be explained by these interactions and is thus deterministic and potentially predictable.« less

NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.

2004-01-01

Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a multi-year, 1 x 1 TRMM re-analysis , which assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using a ID variational continuous assimilation (VCA) procedure in the GEOS-3 global data assimilation system. The analysis period extends from 1 November 1997 through 3 1 December 2002. The goal is to produce a multi-year global analysis that is dynamically consistent with available tropical precipitation observations for the community to assess its utility in climate applications and identify areas for further improvements. A distinct feature of the GEOS-3RRMh4 re-analysis is that its precipitation analysis is not derived from a short-term forecast (as done in most operational systems) but is given by a time- continuous model integration constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields are allowed to directly respond to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, I will assess the impact VCA precipitation assimilation on analyses of climate signals ranging from a few weeks to interannual time scales and compare results against other operational and reanalysis products.

Maximum warming occurs about one decade after carbon dioxide emission

NASA Astrophysics Data System (ADS)

Ricke, K.; Caldeira, K.

2014-12-01

There has been a long tradition of estimating the amount of climate change that would result from various carbon dioxide emission or concentration scenarios but there has been relatively little quantitative analysis of how long it takes to feel the consequences of an individual carbon dioxide emission. Using conjoined results of recent carbon-cycle and physical-climate model intercomparison projects, we find the median time between an emission and maximum warming is 10.1 years, with a 90% probability range of 6.6 to 30.7 years. We evaluate uncertainties in timing and amount of warming, partitioning them into three contributing factors: carbon cycle, climate sensitivity and ocean thermal inertia. To characterize the carbon cycle uncertainty associated with the global temperature response to a carbon dioxide emission today, we use fits to the time series of carbon dioxide concentrations from a CO2-impulse response function model intercomparison project's 15 ensemble members (1). To characterize both the uncertainty in climate sensitivity and in the thermal inertia of the climate system, we use fits to the time series of global temperature change from the Coupled Model Intercomparison Project phase 5 (CMIP5; 2) abrupt4xco2 experiment's 20 ensemble's members separating the effects of each uncertainty factors using one of two simple physical models for each CMIP5 climate model. This yields 6,000 possible combinations of these three factors using a standard convolution integral approach. Our results indicate that benefits of avoided climate damage from avoided CO2 emissions will be manifested within the lifetimes of people who acted to avoid that emission. While the relevant time lags imposed by the climate system are substantially shorter than a human lifetime, they are substantially longer than the typical political election cycle, making the delay and its associated uncertainties both economically and politically significant. References: 1. Joos F et al. (2013) Carbon dioxide and climate impulse response functions for the computation of greenhouse gas metrics: a multi-model analysis. Atmos Chem Phys 13:2793-2825. 2. Taylor KE, Stouffer RJ, Meehl GA (2011) An Overview of CMIP5 and the Experiment Design. Bull Am Meteorol Soc 93:485-498.

Adaptation responses to increasing drought frequency

NASA Astrophysics Data System (ADS)

Loch, A. J.; Adamson, D. C.; Schwabe, K.

2016-12-01

Using state contingent analysis we discuss how and why irrigators adapt to alternative water supply signals. This analysis approach helps to illustrate how and why producers currently use state-general and state-allocable inputs to adapt and respond to known and possible future climatic alternative natures. Focusing on the timing of water allocations, we explore inherent differences in the demand for water by two key irrigation sectors: annual and perennial producers which in Australia have allowed a significant degree of risk-minimisation during droughts. In the absence of land constraints, producers also had a capacity to respond to positive state outcomes and achieve super-normal profits. In the future, however, the probability of positive state outcomes is uncertain; production systems may need to adapt to minimise losses and/or achieve positive returns under altered water supply conditions that may arise as a consequence of more frequent drought states. As such, producers must assess whether altering current input/output choice sets in response to possible future climate states will enhance their long-run competitive advantage for both expected new normal and extreme water supply outcomes. Further, policy supporting agricultural sector climate change resilience must avoid poorly-designed strategies that increase producer vulnerability in the face of drought. Our analysis explores the reliability of alternative water property right bundles and how reduced allocations across time influence alternative responses by producers. We then extend our analysis to explore how management strategies could adapt to two possible future drier state types: i) where an average reduction in water supply is experienced; and ii) where the frequency of droughts increase. The combination of these findings are subsequently used to discuss the role water reform policy has to deal with current and future climate scenarios. We argue current policy strategies could drive producers to more homogeneous production systems over time, which ultimately entail risky adaptation options under future water supply availability or increased drought frequency scenarios. Lastly, our analysis has shown the flexibility of applying SCA toward examining uncertainty surrounding future states of nature under climate change.

Seasonal scale water deficit forecasting in Africa and the Middle East using NASA's Land Information System (LIS)

NASA Astrophysics Data System (ADS)

Peters-Lidard, C. D.; Arsenault, K. R.; Shukla, S.; Getirana, A.; McNally, A.; Koster, R. D.; Zaitchik, B. F.; Badr, H. S.; Roningen, J. M.; Kumar, S.; Funk, C. C.

2017-12-01

A seamless and effective water deficit monitoring and early warning system is critical for assessing food security in Africa and the Middle East. In this presentation, we report on the ongoing development and validation of a seasonal scale water deficit forecasting system based on NASA's Land Information System (LIS) and seasonal climate forecasts. First, our presentation will focus on the implementation and validation of drought and water availability monitoring products in the region. Next, it will focus on evaluating drought and water availability forecasts. Finally, details will be provided of our ongoing collaboration with end-user partners in the region (e.g., USAID's Famine Early Warning Systems Network, FEWS NET), on formulating meaningful early warning indicators, effective communication and seamless dissemination of the products through NASA's web-services. The water deficit forecasting system thus far incorporates NASA GMAO's Catchment and the Noah Multi-Physics (MP) LSMs. In addition, the LSMs' surface and subsurface runoff are routed through the Hydrological Modeling and Analysis Platform (HyMAP) to simulate surface water dynamics. To establish a climatology from 1981-2015, the two LSMs are driven by NASA/GMAO's Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2), and the USGS and UCSB Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) daily rainfall dataset. Comparison of the models' energy and hydrological budgets with independent observations suggests that major droughts are well-reflected in the climatology. The system uses seasonal climate forecasts from NASA's GEOS-5 (the Goddard Earth Observing System Model-5) and NCEP's Climate Forecast System-2, and it produces forecasts of soil moisture, ET and streamflow out to 6 months in the future. Forecasts of those variables are formulated in terms of indicators to provide forecasts of drought and water availability in the region. Current work suggests that for the Blue Nile basin, (1) the combination of GEOS-5 and CFSv2 is equivalent in skill to the full North American Multimodel Ensemble (NMME); and (2) the seasonal water deficit forecasting system skill for both soil moisture and streamflow anomalies is greater than the standard Ensemble Streamflow Prediction (ESP) approach.

Cluster analysis of Southeastern U.S. climate stations

NASA Astrophysics Data System (ADS)

Stooksbury, D. E.; Michaels, P. J.

1991-09-01

A two-step cluster analysis of 449 Southeastern climate stations is used to objectively determine general climate clusters (groups of climate stations) for eight southeastern states. The purpose is objectively to define regions of climatic homogeneity that should perform more robustly in subsequent climatic impact models. This type of analysis has been successfully used in many related climate research problems including the determination of corn/climate districts in Iowa (Ortiz-Valdez, 1985) and the classification of synoptic climate types (Davis, 1988). These general climate clusters may be more appropriate for climate research than the standard climate divisions (CD) groupings of climate stations, which are modifications of the agro-economic United States Department of Agriculture crop reporting districts. Unlike the CD's, these objectively determined climate clusters are not restricted by state borders and thus have reduced multicollinearity which makes them more appropriate for the study of the impact of climate and climatic change.

Consideration of future climatic changes in three geologic settings

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

Petrie, G.M.

Staff at Pacific Northwest Laboratory are evaluating the potential for climatic change to affect the integrity of a nuclear waste repository at: (1) the Gibson Dome area of Utah; (2) the Palo Duro Basin of Texas; and (3) the Gulf Coast. Because a major assumption in this analysis is that a glacial age will recur, the climate of the last glacial period is examined for each location. Combining these paleoclimatic data with the current climatic data, each location is evaluated in light of the criteria given in Draft Revised General Guidelines for Recommendation of Sites for Nuclear Waste Repositories (10more » CFR 960). The results of this analysis suggest that sites located in these areas are likely to meet the climate requirements set forth in the guidelines. However, further study is needed before a definitive statement can be made. In particular, modeling the effect of sea level change on the Gulf Coast groundwater system and obtaining an improved estimation for the increase in recharge during glacier times at the Texas and Utah locations would be useful. Several stragegies are presented for accomplishing this work. 94 references, 27 figures, 5 tables.« less

Remote Sensing the Thermal and Humidity Structure of the Earth's Atmosphere Using the GPS Radio Occultation Technique: Applications in Climate Studies

NASA Astrophysics Data System (ADS)

Vergados, P.; Mannucci, A. J.; Ao, C. O.; Verkhoglyadova, O. P.; Iijima, B.

2017-12-01

This presentation introduces the fundamentals of the Global Positioning System radio occultation (GPS RO) remote sensing technique in retrieving atmospheric temperature and humidity information and presents the use of these observations in climate research. Our objective is to demonstrate and establish the GPS RO remote sensing technique as a complementary data set to existing state-of-the-art space-based platforms for climate studies. We show how GPS RO measurements at 1.2-1.6 GHz frequency band can be used to infer the upper tropospheric water vapor and temperature feedbacks and we present a decade-long specific humidity (SH) record from January 2007 until December 2015. We cross-compare the GPS RO-estimated climate feedbacks and the SH long-record with independent data sets from the Modern-Era Retrospective Analysis for Research and Applications (MERRA), the European Center for Medium-range Weather Forecasts Re-Analysis Interim (ERA-Interim), and the Atmospheric Infrared Sounder (AIRS) instrument. These cross-comparisons serve as a performance guide for the GPS-RO observations with respect to other data sets by providing an independent measure of climate feedbacks and humidity short-term trends.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Lucas, D. D.; Klein, R.; Tannahill, J.; Ivanova, D.; Brandon, S.; Domyancic, D.; Zhang, Y.

2013-08-01

Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models.

Assessing water resource system vulnerability to unprecedented hydrological drought using copulas to characterize drought duration and deficit

PubMed Central

Pflug, Georg; Hall, Jim W.; Hochrainer‐Stigler, Stefan

2015-01-01

Abstract Global climate models suggest an increase in evapotranspiration, changing storm tracks, and moisture delivery in many parts of the world, which are likely to cause more prolonged and severe drought, yet the weakness of climate models in modeling persistence of hydroclimatic variables and the uncertainties associated with regional climate projections mean that impact assessments based on climate model output may underestimate the risk of multiyear droughts. In this paper, we propose a vulnerability‐based approach to test water resource system response to drought. We generate a large number of synthetic streamflow series with different drought durations and deficits and use them as input to a water resource system model. Marginal distributions of the streamflow for each month are generated by bootstrapping the historical data, while the joint probability distributions of consecutive months are constructed using a copula‐based method. Droughts with longer durations and larger deficits than the observed record are generated by perturbing the copula parameter and by adopting an importance sampling strategy for low flows. In this way, potential climate‐induced changes in monthly hydrological persistence are factored into the vulnerability analysis. The method is applied to the London water system (England) to investigate under which drought conditions severe water use restrictions would need to be imposed. Results indicate that the water system is vulnerable to drought conditions outside the range of historical events. The vulnerability assessment results were coupled with climate model information to compare alternative water management options with respect to their vulnerability to increasingly long and severe drought. PMID:27609995

Modelling the mid-Pliocene Warm Period with the IPSLGCM: contribution to PlioMIP and feedback mechanisms from the presence of mega-lakes

NASA Astrophysics Data System (ADS)

Contoux, C.; Jost, A.; Sepulchre, P.; Ramstein, G.

2012-04-01

The mid-Pliocene Warm Period (mPWP, ca. 3.3 -3 Ma) is the last geological period showing a warmer climate than the preindustrial during a sustained period of time, much longer than interglacial periods of the last million years. Moreover, mPWP position of the continents and atmospheric pCO2 are very close to present-day, both conditions making the mPWP a relevant analogue for future global warming. For these reasons, the mPWP has been the focus of Pliocene Modelling Intercomparison Project (PlioMIP), which associates data analysis and modelling. We use the IPSLCM5 Earth System model and its atmospheric component alone (LMDZ), to simulate the climate of the mPWP. Boundary conditions such as sea surface temperatures (SSTs), topography, ice sheet extent and vegetation are the ones used within the PlioMIP framework. On a global scale we show the impact of different boundary conditions with LMDZ, and of a global coupling on the simulated climate. Results from the Earth System model are also compared to SST reconstructions, particularly in the North Atlantic Ocean, where an important warming occurs, generally poorly reproduced by models. These results will then be part of the multi-model analysis for the Pliocene. The PlioMIP exercise is also about better understanding model/data mismatches. In the present-day desertic regions of Lake Chad (Africa) and Lake Eyre (Australia), vegetation data show the presence of tropical savanna at the expense of deserts during the mPWP. Vegetation models forced by mPWP climatic simulations fail to reproduce more humid vegetation in these locations. There might be a reason for this model/data discrepancy: geological data stand for the presence of mega-lakes in these two regions during the mPWP that are not accounted for in previous simulations. Such extended waterbodies could have important feedbacks on the hydrological cycle and regional climate. We use the LMDZ4 atmospheric model imbedding explicitly resolved lake surfaces to simulate the climate under mega-lake conditions, using a zoom on the regions of interest. This allows us to determine the viability of such waterbodies under mid-Pliocene climatic conditions as well as their feedbacks on the climate system.

Using Geographic Information Systems to Evaluate Energy Initiatives in Austere Environments

DTIC Science & Technology

2013-03-01

conducting economic analysis of energy reduction initiatives. This research examined the energy savings potential of improving the thermal properties...shelter improvements in any climate and location in the world. Specifically, solar flies developed through Solar Integrated Power Shelter System...94 Improvements to the Existing Model

Development of web-GIS system for analysis of georeferenced geophysical data

NASA Astrophysics Data System (ADS)

Okladnikov, I.; Gordov, E. P.; Titov, A. G.; Bogomolov, V. Y.; Genina, E.; Martynova, Y.; Shulgina, T. M.

2012-12-01

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 huge 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 web-GIS information-computational system for analysis of georeferenced climatological and meteorological data has been created. The information-computational system consists of 4 basic parts: computational kernel developed using GNU Data Language (GDL), a set of PHP-controllers run within specialized web-portal, JavaScript class libraries for development of typical components of web mapping application graphical user interface (GUI) based on AJAX technology, and an archive of geophysical datasets. Computational kernel comprises of a number of dedicated modules for querying and extraction of data, mathematical and statistical data analysis, visualization, and preparing output files in geoTIFF and netCDF format containing processing results. Specialized web-portal consists of a 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 libraries aiming at graphical user interface development are based on GeoExt library combining ExtJS Framework and OpenLayers software. The archive of geophysical data consists of a number of structured environmental datasets represented by data files in netCDF, HDF, GRIB, ESRI Shapefile formats. For processing by the system are available: 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, DWD Global Precipitation Climatology Centre's data, GMAO Modern Era-Retrospective analysis for Research and Applications, meteorological observational data for the territory of the former USSR for the 20th century, results of modeling by global and regional climatological models, and others. 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 Web-GIS information-computational system for geophysical data analysis provides specialists involved into multidisciplinary research projects with reliable and practical instruments for complex analysis of climate and ecosystems changes on global and regional scales. Using it even unskilled user without specific knowledge can perform computational processing and visualization of large meteorological, climatological and satellite monitoring datasets through unified web-interface in a common graphical web-browser. This work is partially supported by the Ministry of education and science of the Russian Federation (contract #07.514.114044), projects IV.31.1.5, IV.31.2.7, RFBR grants #10-07-00547a, #11-05-01190a, and integrated project SB RAS #131.

Seasonal Forecast Skill And Teleconnections Over East Africa

NASA Astrophysics Data System (ADS)

MacLeod, D.; Palmer, T.

2017-12-01

Many people living in East Africa are significantly exposed to risks arising from climate variability. The region experiences two rainy seasons and poor performance of either or both of these (such as seen recently in 2016/17) reduces agricultural productivity and threatens food security. In combination with other factors this can lead to famine. By utilizing seasonal climate forecasts, preparatory actions can be taken in order to mitigate the risks arising from such climate variability. As part of the project ForPAc: "Towards forecast-based preparedness action", we are working with humanitarian agencies in Kenya to build such early warning systems on subseasonal-to-seasonal timescales. Here, the seasonal predictability and forecast skill of the two East African rainy seasons will be presented. Results from the new ECMWF operational forecasting system SEAS5 will be shown and compared to the previous System 4. Analysis of a new 110 year long atmosphere-only simulation will also be discussed, demonstrating impacts of atmosphere-ocean coupling as well as putting operational forecast skill in a long-term context. Particular focus will be given to the model representation of teleconnections of seasonal climate with global sea surface temperatures; highlighting sources of forecast error and informing future model development.

Studying Climate Response to Forcing by the Nonlinear Dynamical Mode Decomposition

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Projected climate change impacts and short term predictions on staple crops in Sub-Saharan Africa

NASA Astrophysics Data System (ADS)

Mereu, V.; Spano, D.; Gallo, A.; Carboni, G.

2013-12-01

Agriculture in Sub-Saharan Africa (SSA) drives the economy of many African countries and it is mainly rain-fed agriculture used for subsistence. Increasing temperatures, changed precipitation patterns and more frequent droughts may lead to a substantial decrease of crop yields. The projected impacts of future climate change on agriculture are expected to be significant and extensive in the SSA due to the shortening of the growing seasons and the increasing of water-stress risk. Differences in Agro-Ecological Zones and geographical characteristics of SSA influence the diverse impacts of climate change, which can greatly differ across the continent and within countries. The vulnerability of African Countries to climate change is aggravated by the low adaptive capacity of the continent, due to the increasing of its population, the widespread poverty, and other social factors. In this contest, the assessment of climate change impact on agricultural sector has a particular interest to stakeholder and policy makers, in order to identify specific agricultural sectors and Agro-Ecological Zones that could be more vulnerable to changes in climatic conditions and to develop the most appropriate policies to cope with these threats. For these reasons, the evaluation of climate change impacts for key crops in SSA was made exploring climate uncertainty and focusing on short period monitoring, which is particularly useful for food security and risk management analysis. The DSSAT-CSM (Decision Support System for Agrotechnology Transfer - Cropping System Model) software, version 4.5 was used for the analysis. Crop simulation models included in DSSAT-CSM are tools that allow to simulate physiological process of crop growth, development and production, by combining genetic crop characteristics and environmental (soil and weather) conditions. For each selected crop, the models were used, after a parameterization phase, to evaluate climate change impacts on crop phenology and production. Multiple combinations of soils and climate conditions, crop management and varieties were considered for the different Agro-Ecological Zones. The climate impact was assessed using future climate prediction, statistically and/or dynamically downscaled, for specific areas. Direct and indirect effects of different CO2 concentrations projected for the future periods were separately explored to estimate their effects on crops. Several adaptation strategies (e.g., introduction of full irrigation, shift of the ordinary sowing/planting date, changes in the ordinary fertilization management) were also evaluated with the aim to reduce the negative impact of climate change on crop production. The results of the study, analyzed at local, AEZ and country level, will be discussed.

Meeting the Radiative Forcing Targets of the Representative Concentration Pathways with Agricultural Climate Impacts

NASA Astrophysics Data System (ADS)

Kyle, P.; Müller, C.; Calvin, K. V.; Thomson, A. M.

2013-12-01

The Representative Concentration Pathways (RCPs) have formed the basis for much of the current scientific understanding of future climate change impacts and mitigation. However, the emissions scenarios underlying the RCPs were produced by integrated assessment models that did not include impacts of future climate change on the modeled evolution of the agricultural and energy systems. Given the prominent role of bioenergy in greenhouse gas emissions mitigation, and given the importance of land-use-related emissions in determining future atmospheric CO2 concentrations, it is possible that agricultural climate impacts may cause significant changes to the means and costs of mitigating greenhouse gas emissions. This study builds on several international modeling exercises aimed at improving understanding of climate change impacts--CMIP-5 and ISI-MIP--that have generated global gridded climate impacts on yields of major agricultural crops in each of the four RCPs. We use the climate outcomes from the HadGEM2-ES climate model, and the agricultural yield outcomes from the LPJmL crop growth model to inform inputs to the GCAM integrated assessment model, allowing analysis of how agricultural climate impacts may affect the long-term global and regional strategies for achieving the greenhouse gas concentration pathways of the RCPs. Our results indicate that for this combination of models and emissions scenarios, strongly negative climate impacts on several major commodity classes--prominently cereals and oil seeds, and particularly in the high-radiative-forcing RCPs--lead to a long-term increase in cropland and therefore land-use-related CO2 emissions. All else equal, this increases the emissions mitigation burden on the rest of the system, and therefore increases total net costs of emissions mitigation. However, the future climate change impacts on C4 bioenergy crops tend to be positive, limiting the shock of agricultural climate impacts on the modeled energy supply and demand systems. As well, endogenous adaptation in the agricultural sector--mostly through inter-regional shifting in production and changes in trade patterns--limits the shock of climate impacts to consumers. Global average climate impacts on wheat yields for the four emissions scenarios, using base-year weights (asterisks) and using the endogenous land allocations in GCAM (filled diamonds)

To what extent can global warming events influence scaling properties of climatic fluctuations in glacial periods?

NASA Astrophysics Data System (ADS)

Alberti, Tommaso; Lepreti, Fabio; Vecchio, Antonio; Carbone, Vincenzo

2017-04-01

The Earth's climate is an extremely unstable complex system consisting of nonlinear and still rather unknown interactions among atmosphere, land surface, ice and oceans. The system is mainly driven by solar irradiance, even if internal components as volcanic eruptions and human activities affect the atmospheric composition thus acting as a driver for climate changes. Since the extreme climate variability is the result of a set of phenomena operating from daily to multi-millennial timescales, with different correlation times, a study of the scaling properties of the system can evidence non-trivial persistent structures, internal or external physical processes. Recently, the scaling properties of the paleoclimate changes have been analyzed by distinguish between interglacial and glacial climates [Shao and Ditlevsen, 2016]. The results show that the last glacial record (20-120 kyr BP) presents some elements of multifractality, while the last interglacial period (0-10 kyr BP), say the Holocene period, seems to be characterized by a mono-fractal structure. This is associated to the absence of Dansgaard-Oeschger (DO) events in the interglacial climate that could be the cause for the absence of multifractality. This hypothesis is supported by the analysis of the period between 18 and 27 kyr BP, i.e. during the Last Glacial Period, in which a single DO event have been registred. Through the Empirical Mode Decomposition (EMD) we were able to detect a timescale separation within the Last Glacial Period (20-120 kyr BP) in two main components: a high-frequency component, related to the occurrence of DO events, and a low-frequency one, associated to the cooling/warming phase switch [Alberti et al., 2014]. Here, we investigate the scaling properties of the climate fluctuations within the Last Glacial Period, where abrupt climate changes, characterized by fast increase of temperature usually called Dansgaard-Oeschger (DO) events, have been particularly pronounced. By using the MultiFractal Detrended Fluctuation Analysis (MF-DFA), we show that a multifractal structure exists for both high- and low-frequency fluctuations in Northern and Southern hemispheres, with different scaling exponents, thus indicating a long-range persistence of the climatic variability within the whole Last Glacial Period. Our results evidence that both DO events and cooling/warming cycles must be considered as processes of the internal component of the Earth's climate, rather than processes related to external forcings. This study should be helpful for investigation of the internal origin of climate changes. References Shao, Z.G. and Ditlevsen, P.D., Nature Commun., 7, 10951, (2016). Alberti, T., Lepreti, F., Vecchio, A., Bevacqua, E., Capparelli, V. and Carbone, V., Clim. Past, 10, 1751 (2014).

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

PubMed

Scolozzi, Rocco; Geneletti, Davide

2017-02-01

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

Multicentury changes in ocean and land contributions to the climate-carbon feedback

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

Randerson, J. T.; Lindsay, K.; Munoz, E.

Improved constraints on carbon cycle responses to climate change are needed to inform mitigation policy, yet our understanding of how these responses may evolve after 2100 remains highly uncertain. Using the Community Earth System Model (v1.0), we quantified climate-carbon feedbacks from 1850 to 2300 for the Representative Concentration Pathway 8.5 and its extension. In three simulations, land and ocean biogeochemical processes experienced the same trajectory of increasing atmospheric CO 2. Each simulation had a different degree of radiative coupling for CO 2 and other greenhouse gases and aerosols, enabling diagnosis of feedbacks. In a fully coupled simulation, global mean surfacemore » air temperature increased by 9.3 K from 1850 to 2300, with 4.4 K of this warming occurring after 2100. Excluding CO 2, warming from other greenhouse gases and aerosols was 1.6 K by 2300, near a 2 K target needed to avoid dangerous anthropogenic interference with the climate system. Ocean contributions to the climate-carbon feedback increased considerably over time and exceeded contributions from land after 2100. The sensitivity of ocean carbon to climate change was found to be proportional to changes in ocean heat content, as a consequence of this heat modifying transport pathways for anthropogenic CO 2 inflow and solubility of dissolved inorganic carbon. By 2300, climate change reduced cumulative ocean uptake by 330 Pg C, from 1410 Pg C to 1080 Pg C. Land fluxes similarly diverged over time, with climate change reducing stocks by 232 Pg C. Regional influence of climate change on carbon stocks was largest in the North Atlantic Ocean and tropical forests of South America. Our analysis suggests that after 2100, oceans may become as important as terrestrial ecosystems in regulating the magnitude of the climate-carbon feedback.« less

Multicentury changes in ocean and land contributions to the climate-carbon feedback

NASA Astrophysics Data System (ADS)

Randerson, J. T.; Lindsay, K.; Munoz, E.; Fu, W.; Moore, J. K.; Hoffman, F. M.; Mahowald, N. M.; Doney, S. C.

2015-06-01

Improved constraints on carbon cycle responses to climate change are needed to inform mitigation policy, yet our understanding of how these responses may evolve after 2100 remains highly uncertain. Using the Community Earth System Model (v1.0), we quantified climate-carbon feedbacks from 1850 to 2300 for the Representative Concentration Pathway 8.5 and its extension. In three simulations, land and ocean biogeochemical processes experienced the same trajectory of increasing atmospheric CO2. Each simulation had a different degree of radiative coupling for CO2 and other greenhouse gases and aerosols, enabling diagnosis of feedbacks. In a fully coupled simulation, global mean surface air temperature increased by 9.3 K from 1850 to 2300, with 4.4 K of this warming occurring after 2100. Excluding CO2, warming from other greenhouse gases and aerosols was 1.6 K by 2300, near a 2 K target needed to avoid dangerous anthropogenic interference with the climate system. Ocean contributions to the climate-carbon feedback increased considerably over time and exceeded contributions from land after 2100. The sensitivity of ocean carbon to climate change was found to be proportional to changes in ocean heat content, as a consequence of this heat modifying transport pathways for anthropogenic CO2 inflow and solubility of dissolved inorganic carbon. By 2300, climate change reduced cumulative ocean uptake by 330 Pg C, from 1410 Pg C to 1080 Pg C. Land fluxes similarly diverged over time, with climate change reducing stocks by 232 Pg C. Regional influence of climate change on carbon stocks was largest in the North Atlantic Ocean and tropical forests of South America. Our analysis suggests that after 2100, oceans may become as important as terrestrial ecosystems in regulating the magnitude of the climate-carbon feedback.

Conceptualizing Climate Change in the Context of a Climate System: Implications for Climate and Environmental Education

ERIC Educational Resources Information Center

Shepardson, Daniel P.; Niyogi, Dev; Roychoudhury, Anita; Hirsch, Andrew

2012-01-01

Today there is much interest in teaching secondary students about climate change. Much of this effort has focused directly on students' understanding of climate change. We hypothesize, however, that in order for students to understand climate change they must first understand climate as a system and how changes to this system due to both natural…

From petascale to exascale, the future of simulated climate data (Invited)

NASA Astrophysics Data System (ADS)

Lawrence, B.; Juckes, M. N.

2013-12-01

Coleridge ought to have said: data, data, everywhere, and all the data centres groan, data data everywhere, nor any I should clone. Except of course, he didn't say it, and we do clone data! While we've been dealing with terabytes of simulated datasets, downloading ("cloning") and analysing, has been a plausible way forward. In doing so, we have set up systems that support four broad classes of activities: personal and institutional data analysis, federated data systems, and data portals. We use metadata to manage the migration of data between these (and their communities) and we have built software systems. However, our metadata and software solutions are fragile, often based on soft money, and loose governance arrangements. We often download data with minimal provenance, and often many of us download the same data. In the not too distant future we can imagine exabytes of data being produced, and all these problems will get worse. Arguably we have no plausible methods of effectively exploiting such data - particularly if the analysis requires intercomparison. Yet of course, we know full well that intercomparison is at the heart of climate science. In this talk, we review the current status of simulation data management, with special emphasis on accessibility and usability. We talk about file formats, bundles of files, real and virtual, and simulation metadata. We introduce the InfraStructure for the European Network for Earth Simulation (IS-ENES) and its relationship with the Earth System Grid Federation (ESGF) as well as JASMIN, the UK Joint Analysis System. There will be a small digression on parallel data analysis - locally and distributed. we then progress to the near term problems (and solutions) for climate data before scoping out the problems of the future, both for data handling, and the models that produce the data. The way we think about data, computing, models, even ensemble design, may need to change.

Temporal Variability of Observed and Simulated Hyperspectral Earth Reflectance

NASA Technical Reports Server (NTRS)

Roberts, Yolanda; Pilewskie, Peter; Kindel, Bruce; Feldman, Daniel; Collins, William D.

2012-01-01

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) is a climate observation system designed to study Earth's climate variability with unprecedented absolute radiometric accuracy and SI traceability. Observation System Simulation Experiments (OSSEs) were developed using GCM output and MODTRAN to simulate CLARREO reflectance measurements during the 21st century as a design tool for the CLARREO hyperspectral shortwave imager. With OSSE simulations of hyperspectral reflectance, Feldman et al. [2011a,b] found that shortwave reflectance is able to detect changes in climate variables during the 21st century and improve time-to-detection compared to broadband measurements. The OSSE has been a powerful tool in the design of the CLARREO imager and for understanding the effect of climate change on the spectral variability of reflectance, but it is important to evaluate how well the OSSE simulates the Earth's present-day spectral variability. For this evaluation we have used hyperspectral reflectance measurements from the Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY), a shortwave spectrometer that was operational between March 2002 and April 2012. To study the spectral variability of SCIAMACHY-measured and OSSE-simulated reflectance, we used principal component analysis (PCA), a spectral decomposition technique that identifies dominant modes of variability in a multivariate data set. Using quantitative comparisons of the OSSE and SCIAMACHY PCs, we have quantified how well the OSSE captures the spectral variability of Earth?s climate system at the beginning of the 21st century relative to SCIAMACHY measurements. These results showed that the OSSE and SCIAMACHY data sets share over 99% of their total variance in 2004. Using the PCs and the temporally distributed reflectance spectra projected onto the PCs (PC scores), we can study the temporal variability of the observed and simulated reflectance spectra. Multivariate time series analysis of the PC scores using techniques such as Singular Spectrum Analysis (SSA) and Multichannel SSA will provide information about the temporal variability of the dominant variables. Quantitative comparison techniques can evaluate how well the OSSE reproduces the temporal variability observed by SCIAMACHY spectral reflectance measurements during the first decade of the 21st century. PCA of OSSE-simulated reflectance can also be used to study how the dominant spectral variables change on centennial scales for forced and unforced climate change scenarios. To have confidence in OSSE predictions of the spectral variability of hyperspectral reflectance, it is first necessary for us to evaluate the degree to which the OSSE simulations are able to reproduce the Earth?s present-day spectral variability.

Arctic Indicators of Change

NASA Astrophysics Data System (ADS)

Stanitski, D.; Druckenmiller, M.; Fetterer, F. M.; Gerst, M.; Intrieri, J. M.; Kenney, M. A.; Meier, W.; Overland, J. E.; Stroeve, J. C.; Trainor, S.

2016-12-01

The Arctic is undergoing unprecedented change. Indicators of change enable better decision-making at the community to policy levels. The results presented here focus on a subset of physical, biological, societal, and economic indicators of Arctic change recommended in one of a group of papers emanating from the earlier National Climate Indicators System (NCIS) work led by Kenney et al. (2016). The intent of the NCIS was to establish a "system of physical, natural, and societal indicators that communicate and inform decisions about key aspects of the physical climate, climate impacts, vulnerabilities, and preparedness" in support of the sustained U.S. National Climate Assessment. Our analysis, guided by a tailored selection and recommendation criteria, resulted in a list of "existing" indicators, as well as those "in development", "recommended", and "aspirational". A goal of this effort is to identify a set of both lagging and leading indicators that is based on reliable and sustained data sources with known user communities. We intend for these indicators to guide decision-makers in their responses to climate change, and ideally help inform decisions of groups like the Arctic Council and U.S. Global Change Research Program (USGCRP) as they develop plans and priorities.

Climate Change Impact on Rainfall: How will Threaten Wheat Yield?

NASA Astrophysics Data System (ADS)

Tafoughalti, K.; El Faleh, E. M.; Moujahid, Y.; Ouargaga, F.

2018-05-01

Climate change has a significant impact on the environmental condition of the agricultural region. Meknes has an agrarian economy and wheat production is of paramount importance. As most arable area are under rainfed system, Meknes is one of the sensitive regions to rainfall variability and consequently to climate change. Therefore, the use of changes in rainfall is vital for detecting the influence of climate system on agricultural productivity. This article identifies rainfall temporal variability and its impact on wheat yields. We used monthly rainfall records for three decades and wheat yields records of fifteen years. Rainfall variability is assessed utilizing the precipitation concentration index and the variation coefficient. The association between wheat yields and cumulative rainfall amounts of different scales was calculated based on a regression model. The analysis shown moderate seasonal and irregular annual rainfall distribution. Yields fluctuated from 210 to 4500 Kg/ha with 52% of coefficient of variation. The correlation results shows that wheat yields are strongly correlated with rainfall of the period January to March. This investigation concluded that climate change is altering wheat yield and it is crucial to adept the necessary adaptation to challenge the risk.

Assessment of bias correction under transient climate change

NASA Astrophysics Data System (ADS)

Van Schaeybroeck, Bert; Vannitsem, Stéphane

2015-04-01

Calibration of climate simulations is necessary since large systematic discrepancies are generally found between the model climate and the observed climate. Recent studies have cast doubt upon the common assumption of the bias being stationary when the climate changes. This led to the development of new methods, mostly based on linear sensitivity of the biases as a function of time or forcing (Kharin et al. 2012). However, recent studies uncovered more fundamental problems using both low-order systems (Vannitsem 2011) and climate models, showing that the biases may display complicated non-linear variations under climate change. This last analysis focused on biases derived from the equilibrium climate sensitivity, thereby ignoring the effect of the transient climate sensitivity. Based on the linear response theory, a general method of bias correction is therefore proposed that can be applied on any climate forcing scenario. The validity of the method is addressed using twin experiments with a climate model of intermediate complexity LOVECLIM (Goosse et al., 2010). We evaluate to what extent the bias change is sensitive to the structure (frequency) of the applied forcing (here greenhouse gases) and whether the linear response theory is valid for global and/or local variables. To answer these question we perform large-ensemble simulations using different 300-year scenarios of forced carbon-dioxide concentrations. Reality and simulations are assumed to differ by a model error emulated as a parametric error in the wind drag or in the radiative scheme. References [1] H. Goosse et al., 2010: Description of the Earth system model of intermediate complexity LOVECLIM version 1.2, Geosci. Model Dev., 3, 603-633. [2] S. Vannitsem, 2011: Bias correction and post-processing under climate change, Nonlin. Processes Geophys., 18, 911-924. [3] V.V. Kharin, G. J. Boer, W. J. Merryfield, J. F. Scinocca, and W.-S. Lee, 2012: Statistical adjustment of decadal predictions in a changing climate, Geophys. Res. Lett., 39, L19705.

The Mars climate for a photovoltaic system operation

NASA Technical Reports Server (NTRS)

Appelbaum, Joseph; Flood, Dennis J.

1989-01-01

Detailed information on the climatic conditions on Mars are very desirable for the design of photovoltaic systems for establishing outposts on the Martian surface. The distribution of solar insolation (global, direct and diffuse) and ambient temperature is addressed. This data are given at the Viking lander's locations and can also be used, to a first approximation, for other latitudes. The insolation data is based on measured optical depth of the Martian atmosphere derived from images taken of the sun with a special diode on the Viking cameras; and computation based on multiple wavelength and multiple scattering of the solar radiation. The ambient temperature (diurnal and yearly distribution) is based on direct measurements with a thermocouple at 1.6 m above the ground at the Viking lander locations. The insolation and ambient temperature information are short term data. New information about Mars may be forthcoming in the future from new analysis of previously collected data or from future flight missions. The Mars climate data for photovoltaic system operation will thus be updated accordingly.

An analysis of specialist and non-specialist user requirements for geographic climate change information.

PubMed

Maguire, Martin C

2013-11-01

The EU EuroClim project developed a system to monitor and record climate change indicator data based on satellite observations of snow cover, sea ice and glaciers in Northern Europe and the Arctic. It also contained projection data for temperature, rainfall and average wind speed for Europe. These were all stored as data sets in a GIS database for users to download. The process of gathering requirements for a user population including scientists, researchers, policy makers, educationalists and the general public is described. Using an iterative design methodology, a user survey was administered to obtain initial feedback on the system concept followed by panel sessions where users were presented with the system concept and a demonstrator to interact with it. The requirements of both specialist and non-specialist users is summarised together with strategies for the effective communication of geographic climate change information. Copyright © 2013 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Defining climate modeling user needs: which data are actually required to support impact analysis and adaptation policy development?

NASA Astrophysics Data System (ADS)

Swart, R. J.; Pagé, C.

2010-12-01

Until recently, the policy applications of Earth System Models in general and climate models in particular were focusing mainly on the potential future changes in the global and regional climate and attribution of observed changes to anthropogenic activities. Is climate change real? And if so, why do we have to worry about it? Following the broad acceptance of the reality of the risks by the majority of governments, particularly after the publication of IPCC’s 4th Assessment Report and the increasing number of observations of changes in ecological and socio-economic systems that are consistent with the observed climatic changes, governments, companies and other societal groups have started to evaluate their own vulnerability in more detail and to develop adaptation and mitigation strategies. After an early focus on the most vulnerable developing countries, recently, an increasing number of industrialized countries have embarked on the design of adaptation and mitigation plans, or on studies to evaluate the level of climate resilience of their development plans and projects. Which climate data are actually required to effectively support these activities? This paper reports on the efforts of the IS-ENES project, the infrastructure project of the European Network for Earth System Modeling, to address this question. How do we define user needs and can the existing gap between the climate modeling and impact research communities be bridged in support of the ENES long-term strategy? In contrast from the climate modeling community, which has a relatively long history of collaboration facilitated by a relatively uniform subject matter, commonly agreed definitions of key terminology and some level of harmonization of methods, the climate change impacts research community is very diverse and fragmented, using a wide variety of data sources, methods and tools. An additional complicating factor is that researchers working on adaptation usually closely collaborate with non-scientific stakeholders in government, civil society and the private sector, in a context which is different in many European countries. In the IS-ENES effort, a dialogue is set up between the communities in Europe, building on various existing research networks in the area of climate change impacts, vulnerability and adaptation. Generally, the data needs have not been well articulated. If asked, people working on impacts and adaptation routinely seem to ask for data with the highest possible resolution. However, in reality for many impact and adaptation applications this is not needed, and the large resulting data sets may exceed the analytical capacity of the impact researchers. For impact analysis often various types of climate indices, derived from primary climate model output variables, are required, including indices for extremes and in probabilistic format. Rather than making output from climate modeling generically available, e.g. through a climate service e-portal, context-specific tailoring of information for specific applications is important for effective use. This may require some level of interaction between the users and the data providers, dependent on the specific questions to be addressed.

Climate Change: Modeling the Human Response

NASA Astrophysics Data System (ADS)

Oppenheimer, M.; Hsiang, S. M.; Kopp, R. E.

2012-12-01

Integrated assessment models have historically relied on forward modeling including, where possible, process-based representations to project climate change impacts. Some recent impact studies incorporate the effects of human responses to initial physical impacts, such as adaptation in agricultural systems, migration in response to drought, and climate-related changes in worker productivity. Sometimes the human response ameliorates the initial physical impacts, sometimes it aggravates it, and sometimes it displaces it onto others. In these arenas, understanding of underlying socioeconomic mechanisms is extremely limited. Consequently, for some sectors where sufficient data has accumulated, empirically based statistical models of human responses to past climate variability and change have been used to infer response sensitivities which may apply under certain conditions to future impacts, allowing a broad extension of integrated assessment into the realm of human adaptation. We discuss the insights gained from and limitations of such modeling for benefit-cost analysis of climate change.

pyhector: A Python interface for the simple climate model Hector

DOE PAGES

Willner, Sven N.; Hartin, Corinne; Gieseke, Robert

2017-04-01

Here, pyhector is a Python interface for the simple climate model Hector (Hartin et al. 2015) developed in C++. Simple climate models like Hector can, for instance, be used in the analysis of scenarios within integrated assessment models like GCAM1, in the emulation of complex climate models, and in uncertainty analyses. Hector is an open-source, object oriented, simple global climate carbon cycle model. Its carbon cycle consists of a one pool atmosphere, three terrestrial pools which can be broken down into finer biomes or regions, and four carbon pools in the ocean component. The terrestrial carbon cycle includes primary productionmore » and respiration fluxes. The ocean carbon cycle circulates carbon via a simplified thermohaline circulation, calculating air-sea fluxes as well as the marine carbonate system. The model input is time series of greenhouse gas emissions; as example scenarios for these the Pyhector package contains the Representative Concentration Pathways (RCPs)2.« less

Reviewing Bayesian Networks potentials for climate change impacts assessment and management: A multi-risk perspective.

PubMed

Sperotto, Anna; Molina, José-Luis; Torresan, Silvia; Critto, Andrea; Marcomini, Antonio

2017-11-01

The evaluation and management of climate change impacts on natural and human systems required the adoption of a multi-risk perspective in which the effect of multiple stressors, processes and interconnections are simultaneously modelled. Despite Bayesian Networks (BNs) are popular integrated modelling tools to deal with uncertain and complex domains, their application in the context of climate change still represent a limited explored field. The paper, drawing on the review of existing applications in the field of environmental management, discusses the potential and limitation of applying BNs to improve current climate change risk assessment procedures. Main potentials include the advantage to consider multiple stressors and endpoints in the same framework, their flexibility in dealing and communicate with the uncertainty of climate projections and the opportunity to perform scenario analysis. Some limitations (i.e. representation of temporal and spatial dynamics, quantitative validation), however, should be overcome to boost BNs use in climate change impacts assessment and management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dust in the Earth system: the biogeochemical linking of land, air and sea.

PubMed

Ridgwell, Andy J

2002-12-15

Understanding the response of the Earth's climate system to anthropogenic perturbation has been a pressing priority for society since the late 1980s. However, recent years have seen a major paradigm shift in how such an understanding can be reached. Climate change demands analysis within an integrated 'Earth-system' framework, taken to encompass the suite of interacting physical, chemical, biological and human processes that, in transporting and transforming materials and energy, jointly determine the conditions for life on the whole planet. This is a highly complex system, characterized by multiple nonlinear responses and thresholds, with linkages often between apparently disparate components. The interconnected nature of the Earth system is wonderfully illustrated by the diverse roles played by atmospheric transport of mineral 'dust', particularly in its capacity as a key pathway for the delivery of nutrients essential to plant growth, not only on land, but perhaps more importantly, in the ocean. Dust therefore biogeochemically links land, air and sea. This paper reviews the biogeochemical role of mineral dust in the Earth system and its interaction with climate, and, in particular, the potential importance of both past and possible future changes in aeolian delivery of the micro-nutrient iron to the ocean. For instance, if, in the future, there was to be a widespread stabilization of soils for the purpose of carbon sequestration on land, a reduction in aeolian iron supply to the open ocean would occur. The resultant weakening of the oceanic carbon sink could potentially offset much of the carbon sequestered on land. In contrast, during glacial times, enhanced dust supply to the ocean could have 'fertilized' the biota and driven atmospheric CO(2) lower. Dust might even play an active role in driving climatic change; since changes in dust supply may affect climate, and changes in climate, in turn, influence dust, a 'feedback loop' is formed. Possible feedback mechanisms are identified, recognition of whose operation could be crucial to our understanding of major climatic transitions over the past few million years.

Helping Water Utilities Grapple with Climate Change

NASA Astrophysics Data System (ADS)

Yates, D.; Gracely, B.; Miller, K.

2008-12-01

The Water Research Foundation (WRF), serving the drinking water industry and the National Center for Atmospheric Research (NCAR) are collaborating on an effort to develop and implement locally-relevant, structured processes to help water utilities consider the impacts and adaptation options that climate variability and change might have on their water systems. Adopting a case-study approach, the structured process include 1) a problem definition phase, focused on identifying goals, information needs, utility vulnerabilities and possible adaptation options in the face of climate and hydrologic uncertainty; 2) developing and/or modifying system-specific Integrated Water Resource Management (IWRM) models and conducting sensitivity analysis to identify critical variables; 3) developing probabilistic climate change scenarios focused on exploring uncertainties identified as important in the sensitivity analysis in step 2; and 4) implementing the structured process and examining approaches decision making under uncertainty. Collaborators include seven drinking water utilities and two state agencies: 1) The Inland Empire Utility Agency, CA; 2) The El Dorado Irrigation District, Placerville CA; 2) Portland Water Bureau, Portland OR; 3) Colorado Springs Utilities, Colo Spgs, CO; 4) Cincinnati Water, Cincinnati, OH; 5) Massachusetts Water Resources Authority (MWRA), Boston, MA; 6) Durham Water, Durham, NC; and 7) Palm Beach County Water (PBCW), Palm Beach, FL. The California Department of Water Resources and the Colorado Water Conservation Board were the state agencies that we have collaborated with.

Validation and quantification of uncertainty in coupled climate models using network analysis

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

Bracco, Annalisa

We developed a fast, robust and scalable methodology to examine, quantify, and visualize climate patterns and their relationships. It is based on a set of notions, algorithms and metrics used in the study of graphs, referred to as complex network analysis. This approach can be applied to explain known climate phenomena in terms of an underlying network structure and to uncover regional and global linkages in the climate system, while comparing general circulation models outputs with observations. The proposed method is based on a two-layer network representation, and is substantially new within the available network methodologies developed for climate studies.more » At the first layer, gridded climate data are used to identify ‘‘areas’’, i.e., geographical regions that are highly homogeneous in terms of the given climate variable. At the second layer, the identified areas are interconnected with links of varying strength, forming a global climate network. The robustness of the method (i.e. the ability to separate between topological distinct fields, while identifying correctly similarities) has been extensively tested. It has been proved that it provides a reliable, fast framework for comparing and ranking the ability of climate models of reproducing observed climate patterns and their connectivity. We further developed the methodology to account for lags in the connectivity between climate patterns and refined our area identification algorithm to account for autocorrelation in the data. The new methodology based on complex network analysis has been applied to state-of-the-art climate model simulations that participated to the last IPCC (International Panel for Climate Change) assessment to verify their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and rainfall over 1956–2005 have been constrained towards observations or reanalysis data sets, and their differences quantified using two metrics. Projected changes from 2051 to 2300 under the scenario with the highest representative and extended concentration pathways (RCP8.5 and ECP8.5) have then been determined. The network of models capable of reproducing well major climate modes in the recent past, changes little during this century. In contrast, among those models the uncertainties in the projections after 2100 remain substantial, and primarily associated with divergences in the representation of the modes of variability, particularly of the El Niño Southern Oscillation (ENSO), and their connectivity, and therefore with their intrinsic predictability, more so than with differences in the mean state evolution. Additionally, we evaluated the relation between the size and the ‘strength’ of the area identified by the network analysis as corresponding to ENSO noting that only a small subset of models can reproduce realistically the observations.« less

Effect of genetic and phenotypic factors on the composition of commercial marmande type tomatoes studied through HRMAS NMR spectroscopy.

PubMed

Iglesias, María José; García López, Jesús; Collados Luján, Juan Fernando; López Ortiz, Fernando; Bojórquez Pereznieto, Humberto; Toresano, Fernando; Camacho, Francisco

2014-01-01

The effects of genetic, technological and environmental factors on the chemical composition of four marmande type tomato varieties have been investigated. The study is based on the analysis of (1)H HRMAS NMR spectra of tomato purée using a combination of partial least squares (PLS) and assigned signal analysis (ASA). In agreement with genetic, morphological and taste characteristics of the tomatoes studied, the analysis of the NMR data allows two groups of samples to be differentiated. The type of culture and climatic conditions can reduce the compositional differences. The extension of the compositional changes produced by climatic conditions is variety-depend. Neither grafting nor perlite affect significantly the relative content of primary metabolites. This was not the case for tomatoes grown using the pure hydroponic production system based on the recirculation of nutrient solution, New Growing System NGS®, which seems to be an effective agricultural approach to improve tomato quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

Uncertainty Analysis of Runoff Simulations and Parameter Identifiability in the Community Land Model – Evidence from MOPEX Basins

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

Huang, Maoyi; Hou, Zhangshuan; Leung, Lai-Yung R.

2013-12-01

With the emergence of earth system models as important tools for understanding and predicting climate change and implications to mitigation and adaptation, it has become increasingly important to assess the fidelity of the land component within earth system models to capture realistic hydrological processes and their response to the changing climate and quantify the associated uncertainties. This study investigates the sensitivity of runoff simulations to major hydrologic parameters in version 4 of the Community Land Model (CLM4) by integrating CLM4 with a stochastic exploratory sensitivity analysis framework at 20 selected watersheds from the Model Parameter Estimation Experiment (MOPEX) spanning amore » wide range of climate and site conditions. We found that for runoff simulations, the most significant parameters are those related to the subsurface runoff parameterizations. Soil texture related parameters and surface runoff parameters are of secondary significance. Moreover, climate and soil conditions play important roles in the parameter sensitivity. In general, site conditions within water-limited hydrologic regimes and with finer soil texture result in stronger sensitivity of output variables, such as runoff and its surface and subsurface components, to the input parameters in CLM4. This study demonstrated the feasibility of parameter inversion for CLM4 using streamflow observations to improve runoff simulations. By ranking the significance of the input parameters, we showed that the parameter set dimensionality could be reduced for CLM4 parameter calibration under different hydrologic and climatic regimes so that the inverse problem is less ill posed.« less

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.

Use of NARCCAP data to characterize regional climate uncertainty in the impact of global climate change on large river fish population: Missouri River sturgeon example

NASA Astrophysics Data System (ADS)

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

2012-12-01

Climate change operates over a broad range of spatial and temporal scales. Understanding the effects of change on ecosystems requires accounting for the propagation of information and uncertainty across these scales. For example, to understand potential climate change effects on fish populations in riverine ecosystems, climate conditions predicted by course-resolution atmosphere-ocean global climate models must first be translated to the regional climate scale. In turn, this regional information is used to force watershed models, which are used to force river condition models, which impact the population response. A critical challenge in such a multiscale modeling environment is to quantify sources of uncertainty given the highly nonlinear nature of interactions between climate variables and the individual organism. We use a hierarchical modeling approach for accommodating uncertainty in multiscale ecological impact studies. This framework allows for uncertainty due to system models, model parameter settings, and stochastic parameterizations. This approach is a hybrid between physical (deterministic) downscaling and statistical downscaling, recognizing that there is uncertainty in both. We use NARCCAP data to determine confidence the capability of climate models to simulate relevant processes and to quantify regional climate variability within the context of the hierarchical model of uncertainty quantification. By confidence, we mean the ability of the regional climate model to replicate observed mechanisms. We use the NCEP-driven simulations for this analysis. This provides a base from which regional change can be categorized as either a modification of previously observed mechanisms or emergence of new processes. The management implications for these categories of change are significantly different in that procedures to address impacts from existing processes may already be known and need adjustment; whereas, an emergent processes may require new management strategies. The results from hierarchical analysis of uncertainty are used to study the relative change in weights of the endangered Missouri River pallid sturgeon (Scaphirhynchus albus) under a 21st century climate scenario.

Results from the BRACE 1.5 study: Climate change impacts of 1.5 C and 2 C warming

NASA Astrophysics Data System (ADS)

O'Neill, B. C.; Anderson, B.; Monaghan, A. J.; Ren, X.; Sanderson, B.; Tebaldi, C.

2017-12-01

In 2015, 195 countries negotiated the Paris Agreement on climate change, which set long-term goals of limiting global mean warming to well below 2 C and possibly 1.5 C. This event stimulated substantial scientific interest in climate outcomes and impacts on society associated with those levels of warming. Recently, the first set of global climate model simulations explicitly designed to meet those targets were undertaken with the Community Earth System Model (CESM) for use by the research community (Sanderson et al, accepted). The BRACE 1.5 project models societal impacts from these climate outcomes, combined with assumptions about future socioeconomic conditions according to the Shared Socioeconomic Pathways. These analyses build on a recently completed study of the Benefits of Reduced Anthropogenic Climate changE (BRACE), published as a set of 20 papers in Climatic Change, which examined the difference in impacts between two higher scenarios resulting in about 2.5 C and 3.7 C warming by late this century. BRACE 1.5 consists of a set of six papers to be submitted to a special collection in Environmental Research Letters that takes a similar approach but focuses on impacts at 1.5 and 2 C warming. We ask whether impacts differ substantially between the two climate scenarios, accounting for uncertainty in climate outcomes through the use of initial condition ensembles of CESM simulations, and in societal conditions by using alternative SSP-based development pathways. Impact assessment focuses on the health and agricultural sectors; modeling approaches include the use of a global mutli-region CGE model for economic analysis, both a process-based and an empirical crop model, a model of spatial population change, a model of climatic suitability for the aedes aegypti mosquito, and an epidemiological model of heat-related mortality. A methodological analysis also evaluates the use of climate model emulation techniques for providing climate information sufficient to support impact assessment in low warming scenarios.

Improving Crop Yield and Nutrient Use Efficiency via Biofertilization—A Global Meta-analysis

PubMed Central

Schütz, Lukas; Gattinger, Andreas; Meier, Matthias; Müller, Adrian; Boller, Thomas; Mäder, Paul; Mathimaran, Natarajan

2018-01-01

The application of microbial inoculants (biofertilizers) is a promising technology for future sustainable farming systems in view of rapidly decreasing phosphorus stocks and the need to more efficiently use available nitrogen (N). Various microbial taxa are currently used as biofertilizers, based on their capacity to access nutrients from fertilizers and soil stocks, to fix atmospheric nitrogen, to improve water uptake or to act as biocontrol agents. Despite the existence of a considerable knowledge on effects of specific taxa of biofertilizers, a comprehensive quantitative assessment of the performance of biofertilizers with different traits such as phosphorus solubilization and N fixation applied to various crops at a global scale is missing. We conducted a meta-analysis to quantify benefits of biofertilizers in terms of yield increase, nitrogen and phosphorus use efficiency, based on 171 peer reviewed publications that met eligibility criteria. Major findings are: (i) the superiority of biofertilizer performance in dry climates over other climatic regions (yield response: dry climate +20.0 ± 1.7%, tropical climate +14.9 ± 1.2%, oceanic climate +10.0 ± 3.7%, continental climate +8.5 ± 2.4%); (ii) meta-regression analyses revealed that yield response due to biofertilizer application was generally small at low soil P levels; efficacy increased along higher soil P levels in the order arbuscular mycorrhizal fungi (AMF), P solubilizers, and N fixers; (iii) meta-regressions showed that the success of inoculation with AMF was greater at low organic matter content and at neutral pH. Our comprehensive analysis provides a basis and guidance for proper choice and application of biofertilizers. PMID:29375594

Improving Crop Yield and Nutrient Use Efficiency via Biofertilization-A Global Meta-analysis.

PubMed

Schütz, Lukas; Gattinger, Andreas; Meier, Matthias; Müller, Adrian; Boller, Thomas; Mäder, Paul; Mathimaran, Natarajan

2017-01-01

The application of microbial inoculants (biofertilizers) is a promising technology for future sustainable farming systems in view of rapidly decreasing phosphorus stocks and the need to more efficiently use available nitrogen (N). Various microbial taxa are currently used as biofertilizers, based on their capacity to access nutrients from fertilizers and soil stocks, to fix atmospheric nitrogen, to improve water uptake or to act as biocontrol agents. Despite the existence of a considerable knowledge on effects of specific taxa of biofertilizers, a comprehensive quantitative assessment of the performance of biofertilizers with different traits such as phosphorus solubilization and N fixation applied to various crops at a global scale is missing. We conducted a meta-analysis to quantify benefits of biofertilizers in terms of yield increase, nitrogen and phosphorus use efficiency, based on 171 peer reviewed publications that met eligibility criteria. Major findings are: (i) the superiority of biofertilizer performance in dry climates over other climatic regions (yield response: dry climate +20.0 ± 1.7%, tropical climate +14.9 ± 1.2%, oceanic climate +10.0 ± 3.7%, continental climate +8.5 ± 2.4%); (ii) meta-regression analyses revealed that yield response due to biofertilizer application was generally small at low soil P levels; efficacy increased along higher soil P levels in the order arbuscular mycorrhizal fungi (AMF), P solubilizers, and N fixers; (iii) meta-regressions showed that the success of inoculation with AMF was greater at low organic matter content and at neutral pH. Our comprehensive analysis provides a basis and guidance for proper choice and application of biofertilizers.

Geoengineering to Avoid Overshoot: An Uncertainty Analysis

NASA Astrophysics Data System (ADS)

Tanaka, K.

2009-04-01

Geoengineering (or climate engineering) using stratospheric sulfur injections (Crutzen, 2006) has been called for research in case of an urgent need for stopping global warming when other mitigation efforts were exhausted. Although there are a number of concerns over this idea (e.g. Robock, 2008), it is still useful to consider geoengineering as a possible method to limit warming caused by overshoot. Overshoot is a feature accompanied by low stabilizations scenarios aiming for a stringent target (Rao et al., 2008) in which total radiative forcing temporarily exceeds the target before reaching there. Scenarios achieving a 50% emission reduction by 2050 produces overshoot. Overshoot could cause sustained warming for decades due to the inertia of the climate system. If stratospheric sulfur injections were to be used as a "last resort" to avoid overshoot, what would be the suitable start-year and injection profile of such an intervention? Wigley (2006) examined climate response to combined mitigation/geoengineering scenarios with the intent to avert overshoot. Wigley's analysis demonstrated a basic potential of such a combined mitigation/geoengineering approach to avoid temperature overshoot - however it considered only simplistic sulfur injection profiles (all started in 2010), just one mitigation scenario, and did not examine the sensitivity of the climate response to any underlying uncertainties. This study builds upon Wigley's premise of the combined mitigation/geoengineering approach and brings associated uncertainty into the analysis. First, this study addresses the question as to how much geoengineering intervention would be needed to avoid overshoot by considering associated uncertainty? Then, would a geoengineering intervention of such a magnitude including uncertainty be permissible in considering all the other side effects? This study begins from the supposition that geoengineering could be employed to cap warming at 2.0°C since preindustrial. A few mitigation scenarios having overshoot are formulated. Optimal injection profiles (start-year and magnitude) for capping temperature rise at 2.0°C are calculated for each mitigation scenario. The sensitivity of such results to the uncertain parameters (climate sensitivity, tropospheric aerosol forcing, and ocean diffusivity) is then examined - in particular, I account for the inter-dependency of the estimates of these parameters such that they are consistent with historical observations (e.g. temperature records) by using an inverse estimation approach. I use the simple climate model ACC2 (Tanaka and Kriegler et al., 2007; Tanaka, 2008) - which (unlike Wigley's MAGICC model (Wigley and Raper, 2001)) includes an inversion setup that allows for the exploration of parameter inter-dependency based on historical observational constraints. References Crutzen, P. J. (2006) Albedo enhancement by stratospheric sulfur injections: a contribution to resolve a policy dilemma? Climatic Change, 77, 211-219. Rao, S., K. Riahi, E. Stehfest, D. van Vuuren, C. Cho, M. den Elzen, M. Isaac, J. van Vliet (2008) IMAGE and MESSAGE scenarios limiting GHG concentration to low levels. Interim Report at International Institute for Applied Systems Analysis (IIASA) IR-08-020. 57 pp. http://www.iiasa.ac.at/Admin/PUB/Documents/IR-08-020.pdf Robock, A. (2008) 20 reasons why geoengineering may be a bad idea. Bulletin of the Atomic Scientists, 64, 14-18. Tanaka, K., E. Kriegler, T. Bruckner, G. Hooss, W. Knorr, T. Raddatz (2007) Aggregated Carbon Cycle, Atmospheric Chemistry, and Climate Model (ACC2): description of the forward and inverse modes. Reports on Earth System Science No. 40. Max Planck Institute for Meteorology, Hamburg, Germany. 188 pp. http://www.mpimet.mpg.de/wissenschaft/publikationen/erdsystemforschung.html Tanaka, K. (2008) Inverse estimation for the simple Earth system model ACC2 and its applications. Ph.D. dissertation. Hamburg, Germany: Hamburg Universität, International Max Planck Research School on Earth System Modelling, 296 pp. http://www.sub.uni-hamburg.de/opus/volltexte/2008/3654/ Wigley, T. M. L., S. C. B. Raper (2001) Interpretation of high projections for global-mean warming. Science, 293, 451-454. Wigley, T. M. L. (2006) A combined mitigation/geoengineering approach to climate stabilization. Science, 314, 452-454.

Reconciling Scale Mismatch in Water Governance, Hydro-climatic Processes and Infrastructure Systems of Water Supply in Las Vegas

NASA Astrophysics Data System (ADS)

Garcia, M. E.; Alarcon, T.; Portney, K.; Islam, S.

2013-12-01

Water resource systems are a classic example of a common pool resource due to the high cost of exclusion and the subtractability of the resource; for common pool resources, the performance of governance systems primarily depends on how well matched the institutional arrangements and rules are to the biophysical conditions and social norms. Changes in water governance, hydro-climatic processes and infrastructure systems occur on disparate temporal and spatial scales. A key challenge is the gap between current climate change model resolution, and the spatial and temporal scale of urban water supply decisions. This gap will lead to inappropriate management policies if not mediated through a carefully crafted decision making process. Traditional decision support and planning methods (DSPM) such as classical decision analysis are not equipped to deal with a non-static climate. While emerging methods such as decision scaling, robust decision making and real options are designed to deal with a changing climate, governance systems have evolved under the assumption of a static climate and it is not clear if these methods are well suited to the existing governance regime. In our study, these questions are contextualized by examining an urban water utility that has made significant changes in policy to adapt to changing conditions: the Southern Nevada Water Authority (SNWA) which serves metropolitan Las Vegas. Like most desert cities, Las Vegas exists because of water; the artesian springs of the Las Vegas Valley once provided an ample water supply for Native Americans, ranchers and later a small railroad city. However, population growth has increased demands far beyond local supplies. The area now depends on the Colorado River for the majority of its water supply. Natural climate variability with periodic droughts has further challenged water providers; projected climate changes and further population growth will exacerbate these challenges. Las Vegas is selected as a case study due to the combined challenges of population growth and climate change, common in the arid west, and due its cooperative institutional response to these challenges, unprecedented in the arid west. To begin to disentangle this question we have analyzed the institutional arrangements and rules which govern water decision making in the Las Vegas Valley and evaluated the existing DSPM used by the SNWA and partner utilities. Presented here are the preliminary results from an ongoing project.

SE Asian freshwater fish population and networks: the impacts of climatic and environmental change on a vital resource

NASA Astrophysics Data System (ADS)

Santos, Rita; Parsons, Daniel; Cowx, Ian

2016-04-01

The Mekong River is the 10th largest freshwater river in the world, with the second highest biodiversity wealth, behind the much larger Amazon basin. The fisheries activity in the Lower Mekong countries counts for 2.7 million tons of fish per year, with an estimated value worth up to US 7 billion. For the 60 million people living in the basin, fish represent their primary source of economic income and protein intake, with an average per capita consumption estimated at 45.4 Kg. The proposed hydropower development in the basin is threatening its sustainability and resilience. Such developments affect fish migration patterns, hydrograph flood duration and magnitudes and sediment flux. Climate change is also likely to impact the basin, exacerbating the issues created by development. As a monsoonal system, the Mekong River's pronounced annual flood pulse cycle is important in creating variable habitat for fish productivity. Moreover, the annual flood also triggers fish migration and provides vital nutrients carried by the sediment flux. This paper examines the interactions between both dam development and climate change scenarios on fish habitat and habitat connectivity, with the aim of predicting how these will affect fish species composition and fisheries catch. The project will also employ Environmental DNA (eDNA) to quantify and understand the species composition of this complex and large freshwater system. By applying molecular analysis, it is possible to trace species abundance and migration patterns of fish and evaluate the ecological networks establish between an inland system. The aim of this work is to estimate, using process-informed models, the impacts of the proposed dam development and climate change scenarios on the hydrological and hydraulic conditions of habitat availability for fish. Furthermore, it will evaluate the connectivity along the Mekong and its tributaries, and the importance of maintaining these migration pathways, used by a great diversity of fish species. It will also present the preliminary findings on eDNA analysis for species composition and the ecological networks established along the river and particularly on the fish hotspot place for biodiversity, the Tonle Sap system in Cambodia. Keywords: Mekong River, climate change, fish production, dams, eDNA analysis, numerical modelling.

Sustainability analysis and life-cycle ecological impacts of rainwater harvesting systems using holistic analysis and a modified eco-efficiency framework

EPA Science Inventory

Background/Question/Methods A sustainability paradigm is being recognized globally as a path forward for human prosperity and ecological health in the face of climate change and meeting challenges of the water-energy-food nexus. Rainfall shortages for drinking water and crop pro...

Impacts on Water Management and Crop Production of Regional Cropping System Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Zhong, H.; Sun, L.; Tian, Z.; Liang, Z.; Fischer, G.

2014-12-01

China is one of the most populous and fast developing countries, also faces a great pressure on grain production and food security. Multi-cropping system is widely applied in China to fully utilize agro-climatic resources and increase land productivity. As the heat resource keep improving under climate warming, multi-cropping system will also shifting northward, and benefit crop production. But water shortage in North China Plain will constrain the adoption of new multi-cropping system. Effectiveness of multi-cropping system adaptation to climate change will greatly depend on future hydrological change and agriculture water management. So it is necessary to quantitatively express the water demand of different multi-cropping systems under climate change. In this paper, we proposed an integrated climate-cropping system-crops adaptation framework, and specifically focused on: 1) precipitation and hydrological change under future climate change in China; 2) the best multi-cropping system and correspondent crop rotation sequence, and water demand under future agro-climatic resources; 3) attainable crop production with water constraint; and 4) future water management. In order to obtain climate projection and precipitation distribution, global climate change scenario from HADCAM3 is downscaled with regional climate model (PRECIS), historical climate data (1960-1990) was interpolated from more than 700 meteorological observation stations. The regional Agro-ecological Zone (AEZ) model is applied to simulate the best multi-cropping system and crop rotation sequence under projected climate change scenario. Finally, we use the site process-based DSSAT model to estimate attainable crop production and the water deficiency. Our findings indicate that annual land productivity may increase and China can gain benefit from climate change if multi-cropping system would be adopted. This study provides a macro-scale view of agriculture adaptation, and gives suggestions to national agriculture adaptation strategy decisions.

Global Climate Models for the Classroom: The Educational Impact of Student Work with a Key Tool of Climate Scientists

NASA Astrophysics Data System (ADS)

Bush, D. F.; Sieber, R.; Seiler, G.; Chandler, M. A.; Chmura, G. L.

2017-12-01

Efforts to address climate change require public understanding of Earth and climate science. To meet this need, educators require instructional approaches and scientific technologies that overcome cultural barriers to impart conceptual understanding of the work of climate scientists. We compared student inquiry learning with now ubiquitous climate education toy models, data and tools against that which took place using a computational global climate model (GCM) from the National Aeronautics and Space Administration (NASA). Our study at McGill University and John Abbott College in Montreal, QC sheds light on how best to teach the research processes important to Earth and climate scientists studying atmospheric and Earth system processes but ill-understood by those outside the scientific community. We followed a pre/post, control/treatment experimental design that enabled detailed analysis and statistically significant results. Our research found more students succeed at understanding climate change when exposed to actual climate research processes and instruments. Inquiry-based education with a GCM resulted in significantly higher scores pre to post on diagnostic exams (quantitatively) and more complete conceptual understandings (qualitatively). We recognize the difficulty in planning and teaching inquiry with complex technology and we also found evidence that lectures support learning geared toward assessment exams.

Species-free species distribution models describe macroecological properties of protected area networks.

PubMed

Robinson, Jason L; Fordyce, James A

2017-01-01

Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or "footprint") of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have narrow geographic distributions, and are thus prone to future shifts away from the climatic conditions in these parks in current climates. In other cases, some parks are broadly similar to large geographic regions surrounding the park or have climatic envelopes that may persist into near-term climate change. Larger parks predict larger climatic envelopes, in current conditions, but on average the predicted area of climate envelopes are smaller in our single future conditions scenario. Individual units in a protected area network may vary in the potential for climate adaptation, and adaptive management strategies for the network should account for the landscape contexts of the geodiversity or climate diversity within individual units. Conservation strategies, including maintaining connectivity, assessing the feasibility of assisted migration and other landscape restoration or enhancements can be optimized using analysis methods to assess the spatial properties of protected area networks in biogeographic and macroecological contexts.

Sensitivity of bud burst in key tree species in the UK to recent climate variability and change

NASA Astrophysics Data System (ADS)

Abernethy, Rachel; Cook, Sally; Hemming, Deborah; McCarthy, Mark

2017-04-01

Analysing the relationship between the changing climate of the UK and the spatial and temporal distribution of spring bud burst plays an important role in understanding ecosystem functionality and predicting future phenological trends. The location and timing of bud burst of eleven species of trees alongside climatic factors such as, temperature, precipitation and hours of sunshine (photoperiod) were used to investigate: i. which species' bud burst timing experiences the greatest impact from a changing climate, ii. which climatic factor has the greatest influence on the timing of bud burst, and iii. whether the location of bud burst is influenced by climate variability. Winter heatwave duration was also analysed as part of an investigation into the relationship between temperature trends of a specific winter period and the following spring events. Geographic Information Systems (GIS) and statistical analysis tools were used to visualise spatial patterns and to analyse the phenological and climate data through regression and analysis of variance (ANOVA) tests. Where there were areas that showed a strong positive or negative relationship between phenology and climate, satellite imagery was used to calculate a Normalised Difference Vegetation Index (NDVI) and a Leaf Area Index (LAI) to further investigate the relationships found. It was expected that in the north of the UK, where bud burst tends to occur later in the year than in the south, that the bud bursts would begin to occur earlier due to increasing temperatures and increased hours of sunshine. However, initial results show that for some species, the bud burst timing tends to remain or become later in the year. Interesting results will be found when investigating the statistical significance between the changing location of the bud bursts and each climatic factor.

Climate-change scenarios

USGS Publications Warehouse

Wagner, Frederic H.; Stohlgren, T.J.; Baldwin, C.K.; Mearns, L.O.; Wagner, Frederic H.

2003-01-01

Three procedures were used to develop a set of plausible scenarios of anthropogenic climate change by the year 2100 that could be posed to the sectors selected for assessment (Fig. 2.2). First, a workshop of climatologists with expertise in western North American climates was convened from September 10-12, 1998 at the National Center for Ecological Analysis and Synthesis in Santa Barbara, CA to discuss and propose a set of scenarios for the Rocky Mountain/Great Basin (RMGB) region.Secondly, the 20th-century climate record was analyzed to determine what trends might have occurred during the period. Since CO2 and other greenhouse gases increased during the century, it was reasonable to examine whether the changes projected for the 21st century had begun to appear during the 20th, at least qualitatively though not quantitatively.Third, on the assumption of a two-fold increase in atmospheric CO2 by 2100, climate-change scenarios for the 21st century were projected with two, state-of-the-art computer models that simulate the complex interactions between earth, atmosphere, and ocean to produce the earth’s climate system. Each of the last two procedures has its strengths and weaknesses, and each can function to some degree as a check on the other. The historical analysis has the advantage of using empirical measurements of actual climate change taken over an extensive network of measuring stations. These make it possible to subdivide a large region like the RMGB into subreqions to assess the uniformity of climate and climate change over the region. And the historical measurements can to some degree serve as a check on the GCM simulations when the two are compared over the same time period.

Climate change studies and the human sciences

NASA Astrophysics Data System (ADS)

Holm, Poul; Winiwarter, Verena

2017-09-01

Policy makers have made repeated calls for integration of human and natural sciences in the field of climate change. Serious multidisciplinary attempts began already in the 1950s. Progress has certainly been made in understanding the role of humans in the planetary system. New perspectives have clarified policy advice, and three insights are singled out in the paper: the critique of historicism, the distinction between benign and wicked problems, and the cultural critique of the 'myths of nature'. Nevertheless, analysis of the IPCC Assessment Reports indicates that integration is skewed towards a particular dimension of human sciences (economics) and major insights from cultural theory and historical analysis have not made it into climate science. A number of relevant disciplines are almost absent in the composition of authorship. Nevertheless, selective assumptions and arguments are made about e.g. historical findings in key documents. In conclusion, we suggest to seek remedies for the lack of historical scholarship in the IPCC reports. More effort at science-policy exchange is needed, and an Integrated Platform to channel humanities and social science expertise for climate change research might be one promising way.

Improved spectral comparisons of paleoclimate models and observations via proxy system modeling: Implications for multi-decadal variability

NASA Astrophysics Data System (ADS)

Dee, S. G.; Parsons, L. A.; Loope, G. R.; Overpeck, J. T.; Ault, T. R.; Emile-Geay, J.

2017-10-01

The spectral characteristics of paleoclimate observations spanning the last millennium suggest the presence of significant low-frequency (multi-decadal to centennial scale) variability in the climate system. Since this low-frequency climate variability is critical for climate predictions on societally-relevant scales, it is essential to establish whether General Circulation models (GCMs) are able to simulate it faithfully. Recent studies find large discrepancies between models and paleoclimate data at low frequencies, prompting concerns surrounding the ability of GCMs to predict long-term, high-magnitude variability under greenhouse forcing (Laepple and Huybers, 2014a, 2014b). However, efforts to ground climate model simulations directly in paleoclimate observations are impeded by fundamental differences between models and the proxy data: proxy systems often record a multivariate and/or nonlinear response to climate, precluding a direct comparison to GCM output. In this paper we bridge this gap via a forward proxy modeling approach, coupled to an isotope-enabled GCM. This allows us to disentangle the various contributions to signals embedded in ice cores, speleothem calcite, coral aragonite, tree-ring width, and tree-ring cellulose. The paper addresses the following questions: (1) do forward-modeled ;pseudoproxies; exhibit variability comparable to proxy data? (2) if not, which processes alter the shape of the spectrum of simulated climate variability, and are these processes broadly distinguishable from climate? We apply our method to representative case studies, and broaden these insights with an analysis of the PAGES2k database (PAGES2K Consortium, 2013). We find that current proxy system models (PSMs) can help resolve model-data discrepancies on interannual to decadal timescales, but cannot account for the mismatch in variance on multi-decadal to centennial timescales. We conclude that, specific to this set of PSMs and isotope-enabled model, the paleoclimate record may exhibit larger low-frequency variability than GCMs currently simulate, indicative of incomplete physics and/or forcings.

Groundwater level response to low-frequency (interannual to multidecadal) climate variability: an overview across Portugal

NASA Astrophysics Data System (ADS)

Neves, M. L.

2017-12-01

The impact of climate variability on groundwater systems is central to the successful management and sustainability of water resources. In Portugal, strong changes in the seasonal distribution of precipitation, with a concentration of rainfall during the winter season and an increase in the frequency and intensity of droughts, in conjunction with warming, are expected to have a profound impact on water resources. Nonetheless, there is still limited knowledge on the impact of climate variability on aquifer systems across the country. The primary goal of this study is to provide a national-scale assessment of the relative contribution of climate to the temporal and spatial variance of groundwater recharge across the four main hydrogeological units in which the country is divided. Monthly hydrological data sets spanning a common 30 year period include groundwater levels from the Portuguese National System for Water Research Information and precipitation data from both meteorological stations and ERA-Interim global atmospheric reanalysis. The links between large-scale climatic patterns, precipitation, and groundwater levels are explored using singular spectral analysis, wavelet coherence and lag correlation methods. Hydrologic time-series sampling diverse geographic regions and aquifer types have common non-stationary oscillatory components, which can be associated with the leading modes of atmospheric circulation in the western north Atlantic, namely the North Atlantic (NAO) and the Eastern Atlantic (EA) oscillations. Maps of the spatial distribution of the relative contribution of each mode of variability to the total variance of the groundwater levels illustrate which atmospheric mode impacts the most a particular aquifer. The results display the links between groundwater recharge and climate teleconnections but also emphasize the distinctive types of modulation of the climate signals among the several hydrogeological units and aquifer systems under consideration. This work is supported by FCT- project UID/GEO/50019/2013 - IDL.

Climate and floods still govern California levee breaks

USGS Publications Warehouse

Florsheim, J.L.; Dettinger, M.D.

2007-01-01

Even in heavily engineered river systems, climate still governs flood variability and thus still drives many levee breaks and geomorphic changes. We assemble a 155-year record of levee breaks for a major California river system to find that breaks occurred in 25% of years during the 20th Century. A relation between levee breaks and river discharge is present that sets a discharge threshold above which most levee breaks occurred. That threshold corresponds to small floods with recurrence intervals of ???2-3 years. Statistical analysis illustrates that levee breaks and peak discharges cycle (broadly) on a 12-15 year time scale, in time with warm-wet storm patterns in California, but more slowly or more quickly than ENSO and PDO climate phenomena, respectively. Notably, these variations and thresholds persist through the 20th Century, suggesting that historical flood-control effects have not reduced the occurrence or frequency of levee breaks. Copyright 2007 by the American Geophysical Union.

Operationalization of Prediction, Hindcast, and Evaluation Systems using the Freie Univ Evaluation System Framework (Freva) incl. a Showcase in Decadal Climate Prediction

NASA Astrophysics Data System (ADS)

Kadow, Christopher; Illing, Sebastian; Schartner, Thomas; Ulbrich, Uwe; Cubasch, Ulrich

2017-04-01

Operationalization processes are important for Weather and Climate Services. Complex data and work flows need to be combined fast to fulfill the needs of service centers. Standards in data and software formats help in automatic solutions. In this study we show a software solution in between hindcasts, forecasts, and validation to be operationalized. Freva (see below) structures data and evaluation procedures and can easily be monitored. Especially in the development process of operationalized services, Freva supports scientists and project partners. The showcase of the decadal climate prediction project MiKlip (fona-miklip.de) shows such a complex development process. Different predictions, scientists input, tasks, and time evolving adjustments need to be combined to host precise climate informations in a web environment without losing track of its evolution. The Freie Univ Evaluation System Framework (Freva - freva.met.fu-berlin.de) is a software infrastructure for standardized data and tool solutions in Earth system science. Freva runs on high performance computers to handle customizable evaluation systems of research projects, institutes or universities. It combines different software technologies into one common hybrid infrastructure, including all features present in the shell and web environment. The database interface satisfies the international standards provided by the Earth System Grid Federation (ESGF). Freva indexes different data projects into one common search environment by storing the meta data information of the self-describing model, reanalysis and observational data sets in a database. This implemented meta data system with its advanced but easy-to-handle search tool supports users, developers and their plugins to retrieve the required information. A generic application programming interface (API) allows scientific developers to connect their analysis tools with the evaluation system independently of the programming language used. Users of the evaluation techniques benefit from the common interface of the evaluation system without any need to understand the different scripting languages. Facilitation of the provision and usage of tools and climate data automatically increases the number of scientists working with the data sets and identifying discrepancies. The integrated webshell (shellinabox) adds a degree of freedom in the choice of the working environment and can be used as a gateto the research projects HPC. Plugins are able to integrate their e.g. post-processed results into the database ofthe user. This allows e.g. post-processing plugins to feed statistical analysis plugins, which fosters an active exchange between plugin developers of a research project. Additionally, the history and configuration sub-system stores every analysis performed with the evaluation system in a database. Configurations and results of the tools can be shared among scientists via shell or web system. Therefore, plugged-in tools benefit from transparency and reproducibility. Furthermore, if configurations match while starting an evaluation plugin, the system suggests to use results already produced by other users - saving CPU/h, I/O, disk space and time. The efficient interaction between different technologies improves the Earth system modeling science framed by Freva.

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

Pilot Tests of Satellite Snowcover/Runoff Forecasting Systems. [Arizona, Sierra Nevada Mountains (Ca), Colorado, Rocky Mountains (North America)

NASA Technical Reports Server (NTRS)

Rango, A.

1978-01-01

Major snow zones of the western U.S. were selected to test the capability of satellite systems for mapping snowcover in various snow, cloud, climatic, and vegetation regimes. Different satellite snowcover analysis methods used in each area are described along with results.

Evaluating State Principal Evaluation Plans across the United States

ERIC Educational Resources Information Center

Fuller, Edward J.; Hollingworth, Liz; Liu, Jing

2015-01-01

Recent federal legislation has created strong incentives for states to adopt principal evaluation systems, many of which include new measures of principal effectiveness such as estimates of student growth and changes in school climate. Yet, there has been little research on principal evaluation systems and no state-by-state analysis of the…

Mainstreaming Climate Change Into Geosciences Curriculum of Tertiary Educational Systems in Ghana

NASA Astrophysics Data System (ADS)

Nyarko, B. K.

2015-12-01

The impact of Climate Change has a far-reaching implication for economies and people living in the fragile Regions of Africa analysts project that by 2020, between 75 million and 250 million people will be exposed various forms of Climate Change Stresses. Education as a key strategy identified under Agenda 21 has been incorporated into the efforts of various educational institutions as a means of mitigating climate change and enhancing sustainability. Climate Change education offers many opportunities and benefits for educators, researchers, learners, and for wider society, but there are also many challenges, which can hinder the successful mainstreaming of climate change education. The study aims at understanding barriers for Climate Change Education in selected tertiary institutions in Ghana. The study was conducted among Geoscience Departments of the 7 main public universities of Ghana and also juxtapose with the WASCAL graduate school curriculum. The transcript analysis identified issues that hinders the mainstreaming of Climate Change, these includes existing levels of knowledge and understanding of the concept of climate change, appreciating the threshold concepts, ineffective teaching of Climate Change and some Departments are slow in embracing Climate Change as a discipline. Hence to develop strategies to mainstream climate change education it is important to recognize that increasing the efficiency and delivery of Climate Change education requires greater attention and coordination of activities and updating the educators knowledge and skill's. Institutions and Educator should be encouraged to undertake co-curricula activities and finding ways to make Climate Change education practical.

Investigating the Nexus of Climate, Energy, Water, and Land at Decision-Relevant Scales: The Platform for Regional Integrated Modeling and Analysis (PRIMA)

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

Kraucunas, Ian P.; Clarke, Leon E.; Dirks, James A.

2015-04-01

The Platform for Regional Integrated Modeling and Analysis (PRIMA) is an innovative modeling system developed at Pacific Northwest National Laboratory (PNNL) to simulate interactions among natural and human systems at scales relevant to regional decision making. PRIMA brings together state-of-the-art models of regional climate, hydrology, agriculture, socioeconomics, and energy systems using a flexible coupling approach. The platform can be customized to inform a variety of complex questions and decisions, such as the integrated evaluation of mitigation and adaptation options across a range of sectors. Research into stakeholder decision support needs underpins the platform's application to regional issues, including uncertainty characterization.more » Ongoing numerical experiments are yielding new insights into the interactions among human and natural systems on regional scales with an initial focus on the energy-land-water nexus in the upper U.S. Midwest. This paper focuses on PRIMA’s functional capabilities and describes some lessons learned to date about integrated regional modeling.« less

Long-term changes in river system hydrology in Texas

NASA Astrophysics Data System (ADS)

Zhang, Yiwen; Wurbs, Ralph

2018-06-01

Climate change and human actives are recognized as a topical issue that change long-term water budget, flow-frequency, and storage-frequency characteristics of different river systems. Texas is characterized by extreme hydrologic variability both spatially and temporally. Meanwhile, population and economic growth and accompanying water resources development projects have greatly impacted river flows throughout Texas. The relative effects of climate change, water resources development, water use, and other factors on long-term changes in river flow, reservoir storage, evaporation, water use, and other components of the water budgets of different river basins of Texas have been simulated in this research using the monthly version of the Water Rights Analysis Package (WRAP) modelling system with input databases sets from the Texas Commission on Environmental Quality (TCEQ) and Texas Water Development Board (TWDB). The results show that long-term changes are minimal from analysis monthly precipitation depths. Evaporation rates vary greatly seasonally and for much of the state appear to have a gradually upward trend. River/reservoir system water budgets and river flow characteristics have changed significantly during the past 75 years in response to water resources development and use.

Thermal Property Analysis of Axle Load Sensors for Weighing Vehicles in Weigh-in-Motion System

PubMed Central

Burnos, Piotr; Gajda, Janusz

2016-01-01

Systems which permit the weighing of vehicles in motion are called dynamic Weigh-in-Motion scales. In such systems, axle load sensors are embedded in the pavement. Among the influencing factors that negatively affect weighing accuracy is the pavement temperature. This paper presents a detailed analysis of this phenomenon and describes the properties of polymer, quartz and bending plate load sensors. The studies were conducted in two ways: at roadside Weigh-in-Motion sites and at a laboratory using a climate chamber. For accuracy assessment of roadside systems, the reference vehicle method was used. The pavement temperature influence on the weighing error was experimentally investigated as well as a non-uniform temperature distribution along and across the Weigh-in-Motion site. Tests carried out in the climatic chamber allowed the influence of temperature on the sensor intrinsic error to be determined. The results presented clearly show that all kinds of sensors are temperature sensitive. This is a new finding, as up to now the quartz and bending plate sensors were considered insensitive to this factor. PMID:27983704

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.

Uncertainty of climate change impact on groundwater reserves - Application to a chalk aquifer

NASA Astrophysics Data System (ADS)

Goderniaux, Pascal; Brouyère, Serge; Wildemeersch, Samuel; Therrien, René; Dassargues, Alain

2015-09-01

Recent studies have evaluated the impact of climate change on groundwater resources for different geographical and climatic contexts. However, most studies have either not estimated the uncertainty around projected impacts or have limited the analysis to the uncertainty related to climate models. In this study, the uncertainties around impact projections from several sources (climate models, natural variability of the weather, hydrological model calibration) are calculated and compared for the Geer catchment (465 km2) in Belgium. We use a surface-subsurface integrated model implemented using the finite element code HydroGeoSphere, coupled with climate change scenarios (2010-2085) and the UCODE_2005 inverse model, to assess the uncertainty related to the calibration of the hydrological model. This integrated model provides a more realistic representation of the water exchanges between surface and subsurface domains and constrains more the calibration with the use of both surface and subsurface observed data. Sensitivity and uncertainty analyses were performed on predictions. The linear uncertainty analysis is approximate for this nonlinear system, but it provides some measure of uncertainty for computationally demanding models. Results show that, for the Geer catchment, the most important uncertainty is related to calibration of the hydrological model. The total uncertainty associated with the prediction of groundwater levels remains large. By the end of the century, however, the uncertainty becomes smaller than the predicted decline in groundwater levels.

European drought under climate change and an assessment of the uncertainties in projections

NASA Astrophysics Data System (ADS)

Yu, R. M. S.; Osborn, T.; Conway, D.; Warren, R.; Hankin, R.

2012-04-01

Extreme weather/climate events have significant environmental and societal impacts, and anthropogenic climate change has and will continue to alter their characteristics (IPCC, 2011). Drought is one of the most damaging natural hazards through its effects on agricultural, hydrological, ecological and socio-economic systems. Climate change is stimulating demand, from public and private sector decision-makers and also other stakeholders, for better understanding of potential future drought patterns which could facilitate disaster risk management. There remain considerable levels of uncertainty in climate change projections, particularly in relation to extreme events. Our incomplete understanding of the behaviour of the climate system has led to the development of various emission scenarios, carbon cycle models and global climate models (GCMs). Uncertainties arise also from the different types and definitions of drought. This study examines climate change-induced changes in European drought characteristics, and illustrates the robustness of these projections by quantifying the effects of using different emission scenarios, carbon cycle models and GCMs. This is achieved by using the multi-institutional modular "Community Integrated Assessment System (CIAS)" (Warren et al., 2008), a flexible integrated assessment system for modelling climate change. Simulations generated by the simple climate model MAGICC6.0 are assessed. These include ten C4MIP carbon cycle models and eighteen CMIP3 GCMs under five IPCC SRES emission scenarios, four Representative Concentration Pathway (RCP) scenarios, and three mitigation scenarios with CO2-equivalent levels stabilising at 550 ppm, 500 ppm and 450 ppm. Using an ensemble of 2160 future precipitation scenarios, we present an analysis on both short (3-month) and long (12-month) meteorological droughts based on the Standardised Precipitation Index (SPI) for the baseline period (1951-2000) and two future periods of 2001-2050 and 2051-2100. Results indicate, with the exception of high latitude regions, a marked increase in drought condition across Europe especially in the second half of 21st century. Patterns, however, vary substantially depending on the model, emission scenario, region and season. While the variance introduced by choice of carbon cycle model is of minor importance, contribution of emission scenario becomes more important in the second half of the century; nevertheless, GCM uncertainty remains the dominant source throughout the 21st century and across all regions.

Global Climate Change, Food Security, and Local Sustainability: Increasing Climate Literacy in Urban Students

NASA Astrophysics Data System (ADS)

Boger, R. A.; Low, R.; Gorokhovich, Y.

2011-12-01

Three higher education institutions, University of Nebraska-Lincoln (UNL), Brooklyn College, and Lehman College, are working together to share expertise and resources to expand climate change topics offered to undergraduate and graduate students in New York City (NYC). This collaboration combines existing UNL educational learning resources and infrastructure in virtual coursework. It will supply global climate change education and locally-based research experiences to the highly diverse undergraduate students of Brooklyn and Lehman Colleges and to middle and high school teachers in NYC. Through the university partnership, UNL materials are being adapted and augmented to include authentic research experiences for undergraduates and teachers using NASA satellite data, geographic information system (GIS) tools, and/or locally collected microclimate data from urban gardens. Learners download NASA data, apply an Earth system approach, and employ GIS in the analysis of food production landscapes in a dynamically changing climate system. The resulting course will be offered via Blackboard courseware, supported by Web 2.0 technologies designed specifically to support dialogue, data, and web publication sharing between partners, teachers and middle school, high school and undergraduate student researchers. NYC is in the center of the urban farming movement. By exploring water and food topics of direct relevance to students' lives and community, we anticipate that students will be motivated and more empowered to make connections between climate change and potential impacts on the health and happiness of people in their community, in the United States and around the world. Final course will be piloted in 2012.

Changes in Migration Pattern of Transhumance due to Climate Change: An Empirical Analysis of Gaddi Community of Himachal Himalaya, India

NASA Astrophysics Data System (ADS)

Mishra, Himanshu; Wasini Pandey, Bindhy

2017-04-01

Transhumance is a complex and traditional livelihood system seeking to maintain equilibrium between pastures, livestock and local people in variable and inhospitable environments. In Western Himalayas in the Indian state of Himachal Pradesh, pastoral groups of Gaddis inhabit almost inaccessible areas, where scarce resources and extreme climatic conditions limit options for alternative land use and livelihood systems. In such a harsh and unforgiving environment, mobility in the form of transhumance has been the traditional ecological response to climatic extremes. However, recently, such additional factors as global as well as regional climate change have brought about changes in the tree line, snow line and pastoral grounds along the historical route of seasonal migration of the Gaddis. The growing unpredictability of the once static route of migration has raised the possibility of Gaddis shifting to alternative land use and land management techniques. In the present research, we explore how transhumant pastoralism has been sustained and stimulated in the context of socioeconomic and climate change in the mountainous region of Himachal Pradesh and the future challenges that it faces. Based on case study research conducted in Chamba district in Himachal Pradesh; we have analysed the status, opportunities, and constraints of transhumant pastoralism in the changing context and modeled the possible alternative land use decisions. Finally we conclude that unless there are affirmative and progressive policy and institutional framework to support transhumant system, the indigenous practice will soon disappear from this part of the world. Keywords: Climate change, Gaddis, Himachal Pradesh, Transhumance, Alternative Land Use

Characterizing the Sensitivity of Groundwater Storage to Climate variation in the Indus Basin

NASA Astrophysics Data System (ADS)

Huang, L.; Sabo, J. L.

2017-12-01

Indus Basin represents an extensive groundwater aquifer facing the challenge of effective management of limited water resources. Groundwater storage is one of the most important variables of water balance, yet its sensitivity to climate change has rarely been explored. To better estimate present and future groundwater storage and its sensitivity to climate change in the Indus Basin, we analyzed groundwater recharge/discharge and their historical evolution in this basin. Several methods are applied to specify the aquifer system including: water level change and storativity estimates, gravity estimates (GRACE), flow model (MODFLOW), water budget analysis and extrapolation. In addition, all of the socioeconomic and engineering aspects are represented in the hydrological system through the change of temporal and spatial distributions of recharge and discharge (e.g., land use, crop structure, water allocation, etc.). Our results demonstrate that the direct impacts of climate change will result in unevenly distributed but increasing groundwater storage in the short term through groundwater recharge. In contrast, long term groundwater storage will decrease as a result of combined indirect and direct impacts of climate change (e.g. recharge/discharge and human activities). The sensitivity of groundwater storage to climate variation is characterized by topography, aquifer specifics and land use. Furthermore, by comparing possible outcomes of different human interventions scenarios, our study reveals human activities play an important role in affecting the sensitivity of groundwater storage to climate variation. Over all, this study presents the feasibility and value of using integrated hydrological methods to support sustainable water resource management under climate change.

NOMADS-NOAA Operational Model Archive and Distribution System

Science.gov Websites

Forecast Maps Climate Climate Prediction Climate Archives Weather Safety Storm Ready NOAA Central Library (16km) 6 hours grib filter http OpenDAP-alt URMA hourly - http - Climate Models Climate Forecast System Flux Products 6 hours grib filter http - Climate Forecast System 3D Pressure Products 6 hours grib

Development of virtual research environment for regional climatic and ecological studies and continuous education support

NASA Astrophysics Data System (ADS)

Gordov, Evgeny; Lykosov, Vasily; Krupchatnikov, Vladimir; Bogomolov, Vasily; Gordova, Yulia; Martynova, Yulia; Okladnikov, Igor; Titov, Alexander; Shulgina, Tamara

2014-05-01

Volumes of environmental data archives are growing immensely due to recent models, high performance computers and sensors development. It makes impossible their comprehensive analysis in conventional manner on workplace using in house computing facilities, data storage and processing software at hands. One of possible answers to this challenge is creation of virtual research environment (VRE), which should provide a researcher with an integrated access to huge data resources, tools and services across disciplines and user communities and enable researchers to process structured and qualitative data in virtual workspaces. VRE should integrate data, network and computing resources providing interdisciplinary climatic research community with opportunity to get profound understanding of ongoing and possible future climatic changes and their consequences. Presented are first steps and plans for development of VRE prototype element aimed at regional climatic and ecological monitoring and modeling as well as at continuous education and training support. Recently developed experimental software and hardware platform aimed at integrated analysis of heterogeneous georeferenced data "Climate" (http://climate.scert.ru/, Gordov et al., 2013; Shulgina et al., 2013; Okladnikov et al., 2013) is used as a VRE element prototype and approach test bench. VRE under development will integrate on the base of geoportal distributed thematic data storage, processing and analysis systems and set of models of complex climatic and environmental processes run on supercomputers. VRE specific tools are aimed at high resolution rendering on-going climatic processes occurring in Northern Eurasia and reliable and found prognoses of their dynamics for selected sets of future mankind activity scenaria. Currently the VRE element is accessible via developed geoportal at the same link (http://climate.scert.ru/) and integrates the WRF and «Planet Simulator» models, basic reanalysis and instrumental measurements data and support profound statistical analysis of storaged and modeled on demand data. In particular, one can run the integrated models, preprocess modeling results data, using dedicated modules for numerical processing perform analysys and visualize obtained results. New functionality recently has been added to the statistical analysis tools set aimed at detailed studies of climatic extremes occurring in Northern Asia. The VRE element is also supporting thematic educational courses for students and post-graduate students of the Tomsk State University. In particular, it allow students to perform on-line thematic laboratory work cycles on the basics of analysis of current and potential future regional climate change using Siberia territory as an example (Gordova et al, 2013). We plan to expand the integrated models set and add comprehensive surface and Arctic Ocean description. Developed VRE element "Climate" provides specialists involved into multidisciplinary research projects with reliable and practical instruments for integrated research of climate and ecosystems changes on global and regional scales. With its help even a user without programming skills can process and visualize multidimensional observational and model data through unified web-interface using a common graphical web-browser. This work is partially supported by SB RAS project VIII.80.2.1, RFBR grant 13-05-12034, grant 14-05-00502, and integrated project SB RAS 131. References 1. Gordov E.P., Lykosov V.N., Krupchatnikov V.N., Okladnikov I.G., Titov A.G., Shulgina T.M. Computationaland information technologies for monitoring and modeling of climate changes and their consequences. Novosibirsk: Nauka, Siberian branch, 2013. - 195 p. (in Russian) 2. T.M. Shulgina, E.P. Gordov, I.G. Okladnikov, A.G., Titov, E.Yu. Genina, N.P. Gorbatenko, I.V. Kuzhevskaya,A.S. Akhmetshina. Software complex for a regional climate change analysis. // Vestnik NGU. Series: Information technologies. 2013. Vol. 11. Issue 1. P. 124-131. (in Russian) 3. I.G. Okladnikov, A.G. Titov, T.M. Shulgina, E.P. Gordov, V.Yu. Bogomolov, Yu.V. Martynova, S.P. Suschenko,A.V. Skvortsov. Software for analysis and visualization of climate change monitoring and forecasting data //Numerical methods and programming, 2013. Vol. 14. P. 123-131.(in Russian) 4. Yu.E. Gordova, E.Yu. Genina, V.P. Gorbatenko, E.P. Gordov, I.V. Kuzhevskaya, Yu.V. Martynova , I.G. Okladnikov, A.G. Titov, T.M. Shulgina, N.K. Barashkova Support of the educational process in modern climatology within the web-gis platform «Climate». Open and Distant Education. 2013, No 1(49)., P. 14-19.(in Russian)

Language time series analysis

NASA Astrophysics Data System (ADS)

Kosmidis, Kosmas; Kalampokis, Alkiviadis; Argyrakis, Panos

2006-10-01

We use the detrended fluctuation analysis (DFA) and the Grassberger-Proccacia analysis (GP) methods in order to study language characteristics. Despite that we construct our signals using only word lengths or word frequencies, excluding in this way huge amount of information from language, the application of GP analysis indicates that linguistic signals may be considered as the manifestation of a complex system of high dimensionality, different from random signals or systems of low dimensionality such as the Earth climate. The DFA method is additionally able to distinguish a natural language signal from a computer code signal. This last result may be useful in the field of cryptography.

The essential interactions between understanding climate variability and climate change

NASA Astrophysics Data System (ADS)

Neelin, J. D.

2017-12-01

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

Governing for a Healthy Population: Towards an Understanding of How Decision-Making Will Determine Our Global Health in a Changing Climate

PubMed Central

Bowen, Kathryn J.; Friel, Sharon; Ebi, Kristie; Butler, Colin D.; Miller, Fiona; McMichael, Anthony J.

2011-01-01

Enhancing the adaptive capacity of individuals, communities, institutions and nations is pivotal to protecting and improving human health and well-being in the face of systemic social inequity plus dangerous climate change. However, research on the determinants of adaptive capacity in relation to health, particularly concerning the role of governance, is in its infancy. This paper highlights the intersections between global health, climate change and governance. It presents an overview of these key concerns, their relation to each other, and the potential that a greater understanding of governance may present opportunities to strengthen policy and action responses to the health effects of climate change. Important parallels between addressing health inequities and sustainable development practices in the face of global environmental change are also highlighted. We propose that governance can be investigated through two key lenses within the earth system governance theoretical framework; agency and architecture. These two governance concepts can be evaluated using methods of social network research and policy analysis using case studies and is the subject of further research. PMID:22470278

Modeling climate change impacts on water trading.

PubMed

Luo, Bin; Maqsood, Imran; Gong, Yazhen

2010-04-01

This paper presents a new method of evaluating the impacts of climate change on the long-term performance of water trading programs, through designing an indicator to measure the mean of periodic water volume that can be released by trading through a water-use system. The indicator is computed with a stochastic optimization model which can reflect the random uncertainty of water availability. The developed method was demonstrated in the Swift Current Creek watershed of Prairie Canada under two future scenarios simulated by a Canadian Regional Climate Model, in which total water availabilities under future scenarios were estimated using a monthly water balance model. Frequency analysis was performed to obtain the best probability distributions for both observed and simulated water quantity data. Results from the case study indicate that the performance of a trading system is highly scenario-dependent in future climate, with trading effectiveness highly optimistic or undesirable under different future scenarios. Trading effectiveness also largely depends on trading costs, with high costs resulting in failure of the trading program. (c) 2010 Elsevier B.V. All rights reserved.

System robustness analysis for drought risk management in South Florida

NASA Astrophysics Data System (ADS)

Eilander, D.; Bouwer, L.; Barnes, J.; Mens, M.; Obeysekera, J.

2015-12-01

Drought is a frequently returning natural hazard in Florida, with at least one severe drought to be expected every decade. These droughts have had many impacts such as loss of agricultural products, inadequate public water supply and salt water intrusion into freshwater aquifers. Furthermore, climate change projections for South Florida suggest that dry spells are likely to be more frequent and prolonged, with negative impacts on water supply management for all users. In this study a System Robustness Analysis was conducted in order to analyse the effectiveness of strategies to limit the socio-economic impact of droughts under climate change. System Robustness Analysis (SRA) aims to support decision making by quantifying how well a system, with and without additional measures, can remain functioning under a range of external disturbances. Two system characteristics add up to system robustness: Resistance is the ability to withstand disturbances without responding (zero impact), and resilience is the ability to recover from the response to a disturbance. SRA can help to provide insight into the sensitivity of a system to changing magnitudes of extreme weather events. A regional-scale hydrologic and water management model is used to simulate the effect of changing precipitation and evaporation forcing on agricultural and urban water supply and demand in South Florida. The complex water management operational rules including water use restrictions are simulated in the model. Based on model runs with a various climate scenarios, drought events with a wide range of severity are identified and for each event the socio-economic impacts are determined. Here, a drought is defined as a reduced streamflow in the upstream Kissimmee basin, which contributes most to Lake Okeechobee, the major surface water storage in the system. The drought severity is characterized by the maximum drought deficit volume. Drought impacts are analyzed for several users in Miami Dade County. From the relation between drought severity and drought impact the resistance and resilience of the system for hydrological droughts are found. This relation is investigated for an array of adaptation measures and strategies in order to find strategies that will effectively increase the system's ability to deal with future drought events.

Consequences of ecological, evolutionary and biogeochemical uncertainty for coral reef responses to climatic stress.

PubMed

Mumby, Peter J; van Woesik, Robert

2014-05-19

Coral reefs are highly sensitive to the stress associated with greenhouse gas emissions, in particular ocean warming and acidification. While experiments show negative responses of most reef organisms to ocean warming, some autotrophs benefit from ocean acidification. Yet, we are uncertain of the response of coral reefs as systems. We begin by reviewing sources of uncertainty and complexity including the translation of physiological effects into demographic processes, indirect ecological interactions among species, the ability of coral reefs to modify their own chemistry, adaptation and trans-generational plasticity. We then incorporate these uncertainties into two simple qualitative models of a coral reef system under climate change. Some sources of uncertainty are far more problematic than others. Climate change is predicted to have an unambiguous negative effect on corals that is robust to several sources of uncertainty but sensitive to the degree of biogeochemical coupling between benthos and seawater. Macroalgal, zoanthid, and herbivorous fish populations are generally predicted to increase, but the ambiguity (confidence) of such predictions are sensitive to the source of uncertainty. For example, reversing the effect of climate-related stress on macroalgae from being positive to negative had no influence on system behaviour. By contrast, the system was highly sensitive to a change in the stress upon herbivorous fishes. Minor changes in competitive interactions had profound impacts on system behaviour, implying that the outcomes of mesocosm studies could be highly sensitive to the choice of taxa. We use our analysis to identify new hypotheses and suggest that the effects of climatic stress on coral reefs provide an exceptional opportunity to test emerging theories of ecological inheritance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Collateral transgression of planetary boundaries due to climate engineering by terrestrial carbon dioxide removal

NASA Astrophysics Data System (ADS)

Heck, Vera; Donges, Jonathan F.; Lucht, Wolfgang

2016-10-01

The planetary boundaries framework provides guidelines for defining thresholds in environmental variables. Their transgression is likely to result in a shift in Earth system functioning away from the relatively stable Holocene state. As the climate system is approaching critical thresholds of atmospheric carbon, several climate engineering methods are discussed, aiming at a reduction of atmospheric carbon concentrations to control the Earth's energy balance. Terrestrial carbon dioxide removal (tCDR) via afforestation or bioenergy production with carbon capture and storage are part of most climate change mitigation scenarios that limit global warming to less than 2 °C. We analyse the co-evolutionary interaction of societal interventions via tCDR and the natural dynamics of the Earth's carbon cycle. Applying a conceptual modelling framework, we analyse how the degree of anticipation of the climate problem and the intensity of tCDR efforts with the aim of staying within a "safe" level of global warming might influence the state of the Earth system with respect to other carbon-related planetary boundaries. Within the scope of our approach, we show that societal management of atmospheric carbon via tCDR can lead to a collateral transgression of the planetary boundary of land system change. Our analysis indicates that the opportunities to remain in a desirable region within carbon-related planetary boundaries only exist for a small range of anticipation levels and depend critically on the underlying emission pathway. While tCDR has the potential to ensure the Earth system's persistence within a carbon-safe operating space under low-emission pathways, it is unlikely to succeed in a business-as-usual scenario.

Vulnerability of global food production to extreme climatic events.

PubMed

Yeni, F; Alpas, H

2017-06-01

It is known that the frequency, intensity or duration of the extreme climatic events have been changing substantially. The ultimate goal of this study was to identify current vulnerabilities of global primary food production against extreme climatic events, and to discuss potential entry points for adaptation planning by means of an explorative vulnerability analysis. Outcomes of this analysis were demonstrated as a composite index where 118 country performances in maintaining safety of food production were compared and ranked against climate change. In order to better interpret the results, cluster analysis technique was used as a tool to group the countries based on their vulnerability index (VI) scores. Results suggested that one sixth of the countries analyzed were subject to high level of exposure (0.45-1), one third to high to very high level of sensitivity (0.41-1) and low to moderate level of adaptive capacity (0-0.59). Proper adaptation strategies for reducing the microbial and chemical contamination of food products, soil and waters on the field were proposed. Finally, availability of data on food safety management systems and occurrence of foodborne outbreaks with global coverage were proposed as key factors for improving the robustness of future vulnerability assessments. Copyright © 2017 Elsevier Ltd. All rights reserved.

Residential Cold Climate Heat Pump (CCHP) w/Variable Speed Technology

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

Messmer, Craig S.

2016-09-30

This report summarizes the results of a three year program awarded to Unico, Inc. to commercialize a residential cold climate heat pump. Several designs were investigated. Compressors were selected using analysis from Oakridge National Laboratories followed by prototype construction and lab testing in a specially built environmental chamber capable of reaching -30°F. The initial design utilized two variable speed compressors in series with very good capacity results and acceptable efficiency at very cold temperatures. The design was then modified to reduce cost and complexity by redesigning the system using three dual-stage compressors: two in parallel followed by one in series.more » Extensive testing found significant challenge with oil management, reliability, weight and cost which prevented the system from being fully commercialized. Further analysis of other conceptual designs indicated that these challenges could be overcome in the future.« less

Simulating the Pineapple Express in the half degree Community Climate System Model, CCSM4

NASA Astrophysics Data System (ADS)

Shields, Christine A.; Kiehl, Jeffrey T.

2016-07-01

Atmospheric rivers are recognized as major contributors to the poleward transport of water vapor. Upon reaching land, these phenomena also play a critical role in extreme precipitation and flooding events. The Pineapple Express (PE) is defined as an atmospheric river extending out of the deep tropics and reaching the west coast of North America. Community Climate System Model (CCSM4) high-resolution ensemble simulations for the twentieth and 21st centuries are diagnosed to identify the PE. Analysis of the twentieth century simulations indicated that the CCSM4 accurately captures the spatial and temporal climatology of the PE. Analysis of the end 21st century simulations indicates a significant increase in storm duration and intensity of precipitation associated with landfall of the PE. Only a modest increase in the number of atmospheric rivers of a few percent is projected for the end of 21st century.

Projective analysis of staple food crop productivity in adaptation to future climate change in China

NASA Astrophysics Data System (ADS)

Zhang, Qing; Zhang, Wen; Li, Tingting; Sun, Wenjuan; Yu, Yongqiang; Wang, Guocheng

2017-08-01

Climate change continually affects our capabilities to feed the increasing population. Rising temperatures have the potential to shorten the crop growth duration and therefore reduce crop yields. In the past decades, China has successfully improved crop cultivars to stabilize, and even lengthen, the crop growth duration to make use of increasing heat resources. However, because of the complex cropping systems in the different regions of China, the possibility and the effectiveness of regulating crop growth duration to reduce the negative impacts of future climate change remain questionable. Here, we performed a projective analysis of the staple food crop productivity in double-rice, wheat-rice, wheat-maize, single-rice, and single-maize cropping systems in China using modeling approaches. The results indicated that from the present to the 2040s, the warming climate would shorten the growth duration of the current rice, wheat, and maize cultivars by 2-24, 11-13, and 9-29 days, respectively. The most significant shortening of the crop growth duration would be in Northeast China, where single-rice and single-maize cropping dominates the croplands. The shortened crop growth duration would consequently reduce crop productivity. The most significant decreases would be 27-31, 6-20, and 7-22% for the late crop in the double-rice rotation, wheat in the winter wheat-rice rotation, and single maize, respectively. However, our projection analysis also showed that the negative effects of the warming climate could be compensated for by stabilizing the growth duration of the crops via improvement in crop cultivars. In this case, the productivity of rice, wheat, and maize in the 2040s would increase by 4-16, 31-38, and 11-12%, respectively. Our modeling results implied that the possibility of securing future food production exists by adopting proper adaptation options in China.

First decadal lunar results from the Moon and Earth Radiation Budget Experiment.

PubMed

Matthews, Grant

2018-03-01

A need to gain more confidence in computer model predictions of coming climate change has resulted in greater analysis of the quality of orbital Earth radiation budget (ERB) measurements being used today to constrain, validate, and hence improve such simulations. These studies conclude from time series analysis that for around a quarter of a century, no existing satellite ERB climate data record is of a sufficient standard to partition changes to the Earth from those of un-tracked and changing artificial instrumentation effects. This led to the creation of the Moon and Earth Radiation Budget Experiment (MERBE), which instead takes existing decades old climate data to a higher calibration standard using thousands of scans of Earth's Moon. The Terra and Aqua satellite ERB climate records have been completely regenerated using signal-processing improvements, combined with a substantial increase in precision from more comprehensive in-flight spectral characterization techniques. This study now builds on previous Optical Society of America work by describing new Moon measurements derived using accurate analytical mapping of telescope spatial response. That then allows a factor of three reduction in measurement noise along with an order of magnitude increase in the number of retrieved independent lunar results. Given decadal length device longevity and the use of solar and thermal lunar radiance models to normalize the improved ERB results to the International System of Units traceable radiance scale of the "MERBE Watt," the same established environmental time series analysis techniques are applied to MERBE data. They evaluate it to perhaps be of sufficient quality to immediately begin narrowing the largest of climate prediction uncertainties. It also shows that if such Terra/Aqua ERB devices can operate into the 2020s, it could become possible to halve these same uncertainties decades sooner than would be possible with existing or even planned new observing systems.

Projective analysis of staple food crop productivity in adaptation to future climate change in China.

PubMed

Zhang, Qing; Zhang, Wen; Li, Tingting; Sun, Wenjuan; Yu, Yongqiang; Wang, Guocheng

2017-08-01

Climate change continually affects our capabilities to feed the increasing population. Rising temperatures have the potential to shorten the crop growth duration and therefore reduce crop yields. In the past decades, China has successfully improved crop cultivars to stabilize, and even lengthen, the crop growth duration to make use of increasing heat resources. However, because of the complex cropping systems in the different regions of China, the possibility and the effectiveness of regulating crop growth duration to reduce the negative impacts of future climate change remain questionable. Here, we performed a projective analysis of the staple food crop productivity in double-rice, wheat-rice, wheat-maize, single-rice, and single-maize cropping systems in China using modeling approaches. The results indicated that from the present to the 2040s, the warming climate would shorten the growth duration of the current rice, wheat, and maize cultivars by 2-24, 11-13, and 9-29 days, respectively. The most significant shortening of the crop growth duration would be in Northeast China, where single-rice and single-maize cropping dominates the croplands. The shortened crop growth duration would consequently reduce crop productivity. The most significant decreases would be 27-31, 6-20, and 7-22% for the late crop in the double-rice rotation, wheat in the winter wheat-rice rotation, and single maize, respectively. However, our projection analysis also showed that the negative effects of the warming climate could be compensated for by stabilizing the growth duration of the crops via improvement in crop cultivars. In this case, the productivity of rice, wheat, and maize in the 2040s would increase by 4-16, 31-38, and 11-12%, respectively. Our modeling results implied that the possibility of securing future food production exists by adopting proper adaptation options in China.

Challenges of coordinating global climate observations - Role of satellites in climate monitoring

NASA Astrophysics Data System (ADS)

Richter, C.

2017-12-01

Global observation of the Earth's atmosphere, ocean and land is essential for identifying climate variability and change, and for understanding their causes. Observation also provides data that are fundamental for evaluating, refining and initializing the models that predict how the climate system will vary over the months and seasons ahead, and that project how climate will change in the longer term under different assumptions concerning greenhouse gas emissions and other human influences. Long-term observational records have enabled the Intergovernmental Panel on Climate Change to deliver the message that warming of the global climate system is unequivocal. As the Earth's climate enters a new era, in which it is forced by human activities, as well as natural processes, it is critically important to sustain an observing system capable of detecting and documenting global climate variability and change over long periods of time. High-quality climate observations are required to assess the present state of the ocean, cryosphere, atmosphere and land and place them in context with the past. The global observing system for climate is not a single, centrally managed observing system. Rather, it is a composite "system of systems" comprising a set of climate-relevant observing, data-management, product-generation and data-distribution systems. Data from satellites underpin many of the Essential Climate Variables(ECVs), and their historic and contemporary archives are a key part of the global climate observing system. In general, the ECVs will be provided in the form of climate data records that are created by processing and archiving time series of satellite and in situ measurements. Early satellite data records are very valuable because they provide unique observations in many regions which were not otherwise observed during the 1970s and which can be assimilated in atmospheric reanalyses and so extend the satellite climate data records back in time.

Development of climate risk services under climate change scenarios in the North Adriatic coast (Italy).

NASA Astrophysics Data System (ADS)

Valentina, Gallina; Silvia, Torresan; Anna, Sperotto; Elisa, Furlan; Andrea, Critto; Antonio, Marcomini

2014-05-01

Nowadays, the challenge for coastal stakeholders and decision makers is to incorporate climate change in land and policy planning in order to ensure a sustainable integrated coastal zone management aimed at preserve coastal environments and socio-economic activities. Consequently, an increasing amount of information on climate variability and its impact on human and natural ecosystem is requested. Climate risk services allows to bridge the gap between climate experts and decision makers communicating timely science-based information about impacts and risks related to climate change that could be incorporated into land planning, policy and practice. Within the CLIM-RUN project (FP7), a participatory Regional Risk Assessment (RRA) methodology was applied for the evaluation of water-related hazards in coastal areas (i.e. pluvial flood and sea-level rise inundation risks) taking into consideration future climate change scenarios in the case study of the North Adriatic Sea for the period 2040-2050. Specifically, through the analysis of hazard, exposure, vulnerability and risk and the application of Multi-Criteria Decision Analysis (MCDA), the RRA methodology allowed to identify and prioritize targets (i.e. residential and commercial-industrial areas, beaches, infrastructures, wetlands, agricultural typology) and sub-areas that are more likely to be affected by pluvial flood and sea-level rise impacts in the same region. From the early stages of the climate risk services development and application, the RRA followed a bottom-up approach taking into account the needs, knowledge and perspectives of local stakeholders dealing with the Integrated Coastal Zone Management (ICZM), by means of questionnaires, workshops and focus groups organized within the project. Specifically, stakeholders were asked to provide their needs in terms of time scenarios, geographical scale and resolution, choice of receptors, vulnerability factors and thresholds that were considered in the implementation of the RRA methodology. The main output of the analysis are climate risk products produced with the DEcision support SYstem for COastal climate change impact assessment (DESYCO) and represented by GIS-based maps and statistics of hazard, exposure, physical and environmental vulnerability, risk and damage. These maps are useful to transfer information about climate change impacts to stakeholders and decision makers, to allow the classification and prioritization of areas that are likely to be affected by climate change impacts more severely than others in the same region, and therefore to support the identification of suitable areas for infrastructure, economic activities and human settlements toward the development of regional adaptation plans. The climate risk products and the results of North Adriatic case study will be here presented and discussed.

Parametric Analysis of Energy Consumption in Army Buildings by the Building Loads Analysis and System Thermodynamics (BLAST) Computer Program.

DTIC Science & Technology

1980-08-01

orientation, and HVAC systems have on three Army buildings in five different climatic regions. f Optimization of EnerV Usage in Military Facilities...The clinic’s environment is maintained by a multizone air-handling unit served by its own boiler and chiller . The building was modeled with 30... setpoints for the space temperature. This type of throttling range allows the heating system to control around a throttling range of 67 to 69oF (19 to 200

The Climate Data Analytic Services (CDAS) Framework.

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2016-12-01

Faced with unprecedented growth in climate data volume and demand, NASA has developed the Climate Data Analytic Services (CDAS) framework. This framework enables scientists to execute data processing workflows combining common analysis operations in a high performance environment close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted climate data analysis tools (ESMF, CDAT, NCO, etc.). A dynamic caching architecture enables interactive response times. CDAS utilizes Apache Spark for parallelization and a custom array framework for processing huge datasets within limited memory spaces. CDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using either direct web service calls, a python script, a unix-like shell client, or a javascript-based web application. Client packages in python, scala, or javascript contain everything needed to make CDAS requests. The CDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service permits decision makers to investigate climate changes around the globe, inspect model trends and variability, and compare multiple reanalysis datasets.

Advancements to Visualization Control System (VCS, part of UV-CDAT), a Visualization Package Designed for Climate Scientists

NASA Astrophysics Data System (ADS)

Lipsa, D.; Chaudhary, A.; Williams, D. N.; Doutriaux, C.; Jhaveri, S.

2017-12-01

Climate Data Analysis Tools (UV-CDAT, https://uvcdat.llnl.gov) is a data analysis and visualization software package developed at Lawrence Livermore National Laboratory and designed for climate scientists. Core components of UV-CDAT include: 1) Community Data Management System (CDMS) which provides I/O support and a data model for climate data;2) CDAT Utilities (GenUtil) that processes data using spatial and temporal averaging and statistic functions; and 3) Visualization Control System (VCS) for interactive visualization of the data. VCS is a Python visualization package primarily built for climate scientists, however, because of its generality and breadth of functionality, it can be a useful tool to other scientific applications. VCS provides 1D, 2D and 3D visualization functions such as scatter plot and line graphs for 1d data, boxfill, meshfill, isofill, isoline for 2d scalar data, vector glyphs and streamlines for 2d vector data and 3d_scalar and 3d_vector for 3d data. Specifically for climate data our plotting routines include projections, Skew-T plots and Taylor diagrams. While VCS provided a user-friendly API, the previous implementation of VCS relied on slow performing vector graphics (Cairo) backend which is suitable for smaller dataset and non-interactive graphics. LLNL and Kitware team has added a new backend to VCS that uses the Visualization Toolkit (VTK) as its visualization backend. VTK is one of the most popular open source, multi-platform scientific visualization library written in C++. Its use of OpenGL and pipeline processing architecture results in a high performant VCS library. Its multitude of available data formats and visualization algorithms results in easy adoption of new visualization methods and new data formats in VCS. In this presentation, we describe recent contributions to VCS that includes new visualization plots, continuous integration testing using Conda and CircleCI, tutorials and examples using Jupyter notebooks as well as upgrades that we are planning in the near future which will improve its ease of use and reliability and extend its capabilities.

Assessing climate change and socio-economic uncertainties in long term management of water resources

NASA Astrophysics Data System (ADS)

Jahanshahi, Golnaz; Dawson, Richard; Walsh, Claire; Birkinshaw, Stephen; Glenis, Vassilis

2015-04-01

Long term management of water resources is challenging for decision makers given the range of uncertainties that exist. Such uncertainties are a function of long term drivers of change, such as climate, environmental loadings, demography, land use and other socio economic drivers. Impacts of climate change on frequency of extreme events such as drought make it a serious threat to water resources and water security. The release of probabilistic climate information, such as the UKCP09 scenarios, provides improved understanding of some uncertainties in climate models. This has motivated a more rigorous approach to dealing with other uncertainties in order to understand the sensitivity of investment decisions to future uncertainty and identify adaptation options that are as far as possible robust. We have developed and coupled a system of models that includes a weather generator, simulations of catchment hydrology, demand for water and the water resource system. This integrated model has been applied in the Thames catchment which supplies the city of London, UK. This region is one of the driest in the UK and hence sensitive to water availability. In addition, it is one of the fastest growing parts of the UK and plays an important economic role. Key uncertainties in long term water resources in the Thames catchment, many of which result from earth system processes, are identified and quantified. The implications of these uncertainties are explored using a combination of uncertainty analysis and sensitivity testing. The analysis shows considerable uncertainty in future rainfall, river flow and consequently water resource. For example, results indicate that by the 2050s, low flow (Q95) in the Thames catchment will range from -44 to +9% compared with the control scenario (1970s). Consequently, by the 2050s the average number of drought days are expected to increase 4-6 times relative to the 1970s. Uncertainties associated with urban growth increase these risks further. Adaptation measures, such as new reservoirs can manage these risks to a certain extent, but our sensitivity testing demonstrates that they are less robust to future uncertainties than measures taken to reduce water demand. Keywords: Climate change, Uncertainty, Decision making, Drought, Risk, Water resources management.

Application of Multi-Model CMIP5 Analysis in Future Drought Adaptation Strategies

NASA Astrophysics Data System (ADS)

Casey, M.; Luo, L.; Lang, Y.

2014-12-01

Drought influences the efficacy of numerous natural and artificial systems including species diversity, agriculture, and infrastructure. Global climate change raises concerns that extend well beyond atmospheric and hydrological disciplines - as climate changes with time, the need for system adaptation becomes apparent. Drought, as a natural phenomenon, is typically defined relative to the climate in which it occurs. Typically a 30-year reference time frame (RTF) is used to determine the severity of a drought event. This study investigates the projected future droughts over North America with different RTFs. Confidence in future hydroclimate projection is characterized by the agreement of long term (2005-2100) multi-model precipitation (P) and temperature (T) projections within the Coupled model Intercomparison Project Phase 5 (CMIP5). Drought severity and the propensity of extreme conditions are measured by the multi-scalar, probabilistic, RTF-based Standard Precipitation Index (SPI) and Standard Precipitation Evapotranspiration Index (SPEI). SPI considers only P while SPEI incorporates Evapotranspiration (E) via T; comparing the two reveals the role of temperature change in future hydroclimate change. Future hydroclimate conditions, hydroclimate extremity, and CMIP5 model agreement are assessed for each Representative Concentration Pathway (RCP 2.6, 4.5, 6.0, 8.5) in regions throughout North America for the entire year and for the boreal seasons. In addition, multiple time scales of SPI and SPEI are calculated to characterize drought at time scales ranging from short to long term. The study explores a simple, standardized method for considering adaptation in future drought assessment, which provides a novel perspective to incorporate adaptation with climate change. The result of the analysis is a multi-dimension, probabilistic summary of the hydrological (P, E) environment a natural or artificial system must adapt to over time. Studies similar to this with specified criteria (SPI/SPEI value, time scale, RCP, etc.) can provide professionals in a variety of disciplines with necessary climatic insight to develop adaptation strategies.

Lead and Lags of Lake System Responses to Late Allerød and Early Younger Dryas Climatic Fluctuation - an Example from Varved Lake Sediments from Northern Poland (Central Europe)

NASA Astrophysics Data System (ADS)

Slowinski, M. M.; Zawiska, I.; Ott, F.; Noryśkiewicz, A. M.; Plessen, B.; Apolinarska, K.; Lutyńska, M.; Michczynska, D. J.; Wulf, S.; Skubała, P.; Błaszkiewicz, M.; Brauer, A.

2014-12-01

The transition from the warmer Allerød to the cooler Younger Dryas period is well understood to represent sudden and extreme climate changes during the end of the last glaciation. Thus, lake sediment studies within paleoclimatic and paleoecological research on this transition are ideal to enhance the knowledge about "lead and lags" of lake system responses to abrupt climate changes through applying multi-proxy sediment analyses. In this study, we present the results of high-resolution studies on varved late glacial sediments from the Trzechowskie paleolake, located in the northern Poland (center Europe). High-resolution bio-proxies (pollen, macrofossils, Cladocera and diatoms), geochemical analyses (µ-XRF data, TOC, C/N ratios, δ18Ocarb and δ13Corg stable isotopes) and a robust chronology based on varve counting, AMS 14C dating and tephrochronology were used to reconstruct the lake system responses to rapid climatic and environmental changes of Trzechowskie paleolake during the late Allerød - Younger Dryas transition. Paleoecological and geochemical analyses, which were carried out in a 4 to 16 years temporal sample resolution, allowed to defining short-termed shifts of the ecosystem that were triggered by abrupt climate changes. The rapid and pronounced cooling at the beginning of the Younger Dryas had a major impact on the lake and its catchment as clearly reflected by not synchronous changes of both, biotic and geochemical proxies. The results of high-resolution analysis indicate (a) an increased precipitation during the Allerød-YD transition, which is responsible for an increase of soil erosion in the catchment during this period, (b) a delayed response of the vegetation compared to the lake depositional system at the YD onset of 20 years, and (c) a non-synchronicity of vegetation responses between Western (Lake Meerfelder Maar) and Eastern European sites (Trzechowskie palaeolake) at the YD onset. This study is a contribution to the Virtual Institute ICLEA (Integrated Climate and Landscape Evolution Analysis) funded by the Helmholtz Association. The research was supported by the National Science Centre Poland (grants No. NN 306085037 and NCN 2011/01/B/ST10/07367).

Evaluating Transient Global and Regional Model Simulations: Bridging the Model/Observations Information Gap

NASA Astrophysics Data System (ADS)

Rutledge, G. K.; Karl, T. R.; Easterling, D. R.; Buja, L.; Stouffer, R.; Alpert, J.

2001-05-01

A major transition in our ability to evaluate transient Global Climate Model (GCM) simulations is occurring. Real-time and retrospective numerical weather prediction analysis, model runs, climate simulations and assessments are proliferating from a handful of national centers to dozens of groups across the world. It is clear that it is no longer sufficient for any one national center to develop its data services alone. The comparison of transient GCM results with the observational climate record is difficult for several reasons. One limitation is that the global distributions of a number of basic climate quantities, such as precipitation, are not well known. Similarly, observational limitations exist with model re-analysis data. Both the NCEP/NCAR, and the ECMWF, re-analysis eliminate the problems of changing analysis systems but observational data also contain time-dependant biases. These changes in input data are blended with the natural variability making estimates of true variability uncertain. The need for data homogeneity is critical to study questions related to the ability to evaluate simulation of past climate. One approach to correct for time-dependant biases and data sparse regions is the development and use of high quality 'reference' data sets. The primary U.S. National responsibility for the archive and service of weather and climate data rests with the National Climatic Data Center (NCDC). However, as supercomputers increase the temporal and spatial resolution of both Numerical Weather Prediction (NWP) and GCM models, the volume and varied formats of data presented for archive at NCDC, using current communications technologies and data management techniques is limiting the scientific access of these data. To address this ever expanding need for climate and NWP information, NCDC along with the National Center's for Environmental Prediction (NCEP) have initiated the NOAA Operational Model Archive and Distribution System (NOMADS). NOMADS is a collaboration between the Center for Ocean-Land-Atmosphere studies (COLA); the Geophysical Fluid Dynamics Laboratory (GFDL); the George Mason University (GMU); the National Center for Atmospheric Research (NCAR); the NCDC; NCEP; the Pacific Marine Environmental Laboratory (PMEL); and the University of Washington. The objective of the NOMADS is to preserve and provide retrospective access to GCM's and reference quality long-term observational and high volume three dimensional data as well as NCEP NWP models and re-start and re-analysis information. The creation of the NOMADS features a data distribution, format independent, methodology enabling scientific collaboration between researchers. The NOMADS configuration will allow a researcher to transparently browse, extract and intercompare retrospective observational and model data products from any of the participating centers. NOMADS will provide the ability to easily initialize and compare the results of ongoing climate model assessments and NWP output. Beyond the ingest and access capability soon to be implemented with NOMADS is the challenge of algorithm development for the inter-comparison of large-array data (e.g., satellite and radar) with surface, upper-air, and sub-surface ocean observational data. The implementation of NOMADS should foster the development of new quality control processes by taking advantage of distributed data access.