Complex networks as a unified framework for descriptive analysis and predictive modeling in climate
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steinhaeuser, Karsten J K; Chawla, Nitesh; Ganguly, Auroop R
The analysis of climate data has relied heavily on hypothesis-driven statistical methods, while projections of future climate are based primarily on physics-based computational models. However, in recent years a wealth of new datasets has become available. Therefore, we take a more data-centric approach and propose a unified framework for studying climate, with an aim towards characterizing observed phenomena as well as discovering new knowledge in the climate domain. Specifically, we posit that complex networks are well-suited for both descriptive analysis and predictive modeling tasks. We show that the structural properties of climate networks have useful interpretation within the domain. Further,more » we extract clusters from these networks and demonstrate their predictive power as climate indices. Our experimental results establish that the network clusters are statistically significantly better predictors than clusters derived using a more traditional clustering approach. Using complex networks as data representation thus enables the unique opportunity for descriptive and predictive modeling to inform each other.« less
Climate Science Performance, Data and Productivity on Titan
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mayer, Benjamin W; Worley, Patrick H; Gaddis, Abigail L
2015-01-01
Climate Science models are flagship codes for the largest of high performance computing (HPC) resources, both in visibility, with the newly launched Department of Energy (DOE) Accelerated Climate Model for Energy (ACME) effort, and in terms of significant fractions of system usage. The performance of the DOE ACME model is captured with application level timers and examined through a sizeable run archive. Performance and variability of compute, queue time and ancillary services are examined. As Climate Science advances in the use of HPC resources there has been an increase in the required human and data systems to achieve programs goals.more » A description of current workflow processes (hardware, software, human) and planned automation of the workflow, along with historical and projected data in motion and at rest data usage, are detailed. The combination of these two topics motivates a description of future systems requirements for DOE Climate Modeling efforts, focusing on the growth of data storage and network and disk bandwidth required to handle data at an acceptable rate.« less
Pliocene Model Intercomparison (PlioMIP) Phase 2: Scientific Objectives and Experimental Design
NASA Technical Reports Server (NTRS)
Haywood, A. M.; Dowsett, H. J.; Dolan, A. M.; Rowley, D.; Abe-Ouchi, A.; Otto-Bliesner, B.; Chandler, M. A.; Hunter, S. J.; Lunt, D. J.; Pound, M.;
2015-01-01
The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, and their potential relevance in the context of future climate change. PlioMIP operates under the umbrella of the Palaeoclimate Modelling Intercomparison Project (PMIP), which examines multiple intervals in Earth history, the consistency of model predictions in simulating these intervals and their ability to reproduce climate signals preserved in geological climate archives. This paper provides a thorough model intercomparison project description, and documents the experimental design in a detailed way. Specifically, this paper describes the experimental design and boundary conditions that will be utilized for the experiments in Phase 2 of PlioMIP.
Social norms and efficacy beliefs drive the Alarmed segment’s public-sphere climate actions
NASA Astrophysics Data System (ADS)
Doherty, Kathryn L.; Webler, Thomas N.
2016-09-01
Surprisingly few individuals who are highly concerned about climate change take action to influence public policies. To assess social-psychological and cognitive drivers of public-sphere climate actions of Global Warming’s Six Americas `Alarmed’ segment, we developed a behaviour model and tested it using structural equation modelling of survey data from Vermont, USA (N = 702). Our model, which integrates social cognitive theory, social norms research, and value belief norm theory, explains 36-64% of the variance in five behaviours. Here we show descriptive social norms, self-efficacy, personal response efficacy, and collective response efficacy as strong driving forces of: voting, donating, volunteering, contacting government officials, and protesting about climate change. The belief that similar others took action increased behaviour and strengthened efficacy beliefs, which also led to greater action. Our results imply that communication efforts targeting Alarmed individuals and their public actions should include strategies that foster beliefs about positive descriptive social norms and efficacy.
A dynamic, climate-driven model of Rift Valley fever.
Leedale, Joseph; Jones, Anne E; Caminade, Cyril; Morse, Andrew P
2016-03-31
Outbreaks of Rift Valley fever (RVF) in eastern Africa have previously occurred following specific rainfall dynamics and flooding events that appear to support the emergence of large numbers of mosquito vectors. As such, transmission of the virus is considered to be sensitive to environmental conditions and therefore changes in climate can impact the spatiotemporal dynamics of epizootic vulnerability. Epidemiological information describing the methods and parameters of RVF transmission and its dependence on climatic factors are used to develop a new spatio-temporal mathematical model that simulates these dynamics and can predict the impact of changes in climate. The Liverpool RVF (LRVF) model is a new dynamic, process-based model driven by climate data that provides a predictive output of geographical changes in RVF outbreak susceptibility as a result of the climate and local livestock immunity. This description of the multi-disciplinary process of model development is accessible to mathematicians, epidemiological modellers and climate scientists, uniting dynamic mathematical modelling, empirical parameterisation and state-of-the-art climate information.
Barry, Dwight; McDonald, Shea
2013-01-01
Climate change could significantly influence seasonal streamflow and water availability in the snowpack-fed watersheds of Washington, USA. Descriptions of snowpack decline often use linear ordinary least squares (OLS) models to quantify this change. However, the region's precipitation is known to be related to climate cycles. If snowpack decline is more closely related to these cycles, an OLS model cannot account for this effect, and thus both descriptions of trends and estimates of decline could be inaccurate. We used intervention analysis to determine whether snow water equivalent (SWE) in 25 long-term snow courses within the Olympic and Cascade Mountains are more accurately described by OLS (to represent gradual change), stationary (to represent no change), or step-stationary (to represent climate cycling) models. We used Bayesian information-theoretic methods to determine these models' relative likelihood, and we found 90 models that could plausibly describe the statistical structure of the 25 snow courses' time series. Posterior model probabilities of the 29 "most plausible" models ranged from 0.33 to 0.91 (mean = 0.58, s = 0.15). The majority of these time series (55%) were best represented as step-stationary models with a single breakpoint at 1976/77, coinciding with a major shift in the Pacific Decadal Oscillation. However, estimates of SWE decline differed by as much as 35% between statistically plausible models of a single time series. This ambiguity is a critical problem for water management policy. Approaches such as intervention analysis should become part of the basic analytical toolkit for snowpack or other climatic time series data.
NCPP's Use of Standard Metadata to Promote Open and Transparent Climate Modeling
NASA Astrophysics Data System (ADS)
Treshansky, A.; Barsugli, J. J.; Guentchev, G.; Rood, R. B.; DeLuca, C.
2012-12-01
The National Climate Predictions and Projections (NCPP) Platform is developing comprehensive regional and local information about the evolving climate to inform decision making and adaptation planning. This includes both creating and providing tools to create metadata about the models and processes used to create its derived data products. NCPP is using the Common Information Model (CIM), an ontology developed by a broad set of international partners in climate research, as its metadata language. This use of a standard ensures interoperability within the climate community as well as permitting access to the ecosystem of tools and services emerging alongside the CIM. The CIM itself is divided into a general-purpose (UML & XML) schema which structures metadata documents, and a project or community-specific (XML) Controlled Vocabulary (CV) which constraints the content of metadata documents. NCPP has already modified the CIM Schema to accommodate downscaling models, simulations, and experiments. NCPP is currently developing a CV for use by the downscaling community. Incorporating downscaling into the CIM will lead to several benefits: easy access to the existing CIM Documents describing CMIP5 models and simulations that are being downscaled, access to software tools that have been developed in order to search, manipulate, and visualize CIM metadata, and coordination with national and international efforts such as ES-DOC that are working to make climate model descriptions and datasets interoperable. Providing detailed metadata descriptions which include the full provenance of derived data products will contribute to making that data (and, the models and processes which generated that data) more open and transparent to the user community.
Atmospheric Radiation Measurement (ARM) Climate Research Facility Management Plan
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mather, James
2016-04-01
Mission and Vision Statements for the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility Mission The ARM Climate Research Facility, a DOE scientific user facility, provides the climate research community with strategically located in situ and remote-sensing observatories designed to improve the understanding and representation, in climate and earth system models, of clouds and aerosols as well as their interactions and coupling with the Earth’s surface. Vision To provide a detailed and accurate description of the Earth atmosphere in diverse climate regimes to resolve the uncertainties in climate and Earth system models toward the development ofmore » sustainable solutions for the nation's energy and environmental challenges.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Covey, Curt; Hoffman, Forrest
2008-10-02
This project will quantify selected components of climate forcing due to changes in the terrestrial biosphere over the period 1948-2004, as simulated by the climate / carboncycle models participating in C-LAMP (the Carbon-Land Model Intercomparison Project; see http://www.climatemodeling.org/c-lamp). Unlike other C-LAMP projects that attempt to close the carbon budget, this project will focus on the contributions of individual biomes in terms of the resulting climate forcing. Bala et al. (2007) used a similar (though more comprehensive) model-based technique to assess and compare different components of biospheric climate forcing, but their focus was on potential future deforestation rather than the historicalmore » period.« less
Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M.; Quiñónes, Martha L.; Jiménez, Mónica M.; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J.; Thomson, Madeleine C.
2014-01-01
As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. PMID:24891460
NASA Astrophysics Data System (ADS)
Clark, D. B.; Mercado, L. M.; Sitch, S.; Jones, C. D.; Gedney, N.; Best, M. J.; Pryor, M.; Rooney, G. G.; Essery, R. L. H.; Blyth, E.; Boucher, O.; Harding, R. J.; Huntingford, C.; Cox, P. M.
2011-09-01
The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Many studies have demonstrated the important role of the land surface in the functioning of the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of climate change, increasing atmospheric carbon dioxide concentrations, changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. This paper describes the consolidation of these advances in the modelling of carbon fluxes and stores, in both the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bartholomew, M. J.
To improve the quantitative description of precipitation processes in climate models, the Atmospheric Radiation Measurement (ARM) Climate Research Facility deployed rain gauges located near disdrometers (DISD and VDIS data streams). This handbook deals specifically with the rain gauges that make the observations for the RAIN data stream. Other precipitation observations are made by the surface meteorology instrument suite (i.e., MET data stream).
Representation of the Great Lakes in the Coupled Model Intercomparison Project Version 5
NASA Astrophysics Data System (ADS)
Briley, L.; Rood, R. B.
2017-12-01
The U.S. Great Lakes play a significant role in modifying regional temperatures and precipitation, and as the lakes change in response to a warming climate (i.e., warmer surface water temperatures, decreased ice cover, etc) lake-land-atmosphere dynamics are affected. Because the lakes modify regional weather and are a driver of regional climate change, understanding how they are represented in climate models is important to the reliability of model based information for the region. As part of the Great Lakes Integrated Sciences + Assessments (GLISA) Ensemble project, a major effort is underway to evaluate the Coupled Model Intercomparison Project version (CMIP) 5 global climate models for how well they physically represent the Great Lakes and lake-effects. The CMIP models were chosen because they are a primary source of information in many products developed for decision making (i.e., National Climate Assessment, downscaled future climate projections, etc.), yet there is very little description of how well they represent the lakes. This presentation will describe the results of our investigation of if and how the Great Lakes are represented in the CMIP5 models.
Estimation of the fractional coverage of rainfall in climate models
NASA Technical Reports Server (NTRS)
Eltahir, E. A. B.; Bras, R. L.
1993-01-01
The fraction of the grid cell area covered by rainfall, mu, is an essential parameter in descriptions of land surface hydrology in climate models. A simple procedure is presented for estimating this fraction, based on extensive observations of storm areas and rainfall volumes. Storm area and rainfall volume are often linearly related; this relation can be used to compute the storm area from the volume of rainfall simulated by a climate model. A formula is developed for computing mu, which describes the dependence of the fractional coverage of rainfall on the season of the year, the geographical region, rainfall volume, and the spatial and temporal resolution of the model. The new formula is applied in computing mu over the Amazon region. Significant temporal variability in the fractional coverage of rainfall is demonstrated. The implications of this variability for the modeling of land surface hydrology in climate models are discussed.
NASA Astrophysics Data System (ADS)
Vansteenkiste, Thomas; Tavakoli, Mohsen; Ntegeka, Victor; De Smedt, Florimond; Batelaan, Okke; Pereira, Fernando; Willems, Patrick
2014-11-01
The objective of this paper is to investigate the effects of hydrological model structure and calibration on climate change impact results in hydrology. The uncertainty in the hydrological impact results is assessed by the relative change in runoff volumes and peak and low flow extremes from historical and future climate conditions. The effect of the hydrological model structure is examined through the use of five hydrological models with different spatial resolutions and process descriptions. These were applied to a medium sized catchment in Belgium. The models vary from the lumped conceptual NAM, PDM and VHM models over the intermediate detailed and distributed WetSpa model to the fully distributed MIKE SHE model. The latter model accounts for the 3D groundwater processes and interacts bi-directionally with a full hydrodynamic MIKE 11 river model. After careful and manual calibration of these models, accounting for the accuracy of the peak and low flow extremes and runoff subflows, and the changes in these extremes for changing rainfall conditions, the five models respond in a similar way to the climate scenarios over Belgium. Future projections on peak flows are highly uncertain with expected increases as well as decreases depending on the climate scenario. The projections on future low flows are more uniform; low flows decrease (up to 60%) for all models and for all climate scenarios. However, the uncertainties in the impact projections are high, mainly in the dry season. With respect to the model structural uncertainty, the PDM model simulates significantly higher runoff peak flows under future wet scenarios, which is explained by its specific model structure. For the low flow extremes, the MIKE SHE model projects significantly lower low flows in dry scenario conditions in comparison to the other models, probably due to its large difference in process descriptions for the groundwater component, the groundwater-river interactions. The effect of the model calibration was tested by comparing the manual calibration approach with automatic calibrations of the VHM model based on different objective functions. The calibration approach did not significantly alter the model results for peak flow, but the low flow projections were again highly influenced. Model choice as well as calibration strategy hence have a critical impact on low flows, more than on peak flows. These results highlight the high uncertainty in low flow modelling, especially in a climate change context.
W. Devine; C. Aubry; J. Miller; K. Potter; A. Bower
2012-01-01
This guide provides a step-by-step description of the methodology used to apply the Forest Tree Genetic Risk Assessment System (ForGRAS; Potter and Crane 2010) to the tree species of the Pacific Northwest in a recent climate change vulnerability assessment (Devine et al. 2012). We describe our modified version of the ForGRAS model, and we review the modelâs basic...
Ruiz, Daniel; Cerón, Viviana; Molina, Adriana M; Quiñónes, Martha L; Jiménez, Mónica M; Ahumada, Martha; Gutiérrez, Patricia; Osorio, Salua; Mantilla, Gilma; Connor, Stephen J; Thomson, Madeleine C
2014-07-01
As part of the Integrated National Adaptation Pilot project and the Integrated Surveillance and Control System, the Colombian National Institute of Health is working on the design and implementation of a Malaria Early Warning System framework, supported by seasonal climate forecasting capabilities, weather and environmental monitoring, and malaria statistical and dynamic models. In this report, we provide an overview of the local ecoepidemiologic settings where four malaria process-based mathematical models are currently being implemented at a municipal level. The description includes general characteristics, malaria situation (predominant type of infection, malaria-positive cases data, malaria incidence, and seasonality), entomologic conditions (primary and secondary vectors, mosquito densities, and feeding frequencies), climatic conditions (climatology and long-term trends), key drivers of epidemic outbreaks, and non-climatic factors (populations at risk, control campaigns, and socioeconomic conditions). Selected pilot sites exhibit different ecoepidemiologic settings that must be taken into account in the development of the integrated surveillance and control system. © The American Society of Tropical Medicine and Hygiene.
NASA Astrophysics Data System (ADS)
Pascoe, C. L.
2017-12-01
The Coupled Model Intercomparison Project (CMIP) has coordinated climate model experiments involving multiple international modelling teams since 1995. This has led to a better understanding of past, present, and future climate. The 2017 sixth phase of the CMIP process (CMIP6) consists of a suite of common experiments, and 21 separate CMIP-Endorsed Model Intercomparison Projects (MIPs) making a total of 244 separate experiments. Precise descriptions of the suite of CMIP6 experiments have been captured in a Common Information Model (CIM) database by the Earth System Documentation Project (ES-DOC). The database contains descriptions of forcings, model configuration requirements, ensemble information and citation links, as well as text descriptions and information about the rationale for each experiment. The database was built from statements about the experiments found in the academic literature, the MIP submissions to the World Climate Research Programme (WCRP), WCRP summary tables and correspondence with the principle investigators for each MIP. The database was collated using spreadsheets which are archived in the ES-DOC Github repository and then rendered on the ES-DOC website. A diagramatic view of the workflow of building the database of experiment metadata for CMIP6 is shown in the attached figure.The CIM provides the formalism to collect detailed information from diverse sources in a standard way across all the CMIP6 MIPs. The ES-DOC documentation acts as a unified reference for CMIP6 information to be used both by data producers and consumers. This is especially important given the federated nature of the CMIP6 project. Because the CIM allows forcing constraints and other experiment attributes to be referred to by more than one experiment, we can streamline the process of collecting information from modelling groups about how they set up their models for each experiment. End users of the climate model archive will be able to ask questions enabled by the interconnectedness of the metadata such as "Which MIPs make use of experiment A?" and "Which experiments use forcing constraint B?".
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.
Towards a climate-dependent paradigm of ammonia emission and deposition
Existing descriptions of bi-directional ammonia (NH3) land–atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale ...
Dynamical mechanisms of Arctic amplification.
Dethloff, Klaus; Handorf, Dörthe; Jaiser, Ralf; Rinke, Annette; Klinghammer, Pia
2018-05-12
The Arctic has become a hot spot of climate change, but the nonlinear interactions between regional and global scales in the coupled climate system responsible for Arctic amplification are not well understood and insufficiently described in climate models. Here, we compare reanalysis data with model simulations for low and high Arctic sea ice conditions to identify model biases with respect to atmospheric Arctic-mid-latitude linkages. We show that an appropriate description of Arctic sea ice forcing is able to reproduce the observed winter cooling in mid-latitudes as result of improved tropospheric-stratospheric planetary wave propagation triggering a negative phase of the Arctic Oscillation/North Atlantic Oscillation in late winter. © 2018 New York Academy of Sciences.
Documentation of the GLAS fourth order general circulation model. Volume 1: Model documentation
NASA Technical Reports Server (NTRS)
Kalnay, E.; Balgovind, R.; Chao, W.; Edelmann, J.; Pfaendtner, J.; Takacs, L.; Takano, K.
1983-01-01
The volume 1, of a 3 volume technical memoranda which contains a documentation of the GLAS Fourth Order General Circulation Model is presented. Volume 1 contains the documentation, description of the stratospheric/tropospheric extension, user's guide, climatological boundary data, and some climate simulation studies.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bartholomew, Mary Jane
To improve the quantitative description of precipitation processes in climate models, the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) Climate Research Facility deploys several types of rain gauges (MET, RAIN, and optical rain gauge [ORG] datastreams) as well as disdrometers (DISD and VDIS datastreams) at the Southern Great Plains (SGP) Site. This handbook deals specifically with the independent analog ORG (i.e., the ORG datastream).
Description of the NCAR Community Climate Model (CCM3). Technical note
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kiehl, J.T.; Hack, J.J.; Bonan, G.B.
This repor presents the details of the governing equations, physical parameterizations, and numerical algorithms defining the version of the NCAR Community Climate Model designated CCM3. The material provides an overview of the major model components, and the way in which they interact as the numerical integration proceeds. This version of the CCM incorporates significant improvements to the physic package, new capabilities such as the incorporation of a slab ocean component, and a number of enhancements to the implementation (e.g., the ability to integrate the model on parallel distributed-memory computational platforms).
Microcomputer pollution model for civilian airports and Air Force bases. Model description
DOE Office of Scientific and Technical Information (OSTI.GOV)
Segal, H.M.; Hamilton, P.L.
1988-08-01
This is one of three reports describing the Emissions and Dispersion Modeling System (EDMS). EDMS is a complex source emissions/dispersion model for use at civilian airports and Air Force bases. It operates in both a refined and a screening mode and is programmed for an IBM-XT (or compatible) computer. This report--MODEL DESCRIPTION--provides the technical description of the model. It first identifies the key design features of both the emissions (EMISSMOD) and dispersion (GIMM) portions of EDMS. It then describes the type of meteorological information the dispersion model can accept and identifies the manner in which it preprocesses National Climatic Centermore » (NCC) data prior to a refined-model run. The report presents the results of running EDMS on a number of different microcomputers and compares EDMS results with those of comparable models. The appendices elaborate on the information noted above and list the source code.« less
NASA Technical Reports Server (NTRS)
Druyan, Leonard M.
2012-01-01
Climate models is a very broad topic, so a single volume can only offer a small sampling of relevant research activities. This volume of 14 chapters includes descriptions of a variety of modeling studies for a variety of geographic regions by an international roster of authors. The climate research community generally uses the rubric climate models to refer to organized sets of computer instructions that produce simulations of climate evolution. The code is based on physical relationships that describe the shared variability of meteorological parameters such as temperature, humidity, precipitation rate, circulation, radiation fluxes, etc. Three-dimensional climate models are integrated over time in order to compute the temporal and spatial variations of these parameters. Model domains can be global or regional and the horizontal and vertical resolutions of the computational grid vary from model to model. Considering the entire climate system requires accounting for interactions between solar insolation, atmospheric, oceanic and continental processes, the latter including land hydrology and vegetation. Model simulations may concentrate on one or more of these components, but the most sophisticated models will estimate the mutual interactions of all of these environments. Advances in computer technology have prompted investments in more complex model configurations that consider more phenomena interactions than were possible with yesterday s computers. However, not every attempt to add to the computational layers is rewarded by better model performance. Extensive research is required to test and document any advantages gained by greater sophistication in model formulation. One purpose for publishing climate model research results is to present purported advances for evaluation by the scientific community.
NASA Technical Reports Server (NTRS)
Haywood, A. M.; Dowsett, H. J.; Robinson, M. M.; Stoll, D. K.; Dolan, A. M.; Lunt, D. J.; Otto-Bliesner, B.; Chandler, M. A.
2011-01-01
The Palaeoclimate Modelling Intercomparison Project has expanded to include a model intercomparison for the mid-Pliocene warm period (3.29 to 2.97 million yr ago). This project is referred to as PlioMIP (the Pliocene Model Intercomparison Project). Two experiments have been agreed upon and together compose the initial phase of PlioMIP. The first (Experiment 1) is being performed with atmosphere only climate models. The second (Experiment 2) utilizes fully coupled ocean-atmosphere climate models. Following on from the publication of the experimental design and boundary conditions for Experiment 1 in Geoscientific Model Development, this paper provides the necessary description of differences and/or additions to the experimental design for Experiment 2.
Haywood, A.M.; Dowsett, H.J.; Robinson, M.M.; Stoll, D.K.; Dolan, A.M.; Lunt, D.J.; Otto-Bliesner, B.; Chandler, M.A.
2011-01-01
The Palaeoclimate Modelling Intercomparison Project has expanded to include a model intercomparison for the mid-Pliocene warm period (3.29 to 2.97 million yr ago). This project is referred to as PlioMIP (the Pliocene Model Intercomparison Project). Two experiments have been agreed upon and together compose the initial phase of PlioMIP. The first (Experiment 1) is being performed with atmosphere-only climate models. The second (Experiment 2) utilises fully coupled ocean-atmosphere climate models. Following on from the publication of the experimental design and boundary conditions for Experiment 1 in Geoscientific Model Development, this paper provides the necessary description of differences and/or additions to the experimental design for Experiment 2.
ERIC Educational Resources Information Center
Vos, D.; Ellis, S. M.; van der Westhuizen, Philip C.; Mentz, P. J.
2013-01-01
The Organisational Climate Description Questionnaire--Rutgers Elementary (OCDQ--RE) was used to determine the current organizational climate of primary schools in North-West Province, South Africa. This questionnaire evaluates the actions of principals and educators; the current organizational climate in primary schools can be determined from the…
NASA Astrophysics Data System (ADS)
Schlosser, C. A.; Strzepek, K.; Arndt, C.; Gueneau, A.; Cai, Y.; Gao, X.; Robinson, S.; Sokolov, A. P.; Thurlow, J.
2011-12-01
The growing need for risk-based assessments of impacts and adaptation to regional climate change calls for the quantification of the likelihood of regional outcomes and the representation of their uncertainty. Moreover, our global water resources include energy, agricultural and environmental systems, which are linked together as well as to climate. With the prospect of potential climate change and associated shifts in hydrologic variation and extremes, the MIT Integrated Global Systems Model (IGSM) framework, in collaboration with UNU-WIDER, has enhanced its capabilities to model impacts (or effects) on the managed water-resource systems. We first present a hybrid approach that extends the MIT Integrated Global System Model (IGSM) framework to provide probabilistic projections of regional climate changes. This procedure constructs meta-ensembles of the regional hydro-climate, combining projections from the MIT IGSM that represent global-scale uncertainties with regionally resolved patterns from archived climate-model projections. From these, a river routing and water-resource management module allocates water among irrigation, hydropower, urban/industrial, and in-stream uses and investigate how society might adapt water resources due to shifts in hydro-climate variations and extremes. These results are then incorporated into economic models allowing us to consider the implications of climate for growth, land use, and development prospects. In this model-based investigation, we consider how changes in the regional hydro-climate over major river basins in southern Africa, Vietnam, as well as the United States impact agricultural productivity and water-management systems, and whether adaptive strategies can cope with the more severe climate-related threats to growth and development. All this is cast under a probabilistic description of regional climate changes encompassed by the IGSM framework.
NASA Technical Reports Server (NTRS)
Lamarque, J.-F.; Shindell, D. T.; Naik, V.; Plummer, D.; Josse, B.; Righi, M.; Rumbold, S. T.; Schulz, M.; Skeie, R. B.; Strode, S.;
2013-01-01
The Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) consists of a series of time slice experiments targeting the long-term changes in atmospheric composition between 1850 and 2100, with the goal of documenting composition changes and the associated radiative forcing. In this overview paper, we introduce the ACCMIP activity, the various simulations performed (with a requested set of 14) and the associated model output. The 16 ACCMIP models have a wide range of horizontal and vertical resolutions, vertical extent, chemistry schemes and interaction with radiation and clouds. While anthropogenic and biomass burning emissions were specified for all time slices in the ACCMIP protocol, it is found that the natural emissions are responsible for a significant range across models, mostly in the case of ozone precursors. The analysis of selected present-day climate diagnostics (precipitation, temperature, specific humidity and zonal wind) reveals biases consistent with state-of-the-art climate models. The model-to- model comparison of changes in temperature, specific humidity and zonal wind between 1850 and 2000 and between 2000 and 2100 indicates mostly consistent results. However, models that are clear outliers are different enough from the other models to significantly affect their simulation of atmospheric chemistry.
USDA-ARS?s Scientific Manuscript database
Soil carbon (C) models are important tools for examining complex interactions between climate, crop and soil management practices, and to evaluate the long-term effects of management practices on C-storage potential in soils. CQESTR is a process-based carbon balance model that relates crop residue a...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hess, Nancy J.; Brown, Gordon E.; Plata, Charity
2014-02-21
As part of the Belowground Carbon Cycling Processes at the Molecular Scale workshop, an EMSL Science Theme Advisory Panel meeting held in February 2013, attendees discussed critical biogeochemical processes that regulate carbon cycling in soil. The meeting attendees determined that as a national scientific user facility, EMSL can provide the tools and expertise needed to elucidate the molecular foundation that underlies mechanistic descriptions of biogeochemical processes that control carbon allocation and fluxes at the terrestrial/atmospheric interface in landscape and regional climate models. Consequently, the workshop's goal was to identify the science gaps that hinder either development of mechanistic description ofmore » critical processes or their accurate representation in climate models. In part, this report offers recommendations for future EMSL activities in this research area. The workshop was co-chaired by Dr. Nancy Hess (EMSL) and Dr. Gordon Brown (Stanford University).« less
NASA Astrophysics Data System (ADS)
Arneth, A.; Sitch, S.; Bondeau, A.; Butterbach-Bahl, K.; Foster, P.; Gedney, N.; de Noblet-Ducoudré, N.; Prentice, I. C.; Sanderson, M.; Thonicke, K.; Wania, R.; Zaehle, S.
2010-01-01
Exchange of non-CO2 trace gases between the land surface and the atmosphere plays an important role in atmospheric chemistry and climate. Recent studies have highlighted its importance for interpretation of glacial-interglacial ice-core records, the simulation of the pre-industrial and present atmosphere, and the potential for large climate-chemistry and climate-aerosol feedbacks in the coming century. However, spatial and temporal variations in trace gas emissions and the magnitude of future feedbacks are a major source of uncertainty in atmospheric chemistry, air quality and climate science. To reduce such uncertainties Dynamic Global Vegetation Models (DGVMs) are currently being expanded to mechanistically represent processes relevant to non-CO2 trace gas exchange between land biota and the atmosphere. In this paper we present a review of important non-CO2 trace gas emissions, the state-of-the-art in DGVM modelling of processes regulating these emissions, identify key uncertainties for global scale model applications, and discuss a methodology for model integration and evaluation.
NASA Astrophysics Data System (ADS)
Arneth, A.; Sitch, S.; Bondeau, A.; Butterbach-Bahl, K.; Foster, P.; Gedney, N.; de Noblet-Ducoudré, N.; Prentice, I. C.; Sanderson, M.; Thonicke, K.; Wania, R.; Zaehle, S.
2009-07-01
Exchange of non-CO2 trace gases between the land surface and the atmosphere plays an important role in atmospheric chemistry and climate. Recent studies have highlighted its importance for interpretation of glacial-interglacial ice-core records, the simulation of the pre-industrial and present atmosphere, and the potential for large climate-chemistry and climate-aerosol feedbacks in the coming century. However, spatial and temporal variations in trace gas emissions and the magnitude of future feedbacks are a major source of uncertainty in atmospheric chemistry, air quality and climate science. To reduce such uncertainties Dynamic Global Vegetation Models (DGVMs) are currently being expanded to mechanistically represent processes relevant to non-CO2 trace gas exchange between land biota and the atmosphere. In this paper we present a review of important non-CO2 trace gas emissions, the state-of-the-art in DGVM modelling of processes regulating these emissions, identify key uncertainties for global scale model applications, and discuss a methodology for model integration and evaluation.
Generating High Resolution Climate Scenarios Through Regional Climate Modelling Over Southern Africa
NASA Astrophysics Data System (ADS)
Ndhlovu, G. Z.; Woyessa, Y. E.; Vijayaraghavan, S.
2017-12-01
limate change has impacted the global environment and the Continent of Africa, especially Southern Africa, regarded as one of the most vulnerable regions in Africa, has not been spared from these impacts. Global Climate Models (GCMs) with coarse horizontal resolutions of 150-300 km do not provide sufficient details at the local basin scale due to mismatch between the size of river basins and the grid cell of the GCM. This makes it difficult to apply the outputs of GCMs directly to impact studies such as hydrological modelling. This necessitates the use of regional climate modelling at high resolutions that provide detailed information at regional and local scales to study both climate change and its impacts. To this end, an experiment was set up and conducted with PRECIS, a regional climate model, to generate climate scenarios at a high resolution of 25km for the local region in Zambezi River basin of Southern Africa. The major input data used included lateral and surface boundary conditions based on the GCMs. The data is processed, analysed and compared with CORDEX climate change project data generated for Africa. This paper, highlights the major differences of the climate scenarios generated by PRECIS Model and CORDEX Project for Africa and further gives recommendations for further research on generation of climate scenarios. The climatic variables such as precipitation and temperatures have been analysed for flood and droughts in the region. The paper also describes the setting up and running of an experiment using a high-resolution PRECIS model. In addition, a description has been made in running the model and generating the output variables on a sub basin scale. Regional climate modelling which provides information on climate change impact may lead to enhanced understanding of adaptive water resources management. Understanding the regional climate modelling results on sub basin scale is the first step in analysing complex hydrological processes and a basis for designing of adaptation and mitigation strategies in the region. Key words: Climate change, regional climate modelling, hydrological processes, extremes, scenarios [1] Corresponding author: Email:gndhlovu@cut.ac.za Tel:+27 (0) 51 507 3072
The Pliocene Model Intercomparison Project - Phase 2
NASA Astrophysics Data System (ADS)
Haywood, Alan; Dowsett, Harry; Dolan, Aisling; Rowley, David; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Chandler, Mark; Hunter, Stephen; Lunt, Daniel; Pound, Matthew; Salzmann, Ulrich
2016-04-01
The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, and their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate, and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilised for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilise state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land/ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.
Selection of optimal complexity for ENSO-EMR model by minimum description length principle
NASA Astrophysics Data System (ADS)
Loskutov, E. M.; Mukhin, D.; Mukhina, A.; Gavrilov, A.; Kondrashov, D. A.; Feigin, A. M.
2012-12-01
One of the main problems arising in modeling of data taken from natural system is finding a phase space suitable for construction of the evolution operator model. Since we usually deal with strongly high-dimensional behavior, we are forced to construct a model working in some projection of system phase space corresponding to time scales of interest. Selection of optimal projection is non-trivial problem since there are many ways to reconstruct phase variables from given time series, especially in the case of a spatio-temporal data field. Actually, finding optimal projection is significant part of model selection, because, on the one hand, the transformation of data to some phase variables vector can be considered as a required component of the model. On the other hand, such an optimization of a phase space makes sense only in relation to the parametrization of the model we use, i.e. representation of evolution operator, so we should find an optimal structure of the model together with phase variables vector. In this paper we propose to use principle of minimal description length (Molkov et al., 2009) for selection models of optimal complexity. The proposed method is applied to optimization of Empirical Model Reduction (EMR) of ENSO phenomenon (Kravtsov et al. 2005, Kondrashov et. al., 2005). This model operates within a subset of leading EOFs constructed from spatio-temporal field of SST in Equatorial Pacific, and has a form of multi-level stochastic differential equations (SDE) with polynomial parameterization of the right-hand side. Optimal values for both the number of EOF, the order of polynomial and number of levels are estimated from the Equatorial Pacific SST dataset. References: Ya. Molkov, D. Mukhin, E. Loskutov, G. Fidelin and A. Feigin, Using the minimum description length principle for global reconstruction of dynamic systems from noisy time series, Phys. Rev. E, Vol. 80, P 046207, 2009 Kravtsov S, Kondrashov D, Ghil M, 2005: Multilevel regression modeling of nonlinear processes: Derivation and applications to climatic variability. J. Climate, 18 (21): 4404-4424. D. Kondrashov, S. Kravtsov, A. W. Robertson and M. Ghil, 2005. A hierarchy of data-based ENSO models. J. Climate, 18, 4425-4444.
A History of Sandia’s Water Decision Modeling and Analysis Program
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lowry, Thomas Stephen; Pate, Ronald C.
This document provides a brief narrative, and selected project descriptions, that represent Sandia’s history involving data, modeling, and analysis related to water, energy-water nexus, and energy-water-agriculture nexus within the context of climate change. Sandia National Laboratories has been engaged since the early-1990s with program development involving data, modeling, and analysis projects that address the interdependent issues, risks, and technology-based mitigations associated with increasing demands and stresses being placed on energy, water, and agricultural/food resources, and the related impacts on their security and sustainability in the face of both domestic and global population growth, expanding economic development, and climate change.
Applying Descriptive Statistics to Teaching the Regional Classification of Climate.
ERIC Educational Resources Information Center
Lindquist, Peter S.; Hammel, Daniel J.
1998-01-01
Describes an exercise for college and high school students that relates descriptive statistics to the regional climatic classification. The exercise introduces students to simple calculations of central tendency and dispersion, the construction and interpretation of scatterplots, and the definition of climatic regions. Forces students to engage…
A continuous latitudinal energy balance model to explore non-uniform climate engineering strategies
NASA Astrophysics Data System (ADS)
Bonetti, F.; McInnes, C. R.
2016-12-01
Current concentrations of atmospheric CO2 exceed measured historical levels in modern times, largely attributed to anthropogenic forcing since the industrial revolution. The required decline in emissions rates has never been achieved leading to recent interest in climate engineering for future risk-mitigation strategies. Climate engineering aims to offset human-driven climate change. It involves techniques developed both to reduce the concentration of CO2 in the atmosphere (Carbon Dioxide Removal (CDR) methods) and to counteract the radiative forcing that it generates (Solar Radiation Management (SRM) methods). In order to investigate effects of SRM technologies for climate engineering, an analytical model describing the main dynamics of the Earth's climate has been developed. The model is a time-dependent Energy Balance Model (EBM) with latitudinal resolution and allows for the evaluation of non-uniform climate engineering strategies. A significant disadvantage of climate engineering techniques involving the management of solar radiation is regional disparities in cooling. This model offers an analytical approach to design multi-objective strategies that counteract climate change on a regional basis: for example, to cool the Artic and restrict undesired impacts at mid-latitudes, or to control the equator-to-pole temperature gradient. Using the Green's function approach the resulting partial differential equation allows for the computation of the surface temperature as a function of time and latitude when a 1% per year increase in the CO2 concentration is considered. After the validation of the model through comparisons with high fidelity numerical models, it will be used to explore strategies for the injection of the aerosol precursors in the stratosphere. In particular, the model involves detailed description of the optical properties of the particles, the wash-out dynamics and the estimation of the radiative cooling they can generate.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Strzepek, K.; Neumann, Jim; Smith, Joel
Climate change impacts on water resources in the U.S. are likely to be far-reaching and substantial, because the water sector spans many parts of the economy, from supply and demand for agriculture, industry, energy production, transportation and municipal use to damages from natural hazards. This paper provides impact and damage estimates from five water resource-related models in the CIRA frame work, addressing drought risk, flooding damages, water supply and demand, and global water scarcity. The four models differ in the water system assessed, their spatial scale, and the units of assessment, but together they provide a quantitative and descriptive richnessmore » in characterizing water resource sector effects of climate change that no single model can capture. The results also address the sensitivity of these estimates to greenhouse gas emission scenarios, climate sensitivity alternatives, and global climate model selection. While calculating the net impact of climate change on the water sector as a whole may be impractical, because each of the models applied here uses a consistent set of climate scenarios, broad conclusions can be drawn regarding the patterns of change and the benefits of GHG mitigation policies for the water sector. Two key findings emerge: 1) climate mitigation policy substantially reduces the impact of climate change on the water sector across multiple dimensions; and 2) the more managed the water resources system, the more tempered the climate change impacts and the resulting reduction of impacts from climate mitigation policies.« less
Strzepek, K.; Neumann, Jim; Smith, Joel; ...
2014-11-29
Climate change impacts on water resources in the U.S. are likely to be far-reaching and substantial, because the water sector spans many parts of the economy, from supply and demand for agriculture, industry, energy production, transportation and municipal use to damages from natural hazards. This paper provides impact and damage estimates from five water resource-related models in the CIRA frame work, addressing drought risk, flooding damages, water supply and demand, and global water scarcity. The four models differ in the water system assessed, their spatial scale, and the units of assessment, but together they provide a quantitative and descriptive richnessmore » in characterizing water resource sector effects of climate change that no single model can capture. The results also address the sensitivity of these estimates to greenhouse gas emission scenarios, climate sensitivity alternatives, and global climate model selection. While calculating the net impact of climate change on the water sector as a whole may be impractical, because each of the models applied here uses a consistent set of climate scenarios, broad conclusions can be drawn regarding the patterns of change and the benefits of GHG mitigation policies for the water sector. Two key findings emerge: 1) climate mitigation policy substantially reduces the impact of climate change on the water sector across multiple dimensions; and 2) the more managed the water resources system, the more tempered the climate change impacts and the resulting reduction of impacts from climate mitigation policies.« less
Ward-Garrison, Christian; Markstrom, Steven L.; Hay, Lauren E.
2009-01-01
The U.S. Geological Survey Downsizer is a computer application that selects, downloads, verifies, and formats station-based time-series data for environmental-resource models, particularly the Precipitation-Runoff Modeling System. Downsizer implements the client-server software architecture. The client presents a map-based, graphical user interface that is intuitive to modelers; the server provides streamflow and climate time-series data from over 40,000 measurement stations across the United States. This report is the Downsizer user's manual and provides (1) an overview of the software design, (2) installation instructions, (3) a description of the graphical user interface, (4) a description of selected output files, and (5) troubleshooting information.
Using Paleo-climate Comparisons to Constrain Future Projections in CMIP5
NASA Technical Reports Server (NTRS)
Schmidt, G. A.; Annan, J D.; Bartlein, P. J.; Cook, B. I.; Guilyardi, E.; Hargreaves, J. C.; Harrison, S. P.; Kageyama, M.; LeGrande, A. N..; Konecky, B.;
2013-01-01
We present a description of the theoretical framework and best practice for using the paleo-climate model component of the Coupled Model Intercomparison Project (Phase 5) (CMIP5) to constrain future projections of climate using the same models. The constraints arise from measures of skill in hindcasting paleo-climate changes from the present over 3 periods: the Last Glacial Maximum (LGM) (21 thousand years before present, ka), the mid-Holocene (MH) (6 ka) and the Last Millennium (LM) (8501850 CE). The skill measures may be used to validate robust patterns of climate change across scenarios or to distinguish between models that have differing outcomes in future scenarios. We find that the multi-model ensemble of paleo-simulations is adequate for addressing at least some of these issues. For example, selected benchmarks for the LGM and MH are correlated to the rank of future projections of precipitationtemperature or sea ice extent to indicate that models that produce the best agreement with paleoclimate information give demonstrably different future results than the rest of the models. We also find that some comparisons, for instance associated with model variability, are strongly dependent on uncertain forcing timeseries, or show time dependent behaviour, making direct inferences for the future problematic. Overall, we demonstrate that there is a strong potential for the paleo-climate simulations to help inform the future projections and urge all the modeling groups to complete this subset of the CMIP5 runs.
NASA Astrophysics Data System (ADS)
Daniel, M.; Lemonsu, Aude; Déqué, M.; Somot, S.; Alias, A.; Masson, V.
2018-06-01
Most climate models do not explicitly model urban areas and at best describe them as rock covers. Nonetheless, the very high resolutions reached now by the regional climate models may justify and require a more realistic parameterization of surface exchanges between urban canopy and atmosphere. To quantify the potential impact of urbanization on the regional climate, and evaluate the benefits of a detailed urban canopy model compared with a simpler approach, a sensitivity study was carried out over France at a 12-km horizontal resolution with the ALADIN-Climate regional model for 1980-2009 time period. Different descriptions of land use and urban modeling were compared, corresponding to an explicit modeling of cities with the urban canopy model TEB, a conventional and simpler approach representing urban areas as rocks, and a vegetated experiment for which cities are replaced by natural covers. A general evaluation of ALADIN-Climate was first done, that showed an overestimation of the incoming solar radiation but satisfying results in terms of precipitation and near-surface temperatures. The sensitivity analysis then highlighted that urban areas had a significant impact on modeled near-surface temperature. A further analysis on a few large French cities indicated that over the 30 years of simulation they all induced a warming effect both at daytime and nighttime with values up to + 1.5 °C for the city of Paris. The urban model also led to a regional warming extending beyond the urban areas boundaries. Finally, the comparison to temperature observations available for Paris area highlighted that the detailed urban canopy model improved the modeling of the urban heat island compared with a simpler approach.
The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set
NASA Astrophysics Data System (ADS)
Day, J. J.; Tietsche, S.; Collins, M.; Goessling, H. F.; Guemas, V.; Guillory, A.; Hurlin, W. J.; Ishii, M.; Keeley, S. P. E.; Matei, D.; Msadek, R.; Sigmond, M.; Tatebe, H.; Hawkins, E.
2015-10-01
Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño Southern Oscillation.
Synchronized Trajectories in a Climate "Supermodel"
NASA Astrophysics Data System (ADS)
Duane, Gregory; Schevenhoven, Francine; Selten, Frank
2017-04-01
Differences in climate projections among state-of-the-art models can be resolved by connecting the models in run-time, either through inter-model nudging or by directly combining the tendencies for corresponding variables. Since it is clearly established that averaging model outputs typically results in improvement as compared to any individual model output, averaged re-initializations at typical analysis time intervals also seems appropriate. The resulting "supermodel" is more like a single model than it is like an ensemble, because the constituent models tend to synchronize even with limited inter-model coupling. Thus one can examine the properties of specific trajectories, rather than averaging the statistical properties of the separate models. We apply this strategy to a study of the index cycle in a supermodel constructed from several imperfect copies of the SPEEDO model (a global primitive-equation atmosphere-ocean-land climate model). As with blocking frequency, typical weather statistics of interest like probabilities of heat waves or extreme precipitation events, are improved as compared to the standard multi-model ensemble approach. In contrast to the standard approach, the supermodel approach provides detailed descriptions of typical actual events.
NASA Astrophysics Data System (ADS)
Clark, D. B.; Mercado, L. M.; Sitch, S.; Jones, C. D.; Gedney, N.; Best, M. J.; Pryor, M.; Rooney, G. G.; Essery, R. L. H.; Blyth, E.; Boucher, O.; Harding, R. J.; Cox, P. M.
2011-03-01
The Joint UK Land Environment Simulator (JULES) is a process-based model that simulates the fluxes of carbon, water, energy and momentum between the land surface and the atmosphere. Past studies with JULES have demonstrated the important role of the land surface in the Earth System. Different versions of JULES have been employed to quantify the effects on the land carbon sink of separately changing atmospheric aerosols and tropospheric ozone, and the response of methane emissions from wetlands to climate change. There was a need to consolidate these and other advances into a single model code so as to be able to study interactions in a consistent manner. This paper describes the consolidation of these advances into the modelling of carbon fluxes and stores, in the vegetation and soil, in version 2.2 of JULES. Features include a multi-layer canopy scheme for light interception, including a sunfleck penetration scheme, a coupled scheme of leaf photosynthesis and stomatal conductance, representation of the effects of ozone on leaf physiology, and a description of methane emissions from wetlands. JULES represents the carbon allocation, growth and population dynamics of five plant functional types. The turnover of carbon from living plant tissues is fed into a 4-pool soil carbon model. The process-based descriptions of key ecological processes and trace gas fluxes in JULES mean that this community model is well-suited for use in carbon cycle, climate change and impacts studies, either in standalone mode or as the land component of a coupled Earth system model.
Campaign datasets for Observations and Modeling of the Green Ocean Amazon (GOAMAZON)
Martin,Scot; Mei,Fan; Alexander,Lizabeth; Artaxo,Paulo; Barbosa,Henrique; Bartholomew,Mary Jane; Biscaro,Thiago; Buseck,Peter; Chand,Duli; Comstock,Jennifer; Dubey,Manvendra; Godstein,Allen; Guenther,Alex; Hubbe,John; Jardine,Kolby; Jimenez,Jose-Luis; Kim,Saewung; Kuang,Chongai; Laskin,Alexander; Long,Chuck; Paralovo,Sarah; Petaja,Tuukka; Powers,Heath; Schumacher,Courtney; Sedlacek,Arthur; Senum,Gunnar; Smith,James; Shilling,John; Springston,Stephen; Thayer,Mitchell; Tomlinson,Jason; Wang,Jian; Xie,Shaocheng
2016-05-30
The hydrologic cycle of the Amazon Basin is one of the primary heat engines of the Southern Hemisphere. Any accurate climate model must succeed in a good description of the Basin, both in its natural state and in states perturbed by regional and global human activities. At the present time, however, tropical deep convection in a natural state is poorly understood and modeled, with insufficient observational data sets for model constraint. Furthermore, future climate scenarios resulting from human activities globally show the possible drying and the eventual possible conversion of rain forest to savanna in response to global climate change. Based on our current state of knowledge, the governing conditions of this catastrophic change are not defined. Human activities locally, including the economic development activities that are growing the population and the industry within the Basin, also have the potential to shift regional climate, most immediately by an increment in aerosol number and mass concentrations, and the shift is across the range of values to which cloud properties are most sensitive. The ARM Climate Research Facility in the Amazon Basin seeks to understand aerosol and cloud life cycles, particularly the susceptibility to cloud aerosol precipitation interactions, within the Amazon Basin.
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.
ERIC Educational Resources Information Center
Borrevik, Berge Andrew, Jr.
The purpose of this investigation was to construct an Organizational Climate Description Questionnaire-Higher Education that would permit portrayal of the organizational climate of academic departments within colleges and universities. Data collected from the completion of pilot and research instruments was obtained from the faculty members in 72…
NASA Astrophysics Data System (ADS)
Eley, Malte; Schöniger, Hans Matthias; Gelleszun, Marlene; Wolf, Jens; Schneider, Anke; Wiederhold, Helga; Meon, Günter
2017-04-01
Especially coastal areas are vulnerable in case of sea level rise and changing climate conditions. Therefore, the NAWAK study (design of sustainable adaptation strategies for infrastructures in water management under the conditions of climatic and demographic change) started in 2013. It is designed to assess impairments of groundwater availability for a coastal lowland aquifer system in North-West Germany (> 1.000 km2) in the context of climate and socio-economic changes. The research results are focused on the quantification of the groundwater availability for past and future scenarios. Impacts from both climatic and socio-economic changes on the water availability and water balance are assessed by means of hydrologic, hydrogeological and geophysical models and methods, which where developed and adapted by project partners. For the model area there are three fields of work to create the conditions for a density dependent calculation of changings in salt-freshwater budget with the numerical model d3f++ (distributed density-driven Flow). The first is the description of initial conditions in three dimensions, especially for the salt-freshwater boundary. That description is based on airborne electromagnetic data of the underground and a complex processing to identify the differences between salt and freshwater, without anthropogenic and geologic influences. A validation is possible by comparison with groundwater measurements and an online monitoring of specific conductivity. The second is the calculation and measurement of flow conditions to derive the boundary conditions and the groundwater recharge. The groundwater recharge was calculated by using the hydrologic model PANTA RHEI. It is a conceptual model with partly physic-based modules, especially for the soil water processes. The model was calibrated and validated by discharge measurements and groundwater levels. The third step is a detailed information about the spatial discretization and the reconstruction of the geologic body. The interpolation of point information's from boreholes and geologic sections was calculated with the geologic modelling software SubsurfaceViewerMX. For implementation in the groundwater model, the layers were combined to hydrogeological similar units. With this sophisticated models it is possible to model the density-dependent complex groundwater systems at large spatial scales as well as contaminant transport. The modeling analysis is focused on water-budget components (groundwater recharge, submarine groundwater discharge, surface-groundwater interaction and water supply), salt- water intrusion and sea level rise under different climate and water-use scenarios. With our models we offer the capability to evaluate possible coastal aquifer management strategies of real-world applications.
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.
A Model of Cooperation: The VALNet Project.
ERIC Educational Resources Information Center
Oberg, Larry R.
1986-01-01
Description of VALNet (Valley Library Consortium), a consortium of public, academic, and school libraries in Idaho, highlights proposed online public access union catalog which would include nonbibliographic and referral files and circulation and serials control modules. The political climate, marketing, needs assessment, support and consultation,…
NASA Astrophysics Data System (ADS)
Haywood, Alan M.; Dowsett, Harry J.; Dolan, Aisling M.; Rowley, David; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Chandler, Mark A.; Hunter, Stephen J.; Lunt, Daniel J.; Pound, Matthew; Salzmann, Ulrich
2016-03-01
The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land-ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.
NASA Technical Reports Server (NTRS)
Haywood, Alan M.; Dowsett, Harry J.; Dolan, Aisling M.; Rowley, David; Abe-Ouchi, Ayako; Otto-Bliesner, Bette; Chandler, Mark A.; Hunter, Stephen J.; Lunt, Daniel J.; Pound, Matthew;
2016-01-01
The Pliocene Model Intercomparison Project (PlioMIP) is a co-ordinated international climate modelling initiative to study and understand climate and environments of the Late Pliocene, as well as their potential relevance in the context of future climate change. PlioMIP examines the consistency of model predictions in simulating Pliocene climate and their ability to reproduce climate signals preserved by geological climate archives. Here we provide a description of the aim and objectives of the next phase of the model intercomparison project (PlioMIP Phase 2), and we present the experimental design and boundary conditions that will be utilized for climate model experiments in Phase 2. Following on from PlioMIP Phase 1, Phase 2 will continue to be a mechanism for sampling structural uncertainty within climate models. However, Phase 1 demonstrated the requirement to better understand boundary condition uncertainties as well as uncertainty in the methodologies used for data-model comparison. Therefore, our strategy for Phase 2 is to utilize state-of-the-art boundary conditions that have emerged over the last 5 years. These include a new palaeogeographic reconstruction, detailing ocean bathymetry and land-ice surface topography. The ice surface topography is built upon the lessons learned from offline ice sheet modelling studies. Land surface cover has been enhanced by recent additions of Pliocene soils and lakes. Atmospheric reconstructions of palaeo-CO2 are emerging on orbital timescales, and these are also incorporated into PlioMIP Phase 2. New records of surface and sea surface temperature change are being produced that will be more temporally consistent with the boundary conditions and forcings used within models. Finally we have designed a suite of prioritized experiments that tackle issues surrounding the basic understanding of the Pliocene and its relevance in the context of future climate change in a discrete way.
Reconstruction of Historical Weather by Assimilating Old Weather Diary Data
NASA Astrophysics Data System (ADS)
Neluwala, P.; Yoshimura, K.; Toride, K.; Hirano, J.; Ichino, M.; Okazaki, A.
2017-12-01
Climate can control not only human life style but also other living beings. It is important to investigate historical climate to understand the current and future climates. Information about daily weather can give a better understanding of past life on earth. Long-term weather influences crop calendar as well as the development of civilizations. Unfortunately, existing reconstructed daily weather data are limited to 1850s due to the availability of instrumental data. The climate data prior to that are derived from proxy materials (e.g., tree-ring width, ice core isotopes, etc.) which are either in annual or decadal scale. However, there are many historical documents which contain information about weather such as personal diaries. In Japan, around 20 diaries in average during the 16th - 19th centuries have been collected and converted into a digitized form. As such, diary data exist in many other countries. This study aims to reconstruct historical daily weather during the 18th and 19th centuries using personal daily diaries which have analogue weather descriptions such as `cloudy' or `sunny'. A recent study has shown the possibility of assimilating coarse weather data using idealized experiments. We further extend this study by assimilating modern weather descriptions similar to diary data in recent periods. The Global Spectral model (GSM) of National Centers for Environmental Prediction (NCEP) is used to reconstruct weather with the Local Ensemble Kalman filter (LETKF). Descriptive data are first converted to model variables such as total cloud cover (TCC), solar radiation and precipitation using empirical relationships. Those variables are then assimilated on a daily basis after adding random errors to consider the uncertainty of actual diary data. The assimilation of downward short wave solar radiation using weather descriptions improves RMSE from 64.3 w/m2 to 33.0 w/m2 and correlation coefficient (R) from 0.5 to 0.8 compared with the case without any assimilation. Non-assimilated fields are improved as well (e.g., RMSE from 40% to 29% and R 0.1 to 0.5 improved in TCC). Similarly, the assimilation of other variables shows improvements in atmospheric fields. These findings indicate the potential to reconstruct historical weather for the last five centuries by assimilating available weather descriptions.
ERIC Educational Resources Information Center
Shin, Huiyoung
2017-01-01
This study is aimed to gain insights into adolescents' classroom peer climate by examining descriptive and status norms of academic and social behaviors. Descriptive norm was assessed as the average score for each behavior and status norm was assessed using the correlation between each behavior and social status within each classroom. Expanded…
Climate Change: A Multidisciplinary Approach, Second Edition
NASA Astrophysics Data System (ADS)
Kirk-Davidoff, Daniel
2008-07-01
William Burroughs, who died in November 2007, was a wonderfully clear and evocative writer. Chapter 3 of his last work, Climate Change: A Multidisciplinary Approach, begins with the loveliest four-paragraph description of the general circulation of the Earth's atmosphere I have ever encountered. His writing also shines in his descriptions of the climate record of the past few thousand years, and in his introduction to the measurement of climate change. Unfortunately, the book is marred by inconsistencies in its treatment of climate dynamics, as well as by a number of idiosyncratic choices of emphasis that detract from the book's quality as a general introduction to the science of climate change.
NASA Astrophysics Data System (ADS)
Tawfik, Ahmed B.
The atmospheric component is described by rapid fluctuations in typical state variables, such as temperature and water vapor, on timescales of hours to days and the land component evolves on daily to yearly timescales. This dissertation examines the connection between soil moisture and atmospheric tracers under varying degrees of soil moisture-atmosphere coupling. Land-atmosphere coupling is defined over the United States using a regional climate model. A newly examined soil moisture-precipitation feedback is identified for winter months extending the previous summer feedback to colder temperature climates. This feedback is driven by the freezing and thawing of soil moisture, leading to coupled land-atmosphere conditions near the freezing line. Soil moisture can also affect the composition of the troposphere through modifying biogenic emissions of isoprene (C5H8). A novel first-order Taylor series decomposition indicates that isoprene emissions are jointly driven by temperature and soil moisture in models. These compounds are important precursors for ozone formation, an air pollutant and a short-lived forcing agent for climate. A mechanistic description of commonly observed relationships between ground-level ozone and meteorology is presented using the concept of soil moisture-temperature coupling regimes. The extent of surface drying was found to be a better predictor of ozone concentrations than temperature or humidity for the Eastern U.S. This relationship is evaluated in a coupled regional chemistry-climate model under several land-atmosphere coupling and isoprene emissions cases. The coupled chemistry-climate model can reproduce the observed soil moisture-temperature coupling pattern, yet modeled ozone is insensitive to changes in meteorology due to the balance between isoprene and the primary atmospheric oxidant, the hydroxyl radical (OH). Overall, this work highlights the importance of soil moisture-atmosphere coupling for previously neglected cold climate regimes, controlling isoprene emissions variability, and providing a processed-based description of observed ozone-meteorology relationships. From the perspective of ozone air quality, the lack of sensitivity of ozone to meteorology suggests a systematic deficiency in chemistry models in high isoprene emission regions. This shortcoming must be addressed to better estimate tropospheric ozone radiative forcing and to understanding how ozone air quality may respond to future warming.
The Race To Understand A Changing Planet
NASA Technical Reports Server (NTRS)
Sellers, Piers J.
2012-01-01
The Earth's climate is changing rapidly. In some respects, the rate of change is outpacing the predictions of only a few years ago. The challenge to Earth Science is to put forward credible projections of possible future climates so that the public and policy makers can make science-based decisions about energy development strategies. Models, observations and experiments all play strong roles in improving knowledge and increasing confidence in our predictions. The models have progressed from simple, coarse-resolution descriptions of atmospheric dynamics and physics only twenty years ago, to full-up Earth System models (ESMs) that include complete descriptions of the oceans and cryosphere. It has been convincingly argued that such complexity - the construction of realistic "toy" Earth's - is necessary to address the complex processes involved in climate change, including not only the physical atmosphere, oceans and cryosphere, but also the carbon cycle - both its natural and anthropogenic components - and the biosphere. Observations, particularly satellite observations, have more or less kept pace with the demands of the modelers, being able to observe progressively more and different facets of the Earth system, but the global satellite fleet is in need of an overhaul very soon. Lastly, field experiments and process studies confront the models with facts and allow us to develop more sophisticated and accurate satellite data algorithms. The challenges facing our relatively small Earth and planetary science communities are considerable and the stakes are significant. The stakeholders, now numbering 7 billion but soon to be 10 billion, will be relying on our results and capabilitie's to guide them into the future.
The race to understand a changing planet
NASA Astrophysics Data System (ADS)
Sellers, P. J.
2012-12-01
The Earth's climate is changing rapidly. In some respects, the rate of change is outpacing the predictions of only a few years ago. The challenge to Earth Science is to put forward credible projections of possible future climates so that the public and policy makers can make science-based decisions about energy development strategies. Models, observations and experiments all play strong roles in improving knowledge and increasing confidence in our predictions. The models have progressed from simple, coarse-resolution descriptions of atmospheric dynamics and physics only twenty years ago, to full-up Earth System models (ESMs) that include complete descriptions of the oceans and cryosphere. It has been convincingly argued that such complexity - the construction of realistic "toy" Earths - is necessary to address the complex processes involved in climate change, including not only the physical atmosphere, oceans and cryosphere, but also the carbon cycle - both its natural and anthropogenic components - and the biosphere. Observations, particularly satellite observations, have more or less kept pace with the demands of the modelers, being able to observe progressively more and different facets of the Earth system, but the global satellite fleet is in need of an overhaul very soon. Lastly, field experiments and process studies confront the models with facts and allow us to develop more sophisticated and accurate satellite data algorithms. The challenges facing our relatively small Earth and planetary science communities are considerable and the stakes are significant. The stakeholders, now numbering 7 billion but soon to be 10 billion, will be relying on our results and capabilities to guide them into the future.
An overview of mineral dust modeling over East Asia
NASA Astrophysics Data System (ADS)
Chen, Siyu; Huang, Jianping; Qian, Yun; Zhao, Chun; Kang, Litai; Yang, Ben; Wang, Yong; Liu, Yuzhi; Yuan, Tiangang; Wang, Tianhe; Ma, Xiaojun; Zhang, Guolong
2017-08-01
East Asian dust (EAD) exerts considerable impacts on the energy balance and climate/climate change of the earth system through its influence on solar and terrestrial radiation, cloud properties, and precipitation efficiency. Providing an accurate description of the life cycle and climate effects of EAD is therefore critical to better understanding of climate change and socioeconomic development in East Asia and even worldwide. Dust modeling has undergone substantial development since the late 1990s, associated with improved understanding of the role of EAD in the earth system. Here, we review the achievements and progress made in recent decades in terms of dust modeling research, including dust emissions, long-range transport, radiative forcing (RF), and climate effects of dust particles over East Asia. Numerous efforts in dust/EAD modeling have been directed towards furnishing more sophisticated physical and chemical processes into the models on higher spatial resolutions. Meanwhile, more systematic observations and more advanced retrieval methods for instruments that address EAD related science issues have made it possible to evaluate model results and quantify the role of EAD in the earth system, and to further reduce the uncertainties in EAD simulations. Though much progress has been made, large discrepancies and knowledge gaps still exist among EAD simulations. The deficiencies and limitations that pertain to the performance of the EAD simulations referred to in the present study are also discussed.
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.
Do planetary seasons play a role in attaining stable climates?
NASA Astrophysics Data System (ADS)
Olsen, Kasper Wibeck; Bohr, Jakob
2018-05-01
A simple phenomenological account for planetary climate instabilities is presented. The description is based on the standard model where the balance of incoming stellar radiation and outward thermal radiation is described by the effective planet temperature. Often, it is found to have three different points, or temperatures, where the influx of radiation is balanced with the out-flux, even with conserved boundary conditions. Two of these points are relatively long-term stable, namely the point corresponding to a cold climate and the point corresponding to a hot climate. In a classical sense these points are equilibrium balance points. The hypothesis promoted in this paper is the possibility that the intermediate third point can become long-term stable by being driven dynamically. The initially unstable point is made relatively stable over a long period by the presence of seasonal climate variations.
Modelling Climate/Global Change and Assessing Environmental Risks for Siberia
NASA Astrophysics Data System (ADS)
Lykosov, V. N.; Kabanov, M. V.; Heimann, M.; Gordov, E. P.
2009-04-01
The state-of-the-art climate models are based on a combined atmosphere-ocean general circulation model. A central direction of their development is associated with an increasingly accurate description of all physical processes participating in climate formation. In modeling global climate, it is necessary to reconstruct seasonal and monthly mean values, seasonal variability (monsoon cycle, parameters of storm-tracks, etc.), climatic variability (its dominating modes, such as El Niño or Arctic Oscillation), etc. At the same time, it is quite urgent now to use modern mathematical models in studying regional climate and ecological peculiarities, in particular, that of Northern Eurasia. It is related with the fact that, according to modern ideas, natural environment in mid- and high latitudes of the Northern hemisphere is most sensitive to the observed global climate changes. One should consider such tasks of modeling regional climate as detailed reconstruction of its characteristics, investigation of the peculiarities of hydrological cycle, estimation of the possibility of extreme phenomena to occur, and investigation of the consequences of the regional climate changes for the environment and socio-economic relations as its basic tasks. Changes in nature and climate in Siberia are of special interest in view of the global change in the Earth system. The vast continental territory of Siberia is undoubtedly a ponderable natural territorial region of Eurasian continent, which is characterized by the various combinations of climate-forming factors. Forests, water, and wetland areas are situated on a significant part of Siberia. They play planetary important regulating role due to the processes of emission and accumulation of the main greenhouse gases (carbon dioxide, methane, etc.). Evidence of the enhanced rates of the warming observed in the region and the consequences of such warming for natural environment are undoubtedly important reason for integrated regional investigations in this region of the planet. Reported is an overview of some risk consequences of Climate/Global Change for Siberia environment as follows from results of current scientific activity in climate monitoring and modelling. At present, the challenge facing the weather and climate scientists is to improve the prediction of interactions between weather/climate and Earth system. Taking into account significantly increased computing capacity, a special attention in the report is paid to perspectives of the Earth system modelling.
NASA Technical Reports Server (NTRS)
Suarez, Max J. (Editor); Takacs, Lawrence L.; Molod, Andrea; Wang, Tina
1994-01-01
This technical report documents Version 1 of the Goddard Earth Observing System (GEOS) General Circulation Model (GCM). The GEOS-1 GCM is being used by NASA's Data Assimilation Office (DAO) to produce multiyear data sets for climate research. This report provides a documentation of the model components used in the GEOS-1 GCM, a complete description of model diagnostics available, and a User's Guide to facilitate GEOS-1 GCM experiments.
NASA Astrophysics Data System (ADS)
Li, Yanrong; Wang, Jinxia
2018-06-01
Surface water, as the largest part of water resources, plays an important role on China's agricultural production and food security. And surface water is vulnerable to climate change. This paper aims to examine the status of the supply reliability of surface water irrigation, and discusses how it is affected by climate change in rural China. The field data we used in this study was collected from a nine-province field survey during 2012 and 2013. Climate data are offered by China's National Meteorological Information Center which contains temperature and precipitation in the past 30 years. A Tobit model (or censored regression model) was used to estimate the influence of climate change on supply reliability of surface water irrigation. Descriptive results showed that, surface water supply reliability was 74 % in the past 3 years. Econometric results revealed that climate variables significantly influenced the supply reliability of surface water irrigation. Specifically, temperature is negatively related with the supply reliability of surface water irrigation; but precipitation positively influences the supply reliability of surface water irrigation. Besides, climate influence differs by seasons. In a word, this paper improves our understanding of the impact of climate change on agriculture irrigation and water supply reliability in the micro scale, and provides a scientific basis for relevant policy making.
NASA Astrophysics Data System (ADS)
Tang, J.; Riley, W. J.
2015-12-01
Previous studies have identified four major sources of predictive uncertainty in modeling land biogeochemical (BGC) processes: (1) imperfect initial conditions (e.g., assumption of preindustrial equilibrium); (2) imperfect boundary conditions (e.g., climate forcing data); (3) parameterization (type I equifinality); and (4) model structure (type II equifinality). As if that were not enough to cause substantial sleep loss in modelers, we propose here a fifth element of uncertainty that results from implementation ambiguity that occurs when the model's mathematical description is translated into computational code. We demonstrate the implementation ambiguity using the example of nitrogen down regulation, a necessary process in modeling carbon-climate feedbacks. We show that, depending on common land BGC model interpretations of the governing equations for mineral nitrogen, there are three different implementations of nitrogen down regulation. We coded these three implementations in the ACME land model (ALM), and explored how they lead to different preindustrial and contemporary land biogeochemical states and fluxes. We also show how this implementation ambiguity can lead to different carbon-climate feedback estimates across the RCP scenarios. We conclude by suggesting how to avoid such implementation ambiguity in ESM BGC models.
Towards multi-resolution global climate modeling with ECHAM6-FESOM. Part II: climate variability
NASA Astrophysics Data System (ADS)
Rackow, T.; Goessling, H. F.; Jung, T.; Sidorenko, D.; Semmler, T.; Barbi, D.; Handorf, D.
2018-04-01
This study forms part II of two papers describing ECHAM6-FESOM, a newly established global climate model with a unique multi-resolution sea ice-ocean component. While part I deals with the model description and the mean climate state, here we examine the internal climate variability of the model under constant present-day (1990) conditions. We (1) assess the internal variations in the model in terms of objective variability performance indices, (2) analyze variations in global mean surface temperature and put them in context to variations in the observed record, with particular emphasis on the recent warming slowdown, (3) analyze and validate the most common atmospheric and oceanic variability patterns, (4) diagnose the potential predictability of various climate indices, and (5) put the multi-resolution approach to the test by comparing two setups that differ only in oceanic resolution in the equatorial belt, where one ocean mesh keeps the coarse 1° resolution applied in the adjacent open-ocean regions and the other mesh is gradually refined to 0.25°. Objective variability performance indices show that, in the considered setups, ECHAM6-FESOM performs overall favourably compared to five well-established climate models. Internal variations of the global mean surface temperature in the model are consistent with observed fluctuations and suggest that the recent warming slowdown can be explained as a once-in-one-hundred-years event caused by internal climate variability; periods of strong cooling in the model (`hiatus' analogs) are mainly associated with ENSO-related variability and to a lesser degree also to PDO shifts, with the AMO playing a minor role. Common atmospheric and oceanic variability patterns are simulated largely consistent with their real counterparts. Typical deficits also found in other models at similar resolutions remain, in particular too weak non-seasonal variability of SSTs over large parts of the ocean and episodic periods of almost absent deep-water formation in the Labrador Sea, resulting in overestimated North Atlantic SST variability. Concerning the influence of locally (isotropically) increased resolution, the ENSO pattern and index statistics improve significantly with higher resolution around the equator, illustrating the potential of the novel unstructured-mesh method for global climate modeling.
Gender differences in farmers' responses to climate change adaptation in Yongqiao District, China.
Jin, Jianjun; Wang, Xiaomin; Gao, Yiwei
2015-12-15
This study examines the gender differences in farmers' responses to climate change adaption in Yongqiao District, China. A random sampling technique was used to select 220 household heads, while descriptive statistics and binary logit models were used to analyze the data obtained from the households. We determine that male and female respondents are not significantly different in their knowledge and perceptions of climate change, but there is a gender difference in adopting climate change adaptation measures. Male-headed households are more likely to adopt new technology for water conservation and to increase investment in irrigation infrastructure. The research also indicates that the adaptation decisions of male and female heads are influenced by different sets of factors. The findings of this research help to elucidate the determinants of climate change adaptation decisions for male and female-headed households and the strategic interventions necessary for effective adaptation. Copyright © 2015 Elsevier B.V. All rights reserved.
Mars - The regolith-atmosphere-cap system and climate change
NASA Technical Reports Server (NTRS)
Fanale, F. P.; Salvail, J. R.; Banerdt, W. B.; Saunders, R. S.
1982-01-01
A model is derived for the prediction of the Martian regolith-atmosphere-cap CO2 regime's behavior, as well as for the description of the roly of the regime in climate change, through descriptions of the time-temperature histories of 90 regolith 'chunks' on a latitude-depth grid. The influence of differences in regolith adsorption laws for basalt and clay, and the influence of variations in regolith depth with (1) latitude, (2) regolith thermal diffusivity, and (3) total exchangeable CO2 inventory on predicted variations in atmospheric pressure and cap mass, are examined. It is found that the atmosphere acts as a low capacity conduit between two reservoirs through which 10-100 times the current atmospheric mass of CO2 flows. The exchange between the reservoirs is driven by obliquity variations, with the polar cap the dominant CO2 sink at low obliquity and the regolith dominating at high obliquity.
Adapting regional watershed management to climate change in Bavaria and Québec
NASA Astrophysics Data System (ADS)
Ludwig, Ralf; Muerth, Markus; Schmid, Josef; Jobst, Andreas; Caya, Daniel; Gauvin St-Denis, Blaise; Chaumont, Diane; Velazquez, Juan-Alberto; Turcotte, Richard; Ricard, Simon
2013-04-01
The international research project QBic3 (Quebec-Bavarian Collaboration on Climate Change) aims at investigating the potential impacts of climate change on the hydrology of regional scale catchments in Southern Quebec (Canada) and Bavaria (Germany). For this purpose, a hydro-meteorological modeling chain has been established, applying climatic forcing from both dynamical and statistical climate model data to an ensemble of hydrological models of varying complexity. The selection of input data, process descriptions and scenarios allows for the inter-comparison of the uncertainty ranges on selected runoff indicators; a methodology to display the relative importance of each source of uncertainty is developed and results for past runoff (1971-2000) and potential future changes (2041-2070) are obtained. Finally, the impact of hydrological changes on the operational management of dams, reservoirs and transfer systems is investigated and shown for the Bavarian case studies, namely the potential change in i) hydro-power production for the Upper Isar watershed and ii) low flow augmentation and water transfer rates at the Donau-Main transfer system in Central Franconia. Two overall findings will be presented and discussed in detail: a) the climate change response of selected hydrological indicators, especially those related to low flows, is strongly affected by the choice of the hydrological model. It can be shown that an assessment of the changes in the hydrological cycle is best represented by a complex physically based hydrological model, computationally less demanding models (usually simple, lumped and conceptual) can give a significant level of trust for selected indicators. b) the major differences in the projected climate forcing stemming from the ensemble of dynamic climate models (GCM/RCM) versus the statistical-stochastical WETTREG2010 approach. While the dynamic ensemble reveals a moderate modification of the hydrological processes in the investigated catchments, the WETTREG2010 driven runs show a severe detraction for all water operations, mainly related to a strong decline in projected precipitation in all seasons (except winter).
Polar Processes in a 50-year Simulation of Stratospheric Chemistry and Transport
NASA Technical Reports Server (NTRS)
Kawa, S.R.; Douglass, A. R.; Patrick, L. C.; Allen, D. R.; Randall, C. E.
2004-01-01
The unique chemical, dynamical, and microphysical processes that occur in the winter polar lower stratosphere are expected to interact strongly with changing climate and trace gas abundances. Significant changes in ozone have been observed and prediction of future ozone and climate interactions depends on modeling these processes successfully. We have conducted an off-line model simulation of the stratosphere for trace gas conditions representative of 1975-2025 using meteorology from the NASA finite-volume general circulation model. The objective of this simulation is to examine the sensitivity of stratospheric ozone and chemical change to varying meteorology and trace gas inputs. This presentation will examine the dependence of ozone and related processes in polar regions on the climatological and trace gas changes in the model. The model past performance is base-lined against available observations, and a future ozone recovery scenario is forecast. Overall the model ozone simulation is quite realistic, but initial analysis of the detailed evolution of some observable processes suggests systematic shortcomings in our description of the polar chemical rates and/or mechanisms. Model sensitivities, strengths, and weaknesses will be discussed with implications for uncertainty and confidence in coupled climate chemistry predictions.
Enabling the use of climate model data in the Dutch climate effect community
NASA Astrophysics Data System (ADS)
Som de Cerff, Wim; Plieger, Maarten
2010-05-01
Within the climate effect community the usage of climate model data is emerging. Where mostly climate time series and weather generators were used, there is a shift to incorporate climate model data into climate effect models. The use of climate model data within the climate effect models is difficult, due to missing metadata, resolution and projection issues, data formats and availability of the parameters of interest. Often the climate effect modelers are not aware of available climate model data or are not aware of how they can use it. Together with seven other partners (CERFACS, CNR-IPSL, SMHI, INHGA, CMCC, WUR, MF-CNRM), KNMI is involved in the FP7 IS ENES (http://www.enes.org) project work package 10/JRA5 ‘Bridging Climate Research Data and the Needs of the Impact Community. The aims of this work package are to enhance the use of Climate Research Data and to enhance the interaction with climate effect/impact communities. Phase one is to define use cases together with the Dutch climate effect community, which describe the intended use of climate model data in climate effect models. We defined four use cases: 1) FEWS hydrological Framework (Deltares) 2) METAPHOR, a plants and species dispersion model (Wageningen University) 3) Natuurplanner, an Ecological model suite (Wageningen University) 4) Land use models (Free University/JRC). Also the other partners in JRA5 have defined use cases, which are representative for the climate effect and impact communities in their country. Goal is to find commonalities between all defined use cases. The common functionality will be implemented as e-tools and incorporated in the IS-ENES data portal. Common issues relate to e.g., need for high resolution: downscaling from GCM to local scale (also involves interpolation); parameter selection; finding extremes; averaging methods. At the conference we will describe the FEWS case in more detail: Delft FEWS is an open shell system (in development since 1995) for performing hydrological predictions and the handling of time series data. The most important capabilities of FEWS are importing of meteorological and hydrological data and organizing the workflows of the different models which can be used within FEWS, like the Netherlands Hydrological Instrumentarium (NHI). Besides predictions, the system is currently being used for hydrological climate effects studies. Currently regionally downscaled data are used, but using model data will be the next step. This coupling of climate model data to FEWS will open a wider rage of climate impact and effect research, but it is a difficult task to accomplish. Issues to be dealt with are: regridding, downscaling, format conversion, extraction of required data and addition of descriptive metadata, including quality and uncertainty parameters. Finding an appropriate solution involves several iterations: first, the use case was defined, then we just provided a single data file containing some data of interest provided via FTP, next this data was offered through OGC services. Currently we are working on providing larger datasets and improving on the parameters and metadata. We will present the results (e-tools/data) and experiences gained on implementing the described use cases. Note that we are currently using experimental data, as the official climate model runs are not available yet.
Future scenarios for viticultural bioclimatic indices in Europe
NASA Astrophysics Data System (ADS)
Santos, João.; Malheiro, Aureliano C.; Fraga, Helder; Pinto, Joaquim G.
2010-05-01
Winemaking has a predominant economic, social and environmental relevance in several European countries. Studies addressing the influence of climate variability and change in viticulture are particularly pertinent, as climate is one of the main conditioning factors of this activity. In this context, bioclimatic indices are a useful zoning tool, allowing the description of the suitability of a particular region for wine production. In this study, we compute climatic indices (concerning to thermal and hydrological conditions) for Europe, characterize regions with different viticultural aptitude, and assess possible variations in these regions under a future climate conditions using a state-of-the-art regional climate model. The indices are calculated from climatic variables (mostly daily maximum and minimum temperatures and precipitation) obtained from the NCEP reanalysis dataset. Then, the same indices are calculated for present and future climate conditions using data from the regional climate model COSMO-CLM (Consortium for Small Scale Modelling - Climate Limited-area Modelling). Maps of theses indices for recent-past periods (1961-2008) and for the SRES A1B scenario are considered in order to identify significant changes in their patterns. Results show that climate change is projected to have a significant negative impact in wine quality by increased dryness and cumulative thermal effects during growing seasons in Southern European regions (e.g. Portugal, Spain and Italy). These changes represent an important constraint to grapevine growth and development, making crucial adaptation/mitigation strategies to be adopted. On the other hand, regions of western and central Europe (e.g. southern Britain, northern France and Germany) will benefit from this scenario both in wine quality, and in new potential areas for viticulture. This approach provides a macro-characterization of European areas where grapevines may preferentially grow, as well as their projected changes under human-induced forcing. As such, it can be a useful tool for viticultural zoning in a changing climate.
Biospheric feedback effects in a synchronously coupled model of human and Earth systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thornton, Peter E.; Calvin, Katherine; Jones, Andrew D.
Fossil fuel combustion and land-use change are the first and second largest contributors to industrial-era increases in atmospheric carbon dioxide concentration, which is itself the largest driver of present-day climate change1. Projections of fossil fuel consumption and land-use change are thus fundamental inputs for coupled Earth system models (ESM) used to estimate the physical and biological consequences of future climate system forcing2,3. While empirical datasets are available to inform historical analyses4,5, assessments of future climate change have relied on projections of energy and land use based on energy economic models, constrained using historical and present-day data and forced with assumptionsmore » about future policy, land-use patterns, and socio-economic development trajectories6. Here we show that the influence of biospheric change – the integrated effect of climatic, ecological, and geochemical processes – on land ecosystems has a significant impact on energy, agriculture, and land-use projections for the 21st century. Such feedbacks have been ignored in previous ESM studies of future climate. We find that synchronous exposure of land ecosystem productivity in the economic system to biospheric change as it develops in an ESM results in a 10% reduction of land area used for crop cultivation; increased managed forest area and land carbon; a 15-20% decrease in global crop price; and a 17% reduction in fossil fuel emissions for a low-mid range forcing scenario7. These simulation results demonstrate that biospheric change can significantly alter primary human system forcings to the climate system. This synchronous two-way coupling approach removes inconsistencies in description of climate change between human and biosphere components of the coupled model, mitigating a major source of uncertainty identified in assessments of future climate projections8-10.« less
NASA Astrophysics Data System (ADS)
Ntegeka, Victor; Willems, Patrick; Baguis, Pierre; Roulin, Emmanuel
2015-04-01
It is advisable to account for a wide range of uncertainty by including the maximum possible number of climate models and scenarios for future impacts. As this is not always feasible, impact assessments are inevitably performed with a limited set of scenarios. The development of tailored scenarios is a challenge that needs more attention as the number of available climate change simulations grows. Whether these scenarios are representative enough for climate change impacts is a question that needs addressing. This study presents a methodology of constructing tailored scenarios for assessing runoff flows including extreme conditions (peak flows) from an ensemble of future climate change signals of precipitation and potential evapotranspiration (ETo) derived from the climate model simulations. The aim of the tailoring process is to formulate scenarios that can optimally represent the uncertainty spectrum of climate scenarios. These tailored scenarios have the advantage of being few in number as well as having a clear description of the seasonal variation of the climate signals, hence allowing easy interpretation of the implications of future changes. The tailoring process requires an analysis of the hydrological impacts from the likely future change signals from all available climate model simulations in a simplified (computationally less expensive) impact model. Historical precipitation and ETo time series are perturbed with the climate change signals based on a quantile perturbation technique that accounts for the changes in extremes. For precipitation, the change in wetday frequency is taken into account using a markov-chain approach. Resulting hydrological impacts from the perturbed time series are then subdivided into high, mean and low hydrological impacts using a quantile change analysis. From this classification, the corresponding precipitation and ETo change factors are back-tracked on a seasonal basis to determine precipitation-ETo covariation. The established precipitation-ETo covariations are used to inform the scenario construction process. Additionally, the back-tracking of extreme flows from driving scenarios allows for a diagnosis of the physical responses to climate change scenarios. The method is demonstrated through the application of scenarios from 10 Regional Climate Models,21 Global Climate Models and selected catchments in central Belgium. Reference Ntegeka, V., Baguis, P., Roulin, E., & Willems, P. (2014). Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508, 307-321.
NASA Astrophysics Data System (ADS)
Ray, A. J.; Ojima, D. S.; Morisette, J. T.
2012-12-01
The DOI North Central Climate Science Center (NC CSC) and the NOAA/NCAR National Climate Predictions and Projections (NCPP) Platform and have initiated a joint pilot study to collaboratively explore the "best available climate information" to support key land management questions and how to provide this information. NCPP's mission is to support state of the art approaches to develop and deliver comprehensive regional climate information and facilitate its use in decision making and adaptation planning. This presentation will describe the evolving joint pilot as a tangible, real-world demonstration of linkages between climate science, ecosystem science and resource management. Our joint pilot is developing a deliberate, ongoing interaction to prototype how NCPP will work with CSCs to develop and deliver needed climate information products, including translational information to support climate data understanding and use. This pilot also will build capacity in the North Central CSC by working with NCPP to use climate information used as input to ecological modeling. We will discuss lessons to date on developing and delivering needed climate information products based on this strategic partnership. Four projects have been funded to collaborate to incorporate climate information as part of an ecological modeling project, which in turn will address key DOI stakeholder priorities in the region: Riparian Corridors: Projecting climate change effects on cottonwood and willow seed dispersal phenology, flood timing, and seedling recruitment in western riparian forests. Sage Grouse & Habitats: Integrating climate and biological data into land management decision models to assess species and habitat vulnerability Grasslands & Forests: Projecting future effects of land management, natural disturbance, and CO2 on woody encroachment in the Northern Great Plains The value of climate information: Supporting management decisions in the Plains and Prairie Potholes LCC. NCCSC's role in these projects is to provide the connections between climate data and running ecological models, and prototype these for future work. NCPP will develop capacities to provide enhanced climate information at relevant spatial and temporal scales, both for historical climate and projections of future climate, and will work to link expert guidance and understanding of modeling processes and evaluation of modeling with the use of numerical climate data. Translational information thus is a suite of information that aids in translation of numerical climate information into usable knowledge for applications, e.g. ecological response models, hydrologic risk studies. This information includes technical and scientific aspects including, but not limited to: 1) results of objective, quantitative evaluation of climate models & downscaling techniques, 2) guidance on appropriate uses and interpretation, i.e., understanding the advantages and limitations of various downscaling techniques for specific user applications, 3) characterizing and interpreting uncertainty, 4) Descriptions meaningful to applications, e.g. narratives. NCPP believes that translational information is best co-developed between climate scientists and applications scientists, such as the NC-CSC pilot.
Regulating Emotional Responses to Climate Change – A Construal Level Perspective
Ejelöv, Emma; Hansla, André; Bergquist, Magnus; Nilsson, Andreas
2018-01-01
This experimental study (N = 139) examines the role of emotions in climate change risk communication. Drawing on Construal Level Theory, we tested how abstract vs. concrete descriptions of climate threat affect basic and self-conscious emotions and three emotion regulation strategies: changing oneself, repairing the situation and distancing oneself. In a 2 × 2 between subjects factorial design, climate change consequences were described as concrete/abstract and depicted as spatially proximate/distant. Results showed that, as hypothesized, increased self-conscious emotions mediate overall positive effects of abstract description on self-change and repair attempts. Unexpectedly and independent of any emotional process, a concrete description of a spatially distant consequence is shown to directly increase self-change and repair attempts, while it has no such effects when the consequence is spatially proximate. “Concretizing the remote” might refer to a potentially effective strategy for overcoming spatial distance barriers and motivating mitigating behavior. PMID:29780340
Regulating Emotional Responses to Climate Change - A Construal Level Perspective.
Ejelöv, Emma; Hansla, André; Bergquist, Magnus; Nilsson, Andreas
2018-01-01
This experimental study ( N = 139) examines the role of emotions in climate change risk communication. Drawing on Construal Level Theory, we tested how abstract vs. concrete descriptions of climate threat affect basic and self-conscious emotions and three emotion regulation strategies: changing oneself, repairing the situation and distancing oneself. In a 2 × 2 between subjects factorial design, climate change consequences were described as concrete/abstract and depicted as spatially proximate/distant. Results showed that, as hypothesized, increased self-conscious emotions mediate overall positive effects of abstract description on self-change and repair attempts. Unexpectedly and independent of any emotional process, a concrete description of a spatially distant consequence is shown to directly increase self-change and repair attempts, while it has no such effects when the consequence is spatially proximate. "Concretizing the remote" might refer to a potentially effective strategy for overcoming spatial distance barriers and motivating mitigating behavior.
Climate Change and Its Impact on the Incarcerated Population: A Descriptive Review.
Motanya, Njideka C; Valera, Pamela
2016-01-01
This descriptive review article describes climate change and its detrimental effects on incarcerated populations. Case examples are provided of specific natural disasters and deaths due to overheating temperatures. Because public health and social work aims to improve the health and social welfare of vulnerable populations, the authors explain why climate change should be considered a priority area in both fields. Examples are provided on how to improve conditions for the 2.4 million men, women, and youth who are incarcerated.
Flight Testing Under Extreme Climatic Conditions
1988-09-01
30 Categorizing Hazards and Risk Levels .. ......... 31 CLIMATIC LABORATORIES ..... .............. 33 UNITED KINGDOM ENVIRONMENTAL...FACILITY .. ........ 33 MCKINLEY CIMATIC LABORATORY .... ............ 34 Climatic Laboratory Description ... ........... 35 Climatic Laboratory...Profile 10 3 Risk Level Chart .... ............. . 32 4 Plan View of Climatic Laboratory Main Chamber 36 5 Relative Humidity vs Ambient Air Temperature for
NASA Technical Reports Server (NTRS)
Suarex, Max J. (Editor); Chou, Ming-Dah
1994-01-01
A detailed description of a parameterization for thermal infrared radiative transfer designed specifically for use in global climate models is presented. The parameterization includes the effects of the main absorbers of terrestrial radiation: water vapor, carbon dioxide, and ozone. While being computationally efficient, the schemes compute very accurately the clear-sky fluxes and cooling rates from the Earth's surface to 0.01 mb. This combination of accuracy and speed makes the parameterization suitable for both tropospheric and middle atmospheric modeling applications. Since no transmittances are precomputed the atmospheric layers and the vertical distribution of the absorbers may be freely specified. The scheme can also account for any vertical distribution of fractional cloudiness with arbitrary optical thickness. These features make the parameterization very flexible and extremely well suited for use in climate modeling studies. In addition, the numerics and the FORTRAN implementation have been carefully designed to conserve both memory and computer time. This code should be particularly attractive to those contemplating long-term climate simulations, wishing to model the middle atmosphere, or planning to use a large number of levels in the vertical.
NASA Technical Reports Server (NTRS)
Kung, E. C.
1984-01-01
Energetics characteristics of Goddard Laboratory for Atmospheric Sciences (GLAS) General Circulation Models (GCM) as they are reflected on the First GARD GLobal Experiment (FGGE) analysis data set are discussed. Energetics descriptions of GLAS GCM forecast experiments are discussed as well as Eneretics response of GLAS GCM climatic simulation experiments.
Regional climate models downscaling in the Alpine area with Multimodel SuperEnsemble
NASA Astrophysics Data System (ADS)
Cane, D.; Barbarino, S.; Renier, L. A.; Ronchi, C.
2012-08-01
The climatic scenarios show a strong signal of warming in the Alpine area already for the mid XXI century. The climate simulations, however, even when obtained with Regional Climate Models (RCMs), are affected by strong errors where compared with observations, due to their difficulties in representing the complex orography of the Alps and limitations in their physical parametrization. Therefore the aim of this work is reducing these model biases using a specific post processing statistic technique to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we use a selection of RCMs runs from the ENSEMBLES project, carefully chosen in order to maximise the variety of leading Global Climate Models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observation for the Greater Alpine Area are extracted from the European dataset E-OBS produced by the project ENSEMBLES with an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (1957-present) were carefully gridded on a 14-km grid over Piedmont Region with an Optimal Interpolation technique. Hence, we applied the Multimodel SuperEnsemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We propose also the first application to RCMS of a brand new probabilistic Multimodel SuperEnsemble Dressing technique to estimate precipitation fields, already applied successfully to weather forecast models, with careful description of precipitation Probability Density Functions conditioned to the model outputs. This technique reduces the strong precipitation overestimation by RCMs over the alpine chain and reproduces well the monthly behaviour of precipitation in the control period.
Description of water-systems operations in the Arkansas River basin, Colorado
Abbott, P.O.
1985-01-01
To facilitate a current project modeling the hydrology of the Arkansas River basin in Colorado, a description of the regulation of water in the basin is necessary. The geographic and climatic setting of the Arkansas River basin that necessitates the use, reuse, importation, and storage of water are discussed. The history of water-resource development in the basin, leading to the present complex of water systems, also is discussed. Municipal, irrigation, industrial, and multipurpose water systems are described. System descriptions are illustrated with schematic line drawings, and supplemented with physical data tables for the lakes, tunnels, conduits, and canals in the various systems. Copies of criteria under which certain of the water systems operate, are included. (USGS)
Model Interpretation of Climate Signals: Application to the Asian Monsoon Climate
NASA Technical Reports Server (NTRS)
Lau, William K. M.
2002-01-01
This is an invited review paper intended to be published as a Chapter in a book entitled "The Global Climate System: Patterns, Processes and Teleconnections" Cambridge University Press. The author begins with an introduction followed by a primer of climate models, including a description of various modeling strategies and methodologies used for climate diagnostics and predictability studies. Results from the CLIVAR Monsoon Model Intercomparison Project (MMIP) were used to illustrate the application of the strategies to modeling the Asian monsoon. It is shown that state-of-the art atmospheric GCMs have reasonable capability in simulating the seasonal mean large scale monsoon circulation, and response to El Nino. However, most models fail to capture the climatological as well as interannual anomalies of regional scale features of the Asian monsoon. These include in general over-estimating the intensity and/or misplacing the locations of the monsoon convection over the Bay of Bengal, and the zones of heavy rainfall near steep topography of the Indian subcontinent, Indonesia, and Indo-China and the Philippines. The intensity of convection in the equatorial Indian Ocean is generally weaker in models compared to observations. Most important, an endemic problem in all models is the weakness and the lack of definition of the Mei-yu rainbelt of the East Asia, in particular the part of the Mei-yu rainbelt over the East China Sea and southern Japan are under-represented. All models seem to possess certain amount of intraseasonal variability, but the monsoon transitions, such as the onset and breaks are less defined compared with the observed. Evidences are provided that a better simulation of the annual cycle and intraseasonal variability is a pre-requisite for better simulation and better prediction of interannual anomalies.
Evaluating the uncertainty of predicting future climate time series at the hourly time scale
NASA Astrophysics Data System (ADS)
Caporali, E.; Fatichi, S.; Ivanov, V. Y.
2011-12-01
A stochastic downscaling methodology is developed to generate hourly, point-scale time series for several meteorological variables, such as precipitation, cloud cover, shortwave radiation, air temperature, relative humidity, wind speed, and atmospheric pressure. The methodology uses multi-model General Circulation Model (GCM) realizations and an hourly weather generator, AWE-GEN. Probabilistic descriptions of factors of change (a measure of climate change with respect to historic conditions) are computed for several climate statistics and different aggregation times using a Bayesian approach that weights the individual GCM contributions. The Monte Carlo method is applied to sample the factors of change from their respective distributions thereby permitting the generation of time series in an ensemble fashion, which reflects the uncertainty of climate projections of future as well as the uncertainty of the downscaling procedure. Applications of the methodology and probabilistic expressions of certainty in reproducing future climates for the periods, 2000 - 2009, 2046 - 2065 and 2081 - 2100, using the 1962 - 1992 period as the baseline, are discussed for the location of Firenze (Italy). The climate predictions for the period of 2000 - 2009 are tested against observations permitting to assess the reliability and uncertainties of the methodology in reproducing statistics of meteorological variables at different time scales.
Regional climate models downscaling in the Alpine area with multimodel superensemble
NASA Astrophysics Data System (ADS)
Cane, D.; Barbarino, S.; Renier, L. A.; Ronchi, C.
2013-05-01
The climatic scenarios show a strong signal of warming in the Alpine area already for the mid-XXI century. The climate simulations, however, even when obtained with regional climate models (RCMs), are affected by strong errors when compared with observations, due both to their difficulties in representing the complex orography of the Alps and to limitations in their physical parametrization. Therefore, the aim of this work is to reduce these model biases by using a specific post processing statistic technique, in order to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we used a selection of regional climate models (RCMs) runs which were developed in the framework of the ENSEMBLES project. They were carefully chosen with the aim to maximise the variety of leading global climate models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observations for the greater Alpine area were extracted from the European dataset E-OBS (produced by the ENSEMBLES project), which have an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (covering the period from 1957 to the present) were carefully gridded on a 14 km grid over Piedmont region through the use of an optimal interpolation technique. Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We also proposed the application of a brand new probabilistic multimodel superensemble dressing technique, already applied to weather forecast models successfully, to RCMS: the aim was to estimate precipitation fields, with careful description of precipitation probability density functions conditioned to the model outputs. This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to reproduce well the monthly behaviour of precipitation in the control period.
Climate Variability In The Euro-atlantic Sector As Simulated By Echam4
NASA Astrophysics Data System (ADS)
Menezes, I.; Corte-Real, J.; Ramos, A.; Conde, F.
The atmosphere is a fundamental component of the climate system and its influence in local and global climates results from its composition, structure and motion. The best available tools to simulate future climates are coupled atmosphere-ocean general circulation models (AOGCMs), ECHAM4 (T42 L19)[1] being a very relevant exam- ple of such a model due to its elaborated parametrizations of physical processes. The purpose of this work is twofold : (1) to assess the ability of ECHAM4 in reproducing the reference climate of 1961-1990, over the Euro-Atlantic sector (29N-71N; 67W- 59E) in terms of mean sea level pressure, surface temperature and total precipitation; (2) to evaluate the expected changes of the same climate elements in a warmer world. To attain the first goal the ECHAMSs control run output is compared with observed data obtained from the Climatic Research Unit (CRU data set)[2-5]; to achieve the second objective, the modelSs control run is compared with its transient run forced by greenhouse gases. In both cases, comparisons are made in terms of mean values, variability in space and time and extremes. References [1] E. Roeckner, K. Arpe, L. Bengtsson, M. Christoph, M. Claussen, L. Dümenil, M. Esch, M. Giorgetta, U. Schlese, and U. Schulzweida, 1996: The atmospheric gen- eral circulation model ECHAM4: Model description and simulation of present-day climate. Max Planck Institut für Meteorologie, Report No. 218, Hamburg, Germany, 90 pp. [2] M. Hulme, D. Conway, P.D. Jones, T. Jiang, E.M. Barrow, and C. Turney (1995), Construction of a 1961-90 European climatology for climate change impacts and mod- elling applications, Int. J. Climatol., 15, 1333-1363. [3] M. Hulme (1994), The cost of climate data U a European experience, Weather, 49, 168-175. [4] M. Hulme, and M.G. New (1997), Dependence of large-scale precipitation clima- tologies on temporal and spatial sampling, J. Climate, 10, 1099-1113. 1 [5] C.J. Willmot, S.M. Robeson and M.J. Janis (1996), Comparison of approaches for estimating time-averaged precipitation using data from the United States, Int. J. Cli- matol., 16, 1103-1115. 2
NASA Astrophysics Data System (ADS)
Neal, Lucy S.; Dalvi, Mohit; Folberth, Gerd; McInnes, Rachel N.; Agnew, Paul; O'Connor, Fiona M.; Savage, Nicholas H.; Tilbee, Marie
2017-11-01
There is a clear need for the development of modelling frameworks for both climate change and air quality to help inform policies for addressing these issues simultaneously. This paper presents an initial attempt to develop a single modelling framework, by introducing a greater degree of consistency in the meteorological modelling framework by using a two-step, one-way nested configuration of models, from a global composition-climate model (GCCM) (140 km resolution) to a regional composition-climate model covering Europe (RCCM) (50 km resolution) and finally to a high (12 km) resolution model over the UK (AQUM). The latter model is used to produce routine air quality forecasts for the UK. All three models are based on the Met Office's Unified Model (MetUM). In order to better understand the impact of resolution on the downscaling of projections of future climate and air quality, we have used this nest of models to simulate a 5-year period using present-day emissions and under present-day climate conditions. We also consider the impact of running the higher-resolution model with higher spatial resolution emissions, rather than simply regridding emissions from the RCCM. We present an evaluation of the models compared to in situ air quality observations over the UK, plus a comparison against an independent 1 km resolution gridded dataset, derived from a combination of modelling and observations, effectively producing an analysis of annual mean surface pollutant concentrations. We show that using a high-resolution model over the UK has some benefits in improving air quality modelling, but that the use of higher spatial resolution emissions is important to capture local variations in concentrations, particularly for primary pollutants such as nitrogen dioxide and sulfur dioxide. For secondary pollutants such as ozone and the secondary component of PM10, the benefits of a higher-resolution nested model are more limited and reasons for this are discussed. This study highlights the point that the resolution of models is not the only factor in determining model performance - consistency between nested models is also important.
NASA Astrophysics Data System (ADS)
Mercogliano, Paola; Bucchignani, Edoardo; Montesarchio, Myriam; Zollo, Alessandra Lucia
2013-04-01
In the framework of the Work Package 4 (Developing integrated tools for environmental assessment) of PERSEUS Project, high resolution climate simulations have been performed, with the aim of furthering knowledge in the field of climate variability at regional scale, its causes and impacts. CMCC is a no profit centre whose aims are the promotion, research coordination and scientific activities in the field of climate changes. In this work, we show results of numerical simulation performed over a very wide area (13W-46E; 29-56N) at spatial resolution of 14 km, which includes the Mediterranean and Black Seas, using the regional climate model COSMO-CLM. It is a non-hydrostatic model for the simulation of atmospheric processes, developed by the DWD-Germany for weather forecast services; successively, the model has been updated by the CLM-Community, in order to develop climatic applications. It is the only documented numerical model system in Europe designed for spatial resolutions down to 1 km with a range of applicability encompassing operational numerical weather prediction, regional climate modelling the dispersion of trace gases and aerosol and idealised studies and applicable in all regions of the world for a wide range of available climate simulations from global climate and NWP models. Different reasons justify the development of a regional model: the first is the increasing number of works in literature asserting that regional models have also the features to provide more detailed description of the climate extremes, that are often more important then their mean values for natural and human systems. The second one is that high resolution modelling shows adequate features to provide information for impact assessment studies. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate trend but also extremes of the present and future climate, in terms of temperature, precipitation and wind.
NASA Astrophysics Data System (ADS)
Mercogliano, P.; Montesarchio, M.; Zollo, A.; Bucchignani, E.
2012-12-01
In the framework of the Italian GEMINA Project (program of expansion and development of the Euro-Mediterranean Center for Climate Change (CMCC), high resolution climate simulations have been performed, with the aim of furthering knowledge in the field of climate variability at regional scale, its causes and impacts. CMCC is a no profit centre whose aims are the promotion, research coordination and scientific activities in the field of climate changes. In this work, we show results of numerical simulation performed over a very wide area (13W-46E; 29-56N) at spatial resolution of 14 km, which includes all the Mediterranean Sea, using the regional climate model COSMO-CLM. It is a non-hydrostatic model for the simulation of atmospheric processes, developed by the DWD-Germany for weather forecast services; successively, the model has been updated by the CLM-Community, in order to develop climatic applications. It is the only documented numerical model system in Europe designed for spatial resolutions down to 1 km with a range of applicability encompassing operational numerical weather prediction, regional climate modelling the dispersion of trace gases and aerosol and idealised studies and applicable in all regions of the world for a wide range of available climate simulations from global climate and NWP models. Different reasons justify the development of a regional model: the first is the increasing number of works in literature asserting that regional models have also the features to provide more detailed description of the climate extremes, that are often more important then their mean values for natural and human systems. The second one is that high resolution modelling shows adequate features to provide information for impact assessment studies. At CMCC, regional climate modelling is a part of an integrated simulation system and it has been used in different European and African projects to provide qualitative and quantitative evaluation of the hydrogeological and public health risks. A simulation covering the period 1971-2000 and driven by ERA40 reanalysis has been performed, in order to assess the capability of the model to reproduce the present climate, with "perfect boundary conditions". A comparison, in terms of 2-metre temperature and precipitation, with EOBS dataset will be shown and discussed, in order to analyze the capabilities in simulating the main features of the observed climate over a wide area, at high spatial resolution. Then, a comparison between the results of COSMO-CLM driven by the global model CMCC-MED (whose atmospheric component is ECHAM5) and by ERA40 will be provided for a characterization of the errors induced by the global model. Finally, climate projections on the examined area for the XXI century, considering the RCP4.5 emission scenario for the future, will be provided. In this work a special emphasis will be issued to the analysis of the capability to reproduce not only the average climate patterns but also extremes of the present and future climate, in terms of temperature, precipitation and wind.
NASA Astrophysics Data System (ADS)
Hatté, C.; Rousseau, D.-D.; Guiot, J.
2009-04-01
An improved inverse vegetation model has been designed to better specify both temperature and precipitation estimates from vegetation descriptions. It is based on the BIOME4 vegetation model and uses both vegetation δ13C and biome as constraints. Previous inverse models based on only one of the two proxies were already improvements over standard reconstruction methods such as the modern analog since these did not take into account some external forcings, for example CO2 concentration. This new approach makes it possible to describe a potential "isotopic niche" defined by analogy with the "climatic niche" theory. Boreal and temperate biomes simulated by BIOME4 are considered in this study. We demonstrate the impact of CO2 concentration on biome existence domains by replacing a "most likely biome" with another with increased CO2 concentration. Additionally, the climate imprint on δ13C between and within biomes is shown: the colder the biome, the lighter its potential isotopic niche; and the higher the precipitation, the lighter the δ13C. For paleoclimate purposes, previous inverse models based on either biome or δ13C did not allow informative paleoclimatic reconstructions of both precipitation and temperature. Application of the new approach to the Eemian of La Grande Pile palynological and geochemical records reduces the range in precipitation values by more than 50% reduces the range in temperatures by about 15% compared to previous inverse modeling approaches. This shows evidence of climate instabilities during Eemian period that can be correlated with independent continental and marine records.
NASA Astrophysics Data System (ADS)
Hatté, C.; Rousseau, D.-D.; Guiot, J.
2009-01-01
An improved inverse vegetation model has been designed to better specify both temperature and precipitation estimates from vegetation descriptions. It is based on the BIOME4 vegetation model and uses both vegetation δ13C and biome as constraints. Previous inverse models based on only one of the two proxies were already improvements over standard reconstruction methods such as the modern analog since these did not take into account some external forcings, for example CO2 concentration. This new approach makes it possible to describe a potential "isotopic niche" defined by analogy with the "climatic niche" theory. Boreal and temperate biomes simulated by BIOME4 are considered in this study. We demonstrate the impact of CO2 concentration on biome existence domains by replacing a "most likely biome" with another with increased CO2 concentration. Additionally, the climate imprint on δ13C between and within biomes is shown: the colder the biome, the lighter its potential isotopic niche; and the higher the precipitation, the lighter the δ13C. For paleoclimate purposes, previous inverse models based on either biome or δ13C did not allow informative paleoclimatic reconstructions of both precipitation and temperature. Application of the new approach to the Eemian of La Grande Pile palynological and geochemical records reduces the range in precipitation values by more than 50% reduces the range in temperatures by about 15% compared to previous inverse modeling approaches. This shows evidence of climate instabilities during Eemian period that can be correlated with independent continental and marine records.
NASA Astrophysics Data System (ADS)
McGrath, M.; Luyssaert, S.; Naudts, K.; Chen, Y.; Ryder, J.; Otto, J.; Valade, A.
2015-12-01
Forest management has the potential to impact surface physical characteristics to the same degree that changes in land cover do. The impacts of land cover changes on the global climate are well-known. Despite an increasingly detailed understanding of the potential for forest management to affect climate, none of the current generation of Earth system models account for forest management through their land surface modules. We addressed this gap by developing and reparameterizing the ORCHIDEE land surface model to simulate the biogeochemical and biophysical effects of forest management. Through vertical discretization of the forest canopy and corresponding modifications to the energy budget, radiation transfer, and carbon allocation, forest management can now be simulated much more realistically on the global scale. This model was used to explore the effect of forest management on European climate since 1750. Reparameterization was carried out to replace generic forest plant functional types with real tree species, covering the most dominant species across the continent. Historical forest management and land cover maps were created to run the simulations from 1600 until the present day. The model was coupled to the atmospheric model LMDz to explore differences in climate between 1750 and 2010 and attribute those differences to changes in atmospheric carbon dioxide concentrations and concurrent warming, land cover, species composition, and wood extraction. Although Europe's forest are considered a carbon sink in this century, our simulations show the modern forests are still experiencing carbon debt compared to their historical values.
Regional Climate Models Downscaling in the Alpine Area with Multimodel SuperEnsemble
NASA Astrophysics Data System (ADS)
Cane, D.; Barbarino, S.; Renier, L.; Ronchi, C.
2012-04-01
The climatic scenarios show a strong signal of warming in the Alpine area already for the mid XXI century. The climate simulation, however, even when obtained with Regional Climate Models (RCMs), are affected by strong errors where compared with observations in the control period, due to their difficulties in representing the complex orography of the Alps and limitations in their physical parametrization. In this work we use a selection of RCMs runs from the ENSEMBLES project, carefully chosen in order to maximise the variety of leading Global Climate Models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observation for the Greater Alpine Area are extracted from the European dataset E-OBS produced by the project ENSEMBLES with an available resolution of 25 km. For the study area of Piemonte daily temperature and precipitation observations (1957-present) were carefully gridded on a 14-km grid over Piemonte Region with an Optimal Interpolation technique. We applied the Multimodel SuperEnsemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We propose also the first application to RCMs of a brand new probabilistic Multimodel SuperEnsemble Dressing technique to estimate precipitation fields, already applied successfully to weather forecast models, with careful description of precipitation Probability Density Functions conditioned to the model outputs. This technique reduces the strong precipitation overestimation by RCMs over the alpine chain and reproduces the monthly behaviour of observed precipitation in the control period far better than the direct model outputs.
NASA Astrophysics Data System (ADS)
Hassell, David; Gregory, Jonathan; Blower, Jon; Lawrence, Bryan N.; Taylor, Karl E.
2017-12-01
The CF (Climate and Forecast) metadata conventions are designed to promote the creation, processing, and sharing of climate and forecasting data using Network Common Data Form (netCDF) files and libraries. The CF conventions provide a description of the physical meaning of data and of their spatial and temporal properties, but they depend on the netCDF file encoding which can currently only be fully understood and interpreted by someone familiar with the rules and relationships specified in the conventions documentation. To aid in development of CF-compliant software and to capture with a minimal set of elements all of the information contained in the CF conventions, we propose a formal data model for CF which is independent of netCDF and describes all possible CF-compliant data. Because such data will often be analysed and visualised using software based on other data models, we compare our CF data model with the ISO 19123 coverage model, the Open Geospatial Consortium CF netCDF standard, and the Unidata Common Data Model. To demonstrate that this CF data model can in fact be implemented, we present cf-python, a Python software library that conforms to the model and can manipulate any CF-compliant dataset.
NASA Astrophysics Data System (ADS)
Foster, A.; Shuman, J. K.; Shugart, H. H., Jr.; Dwire, K. A.; Fornwalt, P.; Sibold, J.; Negrón, J. F.
2016-12-01
Forests in the Rocky Mountains are a crucial part of the North American carbon budget, but increases in disturbances such as insect outbreaks and fire, in conjunction with climate change, threaten their vitality. Mean annual temperatures in the western United States have increased by 2°C since 1950 and the higher elevations are warming faster than the rest of the landscape. It is predicted that this warming trend will continue, and that by the end of this century, nearly 50% of the western US landscape will have climate profiles with no current analog within that region. Individual tree-based modeling allows various climate change scenarios and their effects on forest dynamics to be tested. We use an updated individual-based gap model, the University of Virginia Forest Model Enhanced (UVAFME) at a subalpine site in the southern Rocky Mountains. UVAFME has been quantitatively and qualitatively validated in the southern Rocky Mountains, and results show that UVAFME-output on size structure, biomass, and species composition compares reasonably to inventory data and descriptions of vegetation zonation and successional dynamics for the region. We perform a climate sensitivity test in which temperature is first increased linearly by 2°C over 100 years, stabilized for 200 years, cooled back to present climate values over 100 years, and again stabilized for 200 years. This test is conducted to determine what effect elevated temperatures may have on vegetation zonation, and how persistent the changes may be if the climate is brought back to its current state. Results show that elevated temperatures within the southern Rocky Mountains may lead to decreases in biomass and changes in species composition as species migrate upslope. These changes are also likely to be fairly persistent for at least one- to two-hundred years. The results from this study suggest that UVAFME and other individual-based gap models can be used to inform forest management and climate mitigation strategies for this vitally important region.
Towards a climate-dependent paradigm of ammonia emission and deposition
Sutton, Mark A.; Reis, Stefan; Riddick, Stuart N.; Dragosits, Ulrike; Nemitz, Eiko; Theobald, Mark R.; Tang, Y. Sim; Braban, Christine F.; Vieno, Massimo; Dore, Anthony J.; Mitchell, Robert F.; Wanless, Sarah; Daunt, Francis; Fowler, David; Blackall, Trevor D.; Milford, Celia; Flechard, Chris R.; Loubet, Benjamin; Massad, Raia; Cellier, Pierre; Personne, Erwan; Coheur, Pierre F.; Clarisse, Lieven; Van Damme, Martin; Ngadi, Yasmine; Clerbaux, Cathy; Skjøth, Carsten Ambelas; Geels, Camilla; Hertel, Ole; Wichink Kruit, Roy J.; Pinder, Robert W.; Bash, Jesse O.; Walker, John T.; Simpson, David; Horváth, László; Misselbrook, Tom H.; Bleeker, Albert; Dentener, Frank; de Vries, Wim
2013-01-01
Existing descriptions of bi-directional ammonia (NH3) land–atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission–deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28–67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45–85) Tg N in 2008 to reach 132 (89–179) Tg by 2100. PMID:23713128
Towards a climate-dependent paradigm of ammonia emission and deposition.
Sutton, Mark A; Reis, Stefan; Riddick, Stuart N; Dragosits, Ulrike; Nemitz, Eiko; Theobald, Mark R; Tang, Y Sim; Braban, Christine F; Vieno, Massimo; Dore, Anthony J; Mitchell, Robert F; Wanless, Sarah; Daunt, Francis; Fowler, David; Blackall, Trevor D; Milford, Celia; Flechard, Chris R; Loubet, Benjamin; Massad, Raia; Cellier, Pierre; Personne, Erwan; Coheur, Pierre F; Clarisse, Lieven; Van Damme, Martin; Ngadi, Yasmine; Clerbaux, Cathy; Skjøth, Carsten Ambelas; Geels, Camilla; Hertel, Ole; Wichink Kruit, Roy J; Pinder, Robert W; Bash, Jesse O; Walker, John T; Simpson, David; Horváth, László; Misselbrook, Tom H; Bleeker, Albert; Dentener, Frank; de Vries, Wim
2013-07-05
Existing descriptions of bi-directional ammonia (NH3) land-atmosphere exchange incorporate temperature and moisture controls, and are beginning to be used in regional chemical transport models. However, such models have typically applied simpler emission factors to upscale the main NH3 emission terms. While this approach has successfully simulated the main spatial patterns on local to global scales, it fails to address the environment- and climate-dependence of emissions. To handle these issues, we outline the basis for a new modelling paradigm where both NH3 emissions and deposition are calculated online according to diurnal, seasonal and spatial differences in meteorology. We show how measurements reveal a strong, but complex pattern of climatic dependence, which is increasingly being characterized using ground-based NH3 monitoring and satellite observations, while advances in process-based modelling are illustrated for agricultural and natural sources, including a global application for seabird colonies. A future architecture for NH3 emission-deposition modelling is proposed that integrates the spatio-temporal interactions, and provides the necessary foundation to assess the consequences of climate change. Based on available measurements, a first empirical estimate suggests that 5°C warming would increase emissions by 42 per cent (28-67%). Together with increased anthropogenic activity, global NH3 emissions may increase from 65 (45-85) Tg N in 2008 to reach 132 (89-179) Tg by 2100.
Reconstruction of regional climate and climate change in past decades
NASA Astrophysics Data System (ADS)
von Storch, H.; Feser, F.; Weisse, R.; Zahn, M.
2009-12-01
Regional climate models, which are constrained by large scale information (spectral nudging) provided by re-analyses, allow for the construction of a mostly homogeneous description of regional weather statistics since about 1950. The potential of this approach has been demonstrated for Northern Europe. That data set, named CoastDat, does not only contain hourly data on atmospheric variables, in particular wind, but also on marine weather, i.e., short term water level, current and sea state variations. Another example is the multi-decadal variability of Polar Lows in the subarctic waters. The utility of such data sets is broad, from risk assessments related to coastal wind and wave conditions, assessment of determining the causes for regional climate change, a-posteriori analysis of the efficiency of environmental legislation (example: lead). In the paper, the methodology is outlined, examples are provided and the utility of the product discussed.
Description and evaluation of the Earth System Regional Climate Model (RegCM-ES)
NASA Astrophysics Data System (ADS)
Farneti, Riccardo; Sitz, Lina; Di Sante, Fabio; Fuentes-Franco, Ramon; Coppola, Erika; Mariotti, Laura; Reale, Marco; Sannino, Gianmaria; Barreiro, Marcelo; Nogherotto, Rita; Giuliani, Graziano; Graffino, Giorgio; Solidoro, Cosimo; Giorgi, Filippo
2017-04-01
The increasing availability of satellite remote sensing data, of high temporal frequency and spatial resolution, has provided a new and enhanced view of the global ocean and atmosphere, revealing strong air-sea coupling processes throughout the ocean basins. In order to obtain an accurate representation and better understanding of the climate system, its variability and change, the inclusion of all mechanisms of interaction among the different sub-components, at high temporal and spatial resolution, becomes ever more desirable. Recently, global coupled models have been able to progressively refine their horizontal resolution to attempt to resolve smaller-scale processes. However, regional coupled ocean-atmosphere models can achieve even finer resolutions and provide additional information on the mechanisms of air-sea interactions and feedbacks. Here we describe a new, state-of-the-art, Earth System Regional Climate Model (RegCM-ES). RegCM-ES presently includes the coupling between atmosphere, ocean, land surface and sea-ice components, as well as an hydrological and ocean biogeochemistry model. The regional coupled model has been implemented and tested over some of the COordinated Regional climate Downscaling Experiment (CORDEX) domains. RegCM-ES has shown improvements in the representation of precipitation and SST fields over the tested domains, as well as realistic representations of coupled air-sea processes and interactions. The RegCM-ES model, which can be easily implemented over any regional domain of interest, is open source making it suitable for usage by the large scientific community.
NASA Astrophysics Data System (ADS)
Von Storch, H.; Klehmet, K.; Geyer, B.; Li, D.; Schubert-Frisius, M.; Tim, N.; Zorita, E.
2015-12-01
Global re-analyses suffer from inhomogeneities, as they process data from networks under development. However, the large-scale component of such re-analyses is mostly homogeneous; additional observational data add in most cases to a better description of regional details and less so on large-scale states. Therefore, the concept of downscaling may be applied to homogeneously complementing the large-scale state of the re-analyses with regional detail - wherever the condition of homogeneity of the large-scales is fulfilled. Technically this can be done by using a regional climate model, or a global climate model, which is constrained on the large scale by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional risks - in particular marine risks - was identified. While the data density in Europe is considerably better than in most other regions of the world, even here insufficient spatial and temporal coverage is limiting risk assessments. Therefore, downscaled data-sets are frequently used by off-shore industries. We have run this system also in regions with reduced or absent data coverage, such as the Lena catchment in Siberia, in the Yellow Sea/Bo Hai region in East Asia, in Namibia and the adjacent Atlantic Ocean. Also a global (large scale constrained) simulation has been. It turns out that spatially detailed reconstruction of the state and change of climate in the three to six decades is doable for any region of the world.The different data sets are archived and may freely by used for scientific purposes. Of course, before application, a careful analysis of the quality for the intended application is needed, as sometimes unexpected changes in the quality of the description of large-scale driving states prevail.
Acadia National Park Climate Change Scenario Planning Workshop summary
Star, Jonathan; Fisichelli, Nicholas; Bryan, Alexander; Babson, Amanda; Cole-Will, Rebecca; Miller-Rushing, Abraham J.
2016-01-01
This report summarizes outcomes from a two-day scenario planning workshop for Acadia National Park, Maine (ACAD). The primary objective of the workshop was to help ACAD senior leadership make management and planning decisions based on up-to-date climate science and assessments of future uncertainty. The workshop was also designed as a training program, helping build participants' capabilities to develop and use scenarios. The details of the workshop are given in later sections. The climate scenarios presented here are based on published global climate model output. The scenario implications for resources and management decisions are based on expert knowledge distilled through scientist-manager interaction during workgroup break-out sessions at the workshop. Thus, the descriptions below are from these small-group discussions in a workshop setting and should not be taken as vetted research statements of responses to the climate scenarios, but rather as insights and examinations of possible futures (Martin et al. 2011, McBride et al. 2012).
ERIC Educational Resources Information Center
Gay, Lesbian, and Straight Education Network, New York, NY.
This workbook provides an instrument to objectively analyze a school's current climate with regard to lesbian, gay, bisexual, and transgendered (LGBT) people and the steps needed to move that school toward a more inclusive environment. It provides a detailed assessment survey (to be completed by key school stakeholders), descriptive data, and…
Landscape fires dominate terrestrial natural aerosol - climate feedbacks
NASA Astrophysics Data System (ADS)
Scott, C.; Arnold, S.; Monks, S. A.; Asmi, A.; Paasonen, P.; Spracklen, D. V.
2017-12-01
The terrestrial biosphere is an important source of natural aerosol including landscape fire emissions and secondary organic aerosol (SOA) formed from biogenic volatile organic compounds (BVOCs). Atmospheric aerosol alters the Earth's climate by absorbing and scattering radiation (direct radiative effect; DRE) and by perturbing the properties of clouds (aerosol indirect effect; AIE). Natural aerosol sources are strongly controlled by, and can influence, climate; giving rise to potential natural aerosol-climate feedbacks. Earth System Models (ESMs) include a description of some of these natural aerosol-climate feedbacks, predicting substantial changes in natural aerosol over the coming century with associated radiative perturbations. Despite this, the sensitivity of natural aerosols simulated by ESMs to changes in climate or emissions has not been robustly tested against observations. Here we combine long-term observations of aerosol number and a global aerosol microphysics model to assess terrestrial natural aerosol-climate feedbacks. We find a strong positive relationship between the summertime anomaly in observed concentration of particles greater than 100 nm diameter and the anomaly in local air temperature. This relationship is reproduced by the model and driven by variability in dynamics and meteorology, as well as natural sources of aerosol. We use an offline radiative transfer model to determine radiative effects due to changes in two natural aerosol sources: landscape fire and biogenic SOA. We find that interannual variability in the simulated global natural aerosol radiative effect (RE) is negatively related to the global temperature anomaly. The magnitude of global aerosol-climate feedback (sum of DRE and AIE) is estimated to be -0.15 Wm-2 K-1 for landscape fire aerosol and -0.06 Wm-2 K-1 for biogenic SOA. These feedbacks are comparable in magnitude, but opposite in sign to the snow albedo feedback, highlighting the need for natural aerosol feedbacks to be included in climate simulations.
The climate4impact portal: bridging CMIP5 data to impact users
NASA Astrophysics Data System (ADS)
Som de Cerff, Wim; Plieger, Maarten; Page, Christian; Hutjes, Ronald; de Jong, Fokke; Barring, Lars; Sjökvist, Elin
2013-04-01
Together with seven other partners (CERFACS, CNRS-IPSL, SMHI, INHGA, CMCC, WUR, MF-CNRM), KNMI is involved in the FP7 project IS-ENES (http://is.enes.org), which supports the European climate modeling infrastructure, in the work package 'Bridging Climate Research Data and the Needs of the Impact Community'. The aim of this work package is to enhance the use of climate model data and to enhance the interaction with climate effect/impact communities. The portal is based on 17 impact use cases from 5 different European countries, and is evaluated by a user panel consisting of use case owners. As the climate impact community is very broad, the focus is mainly on the scientific impact community. This work has resulted in a prototype portal, the ENES portal interface for climate impact communities, that can be visited at www.climate4impact.eu. The portal is connected to all Earth System Grid Federation (ESGF) nodes containing global climate model data (GCM data) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and later from the Coordinated Regional Climate Downscaling Experiment (CORDEX). This global network of all major climate model data centers offers services for data description, discovery and download. The climate4impact portal connects to these services and offers a user interface for searching, visualizing and downloading global climate model data and more. A challenging task was to describe the available model data and how it can be used. The portal tries to inform users about possible caveats when using model data. All impact use cases are described in the documentation section, using highlighted keywords pointing to detailed information in the glossary. The current portal is a Prototype. It is built to explore state-of-art technologies to provide improved access to climate model data. The prototype will be evaluated and is the basis for development of an operational service. The portal and services provided will be sustained and supported during the development of these operational services (2013-2016) in the second phase of the FP7 IS-ENES project, ISENES2. In this presentation the architecture and following items will be detailed: • Security: Login using OpenID for access to the ESGF data nodes. The ESGF works in conjunction with several external websites and systems. The portal provides access to several distributed archives, most importantly the ESGF nodes. Single Sign-on (SSO) is used to let these websites and systems work together. • Discovery: Intelligent search based on e.g. variable name, model, institute. A catalog browser allows for browsing through CMIP5 and other climate model data catalogues (e.g. ESSENCE, EOBS, UNIDATA). • Download: Directly from ESGF nodes and other THREDDS catalogs • Visualization: Visualize any data directly on a map (ADAGUC Map services). • Transformation: Transform your data into other formats, perform basic calculations and extractions
Clime: analyzing and producing climate data in GIS environment
NASA Astrophysics Data System (ADS)
Cattaneo, Luigi; Rillo, Valeria; Mercogliano, Paola
2014-05-01
In the last years, Impacts on Soil and Coasts Division (ISC) of CMCC (Euro-Mediterranean Center on Climate Change) had several collaboration experiences with impact communities, including IS-ENES (FP7-INF) and SafeLand (FP7-ENV) projects, which involved a study of landslide risk in Europe, and is currently active in GEMINA (FIRB) and ORIENTGATE (SEE Transnational Cooperation Programme) research projects. As a result, it has brought research activities about different impact of climate changes as flood and landslide hazards, based on climate simulation obtained from the high resolution regional climate models COSMO CLM, developed at CMCC as member of the consortium CLM Assembly. ISC-Capua also collaborates with local institutions interested in atmospherical climate change and also of their impacts on the soil, such as river basin authorities in the Campania region, ARPA Emilia Romagna and ARPA Calabria. Impact models (e.g. hydraulic or stability models) are usually developed in a GIS environment, since they need an accurate territory description, so Clime has been designed to bridge the usually existing gap between climate data - both observed and simulated - gathered from different sources, and impact communities. The main goal of Clime, special purpose Geographic Information System (GIS) software integrated in ESRI ArcGIS Desktop 10, is to easily evaluate multiple climate features and study climate changes over specific geographical domains with their related effects on environment, including impacts on soil. Developed as an add-in tool, this software has been conceived for research activities of ISC Division in order to provide a substantial contribution during post-processing and validation phase. Therefore, it is possible to analyze and compare multiple datasets (observations, climate simulations, etc.) through processes involving statistical functions, percentiles, trends test and evaluation of extreme events with a flexible system of temporal and spatial filtering, and to represent results as maps, temporal and statistic plots (time series, seasonal cycles, PDFs, scatter plots, Taylor diagrams) or Excel tables; in addition, it features bias correction techniques for climate model results. Summarizing, Clime is able to provide users a simple and fast way to retrieve analysis over simulated climate data and observations within any geographical site of interest (provinces, regions, countries, etc.).
Climate Cycles and Forecasts of Cutaneous Leishmaniasis, a Nonstationary Vector-Borne Disease
Chaves, Luis Fernando; Pascual, Mercedes
2006-01-01
Background Cutaneous leishmaniasis (CL) is one of the main emergent diseases in the Americas. As in other vector-transmitted diseases, its transmission is sensitive to the physical environment, but no study has addressed the nonstationary nature of such relationships or the interannual patterns of cycling of the disease. Methods and Findings We studied monthly data, spanning from 1991 to 2001, of CL incidence in Costa Rica using several approaches for nonstationary time series analysis in order to ensure robustness in the description of CL's cycles. Interannual cycles of the disease and the association of these cycles to climate variables were described using frequency and time-frequency techniques for time series analysis. We fitted linear models to the data using climatic predictors, and tested forecasting accuracy for several intervals of time. Forecasts were evaluated using “out of fit” data (i.e., data not used to fit the models). We showed that CL has cycles of approximately 3 y that are coherent with those of temperature and El Niño Southern Oscillation indices (Sea Surface Temperature 4 and Multivariate ENSO Index). Conclusions Linear models using temperature and MEI can predict satisfactorily CL incidence dynamics up to 12 mo ahead, with an accuracy that varies from 72% to 77% depending on prediction time. They clearly outperform simpler models with no climate predictors, a finding that further supports a dynamical link between the disease and climate. PMID:16903778
Topex/Poseidon: A United States/France mission. Oceanography from space: The oceans and climate
NASA Technical Reports Server (NTRS)
1992-01-01
The TOPEX/POSEIDON space mission, sponsored by NASA and France's space agency, the Centre National d'Etudes Spatiales (CNES), will give new observations of the Earth from space to gain a quantitative understanding of the role of ocean currents in climate change. Rising atmospheric concentrations of carbon dioxide and other 'greenhouse gases' produced as a result of human activities could generate a global warming, followed by an associated rise in sea level. The satellite will use radar altimetry to measure sea-surface height and will be tracked by three independent systems to yield accurate topographic maps over the dimensions of entire ocean basins. The satellite data, together with the Tropical Ocean and Global Atmosphere (TOGA) program and the World Ocean Circulation Experiment (WOCE) measurements, will be analyzed by an international scientific team. By merging the satellite observations with TOGA and WOCE findings, the scientists will establish the extensive data base needed for the quantitative description and computer modeling of ocean circulation. The ocean models will eventually be coupled with atmospheric models to lay the foundation for predictions of global climate change.
NASA Astrophysics Data System (ADS)
Williams, C.; Kniveton, D.; Layberry, R.
2009-04-01
It is increasingly accepted that any possible climate change will not only have an influence on mean climate but may also significantly alter climatic variability. A change in the distribution and magnitude of extreme rainfall events (associated with changing variability), such as droughts or flooding, may have a far greater impact on human and natural systems than a changing mean. This issue is of particular importance for environmentally vulnerable regions such as southern Africa. The subcontinent is considered especially vulnerable to and ill-equipped (in terms of adaptation) for extreme events, due to a number of factors including extensive poverty, famine, disease and political instability. Rainfall variability is a function of scale, so high spatial and temporal resolution data are preferred to identify extreme events and accurately predict future variability. In this research, satellite-derived rainfall data are used as a basis for undertaking model experiments using a state-of-the-art climate model, run at both high and low spatial resolution. Once the model's ability to reproduce extremes has been assessed, idealised regions of sea surface temperature (SST) anomalies are used to force the model, with the overall aim of investigating the ways in which SST anomalies influence rainfall extremes over southern Africa. In this paper, a brief overview is given of the authors' research to date, pertaining to southern African rainfall. This covers (i) a description of present-day rainfall variability over southern Africa; (ii) a comparison of model simulated daily rainfall with the satellite-derived dataset; (iii) results from sensitivity testing of the model's domain size; and (iv) results from the idealised SST experiments.
Climate models with delay differential equations
NASA Astrophysics Data System (ADS)
Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M.
2017-11-01
A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.
Climate models with delay differential equations.
Keane, Andrew; Krauskopf, Bernd; Postlethwaite, Claire M
2017-11-01
A fundamental challenge in mathematical modelling is to find a model that embodies the essential underlying physics of a system, while at the same time being simple enough to allow for mathematical analysis. Delay differential equations (DDEs) can often assist in this goal because, in some cases, only the delayed effects of complex processes need to be described and not the processes themselves. This is true for some climate systems, whose dynamics are driven in part by delayed feedback loops associated with transport times of mass or energy from one location of the globe to another. The infinite-dimensional nature of DDEs allows them to be sufficiently complex to reproduce realistic dynamics accurately with a small number of variables and parameters. In this paper, we review how DDEs have been used to model climate systems at a conceptual level. Most studies of DDE climate models have focused on gaining insights into either the global energy balance or the fundamental workings of the El Niño Southern Oscillation (ENSO) system. For example, studies of DDEs have led to proposed mechanisms for the interannual oscillations in sea-surface temperature that is characteristic of ENSO, the irregular behaviour that makes ENSO difficult to forecast and the tendency of El Niño events to occur near Christmas. We also discuss the tools used to analyse such DDE models. In particular, the recent development of continuation software for DDEs makes it possible to explore large regions of parameter space in an efficient manner in order to provide a "global picture" of the possible dynamics. We also point out some directions for future research, including the incorporation of non-constant delays, which we believe could improve the descriptive power of DDE climate models.
NASA Astrophysics Data System (ADS)
Day, Jonathan J.; Tietsche, Steffen; Collins, Mat; Goessling, Helge F.; Guemas, Virginie; Guillory, Anabelle; Hurlin, William J.; Ishii, Masayoshi; Keeley, Sarah P. E.; Matei, Daniela; Msadek, Rym; Sigmond, Michael; Tatebe, Hiroaki; Hawkins, Ed
2016-06-01
Recent decades have seen significant developments in climate prediction capabilities at seasonal-to-interannual timescales. However, until recently the potential of such systems to predict Arctic climate had rarely been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Interannual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to interannual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre), an assessment of Arctic sea ice extent and volume predictability estimates in these models, and an investigation into to what extent predictability is dependent on the initial state. The inclusion of additional models expands the range of sea ice volume and extent predictability estimates, demonstrating that there is model diversity in the potential to make seasonal-to-interannual timescale predictions. We also investigate whether sea ice forecasts started from extreme high and low sea ice initial states exhibit higher levels of potential predictability than forecasts started from close to the models' mean state, and find that the result depends on the metric. Although designed to address Arctic predictability, we describe the archived data here so that others can use this data set to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño-Southern Oscillation.
AmeriFlux US-MRf Mary's River (Fir) site
DOE Office of Scientific and Technical Information (OSTI.GOV)
Law, Bev
This is the AmeriFlux version of the carbon flux data for the site US-MRf Mary's River (Fir) site. Site Description - The Marys River Fir site is part of the "Synthesis of Remote Sensing and Field Observations to Model and Understand Disturbance and Climate Effects on the Carbon Balance of Oregon and Northern California (ORCA)". Located in the western region of Oregon the Marys River site represents the western extent of the climate gradient that spans eastward into the semi-arid basin of central Oregon. The sites that make up the eastern extent of the ORCA climate gradient is the Metoliusmore » site network (US-Me1, US-ME2, US-ME4, US-Me5) all of which are part of the TERRA PNW project at Oregon State University.« less
Impact Disdrometers Instrument Handbook
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bartholomew, Mary Jane
2016-03-01
To improve the quantitative description of precipitation processes in climate models, the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility has been collecting observations of the drop size spectra of rain events since early in 2006. Impact disdrometers were the initial choice due to their reliability, ease of maintenance, and relatively low cost. Each of the two units deployed was accompanied by a nearby tipping bucket. In 2010, the tipping buckets were replaced by weighing buckets rain gauges. Five video disdrometers were subsequently purchased and are described in ARM’s VDIS Handbook.1 As of April 2011, three ofmore » the weighing bucket instruments were deployed, one was to travel with the second ARM Mobile Facility, and the fifth was a spare. Two of the video disdrometers were deployed, a third was to be deployed later in the spring of 2011, one was to travel with the second ARM Mobile Facility, and the last was a spare. Detailed descriptions of impact disdrometers and their datastreams are provided in this document.« less
ERIC Educational Resources Information Center
Barwell, Richard
2013-01-01
Climate change is one of the most pressing issues of the 21st Century. Mathematics is involved at every level of understanding climate change, including the description, prediction and communication of climate change. As a highly complex issue, climate change is an example of "post-normal" science -- it is urgent, complex and involves a…
The Impacts of Climate Change on Human Health in the United States: A Scientific Assessment
This assessment strengthens and expands our understanding of climate-related health impacts by providing a more definitive description of climate-related health burdens in the United States. It builds on the 2014 USGCRP National Climate Assessment and reviews and synthesizes key ...
Demonstrating the climate4impact portal: bridging the CMIP5 data infrastructure to impact users
NASA Astrophysics Data System (ADS)
Plieger, Maarten; Som de Cerff, Wim; Page, Christian; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Sjökvist, Elin
2013-04-01
Together with seven other partners (CERFACS, CNRS-IPSL, SMHI, INHGA, CMCC, WUR, MF-CNRM), KNMI is involved in the FP7 project IS-ENES (http://is.enes.org), which supports the European climate modeling infrastructure, in the work package 'Bridging Climate Research Data and the Needs of the Impact Community'. The aim of this work package is to enhance the use of climate model data and to enhance the interaction with climate effect/impact communities. The portal is based on 17 impact use cases from 5 different European countries, and is evaluated by a user panel consisting of use case owners. As the climate impact community is very broad, the focus is mainly on the scientific impact community. This work has resulted in a prototype portal, the ENES portal interface for climate impact communities, that can be visited at www.climate4impact.eu. The portal is connected to all Earth System Grid Federation (ESGF) nodes containing global climate model data (GCM data) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and later from the Coordinated Regional Climate Downscaling Experiment (CORDEX). This global network of all major climate model data centers offers services for data description, discovery and download. The climate4impact portal connects to these services and offers a user interface for searching, visualizing and downloading global climate model data and more. During the project, the content management system Drupal was used to enable partners to contribute on the documentation section. The following topics will be demonstrated: - Security: Login using OpenID for access to the ESG data nodes. The ESG works in conjunction with several external websites and systems. The climate4impact portal uses X509 based short lived credentials, generated on behalf of the user with a MyProxy service. Single Sign-on (SSO) is used to make these websites and systems work together. - Discovery: Facetted search based on e.g. variable name, model and institute using the ESG search services. A catalog browser allows for browsing through CMIP5 and other climate model data catalogues (e.g. ESSENCE, EOBS, UNIDATA). - Download: Directly from ESG nodes and other THREDDS catalogs - Visualization: Visualize any data directly using ADAGUC dynamic Web Map Services. - Transformation: Transform your data into other formats, perform basic calculations and extractions using OCG Web Processing Services The current portal is a Prototype. It is built to explore state-of-art technologies to provide improved access to climate model data. The prototype will be evaluated and is the basis for development of an operational service. The portal and services provided will be sustained and supported during the development of these operational services (2013-2016) in the second phase of the FP7 IS-ENES project, ISENES2.
The IS-ENES climate4impact portal: bridging the CMIP5 and CORDEX data to impact users
NASA Astrophysics Data System (ADS)
Som de Cerff, Wim; Plieger, Maarten; Page, Christian; Tatarinova, Natalia; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Sjökvist, Elin; Vega Saldarriaga, Manuel; Santiago Cofiño Gonzalez, Antonio
2015-04-01
The aim of climate4impact (climate4impact.eu) is to enhance the use of Climate Research Data and to enhance the interaction with climate effect/impact communities. The portal is based on 17 impact use cases from 5 different European countries, and is evaluated by a user panel consisting of use case owners. It has been developed within the IS-ENES European project and is currently operated and further developed in the IS ENES2 project. As the climate impact community is very broad, the focus is mainly on the scientific impact community. Climate4impact is connected to the Earth System Grid Federation (ESGF) nodes containing global climate model data (GCM data) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and regional climate model data (RCM) data from the Coordinated Regional Climate Downscaling Experiment (CORDEX). This global network of climate model data centers offers services for data description, discovery and download. The climate4impact portal connects to these services using OpenID, and offers a user interface for searching, visualizing and downloading global climate model data and more. A challenging task is to describe the available model data and how it can be used. The portal informs users about possible caveats when using climate model data. All impact use cases are described in the documentation section, using highlighted keywords pointing to detailed information in the glossary. Climate4impact currently has two main objectives. The first one is to work on a web interface which automatically generates a graphical user interface on WPS endpoints. The WPS calculates climate indices and subset data using OpenClimateGIS/icclim on data stored in ESGF data nodes. Data is then transmitted from ESGF nodes over secured OpenDAP and becomes available in a new, per user, secured OpenDAP server. The results can then be visualized again using ADAGUC WMS. Dedicated wizards for processing of climate indices will be developed in close collaboration with users. The second one is to expose climate4impact services, so as to offer standardized services which can be used by other portals (like the future Copernicus platform, developed in the EU FP7 CLIPC project). This has the advantage to add interoperability between several portals, as well as to enable the design of specific portals aimed at different impact communities, either thematic or national. In the presentation the following subjects will be detailed: - Lessons learned developing climate4impact.eu - Download: Directly from ESGF nodes and other THREDDS catalogs - Connection with the downscaling portal of the university of Cantabria - Experiences on the question and answer site via Askbot - Visualization: Visualize data from ESGF data nodes using ADAGUC Web Map Services. - Processing: Transform data, subset, export into other formats, and perform climate indices calculations using Web Processing Services implemented by PyWPS, based on NCAR NCPP OpenClimateGIS and IS-ENES2 icclim. - Security: Login using OpenID for access to the ESGF data nodes. The ESGF works in conjunction with several external websites and systems. The climate4impact portal uses X509 based short lived credentials, generated on behalf of the user with a MyProxy service. Single Sign-on (SSO) is used to make these websites and systems work together. - Discovery: Facetted search based on e.g. variable name, model and institute using the ESGF search services. A catalog browser allows for browsing through CMIP5 and any other climate model data catalogues (e.g. ESSENCE, EOBS, UNIDATA).
The BRIDGE HadCM3 family of climate models: HadCM3@Bristol v1.0
NASA Astrophysics Data System (ADS)
Valdes, Paul J.; Armstrong, Edward; Badger, Marcus P. S.; Bradshaw, Catherine D.; Bragg, Fran; Crucifix, Michel; Davies-Barnard, Taraka; Day, Jonathan J.; Farnsworth, Alex; Gordon, Chris; Hopcroft, Peter O.; Kennedy, Alan T.; Lord, Natalie S.; Lunt, Dan J.; Marzocchi, Alice; Parry, Louise M.; Pope, Vicky; Roberts, William H. G.; Stone, Emma J.; Tourte, Gregory J. L.; Williams, Jonny H. T.
2017-10-01
Understanding natural and anthropogenic climate change processes involves using computational models that represent the main components of the Earth system: the atmosphere, ocean, sea ice, and land surface. These models have become increasingly computationally expensive as resolution is increased and more complex process representations are included. However, to gain robust insight into how climate may respond to a given forcing, and to meaningfully quantify the associated uncertainty, it is often required to use either or both ensemble approaches and very long integrations. For this reason, more computationally efficient models can be very valuable tools. Here we provide a comprehensive overview of the suite of climate models based around the HadCM3 coupled general circulation model. This model was developed at the UK Met Office and has been heavily used during the last 15 years for a range of future (and past) climate change studies, but has now been largely superseded for many scientific studies by more recently developed models. However, it continues to be extensively used by various institutions, including the BRIDGE (Bristol Research Initiative for the Dynamic Global Environment) research group at the University of Bristol, who have made modest adaptations to the base HadCM3 model over time. These adaptations mean that the original documentation is not entirely representative, and several other relatively undocumented configurations are in use. We therefore describe the key features of a number of configurations of the HadCM3 climate model family, which together make up HadCM3@Bristol version 1.0. In order to differentiate variants that have undergone development at BRIDGE, we have introduced the letter B into the model nomenclature. We include descriptions of the atmosphere-only model (HadAM3B), the coupled model with a low-resolution ocean (HadCM3BL), the high-resolution atmosphere-only model (HadAM3BH), and the regional model (HadRM3B). These also include three versions of the land surface scheme. By comparing with observational datasets, we show that these models produce a good representation of many aspects of the climate system, including the land and sea surface temperatures, precipitation, ocean circulation, and vegetation. This evaluation, combined with the relatively fast computational speed (up to 1000 times faster than some CMIP6 models), motivates continued development and scientific use of the HadCM3B family of coupled climate models, predominantly for quantifying uncertainty and for long multi-millennial-scale simulations.
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.
Koivunen, Marita; Anttila, Minna; Kuosmanen, Lauri; Katajisto, Jouko; Välimäki, Maritta
2015-01-01
Objectives: To describe the association of team climate with attitudes toward information and communication technology among nursing staff working on acute psychiatric wards. Background: Implementation of ICT applications in nursing practice brings new operating models to work environments, which may affect experienced team climate on hospital wards. Method: Descriptive survey was used as a study design. Team climate was measured by the Finnish modification of the Team Climate Inventory, and attitudes toward ICT by Burkes' questionnaire. The nursing staff (N = 181, n = 146) on nine acute psychiatric wards participated in the study. Results: It is not self-evident that experienced team climate associates with attitudes toward ICT, but there are some positive relationships between perceived team climate and ICT attitudes. The study showed that nurses' motivation to use ICT had statistically significant connections with experienced team climate, participative safety (p = 0.021), support for innovation (p = 0.042) and task orientation (p = 0.042). Conclusion: The results suggest that asserting team climate and supporting innovative operations may lead to more positive attitudes toward ICT. It is, in particular, possible to influence nurses' motivation to use ICT. More attention should be paid to psychosocial factors such as group education and co-operation at work when ICT applications are implemented in nursing.
The UPSCALE project: a large simulation campaign
NASA Astrophysics Data System (ADS)
Mizielinski, Matthew; Roberts, Malcolm; Vidale, Pier Luigi; Schiemann, Reinhard; Demory, Marie-Estelle; Strachan, Jane
2014-05-01
The development of a traceable hierarchy of HadGEM3 global climate models, based upon the Met Office Unified Model, at resolutions from 135 km to 25 km, now allows the impact of resolution on the mean state, variability and extremes of climate to be studied in a robust fashion. In 2011 we successfully obtained a single-year grant of 144 million core hours of supercomputing time from the PRACE organization to run ensembles of 27 year atmosphere-only (HadGEM3-A GA3.0) climate simulations at 25km resolution, as used in present global weather forecasting, on HERMIT at HLRS. Through 2012 the UPSCALE project (UK on PRACE: weather-resolving Simulations of Climate for globAL Environmental risk) ran over 650 years of simulation at resolutions of 25 km (N512), 60 km (N216) and 135 km (N96) to look at the value of high resolution climate models in the study of both present climate and a potential future climate scenario based on RCP8.5. Over 400 TB of data was produced using HERMIT, with additional simulations run on HECToR (UK supercomputer) and MONSooN (Met Office NERC Supercomputing Node). The data generated was transferred to the JASMIN super-data cluster, hosted by STFC CEDA in the UK, where analysis facilities are allowing rapid scientific exploitation of the data set. Many groups across the UK and Europe are already taking advantage of these facilities and we welcome approaches from other interested scientists. This presentation will briefly cover the following points; Purpose and requirements of the UPSCALE project and facilities used. Technical implementation and hurdles (model porting and optimisation, automation, numerical failures, data transfer). Ensemble specification. Current analysis projects and access to the data set. A full description of UPSCALE and the data set generated has been submitted to Geoscientific Model development, with overview information available from http://proj.badc.rl.ac.uk/upscale .
Changes in Benefits of Flood Protection Standard under Climate Change
NASA Astrophysics Data System (ADS)
Lim, W. H.; Koirala, S.; Yamazaki, D.; Hirabayashi, Y.; Kanae, S.
2014-12-01
Understanding potential risk of river flooding under future climate scenarios might be helpful for developing risk management strategies (including mitigation, adaptation). Such analyses are typically performed at the macro scales (e.g., regional, global) where the climate model output could support (e.g., Hirabayashi et al., 2013, Arnell and Gosling, 2014). To understand the potential benefits of infrastructure upgrading as part of climate adaptation strategies, it is also informative to understand the potential impact of different flood protection standards (in terms of return periods) on global river flooding under climate change. In this study, we use a baseline period (forced by observed hydroclimate conditions) and CMIP5 model output (historic and future periods) to drive a global river routing model called CaMa-Flood (Yamazaki et al., 2011) and simulate the river water depth at a spatial resolution of 15 min x 15 min. From the simulated results of baseline period, we use the annual maxima river water depth to fit the Gumbel distribution and prepare the return period-flood risk relationship (involving population and GDP). From the simulated results of CMIP5 model, we also used the annual maxima river water depth to obtain the Gumbel distribution and then estimate the exceedance probability (historic and future periods). We apply the return period-flood risk relationship (above) to the exceedance probability and evaluate the potential risk of river flooding and changes in the benefits of flood protection standard (e.g., 100-year flood of the baseline period) from the past into the future (represented by the representative concentration pathways). In this presentation, we show our preliminary results. References: Arnell, N.W, Gosling, S., N., 2014. The impact of climate change on river flood risk at the global scale. Climatic Change 122: 127-140, doi: 10.1007/s10584-014-1084-5. Hirabayashi et al., 2013. Global flood risk under climate change. Nature Climate Change 3: 816-821, doi: 10.1038/nclimate1911. Yamazaki et al., 2011. A physically based description of floodplain inundation dynamics in a global river routing model. Water Resources Research 47, W04501, doi: 10.1029/2010wr009726.
Stochastic soil water balance under seasonal climates
Feng, Xue; Porporato, Amilcare; Rodriguez-Iturbe, Ignacio
2015-01-01
The analysis of soil water partitioning in seasonally dry climates necessarily requires careful consideration of the periodic climatic forcing at the intra-annual timescale in addition to daily scale variabilities. Here, we introduce three new extensions to a stochastic soil moisture model which yields seasonal evolution of soil moisture and relevant hydrological fluxes. These approximations allow seasonal climatic forcings (e.g. rainfall and potential evapotranspiration) to be fully resolved, extending the analysis of soil water partitioning to account explicitly for the seasonal amplitude and the phase difference between the climatic forcings. The results provide accurate descriptions of probabilistic soil moisture dynamics under seasonal climates without requiring extensive numerical simulations. We also find that the transfer of soil moisture between the wet to the dry season is responsible for hysteresis in the hydrological response, showing asymmetrical trajectories in the mean soil moisture and in the transient Budyko's curves during the ‘dry-down‘ versus the ‘rewetting‘ phases of the year. Furthermore, in some dry climates where rainfall and potential evapotranspiration are in-phase, annual evapotranspiration can be shown to increase because of inter-seasonal soil moisture transfer, highlighting the importance of soil water storage in the seasonal context. PMID:25663808
NASA Astrophysics Data System (ADS)
Li, Qiaoling; Ishidaira, Hiroshi
2012-01-01
SummaryThe biosphere and hydrosphere are intrinsically coupled. The scientific question is if there is a substantial change in one component such as vegetation cover, how will the other components such as transpiration and runoff generation respond, especially under climate change conditions? Stand-alone hydrological models have a detailed description of hydrological processes but do not sufficiently parameterize vegetation as a dynamic component. Dynamic global vegetation models (DGVMs) are able to simulate transient structural changes in major vegetation types but do not simulate runoff generation reliably. Therefore, both hydrological models and DGVMs have their limitations as well as advantages for addressing this question. In this study a biosphere hydrological model (LPJH) is developed by coupling a prominent DGVM (Lund-Postdam-Jena model referred to as LPJ) with a stand-alone hydrological model (HYMOD), with the objective of analyzing the role of vegetation in the hydrological processes at basin scale and evaluating the impact of vegetation change on the hydrological processes under climate change. The application and validation of the LPJH model to four basins representing a variety of climate and vegetation conditions shows that the performance of LPJH is much better than that of the original LPJ and is similar to that of stand-alone hydrological models for monthly and daily runoff simulation at the basin scale. It is argued that the LPJH model gives more reasonable hydrological simulation since it considers both the spatial variability of soil moisture and vegetation dynamics, which make the runoff generation mechanism more reliable. As an example, it is shown that changing atmospheric CO 2 content alone would result in runoff increases in humid basins and decreases in arid basins. Theses changes are mainly attributable to changes in transpiration driven by vegetation dynamics, which are not simulated in stand-alone hydrological models. Therefore LPJH potentially provides a powerful tool for simulating vegetation response to climate changes in the biosphere hydrological cycle.
A Safer Place? LGBT Educators, School Climate, and Implications for Administrators
ERIC Educational Resources Information Center
Wright, Tiffany E.; Smith, Nancy J.
2015-01-01
Over an 8-year span, two survey studies were conducted to analyze LGBT -teachers' perceptions of their school climate and the impact of school leaders on that climate. This article presents nonparametric, descriptive, and qualitative results of the National Survey of Educators' Perceptions of School Climate 2011 compared with survey results from…
Climate of Priest River Experimental Forest, northern Idaho
Arnold I. Finklin
1983-01-01
Detailed climatic description of Priest River Experimental Forest; applies to much of the northern Idaho panhandle. Covers year-round pattern and focuses on the fire season. Topographic and local site differences in climate are examined; also, climatic trends or fluctuations during the past 70 years. Includes numerous tables and graphs. Written particularly for forest...
Assessing School and Classroom Climate. A Consumer's Guide.
ERIC Educational Resources Information Center
Arter, Judith A.
School and classroom climate is often cited in effective schools research as being important for student achievement. This consumer guide is intended to help educators evaluate their own educational climate by providing reviews and descriptions of the major tests and surveys used to assess climate. Section 2 presents reasons for examining school…
The climate4impact portal: bridging the CMIP5 data infrastructure to impact users
NASA Astrophysics Data System (ADS)
Plieger, Maarten; Som de Cerff, Wim; Page, Christian; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Sjökvist, Elin
2013-04-01
Together with seven other partners (CERFACS, CNRS-IPSL, SMHI, INHGA, CMCC, WUR, MF-CNRM), KNMI is involved in the FP7 project IS-ENES (http://is.enes.org), which supports the European climate modeling infrastructure, in the work package 'Bridging Climate Research Data and the Needs of the Impact Community'. The aim of this work package is to enhance the use of climate model data and to enhance the interaction with climate effect/impact communities. The portal is based on 17 impact use cases from 5 different European countries, and is evaluated by a user panel consisting of use case owners. As the climate impact community is very broad, the focus is mainly on the scientific impact community. This work has resulted in a prototype portal, the ENES portal interface for climate impact communities, that can be visited at www.climate4impact.eu. The portal is connected to all Earth System Grid Federation (ESGF) nodes containing global climate model data (GCM data) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and later from the Coordinated Regional Climate Downscaling Experiment (CORDEX). This global network of all major climate model data centers offers services for data description, discovery and download. The climate4impact portal connects to these services and offers a user interface for searching, visualizing and downloading global climate model data and more. A challenging task was to describe the available model data and how it can be used. The portal tries to inform users about possible caveats when using GCM data. All impact use cases are described in the documentation section, using highlighted keywords pointing to detailed information in the glossary. During the project, the content management system Drupal was used to enable partners to contribute on the documentation section. In this presentation the architecture and following items will be detailed: - Security: Login using OpenID for access to the ESG data nodes. The ESG works in conjunction with several external websites and systems. The climate4impact portal uses X509 based short lived credentials, generated on behalf of the user with a MyProxy service. Single Sign-on (SSO) is used to make these websites and systems work together. - Discovery: Facetted search based on e.g. variable name, model and institute using the ESG search services. A catalog browser allows for browsing through CMIP5 and other climate model data catalogues (e.g. ESSENCE, EOBS, UNIDATA). - Download: Directly from ESG nodes and other THREDDS catalogs - Visualization: Visualize any data directly using ADAGUC dynamic Web Map Services. - Transformation: Transform your data into other formats, perform basic calculations and extractions using OCG Web Processing Services The current portal is a Prototype. It is built to explore state-of-art technologies to provide improved access to climate model data. The prototype will be evaluated and is the basis for development of an operational service. The portal and services provided will be sustained and supported during the development of these operational services (2013-2016) in the second phase of the FP7 IS-ENES project, ISENES2.
NASA Astrophysics Data System (ADS)
Migliavacca, M.; Sonnentag, O.; Keenan, T. F.; Cescatti, A.; O'Keefe, J.; Richardson, A. D.
2012-01-01
Phenology, the timing of recurring life cycle events, controls numerous land surface feedbacks to the climate systems through the regulation of exchanges of carbon, water and energy between the biosphere and atmosphere. Land surface models, however, are known to have systematic errors in the simulation of spring phenology, which potentially could propagate to uncertainty in modeled responses to future climate change. Here, we analyzed the Harvard Forest phenology record to investigate and characterize the sources of uncertainty in phenological forecasts and the subsequent impacts on model forecasts of carbon and water cycling in the future. Using a model-data fusion approach, we combined information from 20 yr of phenological observations of 11 North American woody species with 12 phenological models of different complexity to predict leaf bud-burst. The evaluation of different phenological models indicated support for spring warming models with photoperiod limitations and, though to a lesser extent, to chilling models based on the alternating model structure. We assessed three different sources of uncertainty in phenological forecasts: parameter uncertainty, model uncertainty, and driver uncertainty. The latter was characterized running the models to 2099 using 2 different IPCC climate scenarios (A1fi vs. B1, i.e. high CO2 emissions vs. low CO2 emissions scenario). Parameter uncertainty was the smallest (average 95% CI: 2.4 day century-1 for scenario B1 and 4.5 day century-1 for A1fi), whereas driver uncertainty was the largest (up to 8.4 day century-1 in the simulated trends). The uncertainty related to model structure is also large and the predicted bud-burst trends as well as the shape of the smoothed projections varied somewhat among models (±7.7 day century-1 for A1fi, ±3.6 day century-1 for B1). The forecast sensitivity of bud-burst to temperature (i.e. days bud-burst advanced per degree of warming) varied between 2.2 day °C-1 and 5.2 day °C-1 depending on model structure. We quantified the impact of uncertainties in bud-burst forecasts on simulated carbon and water fluxes using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of the seasonality of processes, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP) and evapotranspiration (ET) of 9.6% and 2.9% respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±2.0% for ET. For phenology models, differences among future climate scenarios represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, uncertainties related to model parameterization. The uncertainties we have quantified will affect the description of the seasonality of processes and in particular the simulation of carbon uptake by forest ecosystems, with a larger impact of uncertainties related to phenology model structure, followed by uncertainties related to phenological model parameterization.
Changes in crop yields and their variability at different levels of global warming
NASA Astrophysics Data System (ADS)
Ostberg, Sebastian; Schewe, Jacob; Childers, Katelin; Frieler, Katja
2018-05-01
An assessment of climate change impacts at different levels of global warming is crucial to inform the policy discussion about mitigation targets, as well as for the economic evaluation of climate change impacts. Integrated assessment models often use global mean temperature change (ΔGMT) as a sole measure of climate change and, therefore, need to describe impacts as a function of ΔGMT. There is already a well-established framework for the scalability of regional temperature and precipitation changes with ΔGMT. It is less clear to what extent more complex biological or physiological impacts such as crop yield changes can also be described in terms of ΔGMT, even though such impacts may often be more directly relevant for human livelihoods than changes in the physical climate. Here we show that crop yield projections can indeed be described in terms of ΔGMT to a large extent, allowing for a fast estimation of crop yield changes for emissions scenarios not originally covered by climate and crop model projections. We use an ensemble of global gridded crop model simulations for the four major staple crops to show that the scenario dependence is a minor component of the overall variance of projected yield changes at different levels of ΔGMT. In contrast, the variance is dominated by the spread across crop models. Varying CO2 concentrations are shown to explain only a minor component of crop yield variability at different levels of global warming. In addition, we find that the variability in crop yields is expected to increase with increasing warming in many world regions. We provide, for each crop model, geographical patterns of mean yield changes that allow for a simplified description of yield changes under arbitrary pathways of global mean temperature and CO2 changes, without the need for additional climate and crop model simulations.
NASA Astrophysics Data System (ADS)
Migliavacca, M.; Sonnentag, O.; Keenan, T. F.; Cescatti, A.; O'Keefe, J.; Richardson, A. D.
2012-06-01
Phenology, the timing of recurring life cycle events, controls numerous land surface feedbacks to the climate system through the regulation of exchanges of carbon, water and energy between the biosphere and atmosphere. Terrestrial biosphere models, however, are known to have systematic errors in the simulation of spring phenology, which potentially could propagate to uncertainty in modeled responses to future climate change. Here, we used the Harvard Forest phenology record to investigate and characterize sources of uncertainty in predicting phenology, and the subsequent impacts on model forecasts of carbon and water cycling. Using a model-data fusion approach, we combined information from 20 yr of phenological observations of 11 North American woody species, with 12 leaf bud-burst models that varied in complexity. Akaike's Information Criterion indicated support for spring warming models with photoperiod limitations and, to a lesser extent, models that included chilling requirements. We assessed three different sources of uncertainty in phenological forecasts: parameter uncertainty, model uncertainty, and driver uncertainty. The latter was characterized running the models to 2099 using 2 different IPCC climate scenarios (A1fi vs. B1, i.e. high CO2 emissions vs. low CO2 emissions scenario). Parameter uncertainty was the smallest (average 95% Confidence Interval - CI: 2.4 days century-1 for scenario B1 and 4.5 days century-1 for A1fi), whereas driver uncertainty was the largest (up to 8.4 days century-1 in the simulated trends). The uncertainty related to model structure is also large and the predicted bud-burst trends as well as the shape of the smoothed projections varied among models (±7.7 days century-1 for A1fi, ±3.6 days century-1 for B1). The forecast sensitivity of bud-burst to temperature (i.e. days bud-burst advanced per degree of warming) varied between 2.2 days °C-1 and 5.2 days °C-1 depending on model structure. We quantified the impact of uncertainties in bud-burst forecasts on simulated photosynthetic CO2 uptake and evapotranspiration (ET) using a process-based terrestrial biosphere model. Uncertainty in phenology model structure led to uncertainty in the description of forest seasonality, which accumulated to uncertainty in annual model estimates of gross primary productivity (GPP) and ET of 9.6% and 2.9%, respectively. A sensitivity analysis shows that a variation of ±10 days in bud-burst dates led to a variation of ±5.0% for annual GPP and about ±2.0% for ET. For phenology models, differences among future climate scenarios (i.e. driver) represent the largest source of uncertainty, followed by uncertainties related to model structure, and finally, related to model parameterization. The uncertainties we have quantified will affect the description of the seasonality of ecosystem processes and in particular the simulation of carbon uptake by forest ecosystems, with a larger impact of uncertainties related to phenology model structure, followed by uncertainties related to phenological model parameterization.
Eyring, Veronika; Bony, Sandrine; Meehl, Gerald A.; ...
2016-05-26
By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) andmore » CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.« less
Wetland methane modelling over the Scandinavian Arctic: Performance of current land-surface models
NASA Astrophysics Data System (ADS)
Hayman, Garry; Quiquet, Aurélien; Gedney, Nicola; Clark, Douglas; Friend, Andrew; George, Charles; Prigent, Catherine
2014-05-01
Wetlands are generally accepted as being the largest, but least well quantified, single natural source of CH4, with global emission estimates ranging from 100-231 Tg yr-1 [1] and for which the Boreal and Arctic regions make a significant contribution [2, 3]. The recent review by Melton et al. [4] has provided a summary of the current state of knowledge on the modelling of wetlands and the outcome of the WETCHIMP model intercomparison exercise. Melton et al. found a large variation in the wetland areas and associated methane emissions from the participating models and varying responses to climate change. In this paper, we report results from offline runs of two land surface models over Scandinavia (JULES, the Joint UK Land Environment Simulator [5, 6] and HYBRID8 [7]), using the same driving meteorological dataset (CRU-NCEP) for the period from January 1980 to December 2010. Although the two land surface models are very different, both models have used a TOPMODEL approach to derive the wetland area and have similar parameterisations of the methane wetland emissions. We find that both models give broadly similar results. They underestimate the wetland areas over Northern Scandinavia, compared to remote sensing and map-based datasets of wetlands [8]. This leads to lower predicted methane emissions compared to those observed on the ground and from aircraft [9]. We will present these findings and identify possible reasons for the underprediction. We will show the sensitivity to using the observed wetland areas to improve the methane emission estimates. References [1] Denman, K., et al.,: Couplings Between Changes in the Climate System and Biogeochemistry, In Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Cambridge University Press, United Kingdom, 2007; [2] Smith, L. C., et al.: Siberian peatlands a net carbon sink and global methane source since the early Holocene, Science, 303, 353-356, doi:10.1126/science.1090553, 2004; [3] Zhuang, Q., et al.: CO2 and CH4 exchanges between land ecosystems and the atmosphere in northern high latitudes over the 21st century, Geophysical Research Letters, 33, doi:10.1029/2006gl026972, 2006; [4] Melton, J.R., et al.: Present state of global wetland extent and wetland methane modelling: conclusions from a model inter-comparison project (WETCHIMP), Biogeosciences, 10, 753-788, doi:10.5194/bg-10-753-2013, 2013; [5] Best, M. J., et al.: The Joint UK Land Environment Simulator (JULES), model description - Part 1: Energy and water fluxes, Geoscientific Model Development, 4, 677-699, doi:10.5194/gmd-4-677-2011, 2011; [6] Clark, D.B., et al.: The Joint UK Land Environment Simulator (JULES), Model description - Part 2: Carbon fluxes and vegetation. Geoscientific Model Development, 4, 701-722, doi:10.5194/gmd-4-701-2011, 2011; [7] Friend, A.D., and N.Y. Kiang: Land surface model development for the GISS GCM: Effects of improved canopy physiology on simulated climate. J. Climate, 18, 2883-2902, doi:10.1175/JCLI3425.1, 2005; [8] Prigent, C., et al.: Changes in land surface water dynamics since the 1990s and relation to population pressure, Geophys. Res. Lett., 39, L08403, doi:10.1029/2012GL051276, 2012; [9] O'Shea, S., et al.: Methane and carbon dioxide fluxes from the European Arctic wetlands during the MAMM project, paper in preparation.
Nurses' perception of ethical climate and organizational commitment.
Borhani, Fariba; Jalali, Tayebe; Abbaszadeh, Abbas; Haghdoost, Aliakbar
2014-05-01
The high turnover of nurses has become a universal issue. The manner in which nurses view their organization's ethical climate has direct bearing on their organizational commitment. The aim of this study was to determine the correlation between nurses' perception of ethical climate and organizational commitment in teaching hospitals in the southeastern region of Iran. A descriptive analytical design was used in this study. The sample consisted of 275 nurses working in four teaching hospitals in the southeastern region of Iran. The instruments used in this study included a demographic questionnaire, Ethical Climate Questionnaire, and Organizational Commitment Questionnaire. Data analysis was carried out using Pearson's correlation, t-test, and descriptive statistic through Statistical Package for Social Science, version 16. The result of this research indicated a positive correlation among professionalism, caring, rules, independence climate, and organizational commitment. Therefore, findings of this study are a guideline for researchers and managers alike who endeavor to improve organizational commitment.
LUCHS - an approach to introduce Land Use Changes in a regional climate models by using EO data
NASA Astrophysics Data System (ADS)
Preuschmann, S.; Jacob, D.
2012-04-01
Changes in the albedo are influencing climate simulations, which is shown by the results of e.g.: Pongratz et al. (2009), Preuschmann and Jacob (2008), Rechid and Jacob (2006), Vamborg et al. (2011). To investigate the land atmosphere interaction for regional aspects, the lower boundary description for climate models should be able to represent a realistic seasonal cycle of the physical attributed parameters, as albedo, Leaf Area Index and vegetation ratio. The description of the lower boundary for the REgional MOdel REMO has discrepancies for the albedo seasonal cycle. In comparison to satellite observation data, the amplitude and phase of the albedo climatology are showing a too homogeneous pattern. Additionally in case of land use change studies, the parametrization scheme is mixing different constant data sets. Changes in one of them can lead to unexpected values. These aspects are demanding a new approach instead of an adaptation of representing the lower boundary for REMO. A new approach called Land Use CHaracter Shifts (LUCHS), combines techniques of remote sensing techniques and climate modelling techniques. Land cover maps derived from satellite data, are used to get information for each land cover type. Therefore a characteristic albedo climatology gets extracted for every land cover type, which reflects exactly the regional dependent amplitude, phase and level of the seasonal albedo cycle. The extracted information is used as a master information. It is transferalbe onto areas, which are defined as extension areas. To keep regional specific conditions, an autochthonous information is integrated within the character shifting method. It results in a albedo distribution, which reflects characteristics of the transferred land cover type, and accounts implicitly to regional floral, soil and cultural specifications. LUCHS is not free of assumptions and uncertainties, but by using observations, it is reflects a realistic albedo. The observed information on characteristics is regionally specific but persistent in time. Therefore it is transferable through space and at least for ±50 years in time. Pongratz, J., T. Raddatz, C. H. Reick, M. Esch and M. Claussen (2009). Radiative forcing from anthropogenic land cover change since AD 800. Geophysical Research Letters, 36, L02709. Vamborg, F. S. E., V. Brovkin and M. Claussen (2011). The effect of a dynamic background albedo scheme on Sahel/Sahara precipitation during the mid-Holocene. Climate Of The Past, 7(1), 117-131. Preuschmann, S. and D. Jacob (2008). Sensitivity study for parameterization of woods in the regional climate model REMO. In Geophysical Research Abstracts, Vol. 10, EGU2008-A-08618, 2008 SRef-ID: 1607-7962/gra/EGU2008-A-08618 EGU General Assembly 2008.
Institutional Transformation 2.5 Building Module Help Manual.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Villa, Daniel
The Institutional Transformation (IX) building module is a software tool developed at Sandia National Laboratories to evaluate energy conservation measures (ECMs) on hundreds of DOE-2 building energy models simultaneously. In IX, ECMs can be designed through parameterizing DOE-2 building models and doing further processing via visual basic for applications subroutines. IX provides the functionality to handle multiple building models for different years, which enables incrementally changing a site of hundreds of buildings over time. It also enables evaluation of the effects of changing climate, comparisons between data and modeling results, and energy use of centralized utility buildings (CUBs). IX consistsmore » of a Microsoft Excel(r) user interface, Microsoft Access(r) database, and Microsoft Excel(r) CUB build utility whose functionalities are described in detail in this report. In addition to descriptions of the user interfaces, descriptions of every ECM already designed in IX is included. SAND2016-8983 IX 2.5 Help Manual« less
Future projection of design storms using a GCM-informed weather generator
NASA Astrophysics Data System (ADS)
KIm, T. W.; Wi, S.; Valdés-Pineda, R.; Valdés, J. B.
2017-12-01
The rainfall Intensity-Duration-Frequency (IDF) curves are one of the most common tools used to provide planners with a description of the frequency of extreme rainfall events of various intensities and durations. Therefore deriving appropriate IDF estimates is important to avoid malfunctions of water structures that cause huge damage. Evaluating IDF estimates in the context of climate change has become more important because projections from climate models suggest that the frequency of intense rainfall events will increase in the future due to the increase in greenhouse gas emissions. In this study, the Bartlett-Lewis (BL) stochastic rainfall model is employed to generate annual maximum series of various sub-daily durations for test basins of the Model Parameter Estimation Experiment (MOPEX) project, and to derive the IDF curves in the context of climate changes projected by the North American Regional Climate Change (NARCCAP) models. From our results, it has been found that the observed annual rainfall maximum series is reasonably represented by the synthetic annual maximum series generated by the BL model. The observed data is perturbed by change factors to incorporate the NARCCAP climate change scenarios into the IDF estimates. The future IDF curves show a significant difference from the historical IDF curves calculated for the period 1968-2000. Overall, the projected IDF curves show an increasing trend over time. The impacts of changes in extreme rainfall on the hydrologic response of the MOPEX basins are also explored. Acknowledgement: This research was supported by a grant [MPSS-NH-2015-79] through the Disaster and Safety Management Institute funded by Ministry of Public Safety and Security of Korean government.
If We Can't Predict Solar Cycle 24, What About Solar Cycle 34?
NASA Technical Reports Server (NTRS)
Pesnell. William Dean
2008-01-01
Predictions of solar activity in Solar Cycle 24 range from 50% larger than SC 23 to the onset of a Grand Minimum. Because low levels of solar activity are associated with global cooling in paleoclimate and isotopic records, anticipating these extremes is required in any longterm extrapolation of climate variability. Climate models often look forward 100 or more years, which would mean 10 solar cycles into the future. Predictions of solar activity are derived from a number of methods, most of which, such as climatology and physics-based models, will be familiar to atmospheric scientists. More than 50 predictions of the maximum amplitude of SC 24 published before solar minimum will be discussed. Descriptions of several methods that result in the extreme predictions and some anticipation of even longer term predictions will be presented.
NASA Astrophysics Data System (ADS)
Barbosa, A.; Robertson, W. H.
2013-12-01
In the 2012, the National Research Council (NRC) of the National Academies' reported that one of the major issues associated with the development of climate change curriculum was the lack of interdisciplinary materials that also promoted a correlation between science standards and content. Therefore, in order to respond to this need, our group has developed an interdisciplinary climate change curriculum that has had as its fundamental basis the alignment with the guidelines presented by the Next Generation Science Standards (NGSS) and the ones presented by the international document entitled The Earth Charter. In this regards, while the alignment with NGSS disciplinary core ideas, cross-concepts and students' expectations intended to fulfill the need for the development of climate change curriculum activities that were directly associated with the appropriate set of NGSS guidelines, the alignment with The Earth Charter document intended to reinforce the need the for the integration of sociological, philosophical and intercultural analysis of the theme 'climate change'. Additionally, our curriculum was also developed as part of a collaborative project between climate scientists and engineers, who are responsible for the development of a Regional Arctic Simulation Model (RASM). Hence, another important curriculum constituent was the feedback, suggestions and reviews provided by these professionals, who have also contributed to these pedagogical materials' scientific accuracy by facilitating the integration of datasets and visualizations developed by RASM. Furthermore, our group has developed a climate change curriculum for two types of audience: high school and early undergraduate students. Each curriculum unit is divided into modules and each module contains a set of lesson plans. The topics selected to compose each unit and module were designated according to the surveys conducted with scientists and engineers involved with the development of the climate change simulation model. Inside each module, we have provided a description of the general topic being addressed, the appropriate grade levels, students' required prior knowledge, the correspondent NGSS topics, disciplinary core ideas and students' performance expectations, purpose of the activities, and lesson plan activities. Each lesson plan activity is composed by the following: an introductory text that aims at explaining the topic, activities description (classroom tasks and optional classroom activities), time frame, materials, assessment, additional readings and online resources (scientific journals, online simulation models, and books). Each module presents activities and discussions that incorporate historical, philosophical, sociological and/or scientific perspectives on the topics being addressed. Moreover, the activities and lesson plans designed to compose our curriculum have the potential of being used either individually or together, according to the teacher and topic of interest, at the same time that each unit can also be used as a full semester course.
NASA Astrophysics Data System (ADS)
Yarker, M. B.; Stanier, C. O.; Forbes, C.; Park, S.
2011-12-01
As atmospheric scientists, we depend on Numerical Weather Prediction (NWP) models. We use them to predict weather patterns, to understand external forcing on the atmosphere, and as evidence to make claims about atmospheric phenomenon. Therefore, it is important that we adequately prepare atmospheric science students to use computer models. However, the public should also be aware of what models are in order to understand scientific claims about atmospheric issues, such as climate change. Although familiar with weather forecasts on television and the Internet, the general public does not understand the process of using computer models to generate a weather and climate forecasts. As a result, the public often misunderstands claims scientists make about their daily weather as well as the state of climate change. Since computer models are the best method we have to forecast the future of our climate, scientific models and modeling should be a topic covered in K-12 classrooms as part of a comprehensive science curriculum. According to the National Science Education Standards, teachers are encouraged to science models into the classroom as a way to aid in the understanding of the nature of science. However, there is very little description of what constitutes a science model, so the term is often associated with scale models. Therefore, teachers often use drawings or scale representations of physical entities, such as DNA, the solar system, or bacteria. In other words, models used in classrooms are often used as visual representations, but the purpose of science models is often overlooked. The implementation of a model-based curriculum in the science classroom can be an effective way to prepare students to think critically, problem solve, and make informed decisions as a contributing member of society. However, there are few resources available to help teachers implement science models into the science curriculum effectively. Therefore, this research project looks at strategies middle school science teachers use to implement science models into their classrooms. These teachers in this study took part in a week-long professional development designed to orient them towards appropriate use of science models for a unit on weather, climate, and energy concepts. The goal of this project is to describe the professional development and describe how teachers intend to incorporate science models into each of their individual classrooms.
NASA Technical Reports Server (NTRS)
Claverie, Martin; Matthews, Jessica L.; Vermote, Eric F.; Justice, Christopher O.
2016-01-01
In- land surface models, which are used to evaluate the role of vegetation in the context ofglobal climate change and variability, LAI and FAPAR play a key role, specifically with respect to thecarbon and water cycles. The AVHRR-based LAIFAPAR dataset offers daily temporal resolution,an improvement over previous products. This climate data record is based on a carefully calibratedand corrected land surface reflectance dataset to provide a high-quality, consistent time-series suitablefor climate studies. It spans from mid-1981 to the present. Further, this operational dataset is availablein near real-time allowing use for monitoring purposes. The algorithm relies on artificial neuralnetworks calibrated using the MODIS LAI/FAPAR dataset. Evaluation based on cross-comparisonwith MODIS products and in situ data show the dataset is consistent and reliable with overalluncertainties of 1.03 and 0.15 for LAI and FAPAR, respectively. However, a clear saturation effect isobserved in the broadleaf forest biomes with high LAI (greater than 4.5) and FAPAR (greater than 0.8) values.
Quantifying the abundance of co-occurring conifers along Inland Northwest (USA) climate gradients.
Rehfeldt, Gerald E; Ferguson, Dennis E; Crookston, Nicholas L
2008-08-01
The occurrence and abundance of conifers along climate gradients in the Inland Northwest (USA) was assessed using data from 5082 field plots, 81% of which were forested. Analyses using the Random Forests classification tree revealed that the sequential distribution of species along an altitudinal gradient could be predicted with reasonable accuracy from a single climate variable, a growing-season dryness index, calculated from the ratio of degree-days >5 degrees C that accumulate in the frost-free season to the summer precipitation. While the appearance and departure of species in an ascending altitudinal sequence were closely related to the dryness index, the departure was most easily visualized in relation to negative degree-days (degree-days < 0 degrees C). The results were in close agreement with the works of descriptive ecologists. A Weibull response function was used to predict from climate variables the abundance and occurrence probabilities of each species, using binned data. The fit of the models was excellent, generally accounting for >90% of the variance among 100 classes.
NASA Astrophysics Data System (ADS)
Behrens, Jörg; Hanke, Moritz; Jahns, Thomas
2014-05-01
In this talk we present a way to facilitate efficient use of MPI communication for developers of climate models. Exploitation of the performance potential of today's highly parallel supercomputers with real world simulations is a complex task. This is partly caused by the low level nature of the MPI communication library which is the dominant communication tool at least for inter-node communication. In order to manage the complexity of the task, climate simulations with non-trivial communication patterns often use an internal abstraction layer above MPI without exploiting the benefits of communication aggregation or MPI-datatypes. The solution for the complexity and performance problem we propose is the communication library YAXT. This library is built on top of MPI and takes high level descriptions of arbitrary domain decompositions and automatically derives an efficient collective data exchange. Several exchanges can be aggregated in order to reduce latency costs. Examples are given which demonstrate the simplicity and the performance gains for selected climate applications.
Thermosphere Extension of the Whole Atmosphere Community Climate Model
2010-12-04
tropospheric ozone and related tracers: Description and evaluation of MOZART, version 2, J. Geophys. Res., 108(D24), 4784, doi:10.1029/2002JD002853. Immel, T... troposphere to the upper thermosphere and their variability on interannual, seasonal, and daily scales. These quantities are compared with observational and...gravity waves are excited by tropospheric processes. As their amplitudes grow exponen- tially with altitude, they will cause larger variability
DOE Office of Scientific and Technical Information (OSTI.GOV)
Eyring, Veronika; Bony, Sandrine; Meehl, Gerald A.
By coordinating the design and distribution of global climate model simulations of the past, current, and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima) andmore » CMIP historical simulations (1850–near present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP; (2) common standards, coordination, infrastructure, and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble; and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and CMIP historical simulations to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP historical simulations, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. Participation in CMIP6-Endorsed MIPs by individual modelling groups will be at their own discretion and will depend on their scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: – How does the Earth system respond to forcing? – What are the origins and consequences of systematic model biases? – How can we assess future climate changes given internal climate variability, predictability, and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and CMIP6 historical simulations, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.« less
Tackling extremes: challenges for ecological and evolutionary research on extreme climatic events.
Bailey, Liam D; van de Pol, Martijn
2016-01-01
Extreme climatic events (ECEs) are predicted to become more frequent as the climate changes. A rapidly increasing number of studies - though few on animals - suggest that the biological consequences of ECEs can be severe. However, ecological research on the impacts of ECEs has been limited by a lack of cohesiveness and structure. ECEs are often poorly defined and have often been confusingly equated with climatic variability, making comparison between studies difficult. In addition, a focus on short-term studies has provided us with little information on the long-term implications of ECEs, and the descriptive and anecdotal nature of many studies has meant it is still unclear what the key research questions are. Synthesizing the current state of work is essential to identify ways to make progress. We conduct a synthesis of the literature and discuss conceptual and practical challenges faced by research on ECEs. We consider three steps to advance research. First, we discuss the importance of choosing an ECE definition and identify the pros and cons of 'climatological' and 'biological' definitions of ECEs. Secondly, we advocate research beyond short-term descriptive studies to address questions concerning the long-term implications of ECEs, focussing on selective pressures and phenotypically plastic responses and how they might differ from responses to a changing climatic mean. Finally, we encourage a greater focus on multi-event studies that help us understand the implications of changing patterns of ECEs, through the combined use of modelling, experimental and observational field studies. This study aims to open a discussion on the definitions, questions and methods currently used to study ECEs, which will lead to a more cohesive approach to future ECE research. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.
Description of Changes in Climatic Indices in USA over 25 Years (1989 – 2013)
The spatial distribution of long-term changes in climatic factors and its relation with vegetation cover, human health, hydrology and many other ecosystem processes help to identify the consequences of climatic factors changes. In recent studies, the significant changes of select...
NASA Technical Reports Server (NTRS)
Elshorbany, Yasin F.; Duncan, Bryan N.; Strode, Sarah A.; Wang, James S.; Kouatchou, Jules
2015-01-01
We present the Efficient CH4-CO-OH Module (ECCOH) that allows for the simulation of the methane, carbon monoxide and hydroxyl radical (CH4-CO-OH cycle, within a chemistry climate model, carbon cycle model, or earth system model. The computational efficiency of the module allows many multi-decadal, sensitivity simulations of the CH4-CO-OH cycle, which primarily determines the global tropospheric oxidizing capacity. This capability is important for capturing the nonlinear feedbacks of the CH4-CO-OH system and understanding the perturbations to relatively long-lived methane and the concomitant impacts on climate. We implemented the ECCOH module into the NASA GEOS-5 Atmospheric Global Circulation Model (AGCM), performed multiple sensitivity simulations of the CH4-CO-OH system over two decades, and evaluated the model output with surface and satellite datasets of methane and CO. The favorable comparison of output from the ECCOH module (as configured in the GEOS-5 AGCM) with observations demonstrates the fidelity of the module for use in scientific research.
NASA Technical Reports Server (NTRS)
Elshorbany, Yasin F.; Duncan, Bryan N.; Strode, Sarah A.; Wang, James S.; Kouatchou, Jules
2016-01-01
We present the Efficient CH4-CO-OH (ECCOH) chemistry module that allows for the simulation of the methane, carbon monoxide, and hydroxyl radical (CH4-CO- OH) system, within a chemistry climate model, carbon cycle model, or Earth system model. The computational efficiency of the module allows many multi-decadal sensitivity simulations of the CH4-CO-OH system, which primarily determines the global atmospheric oxidizing capacity. This capability is important for capturing the nonlinear feedbacks of the CH4-CO-OH system and understanding the perturbations to methane, CO, and OH, and the concomitant impacts on climate. We implemented the ECCOH chemistry module in the NASA GEOS-5 atmospheric global circulation model (AGCM), performed multiple sensitivity simulations of the CH4-CO-OH system over 2 decades, and evaluated the model output with surface and satellite data sets of methane and CO. The favorable comparison of output from the ECCOH chemistry module (as configured in the GEOS- 5 AGCM) with observations demonstrates the fidelity of the module for use in scientific research.
NASA Astrophysics Data System (ADS)
Butchart, Neal; Anstey, James A.; Hamilton, Kevin; Osprey, Scott; McLandress, Charles; Bushell, Andrew C.; Kawatani, Yoshio; Kim, Young-Ha; Lott, Francois; Scinocca, John; Stockdale, Timothy N.; Andrews, Martin; Bellprat, Omar; Braesicke, Peter; Cagnazzo, Chiara; Chen, Chih-Chieh; Chun, Hye-Yeong; Dobrynin, Mikhail; Garcia, Rolando R.; Garcia-Serrano, Javier; Gray, Lesley J.; Holt, Laura; Kerzenmacher, Tobias; Naoe, Hiroaki; Pohlmann, Holger; Richter, Jadwiga H.; Scaife, Adam A.; Schenzinger, Verena; Serva, Federico; Versick, Stefan; Watanabe, Shingo; Yoshida, Kohei; Yukimoto, Seiji
2018-03-01
The Stratosphere-troposphere Processes And their Role in Climate (SPARC) Quasi-Biennial Oscillation initiative (QBOi) aims to improve the fidelity of tropical stratospheric variability in general circulation and Earth system models by conducting coordinated numerical experiments and analysis. In the equatorial stratosphere, the QBO is the most conspicuous mode of variability. Five coordinated experiments have therefore been designed to (i) evaluate and compare the verisimilitude of modelled QBOs under present-day conditions, (ii) identify robustness (or alternatively the spread and uncertainty) in the simulated QBO response to commonly imposed changes in model climate forcings (e.g. a doubling of CO2 amounts), and (iii) examine model dependence of QBO predictability. This paper documents these experiments and the recommended output diagnostics. The rationale behind the experimental design and choice of diagnostics is presented. To facilitate scientific interpretation of the results in other planned QBOi studies, consistent descriptions of the models performing each experiment set are given, with those aspects particularly relevant for simulating the QBO tabulated for easy comparison.
Towards quantifying uncertainty in predictions of Amazon 'dieback'.
Huntingford, Chris; Fisher, Rosie A; Mercado, Lina; Booth, Ben B B; Sitch, Stephen; Harris, Phil P; Cox, Peter M; Jones, Chris D; Betts, Richard A; Malhi, Yadvinder; Harris, Glen R; Collins, Mat; Moorcroft, Paul
2008-05-27
Simulations with the Hadley Centre general circulation model (HadCM3), including carbon cycle model and forced by a 'business-as-usual' emissions scenario, predict a rapid loss of Amazonian rainforest from the middle of this century onwards. The robustness of this projection to both uncertainty in physical climate drivers and the formulation of the land surface scheme is investigated. We analyse how the modelled vegetation cover in Amazonia responds to (i) uncertainty in the parameters specified in the atmosphere component of HadCM3 and their associated influence on predicted surface climate. We then enhance the land surface description and (ii) implement a multilayer canopy light interception model and compare with the simple 'big-leaf' approach used in the original simulations. Finally, (iii) we investigate the effect of changing the method of simulating vegetation dynamics from an area-based model (TRIFFID) to a more complex size- and age-structured approximation of an individual-based model (ecosystem demography). We find that the loss of Amazonian rainforest is robust across the climate uncertainty explored by perturbed physics simulations covering a wide range of global climate sensitivity. The introduction of the refined light interception model leads to an increase in simulated gross plant carbon uptake for the present day, but, with altered respiration, the net effect is a decrease in net primary productivity. However, this does not significantly affect the carbon loss from vegetation and soil as a consequence of future simulated depletion in soil moisture; the Amazon forest is still lost. The introduction of the more sophisticated dynamic vegetation model reduces but does not halt the rate of forest dieback. The potential for human-induced climate change to trigger the loss of Amazon rainforest appears robust within the context of the uncertainties explored in this paper. Some further uncertainties should be explored, particularly with respect to the representation of rooting depth.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
The regional suitability of underground construction as a climate control technique is discussed with reference to (1) a bioclimatic analysis of long-term weather data for 29 locations in the United States to determine appropriate above ground climate control techniques, (2) a data base of synthesized ground temperatures for the coterminous United States, and (3) monthly dew point ground temperature comparisons for identifying the relative likelihood of condensation from one region to another. It is concluded that the suitability of earth tempering as a practice and of specific earth-sheltered design stereotypes varies geographically; while the subsurface almost always provides a thermalmore » advantage on its own terms when compared to above ground climatic data, it can, nonetheless, compromise the effectiveness of other, regionally more important climate control techniques. Also contained in the report are reviews of above and below ground climate mapping schemes related to human comfort and architectural design, and detailed description of a theoretical model of ground temperature, heat flow, and heat storage in the ground. Strategies of passive climate control are presented in a discussion of the building bioclimatic analysis procedure which has been applied in a computer analysis of 30 years of weather data for each of 29 locations in the United States.« less
Olive cultivars adaptability in Southern Italy in present and future climate
NASA Astrophysics Data System (ADS)
Riccardi, M.; Alfieri, S.; Bonfante, A.; Basile, A.; Di Tommasi, P.; Menenti, M.; De Lorenzi, F.
2012-04-01
The intra-specific biodiversity of agricultural crops is very significant and likely to provide the single major opportunity to cope with the effects of the changing climate on agricultural ecosystems. Assessment of adaptive capacity must rely on quantitative descriptions of plant responses to environmental factors (e.g. soil water availability, temperature). Moreover climate scenario needs to be downscaled to the spatial scale relevant to crop and farm management. Distributed models of crop response to environmental forcing might be used for this purpose, but severely constrained by the very scarce knowledge on variety-specific values of model parameters, thus limiting the potential exploitation of intra-specific biodiversity towards adaptation. We have developed an approach towards this objective that relies on two complementary elements: a)a distributed model of the soil plant atmosphere system to downscale climate scenarios to landscape units, where generic model parameters for each species are used; b)a data base on climatic requirements of as many varieties as feasible for each species relevant to the agricultural production system of a given region. By means of this approach, the adaptability of some olive cultivars was evaluated in a composite (hills and plains) area of Southern Italy (Valle Telesina, Campania Region, about 20.000 ha). The yearly average temperature is 22.5 °C and rainfall ranges between 600 and 900 mm. Two different climate scenarios were considered: current climate (1961-1990) and future climate (2021-2050). Future climate scenarios at low spatial resolution were generated with general circulation models (AOGCM) and down-scaled by means of a statistical model (Tomozeiu et al., 2007). The climate was represented by daily observations of minimum, maximum temperature and precipitation on a regular grid with a spatial resolution of 35 km; 50 realizations were used for future climate. The soil water regime of 45 soil units was described for the two climate scenarios by using an hydrological distributed model (SWAP). For 11 olive cultivars, the yield response function to soil water regime was determined through the re-analysis of experimental data (unpublished or derived from scientific literature). According to these responses, cultivar-specific threshold values of soil water (or evapotranspiration) deficit were defined. The soil water regime calculated by the distributed model was compared with the threshold values to identify cultivars compatible with present and expected climates. The operation is repeated for a set of realizations of each climate scenario. This analysis is performed in a distributed manner, i.e. using the time series for each model grid to assess possible variations in the extent and spatial distribution of cultivated area of olive cultivars. In the study area future climate scenarios predict an increase of monthly minimum and maximum air temperature of about 2°C during the summer (June, July and August) and a reduction of rainfall in autumn. Spatial pattern of cultivars distribution, according their threshold values and soil water regime, was determined in the present and future climate scenarios, thus assessing variations in cultivars adaptability to future climate with respect to the present. Key words: climate change, biodiversity, water availability, yield response. The work was carried out within the Italian national project AGROSCENARI funded by the Ministry for Agricultural, Food and Forest Policies (MIPAAF, D.M. 8608/7303/2008).
Ensemble catchment hydrological modelling for climate change impact analysis
NASA Astrophysics Data System (ADS)
Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick
2014-05-01
It is vital to investigate how the hydrological model structure affects the climate change impact given that future changes not in the range for which the models were calibrated or validated are likely. Thus an ensemble modelling approach which involves a diversity of models with different structures such as spatial resolutions and process descriptions is crucial. The ensemble modelling approach was applied to a set of models: from the lumped conceptual models NAM, PDM and VHM, an intermediate detailed and distributed model WetSpa, to the highly detailed and fully distributed model MIKE-SHE. Explicit focus was given to the high and low flow extremes. All models were calibrated for sub flows and quick flows derived from rainfall and potential evapotranspiration (ETo) time series. In general, all models were able to produce reliable estimates of the flow regimes under the current climate for extreme peak and low flows. An intercomparison of the low and high flow changes under changed climatic conditions was made using climate scenarios tailored for extremes. Tailoring was important for two reasons. First, since the use of many scenarios was not feasible it was necessary to construct few scenarios that would reasonably represent the range of extreme impacts. Second, scenarios would be more informative as changes in high and low flows would be easily traced to changes of ETo and rainfall; the tailored scenarios are constructed using seasonal changes that are defined using different levels of magnitude (high, mean and low) for rainfall and ETo. After simulation of these climate scenarios in the five hydrological models, close agreement was found among the models. The different models predicted similar range of peak flow changes. For the low flows, however, the differences in the projected impact range by different hydrological models was larger, particularly for the drier scenarios. This suggests that the hydrological model structure is critical in low flow predictions, more than in high flow conditions. Hence, the mechanism of the slow flow component simulation requires further attention. It is concluded that a multi-model ensemble approach where different plausible model structures are applied, is extremely useful. It improves the reliability of climate change impact results and allows decision making to be based on uncertainty assessment that includes model structure related uncertainties. References: Ntegeka, V., Baguis, P., Roulin, E., Willems, P., 2014. Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508C, 307-321 Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Willems, P., De Smedt, F., Batelaan, O., 2013. Climate change impact on river flows and catchment hydrology: a comparison of two spatially distributed models. Hydrological Processes, 27(25), 3649-3662. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Van Steenbergen, N., De Smedt, F., Batelaan, O., Pereira, F., Willems, P., 2014. Intercomparison of five lumped and distributed models for catchment runoff and extreme flow simulation. Journal of Hydrology, in press. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., De Smedt, F., Batelaan, O., Pereira, F., Willems, P., 2014. Intercomparison of climate scenario impact predictions by a lumped and distributed model ensemble. Journal of Hydrology, in revision.
Ocean modelling on the CYBER 205 at GFDL
NASA Technical Reports Server (NTRS)
Cox, M.
1984-01-01
At the Geophysical Fluid Dynamics Laboratory, research is carried out for the purpose of understanding various aspects of climate, such as its variability, predictability, stability and sensitivity. The atmosphere and oceans are modelled mathematically and their phenomenology studied by computer simulation methods. The present state-of-the-art in the computer simulation of large scale oceans on the CYBER 205 is discussed. While atmospheric modelling differs in some aspects, the basic approach used is similar. The equations of the ocean model are presented along with a short description of the numerical techniques used to find their solution. Computational considerations and a typical solution are presented in section 4.
Code of Federal Regulations, 2013 CFR
2013-01-01
... temperature in the host rock and surrounding rock units. Section 960.4-2-4Climatic changes. Description of the climatic conditions of the site region, in context with global and regional patterns of climatic changes during the Quaternary Period, in order to project likely future changes in climate such that potential...
Code of Federal Regulations, 2012 CFR
2012-01-01
... temperature in the host rock and surrounding rock units. Section 960.4-2-4Climatic changes. Description of the climatic conditions of the site region, in context with global and regional patterns of climatic changes during the Quaternary Period, in order to project likely future changes in climate such that potential...
Code of Federal Regulations, 2014 CFR
2014-01-01
... temperature in the host rock and surrounding rock units. Section 960.4-2-4Climatic changes. Description of the climatic conditions of the site region, in context with global and regional patterns of climatic changes during the Quaternary Period, in order to project likely future changes in climate such that potential...
A downscaling method for the assessment of local climate change
NASA Astrophysics Data System (ADS)
Bruno, E.; Portoghese, I.; Vurro, M.
2009-04-01
The use of complimentary models is necessary to study the impact of climate change scenarios on the hydrological response at different space-time scales. However, the structure of GCMs is such that their space resolution (hundreds of kilometres) is too coarse and not adequate to describe the variability of extreme events at basin scale (Burlando and Rosso, 2002). To bridge the space-time gap between the climate scenarios and the usual scale of the inputs for hydrological prediction models is a fundamental requisite for the evaluation of climate change impacts on water resources. Since models operate a simplification of a complex reality, their results cannot be expected to fit with climate observations. Identifying local climate scenarios for impact analysis implies the definition of more detailed local scenario by downscaling GCMs or RCMs results. Among the output correction methods we consider the statistical approach by Déqué (2007) reported as a ‘Variable correction method' in which the correction of model outputs is obtained by a function build with the observation dataset and operating a quantile-quantile transformation (Q-Q transform). However, in the case of daily precipitation fields the Q-Q transform is not able to correct the temporal property of the model output concerning the dry-wet lacunarity process. An alternative correction method is proposed based on a stochastic description of the arrival-duration-intensity processes in coherence with the Poissonian Rectangular Pulse scheme (PRP) (Eagleson, 1972). In this proposed approach, the Q-Q transform is applied to the PRP variables derived from the daily rainfall datasets. Consequently the corrected PRP parameters are used for the synthetic generation of statistically homogeneous rainfall time series that mimic the persistency of daily observations for the reference period. Then the PRP parameters are forced through the GCM scenarios to generate local scale rainfall records for the 21st century. The statistical parameters characterizing daily storm occurrence, storm intensity and duration needed to apply the PRP scheme are considered among STARDEX collection of extreme indices.
Olsen, Espen; Bjaalid, Gunhild; Mikkelsen, Aslaug
2017-11-01
To increase understanding of workplace bullying and its relation to work climate and different outcomes among nurses. Examine a proposed bullying model including both job resource and job demands, as well as nurse outcomes reflected in job performance, job satisfaction, and work ability. Workplace bullying has been identified as some of the most damaging mechanisms in workplace settings. It is important to increase understanding of workplace bullying in relation to work climate and different outcomes among nurses. This study adopted a cross-sectional web based survey design. A sample of 2946 Registered Nurses from four public Norwegian hospitals were collected during October 2014. We analysed data using descriptive statistics, correlations, Cronbach's alpa, confirmatory factor analyses, and structural equation modelling. The majority of work climate characteristics confirmed to influence workplace bullying, and additionally had direct influence on nurse outcomes; job performance, job satisfaction, and work ability. Bullying had a mediational role between most of the work climate dimensions and nurse outcomes. This study increases our understanding of organizational antecedent of bullying among nurses. Workplace bullying among nurses functions as a mediator between the majority of work climate dimensions and outcomes related to job satisfaction and work ability. Strategies to reduce bullying should look at the study finding and specifically job resources and job demands that influence bullying and nurse outcomes. © 2017 John Wiley & Sons Ltd.
Urban Canopy Effects in Regional Climate Simulations - An Inter-Model Comparison
NASA Astrophysics Data System (ADS)
Halenka, T.; Huszar, P.; Belda, M.; Karlicky, J.
2017-12-01
To assess the impact of cities and urban surfaces on climate, the modeling approach is often used with inclusion of urban parameterization in land-surface interactions. This is especially important when going to higher resolution, which is common trend both in operational weather prediction and regional climate modelling. Model description of urban canopy related meteorological effects can, however, differ largely given especially the underlying surface models and the urban canopy parameterizations, representing a certain uncertainty. To assess this uncertainty is important for adaptation and mitigation measures often applied in the big cities, especially in connection to climate change perspective, which is one of the main task of the new project OP-PPR Proof of Concept UK. In this study we contribute to the estimation of this uncertainty by performing numerous experiments to assess the urban canopy meteorological forcing over central Europe on climate for the decade 2001-2010, using two regional climate models (RegCM4 and WRF) in 10 km resolution driven by ERA-Interim reanalyses, three surface schemes (BATS and CLM4.5 for RegCM4 and Noah for WRF) and five urban canopy parameterizations available: one bulk urban scheme, three single layer and a multilayer urban scheme. Effects of cities on urban and remote areas were evaluated. There are some differences in sensitivity of individual canopy model implementations to the UHI effects, depending on season and size of the city as well. Effect of reducing diurnal temperature range in cities (around 2 °C in summer mean) is noticeable in all simulations, independent to urban parameterization type and model, due to well-known warmer summer city nights. For the adaptation and mitigation purposes, rather than the average urban heat island intensity the distribution of it is more important providing the information on extreme UHI effects, e.g. during heat waves. We demonstrate that for big central European cities this effect can approach 10°C, even for not so big ones these extreme effects can go above 5°C.
Future southcentral US wildfire probability due to climate change
Stambaugh, Michael C.; Guyette, Richard P.; Stroh, Esther D.; Struckhoff, Matthew A.; Whittier, Joanna B.
2018-01-01
Globally, changing fire regimes due to climate is one of the greatest threats to ecosystems and society. In this paper, we present projections of future fire probability for the southcentral USA using downscaled climate projections and the Physical Chemistry Fire Frequency Model (PC2FM). Future fire probability is projected to both increase and decrease across the study region of Oklahoma, New Mexico, and Texas. Among all end-of-century projections, change in fire probabilities (CFPs) range from − 51 to + 240%. Greatest absolute increases in fire probability are shown for areas within the range of approximately 75 to 160 cm mean annual precipitation (MAP), regardless of climate model. Although fire is likely to become more frequent across the southcentral USA, spatial patterns may remain similar unless significant increases in precipitation occur, whereby more extensive areas with increased fire probability are predicted. Perhaps one of the most important results is illumination of climate changes where fire probability response (+, −) may deviate (i.e., tipping points). Fire regimes of southcentral US ecosystems occur in a geographic transition zone from reactant- to reaction-limited conditions, potentially making them uniquely responsive to different scenarios of temperature and precipitation changes. Identification and description of these conditions may help anticipate fire regime changes that will affect human health, agriculture, species conservation, and nutrient and water cycling.
The climate4impact portal: bridging the CMIP5 and CORDEX data infrastructure to impact users
NASA Astrophysics Data System (ADS)
Plieger, Maarten; Som de Cerff, Wim; Pagé, Christian; Tatarinova, Natalia; Cofiño, Antonio; Vega Saldarriaga, Manuel; Hutjes, Ronald; de Jong, Fokke; Bärring, Lars; Sjökvist, Elin
2015-04-01
The aim of climate4impact is to enhance the use of Climate Research Data and to enhance the interaction with climate effect/impact communities. The portal is based on 21 impact use cases from 5 different European countries, and is evaluated by a user panel consisting of use case owners. It has been developed within the European projects IS-ENES and IS-ENES2 for more than 5 years, and its development currently continues within IS-ENES2 and CLIPC. As the climate impact community is very broad, the focus is mainly on the scientific impact community. This work has resulted in the ENES portal interface for climate impact communities and can be visited at www.climate4impact.eu. The climate4impact is connected to the Earth System Grid Federation (ESGF) nodes containing global climate model data (GCM data) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and regional climate model data (RCM) data from the Coordinated Regional Climate Downscaling Experiment (CORDEX). This global network of climate model data centers offers services for data description, discovery and download. The climate4impact portal connects to these services using OpenID, and offers a user interface for searching, visualizing and downloading global climate model data and more. A challenging task was to describe the available model data and how it can be used. The portal tries to inform users about possible caveats when using climate model data. All impact use cases are described in the documentation section, using highlighted keywords pointing to detailed information in the glossary. During the project, the content management system Drupal was used to enable partners to contribute on the documentation section. In this presentation the architecture and following items will be detailed: - Visualization: Visualize data from ESGF data nodes using ADAGUC Web Map Services. - Processing: Transform data, subset, export into other formats, and perform climate indices calculations using Web Processing Services implemented by PyWPS, based on NCAR NCPP OpenClimateGIS and IS-ENES2 icclim. - Security: Login using OpenID for access to the ESGF data nodes. The ESGF works in conjunction with several external websites and systems. The climate4impact portal uses X509 based short lived credentials, generated on behalf of the user with a MyProxy service. Single Sign-on (SSO) is used to make these websites and systems work together. - Discovery: Facetted search based on e.g. variable name, model and institute using the ESGF search services. A catalog browser allows for browsing through CMIP5 and any other climate model data catalogues (e.g. ESSENCE, EOBS, UNIDATA). - Download: Directly from ESGF nodes and other THREDDS catalogs This architecture will also be used for the future Copernicus platform, developed in the EU FP7 CLIPC project. - Connection with the downscaling portal of the university of Cantabria - Experiences on the question and answer site via Askbot The current main objectives for climate4impact can be summarized in two objectives. The first one is to work on a web interface which automatically generates a graphical user interface on WPS endpoints. The WPS calculates climate indices and subset data using OpenClimateGIS/icclim on data stored in ESGF data nodes. Data is then transmitted from ESGF nodes over secured OpenDAP and becomes available in a new, per user, secured OpenDAP server. The results can then be visualized again using ADAGUC WMS. Dedicated wizards for processing of climate indices will be developed in close collaboration with users. The second one is to expose climate4impact services, so as to offer standardized services which can be used by other portals. This has the advantage to add interoperability between several portals, as well as to enable the design of specific portals aimed at different impact communities, either thematic or national, for example.
Alonso, E; Rubio, A; March, J C; Danet, A
2011-01-01
The aim of this study is to compare the emotional climate, quality of communication and performance indicators in a clinical management unit and two traditional hospital services. Quantitative study. questionnaire of 94 questions. 83 health professionals (63 responders) from the clinical management unit of breast pathology and the hospital services of medical oncology and radiation oncology. descriptive statistics, comparison of means, correlation and linear regression models. The clinical management unit reaches higher values compared with the hospital services about: performance indicators, emotional climate, internal communication and evaluation of the leadership. An important gap between existing and desired sources, channels, media and subjects of communication appear, in both clinical management unit and traditional services. The clinical management organization promotes better internal communication and interpersonal relations, leading to improved performance indicators. Copyright © 2011 SECA. Published by Elsevier Espana. All rights reserved.
Work-related injury factors and safety climate perception in truck drivers.
Anderson, Naomi J; Smith, Caroline K; Byrd, Jesse L
2017-08-01
The trucking industry has a high burden of work-related injuries. This study examined factors, such as safety climate perceptions, that may impact injury risk. A random sample of 9800 commercial driver's license holders (CDL) were sent surveys, only 4360 were eligible truck drivers. Descriptive statistics and logistic regression models were developed to describe the population and identify variables associated with work-related injury. 2189 drivers completed the pertinent interview questions. Driving less-than-truckload, daytime sleepiness, pressure to work faster, and having a poor composite score for safety perceptions were all associated with increased likelihood of work-related injury. Positive safety perception score was protective for odds of work-related injury, and increased claim filing when injured. Positive psychological safety climate is associated with decreased likelihood of work-related injury and increased likelihood that a driver injured on the job files a workers' compensation claim. © 2017 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Köseoğlu, Denizcan; Belt, Simon T.; Smik, Lukas; Yao, Haoyi; Panieri, Giuliana; Knies, Jochen
2018-02-01
The discovery of IP25 as a qualitative biomarker proxy for Arctic sea ice and subsequent introduction of the so-called PIP25 index for semi-quantitative descriptions of sea ice conditions has significantly advanced our understanding of long-term paleo Arctic sea ice conditions over the past decade. We investigated the potential for classification tree (CT) models to provide a further approach to paleo Arctic sea ice reconstruction through analysis of a suite of highly branched isoprenoid (HBI) biomarkers in ca. 200 surface sediments from the Barents Sea. Four CT models constructed using different HBI assemblages revealed IP25 and an HBI triene as the most appropriate classifiers of sea ice conditions, achieving a >90% cross-validated classification rate. Additionally, lower model performance for locations in the Marginal Ice Zone (MIZ) highlighted difficulties in characterisation of this climatically-sensitive region. CT model classification and semi-quantitative PIP25-derived estimates of spring sea ice concentration (SpSIC) for four downcore records from the region were consistent, although agreement between proxy and satellite/observational records was weaker for a core from the west Svalbard margin, likely due to the highly variable sea ice conditions. The automatic selection of appropriate biomarkers for description of sea ice conditions, quantitative model assessment, and insensitivity to the c-factor used in the calculation of the PIP25 index are key attributes of the CT approach, and we provide an initial comparative assessment between these potentially complementary methods. The CT model should be capable of generating longer-term temporal shifts in sea ice conditions for the climatically sensitive Barents Sea.
Olds, Danielle M; Aiken, Linda H; Cimiotti, Jeannie P; Lake, Eileen T
2017-09-01
There are two largely distinct research literatures on the association of the nurse work environment and the safety climate on patient outcomes. To determine whether hospital safety climate and work environment make comparable or distinct contributions to patient mortality. Cross-sectional secondary analysis of linked datasets of Registered Nurse survey responses, adult acute care discharge records, and hospital characteristics. Acute care hospitals in California, Florida, New Jersey, and Pennsylvania. The sample included 600 hospitals linked to 27,009 nurse survey respondents and 852,974 surgical patients. Nurse survey data included assessments of the nurse work environment and hospital safety climate. The outcome of interest was in-hospital mortality. Data analyses included descriptive statistics and multivariate random intercept logistic regression. In a fully adjusted model, a one standard deviation increase in work environment score was associated with an 8.1% decrease in the odds of mortality (OR 0.919, p<0.001). A one-standard deviation increase in safety climate score was similarly associated with a 7.7% decrease in the odds of mortality (OR 0.923, p<0.001). However, when work environment and safety climate were modeled together, the effect of the work environment remained significant, while safety climate became a non-significant predictor of mortality odds (OR 0.940, p=0.035 vs. OR 0.971, p=0.316). We found that safety climate perception is not predictive of patient mortality beyond the effect of the nurse work environment. To advance hospital safety and quality and improve patient outcomes, organizational interventions should be directed toward improving nurse work environments. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Lewis, Jared; Bodeker, Greg E.; Kremser, Stefanie; Tait, Andrew
2017-12-01
A method, based on climate pattern scaling, has been developed to expand a small number of projections of fields of a selected climate variable (X) into an ensemble that encapsulates a wide range of indicative model structural uncertainties. The method described in this paper is referred to as the Ensemble Projections Incorporating Climate model uncertainty (EPIC) method. Each ensemble member is constructed by adding contributions from (1) a climatology derived from observations that represents the time-invariant part of the signal; (2) a contribution from forced changes in X, where those changes can be statistically related to changes in global mean surface temperature (Tglobal); and (3) a contribution from unforced variability that is generated by a stochastic weather generator. The patterns of unforced variability are also allowed to respond to changes in Tglobal. The statistical relationships between changes in X (and its patterns of variability) and Tglobal are obtained in a training
phase. Then, in an implementation
phase, 190 simulations of Tglobal are generated using a simple climate model tuned to emulate 19 different global climate models (GCMs) and 10 different carbon cycle models. Using the generated Tglobal time series and the correlation between the forced changes in X and Tglobal, obtained in the training
phase, the forced change in the X field can be generated many times using Monte Carlo analysis. A stochastic weather generator is used to generate realistic representations of weather which include spatial coherence. Because GCMs and regional climate models (RCMs) are less likely to correctly represent unforced variability compared to observations, the stochastic weather generator takes as input measures of variability derived from observations, but also responds to forced changes in climate in a way that is consistent with the RCM projections. This approach to generating a large ensemble of projections is many orders of magnitude more computationally efficient than running multiple GCM or RCM simulations. Such a large ensemble of projections permits a description of a probability density function (PDF) of future climate states rather than a small number of individual story lines within that PDF, which may not be representative of the PDF as a whole; the EPIC method largely corrects for such potential sampling biases. The method is useful for providing projections of changes in climate to users wishing to investigate the impacts and implications of climate change in a probabilistic way. A web-based tool, using the EPIC method to provide probabilistic projections of changes in daily maximum and minimum temperatures for New Zealand, has been developed and is described in this paper.
Environmental Testing Campaign and Verification of Satellite Deimos-2 at INTA
NASA Astrophysics Data System (ADS)
Hernandez, Daniel; Vazquez, Mercedes; Anon, Manuel; Olivo, Esperanza; Gallego, Pablo; Morillo, Pablo; Parra, Javier; Capraro; Luengo, Mar; Garcia, Beatriz; Villacorta, Pablo
2014-06-01
In this paper the environmental test campaign and verification of the DEIMOS-2 (DM2) satellite will be presented and described. DM2 will be ready for launch in 2014.Firstly, a short description of the satellite is presented, including its physical characteristics and intended optical performances. DEIMOS-2 is a LEO satellite for earth observation that will provide high resolution imaging services for agriculture, civil protection, environmental issues, disasters monitoring, climate change, urban planning, cartography, security and intelligence.Then, the verification and test campaign carried out on the SM and FM models at INTA is described; including Mechanical test for the SM and Climatic, Mechanical and Electromagnetic Compatibility tests for the FM. In addition, this paper includes Centre of Gravity and Moment of Inertia measurements for both models, and other verification activities carried out in order to ensure satellite's health during launch and its in orbit performance.
NASA Astrophysics Data System (ADS)
Palacios-Peña, Laura; Baró, Rocío; Baklanov, Alexander; Balzarini, Alessandra; Brunner, Dominik; Forkel, Renate; Hirtl, Marcus; Honzak, Luka; María López-Romero, José; Montávez, Juan Pedro; Pérez, Juan Luis; Pirovano, Guido; San José, Roberto; Schröder, Wolfram; Werhahn, Johannes; Wolke, Ralf; Žabkar, Rahela; Jiménez-Guerrero, Pedro
2018-04-01
Atmospheric aerosols modify the radiative budget of the Earth due to their optical, microphysical and chemical properties, and are considered one of the most uncertain climate forcing agents. In order to characterise the uncertainties associated with satellite and modelling approaches to represent aerosol optical properties, mainly aerosol optical depth (AOD) and Ångström exponent (AE), their representation by different remote-sensing sensors and regional online coupled chemistry-climate models over Europe are evaluated. This work also characterises whether the inclusion of aerosol-radiation (ARI) or/and aerosol-cloud interactions (ACI) help improve the skills of modelling outputs.Two case studies were selected within the EuMetChem COST Action ES1004 framework when important aerosol episodes in 2010 all over Europe took place: a Russian wildfire episode and a Saharan desert dust outbreak that covered most of the Mediterranean Sea. The model data came from different regional air-quality-climate simulations performed by working group 2 of EuMetChem, which differed according to whether ARI or ACI was included or not. The remote-sensing data came from three different sensors: MODIS, OMI and SeaWIFS. The evaluation used classical statistical metrics to first compare satellite data versus the ground-based instrument network (AERONET) and then to evaluate model versus the observational data (both satellite and ground-based data).Regarding the uncertainty in the satellite representation of AOD, MODIS presented the best agreement with the AERONET observations compared to other satellite AOD observations. The differences found between remote-sensing sensors highlighted the uncertainty in the observations, which have to be taken into account when evaluating models. When modelling results were considered, a common trend for underestimating high AOD levels was observed. For the AE, models tended to underestimate its variability, except when considering a sectional approach in the aerosol representation. The modelling results showed better skills when ARI+ACI interactions were included; hence this improvement in the representation of AOD (above 30 % in the model error) and AE (between 20 and 75 %) is important to provide a better description of aerosol-radiation-cloud interactions in regional climate models.
21st Century Carbon-Climate Change as Simulated by the Canadian Earth System Model CanESM1
NASA Astrophysics Data System (ADS)
Curry, C.; Christian, J. R.; Arora, V.; Boer, G. J.; Denman, K. L.; Flato, G. M.; Scinocca, J. F.; Merryfield, W. J.; Lee, W. G.; Yang, D.
2009-12-01
The Canadian Earth System Model CanESM1 is a fully coupled climate/carbon-cycle model with prognostic ocean and terrestrial components. The model has been used to simulate the 1850-2000 climate using historical greenhouse gas emissions, and future climates using IPCC emission scenarios. Modelled globally averaged CO2 concentration, land and ocean carbon uptake compare well with observation-based values at year 2000, as do the annual cycle and latitudinal distribution of CO2, instilling confidence that the model is suitable for future projections of carbon cycle behaviour in a changing climate. Land use change emissions are calculated explicitly using an observation-based time series of fractional coverage of different plant functional types. A more complete description of the model may be found in Arora et al. (2009). Differences in the land-atmosphere CO2 flux from the present to the future period under the SRES A2 emissions scenario show an increase in land sinks by a factor of 7.5 globally, mostly the result of CO2 fertilization. By contrast, the magnitude of the global ocean CO2 sink increases by a factor of only 2.3 by 2100. Expressed as a fraction of total emissions, ocean carbon uptake decreases throughout the 2000-2100 period, while land carbon uptake increases until around 2050, then declines. The result is an increase in airborne CO2 fraction after the mid-21st century, reaching a value of 0.55 by 2100. The simulated decline in ocean carbon uptake over the 21st century occurs despite steadily rising atmospheric CO2. This behaviour is usually attributed to climate-induced changes in surface temperature and salinity that reduce CO2 solubility, and increasing ocean stratification that weakens the biological pump. However, ocean biological processes such as dinitrogen fixation and calcification may also play an important role. Although not well understood at present, improved parameterizations of these processes will increase confidence in projections of future trends in CO2 uptake.
NASA Astrophysics Data System (ADS)
Titov, A.; Gordov, E.; Okladnikov, I.
2009-04-01
In this report the results of the work devoted to the development of working model of the software system for storage, semantically-enabled search and retrieval along with processing and visualization of environmental datasets containing results of meteorological and air pollution observations and mathematical climate modeling are presented. Specially designed metadata standard for machine-readable description of datasets related to meteorology, climate and atmospheric pollution transport domains is introduced as one of the key system components. To provide semantic interoperability the Resource Description Framework (RDF, http://www.w3.org/RDF/) technology means have been chosen for metadata description model realization in the form of RDF Schema. The final version of the RDF Schema is implemented on the base of widely used standards, such as Dublin Core Metadata Element Set (http://dublincore.org/), Directory Interchange Format (DIF, http://gcmd.gsfc.nasa.gov/User/difguide/difman.html), ISO 19139, etc. At present the system is available as a Web server (http://climate.risks.scert.ru/metadatabase/) based on the web-portal ATMOS engine [1] and is implementing dataset management functionality including SeRQL-based semantic search as well as statistical analysis and visualization of selected data archives [2,3]. The core of the system is Apache web server in conjunction with Tomcat Java Servlet Container (http://jakarta.apache.org/tomcat/) and Sesame Server (http://www.openrdf.org/) used as a database for RDF and RDF Schema. At present statistical analysis of meteorological and climatic data with subsequent visualization of results is implemented for such datasets as NCEP/NCAR Reanalysis, Reanalysis NCEP/DOE AMIP II, JMA/CRIEPI JRA-25, ECMWF ERA-40 and local measurements obtained from meteorological stations on the territory of Russia. This functionality is aimed primarily at finding of main characteristics of regional climate dynamics. The proposed system represents a step in the process of development of a distributed collaborative information-computational environment to support multidisciplinary investigations of Earth regional environment [4]. Partial support of this work by SB RAS Integration Project 34, SB RAS Basic Program Project 4.5.2.2, APN Project CBA2007-08NSY and FP6 Enviro-RISKS project (INCO-CT-2004-013427) is acknowledged. References 1. E.P. Gordov, V.N. Lykosov, and A.Z. Fazliev. Web portal on environmental sciences "ATMOS" // Advances in Geosciences. 2006. Vol. 8. p. 33 - 38. 2. Gordov E.P., Okladnikov I.G., Titov A.G. Development of elements of web based information-computational system supporting regional environment processes investigations // Journal of Computational Technologies, Vol. 12, Special Issue #3, 2007, pp. 20 - 28. 3. Okladnikov I.G., Titov A.G. Melnikova V.N., Shulgina T.M. Web-system for processing and visualization of meteorological and climatic data // Journal of Computational Technologies, Vol. 13, Special Issue #3, 2008, pp. 64 - 69. 4. Gordov E.P., Lykosov V.N. Development of information-computational infrastructure for integrated study of Siberia environment // Journal of Computational Technologies, Vol. 12, Special Issue #2, 2007, pp. 19 - 30.
Educators' Perceptions of School Climate and Health in Selected Primary Schools
ERIC Educational Resources Information Center
Pretorius, Stephanus; de Villiers, Elsabe
2009-01-01
The aims in this research were to determine the perceptions of school climate held by educators of primary schools in the southern Cape. Six primary schools with a staff complement of 178 educators participated in the investigation. Two instruments were used: the Organisational Climate Description Questionnaire Rutgers Elementary (OCDQ-RE) and…
Differences in Assessments of Organizational School Climate between Teachers and Adminsitrators
ERIC Educational Resources Information Center
Duff, Brandy Kinlaw
2013-01-01
The purpose of this quantitative study was to examine the organizational school climate perceptions of teachers and principals and to ascertain the extent to which their perceptions differed. This causal comparative study used the Organizational Climate Description Questionnaire for Elementary Schools (OCDQ-RE) as the survey instrument for data…
Delineation of climate regions in the Northeastern United States
Arthur T. DeGaetano
1996-01-01
Climate is a primary criterion for the development, description and validation of subregional levels of the National Hierarchical Framework of Ecological Units. However, climate information is not currently available in the form or level of detail required for integration with other biophysical factors at the section or subsection levels. In this study, historical...
ERIC Educational Resources Information Center
Pulleyn, Janet L.
2012-01-01
This research considered relationships among teachers' perceptions of principal leadership and teachers' perceptions of school climate by using the Leadership Practices Inventory (LPI) survey and the Organizational Climate Description Questionnaire (Revised) for Middle Schools (OCDQ-RM) survey. Teachers from six middle schools in the same district…
ERIC Educational Resources Information Center
Cottingham, Harold F.; And Others
The study was designed to determine if a significant relationship existed between the organizational climate of the high school and the functions counselors performed in nine selected high schools in Pinellas County, Florida. Two instruments were used: (1) The Organizational Climate Description Questionnaire (OCDQ) dealing with eight…
ERIC Educational Resources Information Center
Hall, John W.
1972-01-01
This study is concerned with the relationship between Halpin and Croft's organizational climates as classified by the Organizational Climate Description Questionnaire and Likert and Likert's organizational systems as classified by the teacher form of the Profile of a School Questionnaire. The positively significant relationship found between these…
Effects of learning climate and registered nurse staffing on medication errors.
Chang, Yunkyung; Mark, Barbara
2011-01-01
Despite increasing recognition of the significance of learning from errors, little is known about how learning climate contributes to error reduction. The purpose of this study was to investigate whether learning climate moderates the relationship between error-producing conditions and medication errors. A cross-sectional descriptive study was done using data from 279 nursing units in 146 randomly selected hospitals in the United States. Error-producing conditions included work environment factors (work dynamics and nurse mix), team factors (communication with physicians and nurses' expertise), personal factors (nurses' education and experience), patient factors (age, health status, and previous hospitalization), and medication-related support services. Poisson models with random effects were used with the nursing unit as the unit of analysis. A significant negative relationship was found between learning climate and medication errors. It also moderated the relationship between nurse mix and medication errors: When learning climate was negative, having more registered nurses was associated with fewer medication errors. However, no relationship was found between nurse mix and medication errors at either positive or average levels of learning climate. Learning climate did not moderate the relationship between work dynamics and medication errors. The way nurse mix affects medication errors depends on the level of learning climate. Nursing units with fewer registered nurses and frequent medication errors should examine their learning climate. Future research should be focused on the role of learning climate as related to the relationships between nurse mix and medication errors.
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.
An open-access CMIP5 pattern library for temperature and precipitation: Description and methodology
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lynch, Cary D.; Hartin, Corinne A.; Bond-Lamberty, Benjamin
Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squared regression methods. We exploremore » the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90°N/S). Bias and mean errors between modeled and pattern predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5°C, but choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. As a result, this paper describes our library of least squared regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns.« less
An open-access CMIP5 pattern library for temperature and precipitation: Description and methodology
Lynch, Cary D.; Hartin, Corinne A.; Bond-Lamberty, Benjamin; ...
2017-05-15
Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squared regression methods. We exploremore » the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90°N/S). Bias and mean errors between modeled and pattern predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5°C, but choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. As a result, this paper describes our library of least squared regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns.« less
Role of Organizational Climate in Organizational Commitment: The Case of Teaching Hospitals.
Bahrami, Mohammad Amin; Barati, Omid; Ghoroghchian, Malake-Sadat; Montazer-Alfaraj, Razieh; Ranjbar Ezzatabadi, Mohammad
2016-04-01
The commitment of employees is affected by several factors, including factors related to the organizational climate. The aim of this study was to investigate the relationship between organizational commitment of nurses and the organizational climate in hospital settings. A cross-sectional study was conducted in 2014 at two teaching hospitals in Yazd, Iran. A total of 90 nurses in these hospitals participated. We used stratified random sampling of the nursing population. The required data were gathered using two valid questionnaires: Allen and Meyer's organizational commitment standard questionnaire and Halpin and Croft's Organizational Climate Description Questionnaire. Data analysis was done through SPSS 20 statistical software (IBM Corp., Armonk, NY, USA). We used descriptive statistics and Pearson's correlation coefficient for the data analysis. The findings indicated a positive and significant correlation between organizational commitment and organizational climate (r = 0.269, p = 0.01). There is also a significant positive relationship between avoidance of organizational climate and affective commitment (r = 0.208, p = 0.049) and between focus on production and normative and continuance commitment (r = 0.308, p = 0.003). Improving the organizational climate could be a valuable strategy for improving organizational commitment.
NASA Technical Reports Server (NTRS)
Suarez, Max J. (Editor); Takacs, Lawrence L.
1995-01-01
A detailed description of the numerical formulation of Version 2 of the ARIES/GEOS 'dynamical core' is presented. This code is a nearly 'plug-compatible' dynamics for use in atmospheric general circulation models (GCMs). It is a finite difference model on a staggered latitude-longitude C-grid. It uses second-order differences for all terms except the advection of vorticity by the rotation part of the flow, which is done at fourth-order accuracy. This dynamical core is currently being used in the climate (ARIES) and data assimilation (GEOS) GCMs at Goddard.
Das Bremerhavener Grundwasser im Klimawandel - Eine FREEWAT-Fallstudie
NASA Astrophysics Data System (ADS)
Panteleit, Björn; Jensen, Sven; Seiter, Katherina; Siebert, Yvonne
2018-01-01
A 3D structural model was created for the state of Bremen based on an extensive borehole database. Parameters were assigned to the model by interpretation and interpolation of the borehole descriptions. This structural model was transferred into a flow model via the FREEWAT platform, an open-source plug-in of the free QGIS software, with connection to the MODFLOW code. This groundwater management tool is intended for long-term use. As a case study for the FREEWAT Project, possible effects of climate change on groundwater levels in the Bremerhaven area have been simulated. In addition to the calibration year 2010, scenarios with a sea-level rise and decreasing groundwater recharge were simulated for the years 2040, 2070 and 2100. In addition to seawater intrusion in the coastal area, declining groundwater levels are also a concern. Possibilities for future groundwater management already include active control of the water level of a lake and the harbor basin. With the help of a focused groundwater monitoring program based on the model results, the planned flow model can become an important forecasting tool for groundwater management within the framework of the planned continuous model management and for representing the effects of changing climatic conditions and mitigation measures.
NASA Astrophysics Data System (ADS)
Kala, Jatin; Lyons, Tom J.; Abbs, Deborah J.; Foster, Ian J.
2010-05-01
Heat stress, frost, and water stress events have significant impacts on grain quality and production within the agricultural region (wheat-belt) of Southwest Western Australia (SWWA) (Cramb, 2000) and understanding how the frequency and intensity of these events will change in the future is crucial for management purposes. Hence, the Regional Atmospheric Modeling System (Pielke et al, 1992) (RAMS Version 6.0) is used to simulate the past 10 years of the climate of SWWA at a 20 km grid resolution by down-scaling the 6-hourly 1.0 by 1.0 degree National Center for Environmental Prediction Final Analyses from December 1999 to Present. Daily minimum and maximum temperatures, as well as daily rainfall are validated against observations. Simulations of future climate are carried out by down-scaling the Commonwealth Scientific and Industrial Research Organization (CSIRO) Mark 3.5 General Circulation Model (Gordon et al, 2002) for 10 years (2046-2055) under the SRES A2 scenario using the Cubic Conformal Atmospheric Model (CCAM) (McGregor and Dix, 2008). The 6-hourly CCAM output is then downscaled to a 20 km resolution using RAMS. Changes in extreme events are discussed within the context of the continued viability of agriculture in SWWA. Cramb, J. (2000) Climate in relation to agriculture in south-western Australia. In: The Wheat Book (Eds W. K. Anderson and J. R. Garlinge). Bulletin 4443. Department of Agriculture, Western Australia. Gordon, H. B., Rotstayn, L. D., McGregor, J. L., Dix, M. R., Kowalczyk, E. A., O'Farrell, S. P., Waterman, L. J., Hirst, A. C., Wilson, S. G., Collier, M. A., Watterson, I. G., and Elliott, T. I. (2002). The CSIRO Mk3 Climate System Model [Electronic publication]. Aspendale: CSIRO Atmospheric Research. (CSIRO Atmospheric Research technical paper; no. 60). 130 p McGregor, J. L., and Dix, M. R., (2008) An updated description of the conformal-cubic atmospheric model. High Resolution Simulation of the Atmosphere and Ocean, Hamilton, K. and Ohfuchi, W., Eds., Springer, 51-76. Pielke, R. A., Cotton, W. R., Walko, R. L., Tremback, C. J., Lyons, W. A., Grasso, L. D., Nicholls, M. E., Moran, M. D., Wesley, D. A., Lee, T. J., Copeland, J. H., (1992) A comprehensive meteorological modeling system - RAMS. Meteorol. Atmos. Phys., 49, 69-91.
Sexual Assault Prevention and Response Climate DEOCS 4.1 Construct Validity Summary
2017-08-01
DEOCS, (7) examining variance and descriptive statistics (8) examining the relationship among items/areas to reduce multicollinearity, and (9...selecting items that demonstrate the strongest scale properties. Included is a review of the 4.0 description and items, followed by the proposed...Tables 1 – 7 for the description of each measure and corresponding items. Table 1. DEOCS 4.0 Perceptions of Safety Measure Description
NASA Astrophysics Data System (ADS)
Gariano, Stefano Luigi; Guzzetti, Fausto
2017-04-01
According to the fifth report of the Intergovernmental Panel on Climate Change, "warming of the climate system is unequivocal". The influence of climate changes on slope stability and landslides is also undisputable. Nevertheless, the quantitative evaluation of the impact of global warming, and the related changes in climate, on landslides remains a complex question to be solved. The evidence that climate and landslides act at only partially overlapping spatial and temporal scales complicates the evaluation. Different research fields, including e.g., climatology, physics, hydrology, geology, hydrogeology, geotechnics, soil science, environmental science, and social science, must be considered. Climatic, environmental, demographic, and economic changes are strictly correlated, with complex feedbacks, to landslide occurrence and variation. Thus, a holistic, multidisciplinary approach is necessary. We reviewed the literature on landslide-climate studies, and found a bias in their geographical distribution, with several studies centered in Europe and North America, and large parts of the world not investigated. We examined advantages and drawbacks of the approaches adopted to evaluate the effects of climate variations on landslides, including prospective modelling and retrospective methods that use landslide and climate records, and paleo-environmental information. We found that the results of landslide-climate studies depend more on the emission scenarios, the global circulation models, the regional climate models, and the methods to downscale the climate variables, than on the description of the variables controlling slope processes. Using ensembles of projections based on a range of emissions scenarios would reduce (or at least quantify) the uncertainties in the obtained results. We performed a preliminary global assessment of the future landslide impact, presenting a global distribution of the projected impact of climate change on landslide activity and abundance. Where global warming is expected to increase, the frequency and intensity of severe rainfall events, a primary trigger of shallow, rapid-moving landslides that cause many landslide fatalities, an increase in the number of people exposed to landslide risk is to be expected. Furthermore, we defined a group of objective and reproducible methods for the quantitative evaluation of the past and future (expected) variations in landslide occurrence and distribution, and in the impact and risk to the population, as a result of changes in climatic and environmental factors (particularly, land use changes), at regional scale. The methods were tested in a southern Italian region, but they can easily applied in other physiographic and climatic regions, where adequate information is available.
NASA Astrophysics Data System (ADS)
Law, Rachel M.; Ziehn, Tilo; Matear, Richard J.; Lenton, Andrew; Chamberlain, Matthew A.; Stevens, Lauren E.; Wang, Ying-Ping; Srbinovsky, Jhan; Bi, Daohua; Yan, Hailin; Vohralik, Peter F.
2017-07-01
Earth system models (ESMs) that incorporate carbon-climate feedbacks represent the present state of the art in climate modelling. Here, we describe the Australian Community Climate and Earth System Simulator (ACCESS)-ESM1, which comprises atmosphere (UM7.3), land (CABLE), ocean (MOM4p1), and sea-ice (CICE4.1) components with OASIS-MCT coupling, to which ocean and land carbon modules have been added. The land carbon model (as part of CABLE) can optionally include both nitrogen and phosphorous limitation on the land carbon uptake. The ocean carbon model (WOMBAT, added to MOM) simulates the evolution of phosphate, oxygen, dissolved inorganic carbon, alkalinity and iron with one class of phytoplankton and zooplankton. We perform multi-centennial pre-industrial simulations with a fixed atmospheric CO2 concentration and different land carbon model configurations (prescribed or prognostic leaf area index). We evaluate the equilibration of the carbon cycle and present the spatial and temporal variability in key carbon exchanges. Simulating leaf area index results in a slight warming of the atmosphere relative to the prescribed leaf area index case. Seasonal and interannual variations in land carbon exchange are sensitive to whether leaf area index is simulated, with interannual variations driven by variability in precipitation and temperature. We find that the response of the ocean carbon cycle shows reasonable agreement with observations. While our model overestimates surface phosphate values, the global primary productivity agrees well with observations. Our analysis highlights some deficiencies inherent in the carbon models and where the carbon simulation is negatively impacted by known biases in the underlying physical model and consequent limits on the applicability of this model version. We conclude the study with a brief discussion of key developments required to further improve the realism of our model simulation.
NASA Astrophysics Data System (ADS)
Wu, Minchao; Smith, Benjamin; Schurgers, Guy; Lindström, Joe; Rummukainen, Markku; Samuelsson, Patrick
2013-04-01
Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical rainforest and reduced precipitation over the Amazon Basin (Cox et al. 2000; Betts et al. 2004; Malhi et al. 2009). Opposite effects are seen in southern Senegal, southern Mali, northern Guinea and Guinea-Bissau, positive evapotranspiration feedback enhancing the cover of trees in forest and savannah, mitigating warming and promoting local moisture recycling as rainfall. We reveal that LAI-driven evapotranspiration feedback may reduced rainfall in parts of Africa, vegetation-climate feedbacks may significantly impact the magnitude and character of simulated changes in climate as well as vegetation and ecosystems in future scenario studies of this region. They should be accounted for in future studies of climate change and its impacts on Africa. Keywords: vegetation-climate feedback, regional climate model, evapotranspiration, CORDEX. References: Betts, R.A., Cox, P.M., Collins, M., Harris, P.P., Huntingford, C. & Jones, C.D. 2004. The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming. Theoretical and Applied Climatology 78: 157-175. Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A. & Totterdell, I.J. 2000. Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408: 184-187. Samuelsson, P., Jones, C., Wilĺen, U., Gollvik, S., Hansson, U. and coauthors. 2011. The Rossby Centre Regional Climate Model RCA3:Model description and performance. Tellus 63A, 4-23. Smith, B., Prentice, I. C. and Sykes, M. T. 2001. Representation of vegetation dynamics in modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecol. Biogeog. 10, 621-637 Smith, B., Samuelsson, P., Wramneby, A. & Rummukainen, M. 2011. A model of the coupled dynamics of climate, vegetation and terrestrial ecosystem biogeochemistry for regional applications. Tellus 63A: 87-106.
A climatic handbook for Glacier National Park-with data for Waterton Lakes National Park
Arnold I. Finklin
1986-01-01
A climatic description of the Glacier-Waterton Lakes Park area; mainly covers Glacier. Contains numerous tables, graphs, and maps showing the year-round pattern of climatic elements and 10-day details during fire season. Data analysis includes frequency distributions in addition to average values. Examines relationship of averages to topography, weather correlations...
An Assessment of Factors Affecting the Organizational Climate of Hawaii Elementary Schools.
ERIC Educational Resources Information Center
Amin, Aminullah; Glenn, Charles E.
The problem undertaken by this study was to determine what, if any, relationships exist between the organizational climates of selected schools, as measured by the Organizational Climate Description Questionnaire (OCDQ), and the scores of teachers on Form E of the Rokeach Dogmatism Scale. The study was conducted in eight Hawaii public elementary…
The Relationship Between School Climate and Implementation of an Innovation in Elementary Schools.
ERIC Educational Resources Information Center
Young, I. Phillip; Kasten, Katherine
As part of a larger project on studies of implementation, specifically of Individually Guided Education (IGE), this paper describes the preliminary results of research on school climate, an important factor in retarding or promoting change. A review of the literature on school climate includes a description of Likert and Likert's Profile of a…
Organizational Climate in Schools in White Communities in South Africa: A Validation of the OCDQ-RS.
ERIC Educational Resources Information Center
Mentz, Kobus; Westhuizen, Philip van der
Teacher-principal relations play an important role in creating a positive school climate. This paper describes findings of a study that sought to: (1) determine the reliability of the Organizational Climate Description Questionnaire--Rutgers Secondary (OCDQ-RS) in a South African context, and (2) measure the openness of the organizational climates…
Description of Mixed-Phase Clouds in Weather Forecast and Climate Models
2014-09-30
deficits, leading to freeze-up of both sea ice and the ocean surface. The surface albedo and processes impacting the energy content of the upper ocean...appear key to producing a temporal difference be- tween the freeze-up of the sea - ice surface and adjacent open water. While synoptic conditions, atmos...Leck, 2013: Cloud and boundary layer interactions over the Arctic sea - ice in late summer, Atmos. Chem. Phys. Discuss., 13, 13191-13244, doi
Daniel J. Isaak; Seth J. Wenger; Erin E. Peterson; Jay M. Ver Hoef; David E. Nagel; Charles H. Luce; Steven W. Hostetler; Jason B. Dunham; Brett B. Roper; Sherry P. Wollrab; Gwynne L. Chandler; Dona L. Horan; Sharon Parkes-Payne
2017-01-01
Thermal regimes are fundamental determinants of aquatic ecosystems, which makes description and prediction of temperatures critical during a period of rapid global change. The advent of inexpensive temperature sensors dramatically increased monitoring in recent decades, and although most monitoring is done by individuals for agency-specific purposes, collectively these...
Description of ecological subregions: sections of the conterminous United States
W.H. McNab; D.T. Cleland; J.A. Freeouf; J.E. Keys; G.J. Nowacki; C.A. Carpenter
2007-01-01
Preliminary descriptions are presented for the 190 section ecological units delineated on the U.S. Department of Agriculture Forest Service 2007 map âEcological Subregions: Sections and Subsections of the Conterminous United States.â Brief descriptions of the section map units provide an abstract primarily of the climate, physiography, and geologic substrate that...
NASA Astrophysics Data System (ADS)
Majasalmi, Titta; Eisner, Stephanie; Astrup, Rasmus; Fridman, Jonas; Bright, Ryan M.
2018-01-01
Forest management affects the distribution of tree species and the age class of a forest, shaping its overall structure and functioning and in turn the surface-atmosphere exchanges of mass, energy, and momentum. In order to attribute climate effects to anthropogenic activities like forest management, good accounts of forest structure are necessary. Here, using Fennoscandia as a case study, we make use of Fennoscandic National Forest Inventory (NFI) data to systematically classify forest cover into groups of similar aboveground forest structure. An enhanced forest classification scheme and related lookup table (LUT) of key forest structural attributes (i.e., maximum growing season leaf area index (LAImax), basal-area-weighted mean tree height, tree crown length, and total stem volume) was developed, and the classification was applied for multisource NFI (MS-NFI) maps from Norway, Sweden, and Finland. To provide a complete surface representation, our product was integrated with the European Space Agency Climate Change Initiative Land Cover (ESA CCI LC) map of present day land cover (v.2.0.7). Comparison of the ESA LC and our enhanced LC products (https://doi.org/10.21350/7zZEy5w3) showed that forest extent notably (κ = 0.55, accuracy 0.64) differed between the two products. To demonstrate the potential of our enhanced LC product to improve the description of the maximum growing season LAI (LAImax) of managed forests in Fennoscandia, we compared our LAImax map with reference LAImax maps created using the ESA LC product (and related cross-walking table) and PFT-dependent LAImax values used in three leading land models. Comparison of the LAImax maps showed that our product provides a spatially more realistic description of LAImax in managed Fennoscandian forests compared to reference maps. This study presents an approach to account for the transient nature of forest structural attributes due to human intervention in different land models.
NASA Technical Reports Server (NTRS)
Peng, G.; Meier, W. N.; Scott, D. J.; Savoie, M. H.
2013-01-01
A long-term, consistent, and reproducible satellite-based passive microwave sea ice concentration climate data record (CDR) is available for climate studies, monitoring, and model validation with an initial operation capability (IOC). The daily and monthly sea ice concentration data are on the National Snow and Ice Data Center (NSIDC) polar stereographic grid with nominal 25 km × 25 km grid cells in both the Southern and Northern Hemisphere polar regions from 9 July 1987 to 31 December 2007. The data files are available in the NetCDF data format at http://nsidc.org/data/g02202.html and archived by the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA) under the satellite climate data record program (http://www.ncdc.noaa.gov/cdr/operationalcdrs.html). The description and basic characteristics of the NOAA/NSIDC passive microwave sea ice concentration CDR are presented here. The CDR provides similar spatial and temporal variability as the heritage products to the user communities with the additional documentation, traceability, and reproducibility that meet current standards and guidelines for climate data records. The data set, along with detailed data processing steps and error source information, can be found at http://dx.doi.org/10.7265/N5B56GN3.
Feleke, Fikeremaryam Birara; Berhe, Melaku; Gebru, Getachew; Hoag, Dana
2016-01-01
The livestock sector serves as a foremost source of revenue for rural people, particularly in many developing countries. Among the livestock species, sheep and goats are the main source of livelihood for rural people in Ethiopia; they can quickly multiply, resilient and are easily convertible to cash to meet financial needs of the rural producers. The multiple contributions of sheep and goat and other livestock to rural farmers are however being challenged by climate change and variability. Farmers are responding to the impacts of climate change by adopting different mechanisms, where choices are largely dependent on many factors. This study, therefore, aims to analyze the determinants of choices of adaptation practices to climate change that causes scarcity of feed, heat stress, shortage of water and pasture on sheep and goat production. The study used 318 sample households drawn from potential livestock producing districts representing 3 agro-ecological settings. Data was analyzed using simple descriptive statistical tools, a multivariate probit model and Ordinary Least Squares (OLS). Most of the respondents (98.6 %) noted that climate is changing. Respondents' perception is that climate change is expressed through increased temperature (88 %) and decline in rainfall (73 %) over the last 10 years. The most commonly used adaptation strategy was marketing during forage shock (96.5 %), followed by home feeding (89.6 %). The estimation from the multivariate probit model showed that access to information, farming experience, number of households in one village, distance to main market, income of household, and agro-ecological settings influenced farmers' adaptation choices to climate change. Furthermore, OLS revealed that the adaptation strategies had positive influence on the household income.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Russell, Lynn M.; Somerville, Richard C.J.; Burrows, Susannah
Description of the Project: This project has improved the aerosol formulation in a global climate model by using innovative new field and laboratory observations to develop and implement a novel wind-driven sea ice aerosol flux parameterization. This work fills a critical gap in the understanding of clouds, aerosol, and radiation in polar regions by addressing one of the largest missing particle sources in aerosol-climate modeling. Recent measurements of Arctic organic and inorganic aerosol indicate that the largest source of natural aerosol during the Arctic winter is emitted from crystal structures, known as frost flowers, formed on a newly frozen seamore » ice surface [Shaw et al., 2010]. We have implemented the new parameterization in an updated climate model making it the first capable of investigating how polar natural aerosol-cloud indirect effects relate to this important and previously unrecognized sea ice source. The parameterization is constrained by Arctic ARM in situ cloud and radiation data. The modified climate model has been used to quantify the potential pan-Arctic radiative forcing and aerosol indirect effects due to this missing source. This research supported the work of one postdoc (Li Xu) for two years and contributed to the training and research of an undergraduate student. This research allowed us to establish a collaboration between SIO and PNNL in order to contribute the frost flower parameterization to the new ACME model. One peer-reviewed publications has already resulted from this work, and a manuscript for a second publication has been completed. Additional publications from the PNNL collaboration are expected to follow.« less
NASA Astrophysics Data System (ADS)
Selvam, A. M.
2017-01-01
Dynamical systems in nature exhibit self-similar fractal space-time fluctuations on all scales indicating long-range correlations and, therefore, the statistical normal distribution with implicit assumption of independence, fixed mean and standard deviation cannot be used for description and quantification of fractal data sets. The author has developed a general systems theory based on classical statistical physics for fractal fluctuations which predicts the following. (1) The fractal fluctuations signify an underlying eddy continuum, the larger eddies being the integrated mean of enclosed smaller-scale fluctuations. (2) The probability distribution of eddy amplitudes and the variance (square of eddy amplitude) spectrum of fractal fluctuations follow the universal Boltzmann inverse power law expressed as a function of the golden mean. (3) Fractal fluctuations are signatures of quantum-like chaos since the additive amplitudes of eddies when squared represent probability densities analogous to the sub-atomic dynamics of quantum systems such as the photon or electron. (4) The model predicted distribution is very close to statistical normal distribution for moderate events within two standard deviations from the mean but exhibits a fat long tail that are associated with hazardous extreme events. Continuous periodogram power spectral analyses of available GHCN annual total rainfall time series for the period 1900-2008 for Indian and USA stations show that the power spectra and the corresponding probability distributions follow model predicted universal inverse power law form signifying an eddy continuum structure underlying the observed inter-annual variability of rainfall. On a global scale, man-made greenhouse gas related atmospheric warming would result in intensification of natural climate variability, seen immediately in high frequency fluctuations such as QBO and ENSO and even shorter timescales. Model concepts and results of analyses are discussed with reference to possible prediction of climate change. Model concepts, if correct, rule out unambiguously, linear trends in climate. Climate change will only be manifested as increase or decrease in the natural variability. However, more stringent tests of model concepts and predictions are required before applications to such an important issue as climate change. Observations and simulations with climate models show that precipitation extremes intensify in response to a warming climate (O'Gorman in Curr Clim Change Rep 1:49-59, 2015).
NASA Astrophysics Data System (ADS)
Dickson, N. C.; Gierens, K. M.; Rogers, H. L.; Jones, R. L.
2010-07-01
The global observation, assimilation and prediction in numerical models of ice super-saturated (ISS) regions (ISSR) are crucial if the climate impact of aircraft condensation trails (contrails) is to be fully understood, and if, for example, contrail formation is to be avoided through aircraft operational measures. Given their small scales compared to typical atmospheric model grid sizes, statistical representations of the spatial scales of ISSR are required, in both horizontal and vertical dimensions, if global occurrence of ISSR is to be adequately represented in climate models. This paper uses radiosonde launches made by the UK Meteorological Office, from the British Isles, Gibraltar, St. Helena and the Falkland Islands between January 2002 and December 2006, to investigate the probabilistic occurrence of ISSR. Each radiosonde profile is divided into 50- and 100-hPa pressure layers, to emulate the coarse vertical resolution of some atmospheric models. Then the high resolution observations contained within each thick pressure layer are used to calculate an average relative humidity and an ISS fraction for each individual thick pressure layer. These relative humidity pressure layer descriptions are then linked through a probability function to produce an s-shaped curve which empirically describes the ISS fraction in any average relative humidity pressure layer. Using this empirical understanding of the s-shaped relationship a mathematical model was developed to represent the ISS fraction within any arbitrary thick pressure layer. Two models were developed to represent both 50- and 100-hPa pressure layers with each reconstructing their respective s-shapes within 8-10% of the empirical curves. These new models can be used, to represent the small scale structures of ISS events, in modelled data where only low vertical resolution is available. This will be useful in understanding, and improving the global distribution, both observed and forecasted, of ice super-saturation.
Role of Organizational Climate in Organizational Commitment: The Case of Teaching Hospitals
Bahrami, Mohammad Amin; Barati, Omid; Ghoroghchian, Malake-sadat; Montazer-alfaraj, Razieh; Ranjbar Ezzatabadi, Mohammad
2015-01-01
Objective The commitment of employees is affected by several factors, including factors related to the organizational climate. The aim of this study was to investigate the relationship between organizational commitment of nurses and the organizational climate in hospital settings. Methods A cross-sectional study was conducted in 2014 at two teaching hospitals in Yazd, Iran. A total of 90 nurses in these hospitals participated. We used stratified random sampling of the nursing population. The required data were gathered using two valid questionnaires: Allen and Meyer's organizational commitment standard questionnaire and Halpin and Croft's Organizational Climate Description Questionnaire. Data analysis was done through SPSS 20 statistical software (IBM Corp., Armonk, NY, USA). We used descriptive statistics and Pearson's correlation coefficient for the data analysis. Results The findings indicated a positive and significant correlation between organizational commitment and organizational climate (r = 0.269, p = 0.01). There is also a significant positive relationship between avoidance of organizational climate and affective commitment (r = 0.208, p = 0.049) and between focus on production and normative and continuance commitment (r = 0.308, p = 0.003). Conclusion Improving the organizational climate could be a valuable strategy for improving organizational commitment. PMID:27169007
[The complex plague--reconsiderations of an epidemic from the past].
Moseng, Ole Georg
2007-12-13
Speculations have arisen about the black plague in recent years - was it a disease caused by YERSINIA PESTIS: or something else? Extensive outbreaks in India in the 1890s have formed the basis for descriptions of the plague, both for those who believe that the medieval plagues and modern plague were different diseases and for those who claim that the plague has been one and the same disease throughout history. The plague was more or less defined as a disease in the 1890s, and the understanding of its clinical course and dissemination at the time has uncritically been understood as the general model for spreading of the plague. But plague is a many-faceted disease. It has spread to five continents in modern times, through an array of ecosystems and under widely different climatic conditions. It can also be passed on to man, and from one individual to another, in different ways. The biological conditions that prevailed in India have not been relevant for medieval Norway. The preconditions for spreading of plague epidemics of the past in a Nordic climate must therefore have been different. It can only be expected that contemporary descriptions of historic epidemics are different from those in modern times.
NASA Astrophysics Data System (ADS)
Meyer, Swen; Ludwig, Ralf
2013-04-01
According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. While there is scientific consensus that climate induced changes on the hydrology of Mediterranean regions are presently occurring and are projected to amplify in the future, very little knowledge is available about the quantification of these changes, which is hampered by a lack of suitable and cost effective hydrological monitoring and modeling systems. The European FP7-project CLIMB is aiming to analyze climate induced changes on the hydrology of the Mediterranean Basins by investigating 7 test sites located in the countries Italy, France, Turkey, Tunisia, Gaza and Egypt. CLIMB employs a combination of novel geophysical field monitoring concepts, remote sensing techniques and integrated hydrologic modeling to improve process descriptions and understanding and to quantify existing uncertainties in climate change impact analysis. The Rio Mannu Basin, located in Sardinia; Italy, is one test site of the CLIMB project. The catchment has a size of 472.5 km2, it ranges from 62 to 946 meters in elevation, at mean annual temperatures of 16°C and precipitation of about 700 mm, the annual runoff volume is about 200 mm. The physically based Water Simulation Model WaSiM Vers. 2 (Schulla & Jasper (1999)) was setup to model current and projected future hydrological conditions. The availability of measured meteorological and hydrological data is poor as common to many Mediterranean catchments. The lack of available measured input data hampers the calibration of the model setup and the validation of model outputs. State of the art remote sensing techniques and field measuring techniques were applied to improve the quality of hydrological input parameters. In a field campaign about 250 soil samples were collected and lab-analyzed. Different geostatistical regionalization methods were tested to improve the model setup. The soil parameterization of the model was tested against publically available soil data. Results show a significant improvement of modeled soil moisture outputs. To validate WaSiMs evapotranspiration (ETact) outputs, Landsat TM images were used to calculate the actual monthly mean ETact rates using the triangle method (Jiang and Islam, 1999). Simulated spatial ETact patterns and those derived from remote sensing show a good fit especially for the growing season. WaSiM was driven with the meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. Output results were analyzed for climate induced changes on selected hydrological variables. While the climate projections reveal increased precipitation rates in the spring season, first simulation results show an earlier onset and an increased duration of the dry season, imposing an increased irrigation demand and higher vulnerability of agricultural productivity.
Description of Mixed-Phase Clouds in Weather Forecast and Climate Models
2013-09-30
energy budget and thus the melting and freezing of sea ice , both at present and into the future. RELATED PROJECTS This project is a follow-up...Arctic sea - ice in late summer, Atmos. Chem. Phys. Discuss., 13, 13191-13244, doi: 10.5194/acpd-13-13191-2013. Sotiropoulou, G., M. Tjernström, J. Sedlar...common, by far the most common cloud type over the Arctic, when thermodynamic principles suggest that ice and liquid particles cannot coexist for
The seasonal influence of climate and environment on yellow fever transmission across Africa.
Hamlet, Arran; Jean, Kévin; Perea, William; Yactayo, Sergio; Biey, Joseph; Van Kerkhove, Maria; Ferguson, Neil; Garske, Tini
2018-03-01
Yellow fever virus (YFV) is a vector-borne flavivirus endemic to Africa and Latin America. Ninety per cent of the global burden occurs in Africa where it is primarily transmitted by Aedes spp, with Aedes aegypti the main vector for urban yellow fever (YF). Mosquito life cycle and viral replication in the mosquito are heavily dependent on climate, particularly temperature and rainfall. We aimed to assess whether seasonal variations in climatic factors are associated with the seasonality of YF reports. We constructed a temperature suitability index for YFV transmission, capturing the temperature dependence of mosquito behaviour and viral replication within the mosquito. We then fitted a series of multilevel logistic regression models to a dataset of YF reports across Africa, considering location and seasonality of occurrence for seasonal models, against the temperature suitability index, rainfall and the Enhanced Vegetation Index (EVI) as covariates alongside further demographic indicators. Model fit was assessed by the Area Under the Curve (AUC), and models were ranked by Akaike's Information Criterion which was used to weight model outputs to create combined model predictions. The seasonal model accurately captured both the geographic and temporal heterogeneities in YF transmission (AUC = 0.81), and did not perform significantly worse than the annual model which only captured the geographic distribution. The interaction between temperature suitability and rainfall accounted for much of the occurrence of YF, which offers a statistical explanation for the spatio-temporal variability in transmission. The description of seasonality offers an explanation for heterogeneities in the West-East YF burden across Africa. Annual climatic variables may indicate a transmission suitability not always reflected in seasonal interactions. This finding, in conjunction with forecasted data, could highlight areas of increased transmission and provide insights into the occurrence of large outbreaks, such as those seen in Angola, the Democratic Republic of the Congo and Brazil.
The seasonal influence of climate and environment on yellow fever transmission across Africa
Hamlet, Arran; Perea, William; Yactayo, Sergio; Biey, Joseph; Van Kerkhove, Maria; Ferguson, Neil
2018-01-01
Background Yellow fever virus (YFV) is a vector-borne flavivirus endemic to Africa and Latin America. Ninety per cent of the global burden occurs in Africa where it is primarily transmitted by Aedes spp, with Aedes aegypti the main vector for urban yellow fever (YF). Mosquito life cycle and viral replication in the mosquito are heavily dependent on climate, particularly temperature and rainfall. We aimed to assess whether seasonal variations in climatic factors are associated with the seasonality of YF reports. Methodology/Principal findings We constructed a temperature suitability index for YFV transmission, capturing the temperature dependence of mosquito behaviour and viral replication within the mosquito. We then fitted a series of multilevel logistic regression models to a dataset of YF reports across Africa, considering location and seasonality of occurrence for seasonal models, against the temperature suitability index, rainfall and the Enhanced Vegetation Index (EVI) as covariates alongside further demographic indicators. Model fit was assessed by the Area Under the Curve (AUC), and models were ranked by Akaike’s Information Criterion which was used to weight model outputs to create combined model predictions. The seasonal model accurately captured both the geographic and temporal heterogeneities in YF transmission (AUC = 0.81), and did not perform significantly worse than the annual model which only captured the geographic distribution. The interaction between temperature suitability and rainfall accounted for much of the occurrence of YF, which offers a statistical explanation for the spatio-temporal variability in transmission. Conclusions/Significance The description of seasonality offers an explanation for heterogeneities in the West-East YF burden across Africa. Annual climatic variables may indicate a transmission suitability not always reflected in seasonal interactions. This finding, in conjunction with forecasted data, could highlight areas of increased transmission and provide insights into the occurrence of large outbreaks, such as those seen in Angola, the Democratic Republic of the Congo and Brazil. PMID:29543798
The Ogallala Agro-Climate Tool (Technical Description)
USDA-ARS?s Scientific Manuscript database
A Visual Basic agro-climate application capable of estimating irrigation demand and crop water use over the Ogallala Aquifer region is described here. The application’s meteorological database consists of daily precipitation and temperature data from 141 U.S. Historical Climatology Network stations ...
LPJmL4 - a dynamic global vegetation model with managed land - Part 1: Model description
NASA Astrophysics Data System (ADS)
Schaphoff, Sibyll; von Bloh, Werner; Rammig, Anja; Thonicke, Kirsten; Biemans, Hester; Forkel, Matthias; Gerten, Dieter; Heinke, Jens; Jägermeyr, Jonas; Knauer, Jürgen; Langerwisch, Fanny; Lucht, Wolfgang; Müller, Christoph; Rolinski, Susanne; Waha, Katharina
2018-04-01
This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates - internally consistently - the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL, we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.
An open-access CMIP5 pattern library for temperature and precipitation: description and methodology
NASA Astrophysics Data System (ADS)
Lynch, Cary; Hartin, Corinne; Bond-Lamberty, Ben; Kravitz, Ben
2017-05-01
Pattern scaling is used to efficiently emulate general circulation models and explore uncertainty in climate projections under multiple forcing scenarios. Pattern scaling methods assume that local climate changes scale with a global mean temperature increase, allowing for spatial patterns to be generated for multiple models for any future emission scenario. For uncertainty quantification and probabilistic statistical analysis, a library of patterns with descriptive statistics for each file would be beneficial, but such a library does not presently exist. Of the possible techniques used to generate patterns, the two most prominent are the delta and least squares regression methods. We explore the differences and statistical significance between patterns generated by each method and assess performance of the generated patterns across methods and scenarios. Differences in patterns across seasons between methods and epochs were largest in high latitudes (60-90° N/S). Bias and mean errors between modeled and pattern-predicted output from the linear regression method were smaller than patterns generated by the delta method. Across scenarios, differences in the linear regression method patterns were more statistically significant, especially at high latitudes. We found that pattern generation methodologies were able to approximate the forced signal of change to within ≤ 0.5 °C, but the choice of pattern generation methodology for pattern scaling purposes should be informed by user goals and criteria. This paper describes our library of least squares regression patterns from all CMIP5 models for temperature and precipitation on an annual and sub-annual basis, along with the code used to generate these patterns. The dataset and netCDF data generation code are available at doi:10.5281/zenodo.495632.
NASA Astrophysics Data System (ADS)
Simeone, C.; Maneta, M. P.; Holden, Z. A.; Dobrowski, S.; Sala, A.
2017-12-01
Recent studies indicate that increases in drought stress due to climate change will increase forest mortality across the western U.S. Although ecohydrologic models used to study regional hydrologic stress response in forests have made rapid advances in recent years, they often incorporate simplified descriptions of the local hydrology, do not implement an explicit description of plant hydraulics, and do not permit to study the tradeoffs between frequency, intensity, and accumulation of hydrologic stress in vegetation. We use the spatially-distributed, mechanistic ecohydrologic model Ech2o, which effectively captures spatial variations in both hydrology, energy exchanges, and regional climate to simulate high-resolution tree hydraulics, estimating soil and leaf water potential, tree effective water conductance, and percent loss of conductivity in the xylem (PLC) at 250 meter resolution and sub-daily timestep across a topographically complex landscape. Tree hydraulics are simulated assuming a diffusive process in the soil-tree-atmosphere continuum. We use PLC to develop a vegetation dynamic stress index that scales plant-level processes to the landscape scale, and that takes into account the temporal accumulation of instantaneous hydraulic stress, growing season length, frequency and duration of drought periods, and plant drought tolerance. The resulting index is interpreted as the probability of drought induced tree mortality in a given location during the simulated period. We apply this index to regions of Northern Idaho and Western Montana. Results show that drought stress is highly spatially variable, sensitive to local-scale hydrologic and atmospheric conditions, and responsive to the recovery rate from individual hydraulic stress episodes.
Near-surface turbulence as a missing link in modeling evapotranspiration-soil moisture relationships
NASA Astrophysics Data System (ADS)
Haghighi, Erfan; Kirchner, James W.
2017-07-01
Despite many efforts to develop evapotranspiration (ET) models with improved parametrizations of resistance terms for water vapor transfer into the atmosphere, estimates of ET and its partitioning remain prone to bias. Much of this bias could arise from inadequate representations of physical interactions near nonuniform surfaces from which localized heat and water vapor fluxes emanate. This study aims to provide a mechanistic bridge from land-surface characteristics to vertical transport predictions, and proposes a new physically based ET model that builds on a recently developed bluff-rough bare soil evaporation model incorporating coupled soil moisture-atmospheric controls. The newly developed ET model explicitly accounts for (1) near-surface turbulent interactions affecting soil drying and (2) soil-moisture-dependent stomatal responses to atmospheric evaporative demand that influence leaf (and canopy) transpiration. Model estimates of ET and its partitioning were in good agreement with available field-scale data, and highlight hidden processes not accounted for by commonly used ET schemes. One such process, nonlinear vegetation-induced turbulence (as a function of vegetation stature and cover fraction) significantly influences ET-soil moisture relationships. Our results are particularly important for water resources and land use planning of semiarid sparsely vegetated ecosystems where soil surface interactions are known to play a critical role in land-climate interactions. This study potentially facilitates a mathematically tractable description of the strength (i.e., the slope) of the ET-soil moisture relationship, which is a core component of models that seek to predict land-atmosphere coupling and its feedback to the climate system in a changing climate.
Regional reanalysis without local data: Exploiting the downscaling paradigm
NASA Astrophysics Data System (ADS)
von Storch, Hans; Feser, Frauke; Geyer, Beate; Klehmet, Katharina; Li, Delei; Rockel, Burkhardt; Schubert-Frisius, Martina; Tim, Nele; Zorita, Eduardo
2017-08-01
This paper demonstrates two important aspects of regional dynamical downscaling of multidecadal atmospheric reanalysis. First, that in this way skillful regional descriptions of multidecadal climate variability may be constructed in regions with little or no local data. Second, that the concept of large-scale constraining allows global downscaling, so that global reanalyses may be completed by additions of consistent detail in all regions of the world. Global reanalyses suffer from inhomogeneities. However, their large-scale componenst are mostly homogeneous; Therefore, the concept of downscaling may be applied to homogeneously complement the large-scale state of the reanalyses with regional detail—wherever the condition of homogeneity of the description of large scales is fulfilled. Technically, this can be done by dynamical downscaling using a regional or global climate model, which's large scales are constrained by spectral nudging. This approach has been developed and tested for the region of Europe, and a skillful representation of regional weather risks—in particular marine risks—was identified. We have run this system in regions with reduced or absent local data coverage, such as Central Siberia, the Bohai and Yellow Sea, Southwestern Africa, and the South Atlantic. Also, a global simulation was computed, which adds regional features to prescribed global dynamics. Our cases demonstrate that spatially detailed reconstructions of the climate state and its change in the recent three to six decades add useful supplementary information to existing observational data for midlatitude and subtropical regions of the world.
Retrieval of effective cloud field parameters from radiometric data
NASA Astrophysics Data System (ADS)
Paulescu, Marius; Badescu, Viorel; Brabec, Marek
2017-06-01
Clouds play a key role in establishing the Earth's climate. Real cloud fields are very different and very complex in both morphological and microphysical senses. Consequently, the numerical description of the cloud field is a critical task for accurate climate modeling. This study explores the feasibility of retrieving the effective cloud field parameters (namely the cloud aspect ratio and cloud factor) from systematic radiometric measurements at high frequency (measurement is taken every 15 s). Two different procedures are proposed, evaluated, and discussed with respect to both physical and numerical restrictions. None of the procedures is classified as best; therefore, the specific advantages and weaknesses are discussed. It is shown that the relationship between the cloud shade and point cloudiness computed using the estimated cloud field parameters recovers the typical relationship derived from measurements.
Jeton, A.E.; Dettinger, M.D.; Smith, J. LaRue
1996-01-01
Precipitation-runoff models of the East Fork Carson and North Fork American Rivers were developed and calibrated for use in evaluating the sensitivity of streamflow in the north-central Sierra Nevada to climate change. The East Fork Carson River drains part of the rain-shadowed, eastern slope of the Sierra Nevada and is generally higher than the North Fork American River, which drains the wetter, western slope. First, a geographic information system was developed to describe the spatial variability of basin characteristics and to help estimate model parameters. The result was a partitioning of each basin into noncontiguous, but hydrologically uniform, land units. Hydrologic descriptions of these units were developed and the Precipitation- Runoff Modeling System (PRMS) was used to simulate water and energy balances for each unit in response to daily weather conditions. The models were calibrated and verified using historical streamflows over 22-year (Carson River) and 42-year (American River) periods. Simulated annual streamflow errors average plus 10 percent of the observed flow for the East Fork Carson River basin and plus 15 percent for the North Fork American River basin. Interannual variability is well simulated overall, but, at daily scales, wet periods are simulated more accurately than drier periods. The simulated water budgets for the two basins are significantly different in seasonality of streamflow, sublimation, evapotranspiration, and snowmelt. The simulations indicate that differences in snowpack and snowmelt timing can play pervasive roles in determining the sensitivity of water resources to climate change, in terms of both resource availability and amount. The calibrated models were driven by more than 25 hypothetical climate-change scenarios, each 100 years long. The scenarios were synthesized and spatially disaggregated by methods designed to preserve realistic daily, monthly, annual, and spatial statistics. Simulated streamflow timing was not very sensitive to changes in mean precipitation, but was sensitive to changes in mean temperatures. Changes in annual streamflow amounts were amplified reflections of imposed mean precipitation changes, with especially large responses to wetter climates. In contrast, streamflow amount was surprisingly insensitive to mean temperature changes as a result of temporal links between peak snowmelt and the beginning of warm-season evapotranspiration. Comparisons of simulations driven by temporally detailed climate-model changes in which mean temperature changes vary from month to month and simulations in which uniform climate changes were imposed throughout the year indicate that the snowpack accumulates the influences of short-term conditions so that season average climate changes were more important than shorter term changes.
NASA Technical Reports Server (NTRS)
Starr, D. OC. (Editor); Melfi, S. Harvey (Editor)
1991-01-01
The proposed GEWEX Water Vapor Project (GVaP) addresses fundamental deficiencies in the present understanding of moist atmospheric processes and the role of water vapor in the global hydrologic cycle and climate. Inadequate knowledge of the distribution of atmospheric water vapor and its transport is a major impediment to progress in achieving a fuller understanding of various hydrologic processes and a capability for reliable assessment of potential climatic change on global and regional scales. GVap will promote significant improvements in knowledge of atmospheric water vapor and moist processes as well as in present capabilities to model these processes on global and regional scales. GVaP complements a number of ongoing and planned programs focused on various aspects of the hydrologic cycle. The goal of GVaP is to improve understanding of the role of water vapor in meteorological, hydrological, and climatological processes through improved knowledge of water vapor and its variability on all scales. A detailed description of the GVaP is presented.
The Global Ocean Data Assimilation Experiment (GODAE)
NASA Astrophysics Data System (ADS)
Le Traon, P.; Smith, N.
The Global Ocean Data Assimilation Experiment (GODAE) will conduct its main demonstration phase from 2003 to 2005. From 2003 to 2005, operational and research institutions from Australia, Japan, United States, United Kingdom, France and Norway will be performing global oceanic data assimilation and ocean forecast in order to provide regular and comprehensive descriptions of ocean fields such as temperature, salinity and currents at high temporal and spatial resolution. A central objective of GODAE is to provide an integrated description that combines remote sensing data, in-situ data and models through data assimilation. Climate and seasonal forecasting, navy applications, marine safety, fisheries, the offshore industry and management of shelf/coastal areas are among the expected beneficiaries of GODAE. The integrated description of the ocean that GODAE will provide will also be highly beneficial to the research community. An overview of GODAE will be given; we will detail the GODAE objectives and strategy and the way it is implemented as an international experiment. Results from first pre-operational or prototype systems will finally be shown.
James M. Vose; David L. Peterson; Toral Patel-Weynand
2012-01-01
This report is a scientific assessment of the current condition and likely future condition of forest resources in the United States relative to climatic variability and change. It serves as the U.S. Forest Service forest sector technical report for the National Climate Assessment and includes descriptions of key regional issues and examples of a risk-based framework...
Nurses’ perception of ethical climate and job satisfaction
Borhani, Fariba; Jalali, Tayebeh; Abbaszadeh, Abbas; Haghdoost, Ali Akbar; Amiresmaili, Mohammadreza
2012-01-01
The high turnover of nurses has become a universal issue. The manner in which nurses view their organization’s ethical climate has direct bearing on their job satisfaction. There is little empirical evidence confirming a relationship between different sorts of ethical climate within organizations and job satisfaction in Iran. The aim of this study was to determine the correlation between nurses’ perception of ethical climate and job satisfaction in the Teaching Hospital of Kerman University of Medical Sciences. A descriptive analytical design was used in this study. The sample consisted of 275 nurses working in 4 hospitals affiliated with the Kerman University of Medical Sciences. The instruments used in this study included a demographic questionnaire, Ethical Climate Questionnaire (ECQ), and Job Satisfaction Scale (JS). Data analysis was carried out using Pearson’s correlation, one-way ANOVA, T-test and descriptive statistic through Statistical Package for Social Science (SPSS), version 16. Across the five dimensions of ECQ the highest mean score pertained to professionalism (mean = 13.45±3.68), followed by rules climate (mean = 13.41±4.01), caring climate (mean = 12.92±3.95), independence climate (mean = 11.35±3.88), and instrumental climate (mean = 8.93±2.95). The results showed a positive correlation among ethical climate type of: professionalism (p=0.001), rules (p=0.045), caring (p=0.000), independence (p=0.000) with job satisfaction, and no correlation was found between instrumental climate and job satisfaction. The result of this research indicated a positive correlation among professionalism, caring, rules, independence climate and job satisfaction. Therefore managers of hospitals can promote nurses’ job satisfaction by providing ethics training programs that establish a working team and a culture that strengthens team spirit among nurses. PMID:23908759
Conceptualizing Organizational Climates. Research Report No. 7.
ERIC Educational Resources Information Center
Schneider, Benjamin
Part 1 of this paper presents some logical and conceptual distinctions between job satisfaction and organizational climate, the former being viewed as micro, evaluative, individual perceptions of personal events and experiences the latter as macro, relatively descriptive, organizational level perceptions that are abstractions of organizational…
OIL SPILL RESPONSE SCENARIOS FOR REMOTE ARCTIC ENVIRONMENTS
Special problems occur during oil spill cleanup in remote inland areas in cold climates. In Alaska these problems result from the harsh climate, the unusual terrain features, and the special problems of spills along swift rivers. The analysis begins with a description of the envi...
Process evaluation of sea salt aerosol concentrations at remote marine locations
NASA Astrophysics Data System (ADS)
Struthers, H.; Ekman, A. M.; Nilsson, E. D.
2011-12-01
Sea salt, an important natural aerosol, is generated by bubbles bursting at the surface of the ocean. Sea salt aerosol contributes significantly to the global aerosol burden and radiative budget and are a significant source of cloud condensation nuclei in remote marine areas (Monahan et al., 1986). Consequently, changes in marine aerosol abundance is expected to impact on climate forcing. Estimates of the atmospheric burden of sea salt aerosol mass derived from chemical transport and global climate models vary greatly both in the global total and the spatial distribution (Texor et al. 2006). This large uncertainty in the sea salt aerosol distribution in turn contributes to the large uncertainty in the current estimates of anthropogenic aerosol climate forcing (IPCC, 2007). To correctly attribute anthropogenic climate change and to veraciously project future climate, natural aerosols including sea salt must be understood and accurately modelled. In addition, the physical processes that determine the sea salt aerosol concentration are susceptible to modification due to climate change (Carslaw et al., 2010) which means there is the potential for feedbacks within the climate/aerosol system. Given the large uncertainties in sea salt aerosol modelling, there is an urgent need to evaluate the process description of sea salt aerosols in global models. An extremely valuable source of data for model evaluation is the long term measurements of PM10 sea salt aerosol mass available from a number of remote marine observation sites around the globe (including the GAW network). Sea salt aerosol concentrations at remote marine locations depend strongly on the surface exchange (emission and deposition) as well as entrainment or detrainment to the free troposphere. This suggests that the key parameters to consider in any analysis include the sea surface water temperature, wind speed, precipitation rate and the atmospheric stability. In this study, the sea salt aerosol observations are analysed to quantify the key sensitivities of the processes connecting the physical drivers of sea salt aerosol to the mass tendency. The analysis employs a semi-empirical model based on the time-tendency of the aerosol mass. This approach of focusing on the time-tendency of the sea salt aerosol concentration provides a framework for the process evaluation of sea salt aerosol concentrations in global models. The same analysis methodology can be applied to output from global models. A process of comparing the sensitivity parameters derived from observations and models will reveal model inadequacies and thus guide model improvements. Carslaw, K. S., Boucher, O., Spracklen, D. V., Mann G. W., Rae, J. G. L, Woodward, S., Kulmala, M. (2010). Atmos. Chem. Phys., 10, 1701-1737 IPCC (2007). Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Solomon, S., D. Monahan, E. C., Spiel, D. E., Davidson, K. L. (1986) Oceanic Whitecaps ed. Monahan E. C. & MacNiochaill, D. Reidel, Norwell, Mass. Texor, C., et al. (2006) Atmos. Chem. Phys., 6, 1777-1813.
NASA Technical Reports Server (NTRS)
Gregory, Kathryn M.; Chase, Clement G
1994-01-01
New paleobotanical data suggest that in the late Eocene the erosion surface which capped the Front Range, Colorado was 2.2-2.3 km in elevation, which is similar to the 2.5-km present elevation of surface remnants. This estimated elevation casts doubt on the conventional belief that the low-relief geomorphic surface was formed by lateral planation of streams to a base level not much higher than sea level and that the present deeply incised canyons must represent Neogene uplift of Colorado. Description of the surface, calculations of sediment volume, and isostatic balance and fluvial landsculpting models demonstrate that while the high elevation of the erosion surface was due to tectonic forces, its smoothness was mostly a result of climatic factors. A sediment balance calculated for the Front Range suggests that from 2 to 4 km of material were eroded by the late Eocene, consistent with fission track ages. This amount of erosion would remove a significant portionof the 7 km of Laramide upper crustal thickening. Isostatic modeling implies that the 2.2-3.3 km elevation was most likely created by lower crustal thickening during the Laramide. A numerical model of fluvial erosion and deposition suggests a way that a late Eocene surface could have formed at this high elevation without incision. A humid climate with a preponderance of small storm events will diffusively smooth topography and is a possible mechanism for formation oflow-relief, high-level surfaces. Paleoclimate models suggest a lack of large strom events in the late Eocene because of cool sea surface temperatures in the equatorial region. Return to a drier but stormier climate post-Eocene could have caused the incision of the surface by young canyons. By this interpretation, regional erosion surfaces may represent regional climatic rather than tectonic conditions.
York, L; Heffernan, C; Rymer, C; Panda, N
2017-05-01
In the global South, dairying is often promoted as a means of poverty alleviation. Yet, under conditions of climate warming, little is known regarding the ability of small-scale dairy producers to maintain production and/or the robustness of possible adaptation options in meeting the challenges presented, particularly heat stress. The authors created a simple, deterministic model to explore the influence of breed and heat stress relief options on smallholder dairy farmers in Odisha, India. Breeds included indigenous Indian (non-descript), low-grade Jersey crossbreed and high-grade Jersey crossbreed. Relief strategies included providing shade, fanning and bathing. The impact of predicted critical global climate parameters, a 2°C and 4°C temperature rise were explored. A feed price scenario was modelled to illustrate the importance of feed in impact estimation. Feed costs were increased by 10% to 30%. Across the simulations, high-grade Jersey crossbreeds maintained higher milk yields, despite being the most sensitive to the negative effects of temperature. Low-capital relief strategies were the most effective at reducing heat stress impacts on household income. However, as feed costs increased the lower-grade Jersey crossbreed became the most profitable breed. The high-grade Jersey crossbreed was only marginally (4.64%) more profitable than the indigenous breed. The results demonstrate the importance of understanding the factors and practical trade-offs that underpin adaptation. The model also highlights the need for hot-climate dairying projects and programmes to consider animal genetic resources alongside environmentally sustainable adaptation measures for greatest poverty impact.
NASA Astrophysics Data System (ADS)
Maibach, E.; Leiserowitz, A.; Gould, R.
2013-12-01
Large numbers of Americans mistakenly believe that there is disagreement among the experts about the reality of climate change. For example, in our nationally representative survey conducted in April 2013, only 42% of respondents reported 'most scientists think global warming is happening;' conversely, 33% reported 'there is a lot of disagreement among scientists about whether or not global warming is happening,' and an additional 20% responded they 'don't know enough to say.' Our research has also shown that this common misperception is highly consequential: people who misunderstand the scientific consensus are less convinced that climate change is occurring, is human-caused, serious, and solvable; they are also less likely to support societal responses to address the problem. In this paper, we will present the results of a series of randomized controlled message experiments conducted to determine the most effective means of conveying the extent of the scientific consensus about human-caused climate change. The variables tested include quantitative vs. qualitative consensus descriptions, more vs. less precise descriptions, contextualizing metaphors, graphical representations, and explanations regarding why people may have developed a misperception. The findings from this formative research are being used to create a communication campaign that will be launched in fall 2013 by a leading American scientific society prior to the AGU Annual Meeting. A full description of the campaign will be presented.
A glossary for carbon dioxide and climate
DOE Office of Scientific and Technical Information (OSTI.GOV)
Millemann, R.E.
1988-03-01
This glossary contains definitions of selected CO/sub 2/-related terms as well as tables containing information related to CO/sub 2/climate. Each term is deined first, emphasizing its relationship to CO/sub 2/ and climate, and then for many of the terms the definition is followed by a more detailed description. References to the literature from which the definitions were taken are listed at the end of the Glossary
Sources of global climate data and visualization portals
Douglas, David C.
2014-01-01
Climate is integral to the geophysical foundation upon which ecosystems are structured. Knowledge about mechanistic linkages between the geophysical and biological environments is essential for understanding how global warming may reshape contemporary ecosystems and ecosystem services. Numerous global data sources spanning several decades are available that document key geophysical metrics such as temperature and precipitation, and metrics of primary biological production such as vegetation phenology and ocean phytoplankton. This paper provides an internet directory to portals for visualizing or servers for downloading many of the more commonly used global datasets, as well as a description of how to write simple computer code to efficiently retrieve these data. The data are broadly useful for quantifying relationships between climate, habitat availability, and lower-trophic-level habitat quality - especially in Arctic regions where strong seasonality is accompanied by intrinsically high year-to-year variability. If defensible linkages between the geophysical (climate) and the biological environment can be established, general circulation model (GCM) projections of future climate conditions can be used to infer future biological responses. Robustness of this approach is, however, complicated by the number of direct, indirect, or interacting linkages involved. For example, response of a predator species to climate change will be influenced by the responses of its prey and competitors, and so forth throughout a trophic web. The complexities of ecological systems warrant sensible and parsimonious approaches for assessing and establishing the role of natural climate variability in order to substantiate inferences about the potential effects of global warming.
NASA Astrophysics Data System (ADS)
Vico, G.; Weih, M.
2014-12-01
Autumn-sown crops act as winter cover crop, reducing soil erosion and nutrient leaching, while potentially providing higher yields than spring varieties in many environments. Nevertheless, overwintering crops are exposed for longer periods to the vagaries of weather conditions. Adverse winter conditions, in particular, may negatively affect the final yield, by reducing crop survival or its vigor. The net effect of the projected shifts in climate is unclear. On the one hand, warmer temperatures may reduce the frequency of low temperatures, thereby reducing damage risk. On the other hand, warmer temperatures, by reducing plant acclimation level and the amount and duration of snow cover, may increase the likelihood of damage. Thus, warmer climates may paradoxically result in more extensive low temperature damage and reduced viability for overwintering plants. The net effect of a shift in climate is explored by means of a parsimonious probabilistic model, based on a coupled description of air temperature, snow cover, and crop tolerable temperature. Exploiting an extensive dataset of winter wheat responses to low temperature exposure, the risk of winter damage occurrence is quantified under conditions typical of northern temperate latitudes. The full spectrum of variations expected with climate change is explored, quantifying the joint effects of alterations in temperature averages and their variability as well as shifts in precipitation. The key features affecting winter wheat vulnerability to low temperature damage under future climates are singled out.
NASA Technical Reports Server (NTRS)
Fronzek, Stefan; Pirttioja, Nina; Carter, Timothy R.; Bindi, Marco; Hoffmann, Holger; Palosuo, Taru; Ruiz-Ramos, Margarita; Tao, Fulu; Trnka, Miroslav; Acutis, Marco;
2017-01-01
Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.
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.
Research strategies for addressing uncertainties
Busch, David E.; Brekke, Levi D.; Averyt, Kristen; Jardine, Angela; Welling, Leigh; Garfin, Gregg; Jardine, Angela; Merideth, Robert; Black, Mary; LeRoy, Sarah
2013-01-01
Research Strategies for Addressing Uncertainties builds on descriptions of research needs presented elsewhere in the book; describes current research efforts and the challenges and opportunities to reduce the uncertainties of climate change; explores ways to improve the understanding of changes in climate and hydrology; and emphasizes the use of research to inform decision making.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-08-13
... to further declines through stochastic wildfire events, spread of the nonnative grasses, and climate... descriptions predict the annual production (pounds per acre) of plant groups (grass/grass-like, forbs, shrub... than fewer numbers of shrubs and perennial grasses. Therefore, although an ecological site description...
NASA Astrophysics Data System (ADS)
Hülse, Dominik; Arndt, Sandra; Ridgwell, Andy; Wilson, Jamie
2016-04-01
The ocean-sediment system, as the biggest carbon reservoir in the Earth's carbon cycle, plays a crucial role in regulating atmospheric carbon dioxide concentrations and climate. Therefore, it is essential to constrain the importance of marine carbon cycle feedbacks on global warming and ocean acidification. Arguably, the most important single component of the ocean's carbon cycle is the so-called "biological carbon pump". It transports carbon that is fixed in the light-flooded surface layer of the ocean to the deep ocean and the surface sediment, where it is degraded/dissolved or finally buried in the deep sediments. Over the past decade, progress has been made in understanding different factors that control the efficiency of the biological carbon pump and their feedbacks on the global carbon cycle and climate (i.e. ballasting = ocean acidification feedback; temperature dependant organic matter degradation = global warming feedback; organic matter sulphurisation = anoxia/euxinia feedback). Nevertheless, many uncertainties concerning the interplay of these processes and/or their relative significance remain. In addition, current Earth System Models tend to employ empirical and static parameterisations of the biological pump. As these parametric representations are derived from a limited set of present-day observations, their ability to represent carbon cycle feedbacks under changing climate conditions is limited. The aim of my research is to combine past carbon cycling information with a spatially resolved global biogeochemical model to constrain the functioning of the biological pump and to base its mathematical representation on a more mechanistic approach. Here, I will discuss important aspects that control the efficiency of the ocean's biological carbon pump, review how these processes of first order importance are mathematically represented in existing Earth system Models of Intermediate Complexity (EMIC) and distinguish different approaches to approximate biogeochemical processes in the sediments. The performance of the respective mathematical representations in constraining the importance of carbon pump feedbacks on marine biogeochemical dynamics is then compared and evaluated under different extreme climate scenarios (e.g. OAE2, Eocene) using the Earth system model 'GENIE' and proxy records. The compiled mathematical descriptions and the model results underline the lack of a complete and mechanistic framework to represent the short-term carbon cycle in most EMICs which seriously limits the ability of these models to constrain the response of the ocean's carbon cycle to past and in particular future climate change. In conclusion, this presentation will critically evaluate the approaches currently used in marine biogeochemical modelling and outline key research directions concerning model development in the future.
Psychometric properties of the Persian version of the “Hospital Ethical Climate Survey”
Khalesi, Nader; Arabloo, Jalal; Khosravizadeh, Omid; Taghizadeh, Sanaz; Heyrani, Ali; Ebrahimian, Abbasali
2014-01-01
In order to improve the ethical climate in health care organizations, it is important to apply a valid measure. This study aimed to investigate the psychometric properties of the Persian version of the Hospital Ethical Climate Survey (HECS) and to assess nurses’ perceptions of the ethical climate in teaching hospitals of Iran. A cross-sectional study of randomly selected nurses (n = 187) was conducted in three teaching general hospitals of Tehran, capital of Iran. Olson’s Hospital Ethical Climate Survey (HECS), a self-administered questionnaire, was used to assess the nurses’ perceptions of the hospital ethical climate. Descriptive statistics, confirmatory factor analysis (CFA), internal consistency, and correlation were used to analyze the data. CFA showed acceptable model fit: an standardized root mean square residual (SRMR) of 0.064, an non-normalized fit index (NNFI) of 0.96, a comparative fit index (CFI) of 0.96, and an root mean square error of approximation (RMSEA) of 0.075. The Cronbach’s alpha values were acceptable and ranging from 0.69 to 0.85. The overall Cronbach’s alpha coefficient was 0.94. The factor loadings for all ethical climate items were between 0.50 and 0.80, which revealed good structure of the Persian version of the HECS. Survey findings showed that the “managers” subscale had the highest score and the subscale of “doctors” had the lowest score. This study shows that the Persian version of the HECS is a valid and reliable instrument for measuring nurses’ perceptions of the ethical climate in hospitals of Iran PMID:25512834
CRYSTAL: The Cirrus Regional Study of Tropical Anvils and Layers
NASA Technical Reports Server (NTRS)
Delnore, Victor E.; Cox, Stephen K.; Curran, Robert J.
1999-01-01
CRYSTAL the Cirrus Regional Study of Tropical Anvils and Layers is part of the ongoing series of field experiments to study clouds and their impact on world weather and climate, and will attempt to improve the application of cloud effects in global climate models. CRYSTAL is being planned as two parts: a limited CRYSTAL field campaign in 2001 to examine towering clouds and anvil genesis over the Everglades of Florida, and the main CRYSTAL field campaign in the summer of 2003 in the Tropical Western Pacific. The latter is timed to take advantage of several cloud measurement satellites that will be operational at that time. This paper discusses some of the issues to be addressed in CRYSTAL, gives a brief description of the research plan, and describes its relationship to other important field experiments.
NASA Astrophysics Data System (ADS)
Duane, Gregory S.; Grabow, Carsten; Selten, Frank; Ghil, Michael
2017-12-01
The synchronization of loosely coupled chaotic systems has increasingly found applications to large networks of differential equations and to models of continuous media. These applications are at the core of the present Focus Issue. Synchronization between a system and its model, based on limited observations, gives a new perspective on data assimilation. Synchronization among different models of the same system defines a supermodel that can achieve partial consensus among models that otherwise disagree in several respects. Finally, novel methods of time series analysis permit a better description of synchronization in a system that is only observed partially and for a relatively short time. This Focus Issue discusses synchronization in extended systems or in components thereof, with particular attention to data assimilation, supermodeling, and their applications to various areas, from climate modeling to macroeconomics.
Duane, Gregory S; Grabow, Carsten; Selten, Frank; Ghil, Michael
2017-12-01
The synchronization of loosely coupled chaotic systems has increasingly found applications to large networks of differential equations and to models of continuous media. These applications are at the core of the present Focus Issue. Synchronization between a system and its model, based on limited observations, gives a new perspective on data assimilation. Synchronization among different models of the same system defines a supermodel that can achieve partial consensus among models that otherwise disagree in several respects. Finally, novel methods of time series analysis permit a better description of synchronization in a system that is only observed partially and for a relatively short time. This Focus Issue discusses synchronization in extended systems or in components thereof, with particular attention to data assimilation, supermodeling, and their applications to various areas, from climate modeling to macroeconomics.
Assessment of mid-latitude atmospheric variability in CMIP5 models using a process oriented-metric
NASA Astrophysics Data System (ADS)
Di Biagio, Valeria; Calmanti, Sandro; Dell'Aquila, Alessandro; Ruti, Paolo
2013-04-01
We compare, for the period 1962-2000, an estimate of the northern hemisphere mid-latitude winter atmospheric variability according several global climate models included in the fifth phase of the Climate Model Intercomparison Project (CMIP5) with the results of the models belonging to the previous CMIP3 and with the NCEP-NCAR reanalysis. We use the space-time Hayashi spectra of the 500hPa geopotential height fields to characterize the variability of atmospheric circulation regimes and we introduce an ad hoc integral measure of the variability observed in the Northern Hemisphere on different spectral sub-domains. The overall performance of each model is evaluated by considering the total wave variability as a global scalar measure of the statistical properties of different types of atmospheric disturbances. The variability associated to eastward propagating baroclinic waves and to planetary waves is instead used to describe the performance of each model in terms of specific physical processes. We find that the two model ensembles (CMIP3 and CMIP5) do not show substantial differences in the description of northern hemisphere winter mid-latitude atmospheric variability, although some CMIP5 models display performances superior to their previous versions implemented in CMIP3. Preliminary results for the 21th century RCP 4.5 scenario will be also discussed for the CMIP5 models.
D. J. Isaak; S. Wollrab; D. Horan; G. Chandler
2011-01-01
Thermal regimes in rivers and streams are fundamentally important to aquatic ecosystems and are expected to change in response to climate forcing as the Earthâs temperature warms. Description and attribution of stream temperature changes are key to understanding how these ecosystems may be affected by climate change, but difficult given the rarity of long-term...
Glossary: Carbon dioxide and climate
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1990-08-01
This Glossary contains definitions of selected CO{sub 2}-related terms as well as tables containing information related to CO{sub 2} and climate. Each term is defined with an emphasis on its relationship to CO{sub 2} and climate. Many of the definitions are then followed by a more detailed description of the term and its use. References to the literature from which the definitions were taken are listed at the end of the Glossary.
Gazica, Michele W; Spector, Paul E
2016-01-01
Safety climate, violence prevention climate, and civility climate were independently developed and linked to domain-specific workplace hazards, although all three were designed to promote the physical and psychological safety of workers. To test domain specificity between conceptually related workplace climates and relevant workplace hazards. Data were collected from 368 persons employed in various industries and descriptive statistics were calculated for all study variables. Correlational and relative weights analyses were used to test for domain specificity. The three climate domains were similarly predictive of most workplace hazards, regardless of domain specificity. This study suggests that the three climate domains share a common higher order construct that may predict relevant workplace hazards better than any of the scales alone.
Using palaeoclimate data to improve models of the Antarctic Ice Sheet
NASA Astrophysics Data System (ADS)
Phipps, Steven; King, Matt; Roberts, Jason; White, Duanne
2017-04-01
Ice sheet models are the most descriptive tools available to simulate the future evolution of the Antarctic Ice Sheet (AIS), including its contribution towards changes in global sea level. However, our knowledge of the dynamics of the coupled ice-ocean-lithosphere system is inevitably limited, in part due to a lack of observations. Furthemore, to build computationally efficient models that can be run for multiple millennia, it is necessary to use simplified descriptions of ice dynamics. Ice sheet modelling is therefore an inherently uncertain exercise. The past evolution of the AIS provides an opportunity to constrain the description of physical processes within ice sheet models and, therefore, to constrain our understanding of the role of the AIS in driving changes in global sea level. We use the Parallel Ice Sheet Model (PISM) to demonstrate how palaeoclimate data can improve our ability to predict the future evolution of the AIS. A 50-member perturbed-physics ensemble is generated, spanning uncertainty in the parameterisations of three key physical processes within the model: (i) the stress balance within the ice sheet, (ii) basal sliding and (iii) calving of ice shelves. A Latin hypercube approach is used to optimally sample the range of uncertainty in parameter values. This perturbed-physics ensemble is used to simulate the evolution of the AIS from the Last Glacial Maximum ( 21,000 years ago) to present. Palaeoclimate records are then used to determine which ensemble members are the most realistic. This allows us to use data on past climates to directly constrain our understanding of the past contribution of the AIS towards changes in global sea level. Critically, it also allows us to determine which ensemble members are likely to generate the most realistic projections of the future evolution of the AIS.
Using paleoclimate data to improve models of the Antarctic Ice Sheet
NASA Astrophysics Data System (ADS)
King, M. A.; Phipps, S. J.; Roberts, J. L.; White, D.
2016-12-01
Ice sheet models are the most descriptive tools available to simulate the future evolution of the Antarctic Ice Sheet (AIS), including its contribution towards changes in global sea level. However, our knowledge of the dynamics of the coupled ice-ocean-lithosphere system is inevitably limited, in part due to a lack of observations. Furthemore, to build computationally efficient models that can be run for multiple millennia, it is necessary to use simplified descriptions of ice dynamics. Ice sheet modeling is therefore an inherently uncertain exercise. The past evolution of the AIS provides an opportunity to constrain the description of physical processes within ice sheet models and, therefore, to constrain our understanding of the role of the AIS in driving changes in global sea level. We use the Parallel Ice Sheet Model (PISM) to demonstrate how paleoclimate data can improve our ability to predict the future evolution of the AIS. A large, perturbed-physics ensemble is generated, spanning uncertainty in the parameterizations of four key physical processes within ice sheet models: ice rheology, ice shelf calving, and the stress balances within ice sheets and ice shelves. A Latin hypercube approach is used to optimally sample the range of uncertainty in parameter values. This perturbed-physics ensemble is used to simulate the evolution of the AIS from the Last Glacial Maximum ( 21,000 years ago) to present. Paleoclimate records are then used to determine which ensemble members are the most realistic. This allows us to use data on past climates to directly constrain our understanding of the past contribution of the AIS towards changes in global sea level. Critically, it also allows us to determine which ensemble members are likely to generate the most realistic projections of the future evolution of the AIS.
Marsh, Erin E.; Anderson, Eric D.
2011-01-01
Nickel-cobalt (Ni-Co) laterite deposits are an important source of nickel (Ni). Currently, there is a decline in magmatic Ni-bearing sulfide lode deposit resources. New efforts to develop an alternative source of Ni, particularly with improved metallurgy processes, make the Ni-Co laterites an important exploration target in anticipation of the future demand for Ni. This deposit model provides a general description of the geology and mineralogy of Ni-Co laterite deposits, and contains discussion of the influences of climate, geomorphology (relief), drainage, tectonism, structure, and protolith on the development of favorable weathering profiles. This model of Ni-Co laterite deposits represents part of the U.S. Geological Survey Mineral Resources Program's effort to update the existing models to be used for an upcoming national mineral resource assessment.
Spatial interactions in a modified Daisyworld model: Heat diffusivity and greenhouse effects
NASA Astrophysics Data System (ADS)
Alberti, T.; Primavera, L.; Vecchio, A.; Lepreti, F.; Carbone, V.
2015-11-01
In this work we investigate a modified version of the Daisyworld model, originally introduced by Lovelock and Watson to describe in a simple way the interactions between an Earth-like planet, its biosphere, and the incoming solar radiation. Here a spatial dependency on latitude is included, and both a variable heat diffusivity along latitudes and a simple greenhouse effect description are introduced in the model. We show that the spatial interactions between the variables of the system can locally stabilize the coexistence of the two vegetation types. The feedback on albedo is able to generate equilibrium solutions which can efficiently self-regulate the planet climate, even for values of the solar luminosity relatively far from the current Earth conditions.
Energy efficiency in waste-to-energy and its relevance with regard to climate control.
Ragossnig, Arne M; Wartha, Christian; Kirchner, Andreas
2008-02-01
This article focuses on systematically highlighting the ways to optimize waste-to-energy plants in terms of their energy efficiency as an indicator of the positive effect with regard to climate control. Potentials for increasing energy efficiency are identified and grouped into categories. The measures mentioned are illustrated by real-world examples. As an example, district cooling as a means for increasing energy efficiency in the district heating network of Vienna is described. Furthermore a scenario analysis shows the relevance of energy efficiency in waste management scenarios based on thermal treatment of waste with regard to climate control. The description is based on a model that comprises all relevant processes from the collection and transportation up to the thermal treatment of waste. The model has been applied for household-like commercial waste. The alternatives compared are a combined heat and power incinerator, which is being introduced in many places as an industrial utility boiler or in metropolitan areas where there is a demand for district heating and a classical municipal solid waste incinerator producing solely electrical power. For comparative purposes a direct landfilling scenario has been included in the scenario analysis. It is shown that the energy efficiency of thermal treatment facilities is crucial to the quantity of greenhouse gases emitted.
Development of new impact functions for global risk caused by climate change
NASA Astrophysics Data System (ADS)
Miyazaki, C.
2014-12-01
The purpose of our study is to identify and quantify global-scale risks which can be caused by future climate change. In particular, we focus on the global-scale risks which have critical impacts to human environments. Use of impact functions is one of the common way to quantify global-scale risks. Output of impact function is climate impacts (e.g. economic damage by temperature increasing) and input can be global temperature increasing and/or socioeconomic condition (e.g. GDP). As the first step of study, we referred to AR5 WG II report (AR5, hereafter) and comprehensive inventories of climate change risks developed by Strategic R&D Area Project of the Environment Research and Technology Development Fund (ICA-RUS project). Then we extracted information which can be used to develop impact function from them. By following SPM/AR5, we focused on 11 sectors and extracted quantitative description on climate impacts from the AR5 and paper/reports cited in AR5. As a result, we identified about 40 risk items to focus as global-scale risks by climate change. Using the collected information, we tentatively made impact function on sea level rise and so on. In addition, we also extracted the impact functions used in Integrated Assessment Models (IAMs). The literature survey on IAM suggested the risk items considered in IAMs are limited. For instance, although FUND model provides detailed impact functions compared with most of other IAMs, its impact functions deal with only several sectors (e.g. agriculture, forestry, biodiversity, sea level rise, human health, energy demand and water resources). The survey on impact functions in IAMs also suggested impact function for abrupt climate change (so-called Tipping Element) is premature. Moreover, as example for quantifying health risk by our calculation, we also present the result on global-scale projection of the health burden attributable to childhood undernutrition (Ishida et al., 2014, ERL).
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)
NASA Astrophysics Data System (ADS)
Bonaldo, Davide
2017-04-01
The increasing awareness of the potential threats acting on the coastal regions, combined with the intense anthropic pressure and the broad variety of socio-economic drivers acting on these systems, bestowed progressively stronger emphasis to the development of sound planning and management policies. The assessment and the formulation of plans for the response to coastal morphological vulnerability is a multidisciplinary challenge, in which different typology of information, approaches and scales need to be integrated and framed within a consistent dynamical description. To this aim, within the RITMARE National Flagship Project, a specific research line on "Coastal Vulnerability to Erosion and Relative Sea level rise in climate change scenarios" was activated with reference to the Adriatic-Ionian region (Eastern Mediterranean Sea). The activities, supported by the Italian Ministry of University and Research 2016-18, move along three interconnected branches, namely: 1) Assessment of vulnerability to relative sea level rise in the Adriatic-Ionian region, in present conditions and in different climate change scenarios; 2) Development of high-resolution oceanographic modelling tools for the description of meteo-marine climate and sediment transport at different scales and rapid response intervention protocols for the evaluation of the impact of erosive events on sandy sediments; 3) Identification of possible geomorphological setting scenarios and definition of intervention strategies, with special care to the exploitment of marine sand as a strategic resource. The work provides an overview of the strategy underlying the Research Line and present preliminary results and main achievements. Next steps will be aiming to pave the way towards a road map for an integrated observational and modelling approach for monitoring and managing the erosion and marine ingression risk throughout Italian coasts, striving to bridge the cultural and methodological gaps between the scientific and administrative sectors active in the coastal management field.
Parks, Sean A; Parisien, Marc-André; Miller, Carol; Dobrowski, Solomon Z
2014-01-01
Numerous theoretical and empirical studies have shown that wildfire activity (e.g., area burned) at regional to global scales may be limited at the extremes of environmental gradients such as productivity or moisture. Fire activity, however, represents only one component of the fire regime, and no studies to date have characterized fire severity along such gradients. Given the importance of fire severity in dictating ecological response to fire, this is a considerable knowledge gap. For the western US, we quantify relationships between climate and the fire regime by empirically describing both fire activity and severity along two climatic water balance gradients, actual evapotranspiration (AET) and water deficit (WD), that can be considered proxies for fuel amount and fuel moisture, respectively. We also concurrently summarize fire activity and severity among ecoregions, providing an empirically based description of the geographic distribution of fire regimes. Our results show that fire activity in the western US increases with fuel amount (represented by AET) but has a unimodal (i.e., humped) relationship with fuel moisture (represented by WD); fire severity increases with fuel amount and fuel moisture. The explicit links between fire regime components and physical environmental gradients suggest that multivariable statistical models can be generated to produce an empirically based fire regime map for the western US. Such models will potentially enable researchers to anticipate climate-mediated changes in fire recurrence and its impacts based on gridded spatial data representing future climate scenarios.
Parks, Sean A.; Parisien, Marc-André; Miller, Carol; Dobrowski, Solomon Z.
2014-01-01
Numerous theoretical and empirical studies have shown that wildfire activity (e.g., area burned) at regional to global scales may be limited at the extremes of environmental gradients such as productivity or moisture. Fire activity, however, represents only one component of the fire regime, and no studies to date have characterized fire severity along such gradients. Given the importance of fire severity in dictating ecological response to fire, this is a considerable knowledge gap. For the western US, we quantify relationships between climate and the fire regime by empirically describing both fire activity and severity along two climatic water balance gradients, actual evapotranspiration (AET) and water deficit (WD), that can be considered proxies for fuel amount and fuel moisture, respectively. We also concurrently summarize fire activity and severity among ecoregions, providing an empirically based description of the geographic distribution of fire regimes. Our results show that fire activity in the western US increases with fuel amount (represented by AET) but has a unimodal (i.e., humped) relationship with fuel moisture (represented by WD); fire severity increases with fuel amount and fuel moisture. The explicit links between fire regime components and physical environmental gradients suggest that multivariable statistical models can be generated to produce an empirically based fire regime map for the western US. Such models will potentially enable researchers to anticipate climate-mediated changes in fire recurrence and its impacts based on gridded spatial data representing future climate scenarios. PMID:24941290
Knowledge Discovery and Data Mining in Iran's Climatic Researches
NASA Astrophysics Data System (ADS)
Karimi, Mostafa
2013-04-01
Advances in measurement technology and data collection is the database gets larger. Large databases require powerful tools for analysis data. Iterative process of acquiring knowledge from information obtained from data processing is done in various forms in all scientific fields. However, when the data volume large, and many of the problems the Traditional methods cannot respond. in the recent years, use of databases in various scientific fields, especially atmospheric databases in climatology expanded. in addition, increases in the amount of data generated by the climate models is a challenge for analysis of it for extraction of hidden pattern and knowledge. The approach to this problem has been made in recent years uses the process of knowledge discovery and data mining techniques with the use of the concepts of machine learning, artificial intelligence and expert (professional) systems is overall performance. Data manning is analytically process for manning in massive volume data. The ultimate goal of data mining is access to information and finally knowledge. climatology is a part of science that uses variety and massive volume data. Goal of the climate data manning is Achieve to information from variety and massive atmospheric and non-atmospheric data. in fact, Knowledge Discovery performs these activities in a logical and predetermined and almost automatic process. The goal of this research is study of uses knowledge Discovery and data mining technique in Iranian climate research. For Achieve This goal, study content (descriptive) analysis and classify base method and issue. The result shown that in climatic research of Iran most clustering, k-means and wards applied and in terms of issues precipitation and atmospheric circulation patterns most introduced. Although several studies in geography and climate issues with statistical techniques such as clustering and pattern extraction is done, Due to the nature of statistics and data mining, but cannot say for internal climate studies in data mining and knowledge discovery techniques are used. However, it is necessary to use the KDD Approach and DM techniques in the climatic studies, specific interpreter of climate modeling result.
Modelling ice microphysics of mixed-phase clouds
NASA Astrophysics Data System (ADS)
Ahola, J.; Raatikainen, T.; Tonttila, J.; Romakkaniemi, S.; Kokkola, H.; Korhonen, H.
2017-12-01
The low-level Arctic mixed-phase clouds have a significant role for the Arctic climate due to their ability to absorb and reflect radiation. Since the climate change is amplified in polar areas, it is vital to apprehend the mixed-phase cloud processes. From a modelling point of view, this requires a high spatiotemporal resolution to capture turbulence and the relevant microphysical processes, which has shown to be difficult.In order to solve this problem about modelling mixed-phase clouds, a new ice microphysics description has been developed. The recently published large-eddy simulation cloud model UCLALES-SALSA offers a good base for a feasible solution (Tonttila et al., Geosci. Mod. Dev., 10:169-188, 2017). The model includes aerosol-cloud interactions described with a sectional SALSA module (Kokkola et al., Atmos. Chem. Phys., 8, 2469-2483, 2008), which represents a good compromise between detail and computational expense.Newly, the SALSA module has been upgraded to include also ice microphysics. The dynamical part of the model is based on well-known UCLA-LES model (Stevens et al., J. Atmos. Sci., 56, 3963-3984, 1999) which can be used to study cloud dynamics on a fine grid.The microphysical description of ice is sectional and the included processes consist of formation, growth and removal of ice and snow particles. Ice cloud particles are formed by parameterized homo- or heterogeneous nucleation. The growth mechanisms of ice particles and snow include coagulation and condensation of water vapor. Autoconversion from cloud ice particles to snow is parameterized. The removal of ice particles and snow happens by sedimentation and melting.The implementation of ice microphysics is tested by initializing the cloud simulation with atmospheric observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC). The results are compared to the model results shown in the paper of Ovchinnikov et al. (J. Adv. Model. Earth Syst., 6, 223-248, 2014) and they show a good match. One of the advantages of UCLALES-SALSA is that it can be used to quantify the effect of aerosol scavenging on cloud properties in a precise way.
NASA Astrophysics Data System (ADS)
Voss, Anja; Bärlund, Ilona; Punzet, Manuel; Williams, Richard; Teichert, Ellen; Malve, Olli; Voß, Frank
2010-05-01
Although catchment scale modelling of water and solute transport and transformations is a widely used technique to study pollution pathways and effects of natural changes, policies and mitigation measures there are only a few examples of global water quality modelling. This work will provide a description of the new continental-scale model of water quality WorldQual and the analysis of model simulations under changed climate and anthropogenic conditions with respect to changes in diffuse and point loading as well as surface water quality. BOD is used as an indicator of the level of organic pollution and its oxygen-depleting potential, and for the overall health of aquatic ecosystems. The first application of this new water quality model is to river systems of Europe. The model itself is being developed as part of the EU-funded SCENES Project which has the principal goal of developing new scenarios of the future of freshwater resources in Europe. The aim of the model is to determine chemical fluxes in different pathways combining analysis of water quantity with water quality. Simple equations, consistent with the availability of data on the continental scale, are used to simulate the response of in-stream BOD concentrations to diffuse and anthropogenic point loadings as well as flow dilution. Point sources are divided into manufacturing, domestic and urban loadings, whereas diffuse loadings come from scattered settlements, agricultural input (for instance livestock farming), and also from natural background sources. The model is tested against measured longitudinal gradients and time series data at specific river locations with different loading characteristics like the Thames that is driven by domestic loading and Ebro with relative high share of diffuse loading. With scenario studies the influence of climate and anthropogenic changes on European water resources shall be investigated with the following questions: 1. What percentage of river systems will have degraded water quality due to different driving forces? 2. How will climate change and changes in wastewater discharges affect water quality? For the analysis these scenario aspects are included: 1. climate with changed runoff (affecting diffuse pollution and loading from sealed areas), river discharge (causing dilution or concentration of point source pollution) and water temperature (affecting BOD degradation). 2. Point sources with changed population (affecting domestic pollution), connectivity to treatment plants (influencing domestic and manufacturing pollution as well as input from sealed areas and scattered settlements).
Analysis of trend changes in Northern African palaeo-climate by using Bayesian inference
NASA Astrophysics Data System (ADS)
Schütz, Nadine; Trauth, Martin H.; Holschneider, Matthias
2010-05-01
Climate variability of Northern Africa is of high interest due to climate-evolutionary linkages under study. The reconstruction of the palaeo-climate over long time scales, including the expected linkages (> 3 Ma), is mainly accessible by proxy data from deep sea drilling cores. By concentrating on published data sets, we try to decipher rhythms and trends to detect correlations between different proxy time series by advanced mathematical methods. Our preliminary data is dust concentration, as an indicator for climatic changes such as humidity, from the ODP sites 659, 721 and 967 situated around Northern Africa. Our interest is in challenging the available time series with advanced statistical methods to detect significant trend changes and to compare different model assumptions. For that purpose, we want to avoid the rescaling of the time axis to obtain equidistant time steps for filtering methods. Additionally we demand an plausible description of the errors for the estimated parameters, in terms of confidence intervals. Finally, depending on what model we restrict on, we also want an insight in the parameter structure of the assumed models. To gain this information, we focus on Bayesian inference by formulating the problem as a linear mixed model, so that the expectation and deviation are of linear structure. By using the Bayesian method we can formulate the posteriori density as a function of the model parameters and calculate this probability density in the parameter space. Depending which parameters are of interest, we analytically and numerically marginalize the posteriori with respect to the remaining parameters of less interest. We apply a simple linear mixed model to calculate the posteriori densities of the ODP sites 659 and 721 concerning the last 5 Ma at maximum. From preliminary calculations on these data sets, we can confirm results gained by the method of breakfit regression combined with block bootstrapping ([1]). We obtain a significant change point around (1.63 - 1.82) Ma, which correlates with a global climate transition due to the establishment of the Walker circulation ([2]). Furthermore we detect another significant change point around (2.7 - 3.2) Ma, which correlates with the end of the Pliocene warm period (permanent El Niño-like conditions) and the onset of a colder global climate ([3], [4]). The discussion on the algorithm, the results of calculated confidence intervals, the available information about the applied model in the parameter space and the comparison of multiple change point models will be presented. [1] Trauth, M.H., et al., Quaternary Science Reviews, 28, 2009 [2] Wara, M.W., et al., Science, Vol. 309, 2005 [3] Chiang, J.C.H., Annual Review of Earth and Planetary Sciences, Vol. 37, 2009 [4] deMenocal, P., Earth and Planetary Science Letters, 220, 2004
ERIC Educational Resources Information Center
Pozveh, Asghar Zamani; Karimi, Fariba
2016-01-01
The aim of the present study was to determine the relationship between organizational climate and the organizational silence of administrative staff in Education Department in Isfahan. The research method was descriptive and correlational-type method. The study population was administrative staff of Education Department in Isfahan during the…
status of ENSO go to the ENSO Advisory (issued when appropriate) or the latest monthly Climate Diagnostics Bulletin. More technical information on the global patterns of abnormal precipitation and , J. Climate, 5, 577-593). A general description of a warm (ENSO) episode and its composite evolution
ERIC Educational Resources Information Center
Giles, Pamela
2010-01-01
Leaders in Christian higher education are often unaware of how adult degree completion programs (ADCPs) impact a school's organizational behavior, and no research has examined employees' perceptions of its impact. This nonexperimental, descriptive study examined differences in employees' perceptions of the impact on organizational climate of the…
Use of a stochastic approach for description of water balance and runoff production dynamics
NASA Astrophysics Data System (ADS)
Gioia, A.; Manfreda, S.; Iacobellis, V.; Fiorentino, M.
2009-04-01
The present study exploits an analytical model (Manfreda, NHESS [2008]) for the description of the probability density function of soil water balance and runoff generation over a set of river basins belonging to Southern Italy. The model is based on a stochastic differential equation where the rainfall forcing is interpreted as an additive noise in the soil water balance; the watershed heterogeneity is described exploiting the conceptual lumped watershed Xinanjiang model (widely used in China) that uses a parabolic curve for the distribution of the soil water storage capacity (Zhao et al. [1980]). The model, characterized by parameters that depend on soil, vegetation and basin morphology, allowed to derive the probability density function of the relative saturation and the surface runoff of a basin accounting for the spatial heterogeneity in soil water storage. Its application on some river basins belonging to regions of Southern Italy, gives interesting insights for the investigation of the role played by the dynamical interaction between climate, soil, and vegetation in soil moisture and runoff production dynamics. Manfreda, S., Runoff Generation Dynamics within a Humid River Basin, Natural Hazard and Earth System Sciences, 8, 1349-1357, 2008. Zhao, R. -J., Zhang, Y. L., and Fang, L. R.: The Xinanjiang model, Hydrological Forecasting Proceedings Oxford Symposium, IAHS Pub. 129, 351-356, 1980.
Linking seasonal climate forecasts with crop models in Iberian Peninsula
NASA Astrophysics Data System (ADS)
Capa, Mirian; Ines, Amor; Baethgen, Walter; Rodriguez-Fonseca, Belen; Han, Eunjin; Ruiz-Ramos, Margarita
2015-04-01
Translating seasonal climate forecasts into agricultural production forecasts could help to establish early warning systems and to design crop management adaptation strategies that take advantage of favorable conditions or reduce the effect of adverse conditions. In this study, we use seasonal rainfall forecasts and crop models to improve predictability of wheat yield in the Iberian Peninsula (IP). Additionally, we estimate economic margins and production risks associated with extreme scenarios of seasonal rainfall forecast. This study evaluates two methods for disaggregating seasonal climate forecasts into daily weather data: 1) a stochastic weather generator (CondWG), and 2) a forecast tercile resampler (FResampler). Both methods were used to generate 100 (with FResampler) and 110 (with CondWG) weather series/sequences for three scenarios of seasonal rainfall forecasts. Simulated wheat yield is computed with the crop model CERES-wheat (Ritchie and Otter, 1985), which is included in Decision Support System for Agrotechnology Transfer (DSSAT v.4.5, Hoogenboom et al., 2010). Simulations were run at two locations in northeastern Spain where the crop model was calibrated and validated with independent field data. Once simulated yields were obtained, an assessment of farmer's gross margin for different seasonal climate forecasts was accomplished to estimate production risks under different climate scenarios. This methodology allows farmers to assess the benefits and risks of a seasonal weather forecast in IP prior to the crop growing season. The results of this study may have important implications on both, public (agricultural planning) and private (decision support to farmers, insurance companies) sectors. Acknowledgements Research by M. Capa-Morocho has been partly supported by a PICATA predoctoral fellowship of the Moncloa Campus of International Excellence (UCM-UPM) and MULCLIVAR project (CGL2012-38923-C02-02) References Hoogenboom, G. et al., 2010. The Decision Support System for Agrotechnology Transfer (DSSAT).Version 4.5 [CD-ROM].University of Hawaii, Honolulu, Hawaii. Ritchie, J.T., Otter, S., 1985. Description and performanceof CERES-Wheat: a user-oriented wheat yield model. In: ARS Wheat Yield Project. ARS-38.Natl Tech Info Serv, Springfield, Missouri, pp. 159-175.
Joint projections of sea level and storm surge using a flood index
NASA Astrophysics Data System (ADS)
Little, C. M.; Lin, N.; Horton, R. M.; Kopp, R. E.; Oppenheimer, M.
2016-02-01
Capturing the joint influence of sea level rise (SLR) and tropical cyclones (TCs) on future coastal flood risk poses significant challenges. To address these difficulties, Little et al. (2015) use a proxy of tropical cyclone activity and a probabilistic flood index that aggregates flood height and duration over a wide area (the US East and Gulf coasts). This technique illuminates the individual impacts of TCs and SLR and their correlation across different coupled climate models. By 2080-2099, changes in the flood index relative to 1986-2005 are substantial and positively skewed: a 10th-90th percentile range of 35-350x higher for a high-end business-as-usual emissions scenario (see figure). This aggregated flood index: 1) is a means to consistently combine TC-driven storm surges and SLR; 2) provides a more robust description of historical surge-climate relationships than is available at any one location; and 3) allows the incorporation of a larger climate model ensemble - which is critical to uncertainty characterization. It does not provide a local view of the complete spectrum of flood severity (i.e. return curves). However, alternate techniques that provide localized return curves (e.g. Lin et al., 2012) are computationally intensive, limiting the set of large-scale climate models that can be incorporated, and require several linked statistical and dynamical models, each with structural uncertainties that are difficult to quantify. Here, we present the results of Little et al. (2015) along with: 1) alternate formulations of the flood index; 2) strategies to localize the flood index; and 3) a comparison of flood index projections to those provided by model-based return curves. We look to this interdisciplinary audience for feedback on the advantages and disadvantages of each tool for coastal planning and decision-making. Lin, N., K. Emanuel, M. Oppenheimer, and E. Vanmarcke, 2012: Physically based assessment of hurricane surge threat under climate change. Nature Clim. Change, 2(6), 462-467. Little, C. M., R. M. Horton, R. E. Kopp, M. Oppenheimer, G. A. Vecchi, and G. Villarini, 2015: Joint projections of us east coast sea level and storm surge. Nature Clim. Change, advance online publication.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kriegler, Elmar; Edmonds, James A.; Hallegatte, Stephane
2014-04-01
The paper presents the concept of shared climate policy assumptions as an important element of the new scenario framework. Shared climate policy assumptions capture key climate policy dimensions such as the type and scale of mitigation and adaptation measures. They are not specified in the socio-economic reference pathways, and therefore introduce an important third dimension to the scenario matrix architecture. Climate policy assumptions will have to be made in any climate policy scenario, and can have a significant impact on the scenario description. We conclude that a meaningful set of shared climate policy assumptions is useful for grouping individual climatemore » policy analyses and facilitating their comparison. Shared climate policy assumptions should be designed to be policy relevant, and as a set to be broad enough to allow a comprehensive exploration of the climate change scenario space.« less
Modeling the "Year without summer 1816" with the CCM SOCOL
NASA Astrophysics Data System (ADS)
Arfeuille, Florian; Rozanov, Eugene; Peter, Thomas; Fischer, Andreas. M.; Weisenstein, Debra; Brönnimann, Stefan
2010-05-01
The "Year without summer" 1816 had profound social and environmental effects, and although the cataclysmic eruption of Mt Tambora is now commonly known to have largely contributed to the negative temperature anomalies of the summer 1816 in Europe and North America, lots of uncertainties remain. The eruption of Mt. Tambora in April 1815 is the largest within the last 500 years. A crucial parameter to assess in order to simulate this eruption is the aerosol size distribution, which strongly influences the radiative impact of the aerosols (changes in albedo and residence time in the stratosphere, among others) and the impacts on dynamics and chemistry. The representation of this major forcing is done by using the AER-2D aerosol model which calculates the size distribution of the aerosols formed after the eruption. The modeling of the climatic impacts is then done by the state-of-the-art Chemistry-Climate model (CCM) SOCOL. The importance of stratospheric processes for the study of the "Year without summer" 1816 justifies the choice of a CCM which allows a precise analysis of the radiative, dynamical and chemical impacts of the Tambora eruption. The 1810's decade is an interesting period as it combines both a strong signal to noise ratio for the study of the impacts of the volcanic forcing, and an availability of several high resolution climate proxies allowing a credible reconstruction of interesting climatic components like Sea Surface Temperatures (SST) which are forced in the CCM . This can particularly provide a realistic description of the inter-annual variability linked to the major atmosphere/ocean coupled oscillations such as ENSO. Reconstructions based on inland natural proxies and early instrumental records can then be used to validate the simulated climate. I will present the characteristics of the Tambora eruption and show some results from simulations made using the aerosol model/CCM, with an emphasis on the radiative and chemical implications of the large aerosol sizes produced by the Mt. Tambora 60-80MT SO2 release. For instance, the specific absorption/scattering ratio of Mt.Tambora aerosols induced a very large stratospheric warming which will be analyzed. The climatic impacts will also be discussed in regards of the high sedimentation rate of Mt. Tambora aerosols, leading to a fast decrease of the atmospheric optical depth in the first two years after the eruption.
A Historical Forcing Ice Sheet Model Validation Framework for Greenland
NASA Astrophysics Data System (ADS)
Price, S. F.; Hoffman, M. J.; Howat, I. M.; Bonin, J. A.; Chambers, D. P.; Kalashnikova, I.; Neumann, T.; Nowicki, S.; Perego, M.; Salinger, A.
2014-12-01
We propose an ice sheet model testing and validation framework for Greenland for the years 2000 to the present. Following Perego et al. (2014), we start with a realistic ice sheet initial condition that is in quasi-equilibrium with climate forcing from the late 1990's. This initial condition is integrated forward in time while simultaneously applying (1) surface mass balance forcing (van Angelen et al., 2013) and (2) outlet glacier flux anomalies, defined using a new dataset of Greenland outlet glacier flux for the past decade (Enderlin et al., 2014). Modeled rates of mass and elevation change are compared directly to remote sensing observations obtained from GRACE and ICESat. Here, we present a detailed description of the proposed validation framework including the ice sheet model and model forcing approach, the model-to-observation comparison process, and initial results comparing model output and observations for the time period 2000-2013.
A two-component rain model for the prediction of attenuation and diversity improvement
NASA Technical Reports Server (NTRS)
Crane, R. K.
1982-01-01
A new model was developed to predict attenuation statistics for a single Earth-satellite or terrestrial propagation path. The model was extended to provide predictions of the joint occurrences of specified or higher attenuation values on two closely spaced Earth-satellite paths. The joint statistics provide the information required to obtain diversity gain or diversity advantage estimates. The new model is meteorologically based. It was tested against available Earth-satellite beacon observations and terrestrial path measurements. The model employs the rain climate region descriptions of the Global rain model. The rms deviation between the predicted and observed attenuation values for the terrestrial path data was 35 percent, a result consistent with the expectations of the Global model when the rain rate distribution for the path is not used in the calculation. Within the United States the rms deviation between measurement and prediction was 36 percent but worldwide it was 79 percent.
Climate fluctuations in the Czech Lands from AD 1500 compiled from various proxies
NASA Astrophysics Data System (ADS)
Dobrovolný, Petr; Brázdil, Rudolf; Možný, Martin; Trnka, Miroslav; Řezníčková, Ladislava; Kotyza, Oldřich; Valášek, Hubert; Dolák, Lukáš
2017-04-01
The territory of the Czech Lands (recent Czech Republic) belongs to European areas well covered by dedrochronological, documentary and instrumental data which can be used for climate reconstructions for the last c. 500 years, i.e. for description of climate fluctuations during the greater part of the Little Ice Age (LIA) and the subsequent period of the recent Global Warming. Synthesis of various existing reconstructions should help to create more consistent description of climate variability in that period in Central Europe. The contribution starts from characteristic of the basic features of three existing data sources and a general method of climate reconstruction. Monthly, seasonal and annual climate reconstructions based on different data are presented: a) temperature reconstructions derived from series of temperature indices, winter wheat harvest days and grape harvest days; b) precipitation reconstructions derived from series of precipitation indices and fir tree-rings; c) drought indices (SPI, SPEI, Z-index and PDSI) reconstructions derived from series of fir tree-rings, grape harvest days and documentary-based temperature and precipitation reconstructions. Basic features of past c. 500 years are represented by various time intervals of cooler and warmer climate on the one hand and wetter and drier climate on the other. Examples of such particularly warmer and drier period can be the 1530s (with extreme 1540 year) or colder and wetter conditions during the 1590s and 1690s. Outstanding extreme weather events during LIA in Central Europe are briefly mentioned and our findings are discussed with respect to climate fluctuations and forcings in wider European context. (This study was supported by Czech Science Foundation, project nos. 13-04291S and 17-10026S).
Descriptive modelling to predict deoxynivalenol in winter wheat in the Netherlands.
Van Der Fels-Klerx, H J; Burgers, S L G E; Booij, C J H
2010-05-01
Predictions of deoxynivalenol (DON) content in wheat at harvest can be useful for decision-making by stakeholders of the wheat feed and food supply chain. The objective of the current research was to develop quantitative predictive models for DON in mature winter wheat in the Netherlands for two specific groups of end-users. One model was developed for use by farmers in underpinning Fusarium spp. disease management, specifically the application of fungicides around wheat flowering (model A). The second model was developed for industry and food safety authorities, and considered the entire wheat cultivation period (model B). Model development was based on observational data collected from 425 fields throughout the Netherlands between 2001 and 2008. For each field, agronomical information, climatic data and DON levels in mature wheat were collected. Using multiple regression analyses, the set of biological relevant variables that provided the highest statistical performance was selected. The two final models include the following variables: region, wheat resistance level, spraying, flowering date, several climatic variables in the different stages of wheat growing, and length of the period between flowering and harvesting (model B only). The percentages of variance accounted for were 64.4% and 65.6% for models A and B, respectively. Model validation showed high correlation between the predicted and observed DON levels. The two models may be applied by various groups of end-users to reduce DON contamination in wheat-derived feed and food products and, ultimately, reduce animal and consumer health risks.
Climate gentrification: from theory to empiricism in Miami-Dade County, Florida
NASA Astrophysics Data System (ADS)
Keenan, Jesse M.; Hill, Thomas; Gumber, Anurag
2018-05-01
This article provides a conceptual model for the pathways by which climate change could operate to impact geographies and property markets whose inferior or superior qualities for supporting the built environment are subject to a descriptive theory known as ‘Climate Gentrification.’ The article utilizes Miami-Dade County, Florida (MDC) as a case study to explore the market mechanisms that speak to the operations and processes inherent in the theory. This article tests the hypothesis that the rate of price appreciation of single-family properties in MDC is positively related to and correlated with incremental measures of higher elevation (the ‘Elevation Hypothesis’). As a reflection of an increase in observed nuisance flooding and relative SLR, the second hypothesis is that the rates of price appreciation in lowest the elevation cohorts have not kept up with the rates of appreciation of higher elevation cohorts since approximately 2000 (the ‘Nuisance Hypothesis’). The findings support a validation of both hypotheses and suggest the potential existence of consumer preferences that are based, in part, on perceptions of flood risk and/or observations of flooding. These preferences and perceptions are anticipated to be amplified by climate change in a manner that reinforces the proposition that climate change impacts will affect the marketability and valuation of property with varying degrees of environmental exposure and resilience functionality. Uncovering these empirical relationships is a critical first step for understanding the occurrence and parameters of Climate Gentrification.
NASA Astrophysics Data System (ADS)
Ogutu, K. B. Z.; D'Andrea, F.; Ghil, M.; Nyandwi, C.; Manene, M. M.; Muthama, J. N.
2015-04-01
This study uses the global climate-economy-biosphere (CoCEB) model developed in Part 1 to investigate economic aspects of deforestation control and carbon sequestration in forests, as well as the efficiency of carbon capture and storage (CCS) technologies as policy measures for climate change mitigation. We assume - as in Part 1 - that replacement of one technology with another occurs in terms of a logistic law, so that the same law also governs the dynamics of reduction in carbon dioxide emission using CCS technologies. In order to take into account the effect of deforestation control, a slightly more complex description of the carbon cycle than in Part 1 is needed. Consequently, we add a biomass equation into the CoCEB model and analyze the ensuing feedbacks and their effects on per capita gross domestic product (GDP) growth. Integrating biomass into the CoCEB and applying deforestation control as well as CCS technologies has the following results: (i) low investment in CCS contributes to reducing industrial carbon emissions and to increasing GDP, but further investment leads to a smaller reduction in emissions, as well as in the incremental GDP growth; and (ii) enhanced deforestation control contributes to a reduction in both deforestation emissions and in atmospheric carbon dioxide concentration, thus reducing the impacts of climate change and contributing to a slight appreciation of GDP growth. This effect is however very small compared to that of low-carbon technologies or CCS. We also find that the result in (i) is very sensitive to the formulation of CCS costs, while to the contrary, the results for deforestation control are less sensitive.
Terrestrial carbon turnover time constraints on future carbon cycle-climate feedback
NASA Astrophysics Data System (ADS)
Fan, N.; Carvalhais, N.; Reichstein, M.
2017-12-01
Understanding the terrestrial carbon cycle-climate feedback is essential to reduce the uncertainties resulting from the between model spread in prognostic simulations (Friedlingstein et al., 2006). One perspective is to investigate which factors control the variability of the mean residence times of carbon in the land surface, and how these may change in the future, consequently affecting the response of the terrestrial ecosystems to changes in climate as well as other environmental conditions. Carbon turnover time of the whole ecosystem is a dynamic parameter that represents how fast the carbon cycle circulates. Turnover time τ is an essential property for understanding the carbon exchange between the land and the atmosphere. Although current Earth System Models (ESMs), supported by GVMs for the description of the land surface, show a strong convergence in GPP estimates, but tend to show a wide range of simulated turnover times (Carvalhais, 2014). Thus, there is an emergent need of constraints on the projected response of the balance between terrestrial carbon fluxes and carbon stock which will give us more certainty in response of carbon cycle to climate change. However, the difficulty of obtaining such a constraint is partly due to lack of observational data on temporal change of terrestrial carbon stock. Since more new datasets of carbon stocks such as SoilGrid (Hengl, et al., 2017) and fluxes such as GPP (Jung, et al., 2017) are available, improvement in estimating turnover time can be achieved. In addition, previous study ignored certain aspects such as the relationship between τ and nutrients, fires, etc. We would like to investigate τ and its role in carbon cycle by combining observatinoal derived datasets and state-of-the-art model simulations.
Lindborg, T; Thorne, M; Andersson, E; Becker, J; Brandefelt, J; Cabianca, T; Gunia, M; Ikonen, A T K; Johansson, E; Kangasniemi, V; Kautsky, U; Kirchner, G; Klos, R; Kowe, R; Kontula, A; Kupiainen, P; Lahdenperä, A-M; Lord, N S; Lunt, D J; Näslund, J-O; Nordén, M; Norris, S; Pérez-Sánchez, D; Proverbio, A; Riekki, K; Rübel, A; Sweeck, L; Walke, R; Xu, S; Smith, G; Pröhl, G
2018-03-01
The International Atomic Energy Agency has coordinated an international project addressing climate change and landscape development in post-closure safety assessments of solid radioactive waste disposal. The work has been supported by results of parallel on-going research that has been published in a variety of reports and peer reviewed journal articles. The project is due to be described in detail in a forthcoming IAEA report. Noting the multi-disciplinary nature of post-closure safety assessments, here, an overview of the work is given to provide researchers in the broader fields of radioecology and radiological safety assessment with a review of the work that has been undertaken. It is hoped that such dissemination will support and promote integrated understanding and coherent treatment of climate change and landscape development within an overall assessment process. The key activities undertaken in the project were: identification of the key processes that drive environmental change (mainly those associated with climate and climate change), and description of how a relevant future may develop on a global scale; development of a methodology for characterising environmental change that is valid on a global scale, showing how modelled global changes in climate can be downscaled to provide information that may be needed for characterising environmental change in site-specific assessments, and illustrating different aspects of the methodology in a number of case studies that show the evolution of site characteristics and the implications for the dose assessment models. Overall, the study has shown that quantitative climate and landscape modelling has now developed to the stage that it can be used to define an envelope of climate and landscape change scenarios at specific sites and under specific greenhouse-gas emissions assumptions that is suitable for use in quantitative post-closure performance assessments. These scenarios are not predictions of the future, but are projections based on a well-established understanding of the important processes involved and their impacts on different types of landscape. Such projections support the understanding of, and selection of, plausible ranges of scenarios for use in post-closure safety assessments. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Transformation of soil organics under extreme climate events: a project description
NASA Astrophysics Data System (ADS)
Blagodatskaya, Evgenia
2017-04-01
Recent climate scenarios predict not only continued global warming but also an increased frequency and intensity of extreme climatic events such as strong changes in temperature and precipitation with unusual regional dynamics. Weather anomalies at European territory of Russia are currently revealed as long-term drought and strong showers in summer and as an increased frequency of soil freezing-thawing cycles. Climate extremes totally change biogeochemical processes and elements cycling both at the ecosystem level and at the level of soil profile mainly affecting soil biota. Misbalance in these processes can cause a reduction of soil carbon stock and an increase of greenhouse gases emission. Our project aims to reveal the transformation mechanisms of soil organic matter caused by extreme weather events taking into consideration the role of biotic-abiotic interactions in regulation of formation, maintenance and turnover of soil carbon stock. Our research strategy is based on the novel concept considering extreme climatic events (showers after long-term droughts, soil flooding, freezing-thawing) as abiotic factors initiating a microbial succession. Study on stoichiometric flexibility of plants under climate extremes as well as on resulting response of soil heterotrophs on stoichiometric changes in substrate will be used for experimental prove and further development of the theory of ecological stoichiometry. The results enable us to reveal the mechanisms of biotic - abiotic interactions responsible for the balance between mobilization and stabilization of soil organic matter. Identified mechanisms will form the basis of an ecosystem model enabled to predict the effects of extreme climatic events on biogenic carbon cycle in the biosphere.
NASA Astrophysics Data System (ADS)
Cauquoin, A.; Jean Baptiste, P.; Risi, C. M.; Fourre, E.; Landais, A.
2014-12-01
Understanding the links between climate and water cycle is essential in the current context of global warming. The water isotopic composition, quantified as δD, δ18O or δ17O, has a great potential to trace the organization of present-day hydrological cycle. When recorded in various archives as tree rings, sediments, ice cores, they have also been largely used to reconstruct the past evolution of climate and water. The Antarctic cap is extremely sensitive to climate change. Moreover, this region is under the influence of exchanges between the troposphere and the stratosphere because of the presence of the polar vortex. Tritium (3H) has been shown to be an appropriate tracer for the intrusion of stratospheric air masses into the lower troposphere. Natural tritium is mainly produced by the interaction of cosmic radiations with the upper atmosphere. This tritium enters the hydrological cycle in the form of tritiated water molecules (HTO) and has a radioactive half-life of 4500±8 days. In an approach combining data and model, we have first implemented tritium in the coupled Laboratoire de Météorologie Dynamique Zoom (LMDZ) Atmospheric General Circulation Model developed at IPSL [Risi et al., 2010]: LMDZ-iso. The implementation of natural tritium uses the same model architecture as for the other water isotopes, after a correct description of associated cosmogenic production terms [Masarik and Beer, 2009]. The model is used in a configuration dedicated to the simulation of the stratosphere, with 39 layers. In this presentation, we will focus on the modeling of spatial and temporal natural variations of tritium content in precipitation. The model is validated against a compilation of available data for natural tritium. We show that the continental and latitudinal effects are well reproduced by the model and that simulated seasonal variations of the tritium content of precipitation are coherent with our current knowledge of troposphere-stratosphere exchanges. Masarik and Beer (2009) J. Geophys. Res., 114, D11103. Risi et al. (2010) J. Geophys. Res., 115, D12118.
Spector, Paul E.
2016-01-01
Background Safety climate, violence prevention climate, and civility climate were independently developed and linked to domain-specific workplace hazards, although all three were designed to promote the physical and psychological safety of workers. Purpose To test domain specificity between conceptually related workplace climates and relevant workplace hazards. Methods Data were collected from 368 persons employed in various industries and descriptive statistics were calculated for all study variables. Correlational and relative weights analyses were used to test for domain specificity. Results The three climate domains were similarly predictive of most workplace hazards, regardless of domain specificity. Discussion This study suggests that the three climate domains share a common higher order construct that may predict relevant workplace hazards better than any of the scales alone. PMID:27110930
NASA Astrophysics Data System (ADS)
Roderick, Michael L.; Farquhar, Graham D.
2011-12-01
We use the Budyko framework to calculate catchment-scale evapotranspiration (E) and runoff (Q) as a function of two climatic factors, precipitation (P) and evaporative demand (Eo = 0.75 times the pan evaporation rate), and a third parameter that encodes the catchment properties (n) and modifies how P is partitioned between E and Q. This simple theory accurately predicted the long-term evapotranspiration (E) and runoff (Q) for the Murray-Darling Basin (MDB) in southeast Australia. We extend the theory by developing a simple and novel analytical expression for the effects on E and Q of small perturbations in P, Eo, and n. The theory predicts that a 10% change in P, with all else constant, would result in a 26% change in Q in the MDB. Future climate scenarios (2070-2099) derived using Intergovernmental Panel on Climate Change AR4 climate model output highlight the diversity of projections for P (±30%) with a correspondingly large range in projections for Q (±80%) in the MDB. We conclude with a qualitative description about the impact of changes in catchment properties on water availability and focus on the interaction between vegetation change, increasing atmospheric [CO2], and fire frequency. We conclude that the modern version of the Budyko framework is a useful tool for making simple and transparent estimates of changes in water availability.
Perkins, T. Alex; Metcalf, C. Jessica E.; Grenfell, Bryan T.; Tatem, Andrew J.
2015-01-01
Background Chikungunya is an emerging arbovirus that has caused explosive outbreaks in Africa and Asia for decades and invaded the Americas just over a year ago. During this ongoing invasion, it has spread to 45 countries where it has been transmitted autochthonously, infecting nearly 1.3 million people in total. Methods Here, we made use of weekly, country-level case reports to infer relationships between transmission and two putative climatic drivers: temperature and precipitation averaged across each country on a monthly basis. To do so, we used a TSIR model that enabled us to infer a parametric relationship between climatic drivers and transmission potential, and we applied a new method for incorporating a probabilistic description of the serial interval distribution into the TSIR framework. Results We found significant relationships between transmission and linear and quadratic terms for temperature and precipitation and a linear term for log incidence during the previous pathogen generation. The lattermost suggests that case numbers three to four weeks ago are largely predictive of current case numbers. This effect is quite nonlinear at the country level, however, due to an estimated mixing parameter of 0.74. Relationships between transmission and the climatic variables that we estimated were biologically plausible and in line with expectations. Conclusions Our analysis suggests that autochthonous transmission of Chikungunya in the Americas can be correlated successfully with putative climatic drivers, even at the coarse scale of countries and using long-term average climate data. Overall, this provides a preliminary suggestion that successfully forecasting the future trajectory of a Chikungunya outbreak and the receptivity of virgin areas may be possible. Our results also provide tentative estimates of timeframes and areas of greatest risk, and our extension of the TSIR model provides a novel tool for modeling vector-borne disease transmission. PMID:25737803
NASA Astrophysics Data System (ADS)
Ludwig, Ralf
2010-05-01
According to future climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. These changes are expected to have severe direct impacts on the management of water resources. Threats include severe droughts and extreme flooding, salinization of coastal aquifers, degradation of fertile soils and desertification due to poor and unsustainable water management practices. It can be foreseen that, unless appropriate adaptation measures are undertaken, the changes in the hydrologic cycle will give rise to an increasing potential for tension and conflict among the political and economic actors in this vulnerable region. The presented project initiative CLIMB, funded under EC's 7th Framework Program (FP7-ENV-2009-1), has started in January 2010. In its 4-year design, it shall analyze ongoing and future climate induced changes in hydrological budgets and extremes across the Mediterranean and neighboring regions. This is undertaken in study sites located in Sardinia, Northern Italy, Southern France, Tunisia, Egypt and the Palestinian-administered area Gaza. The work plan is targeted to selected river or aquifer catchments, where the consortium will employ a combination of novel field monitoring and remote sensing concepts, data assimilation, integrated hydrologic (and biophysical) modeling and socioeconomic factor analyses to reduce existing uncertainties in climate change impact analysis. Advanced climate scenario analysis will be employed and available ensembles of regional climate model simulations will be downscaling. This process will provide the drivers for an ensemble of hydro(-geo)logical models with different degrees of complexity in terms of process description and level of integration. The results of hydrological modeling and socio-economic factor analysis will enable the development of a GIS-based Vulnerability and Risk Assessment Tool. This tool will serve as a platform for the dissemination of project results, including communication with and planning for local and regional stakeholders. An im¬portant output of the research in the individual study sites will be the development of a set of recommendations for an improved monitoring and modeling strategy for climate change impact assessment. CLIMB is forming a cluster of independent projects with WASSERMed from the Environment and CLICO from Social Sciences and Humanities Call of FP7 in 2009. The intention of this clustering is to foster scientific synergy and cooperation between the partner projects to achieve improvements in policy outreach on different spatial scales.
NASA Astrophysics Data System (ADS)
Haghighi, Erfan; Gianotti, Daniel J.; Rigden, Angela J.; Salvucci, Guido D.; Kirchner, James W.; Entekhabi, Dara
2017-04-01
Being located in the transitional zone between dry and wet climate areas, semiarid ecosystems (and their associated ecohydrological processes) play a critical role in controlling climate change and global warming. Land evapotranspiration (ET), which is a central process in the climate system and a nexus of the water, energy and carbon cycles, typically accounts for up to 95% of the water budget in semiarid areas. Thus, the manner in which ET is partitioned into soil evaporation and plant transpiration in these settings is of practical importance for water and carbon cycling and their feedbacks to the climate system. ET (and its partitioning) in these regions is primarily controlled by surface soil moisture which varies episodically under stochastic precipitation inputs. Important as the ET-soil moisture relationship is, it remains empirical, and physical mechanisms governing its nature and dynamics are underexplored. Thus, the objective of this study is twofold: (1) to provide observational evidence for the influence of surface cover conditions on ET-soil moisture coupling in semiarid regions using soil moisture data from NASA's SMAP satellite mission combined with independent observationally based ET estimates, and (2) to develop a relatively simple mechanistic modeling platform improving our physical understanding of interactions between micro and macroscale processes controlling ET and its partitioning in partially vegetated areas. To this end, we invoked concepts from recent progress in mechanistic modeling of turbulent energy flux exchange in bluff-rough regions, and developed a physically based ET model that explicitly accounts for how vegetation-induced turbulence in the near-surface region influences soil drying and thus ET rates and dynamics. Model predictions revealed nonlinearities in the strength of the ET-soil moisture relationship (i.e., ∂ET/∂θ) as vegetation cover fraction increases, accounted for by the nonlinearity of surface-cover-dependent turbulent interactions. We identified a (predictable) critical vegetation cover fraction (as a function of vegetation stature and environmental conditions) that yields the strongest ET-soil moisture relationship under prescribed atmospheric conditions. Overall, the results suggest that ∂ET/ ∂θ varies more widely in regions with tall-stature woody vegetation that experience higher rates of change in turbulence intensity as the cover fraction increases. Our results facilitate a mathematically tractable description of ∂ET/ ∂θ, which is a core component of models that seek to predict hydrology-climate feedback processes in a changing climate.
Laboratory for Atmospheres: Philosophy, Organization, Major Activities, and 1999 Highlights
NASA Technical Reports Server (NTRS)
Einaudi, Franco (Technical Monitor)
2000-01-01
The Laboratory for Atmospheres is helping to answer questions related to climate, and climate change and other scientific questions about our planet and its neighbors. The Laboratory conducts a broad theoretical and experimental research program studying all aspects of the atmospheres of the Earth and other planets, including their structural, dynamical, radiative, and chemical properties. In this report,there is a statement of the labs philosophy and a description of it's role in NASA's mission. A broad description of the research and a summary of the scientists' major accomplishments in 1999 is also included. The report also presents useful information on human resources, scientific interactions, and outreach activities with the outside community.
Complex systems approach to fire dynamics and climate change impacts
NASA Astrophysics Data System (ADS)
Pueyo, S.
2012-04-01
I present some recent advances in complex systems theory as a contribution to understanding fire regimes and forecasting their response to a changing climate, qualitatively and quantitatively. In many regions of the world, fire sizes have been found to follow, approximately, a power-law frequency distribution. As noted by several authors, this distribution also arises in the "forest fire" model used by physicists to study mechanisms that give rise to scale invariance (the power law is a scale-invariant distribution). However, this model does not give and does not pretend to give a realistic description of fire dynamics. For example, it gives no role to weather and climate. Pueyo (2007) developed a variant of the "forest fire" model that is also simple but attempts to be more realistic. It also results into a power law, but the parameters of this distribution change through time as a function of weather and climate. Pueyo (2007) observed similar patterns of response to weather in data from boreal forest fires, and used the fitted response functions to forecast fire size distributions in a possible climate change scenario, including the upper extreme of the distribution. For some parameter values, the model in Pueyo (2007) displays a qualitatively different behavior, consisting of simple percolation. In this case, fire is virtually absent, but megafires sweep through the ecosystem a soon as environmental forcings exceed a critical threshold. Evidence gathered by Pueyo et al. (2010) suggests that this is realistic for tropical rainforests (specifically, well-conserved upland rainforests). Some climate models suggest that major tropical rainforest regions are going to become hotter and drier if climate change goes ahead unchecked, which could cause such abrupt shifts. Not all fire regimes are well described by this model. Using data from a tropical savanna region, Pueyo et al. (2010) found that the dynamics in this area do not match its assumptions, even though fire sizes are also well fitted by a power law. A possible interpretation is that the spatial structure of fire in savannas is strongly constrained by the spatial structure of their environment. Instead of resulting from ecosystem self-organization as in the model, in this case the scale invariance in fire events would be just a reflection of scale invariance in the environment in which the ecosystem lives. These results suggest at least three major types of fire dynamics: endogenous scaling, percolating, and exogenous scaling, in addition to intermediate options. The world's biomes can be classified based on the type of dynamics that is most likely to apply in each of them, and forecasts can be carried out with the tools developed for each of these types.
Nurses' perception of ethical climate at a large academic medical center.
Lemmenes, Donna; Valentine, Pamela; Gwizdalski, Patricia; Vincent, Catherine; Liao, Chuanhong
2016-09-07
Nurses are confronted daily with ethical issues while providing patient care. Hospital ethical climates can affect nurses' job satisfaction, organizational commitment, retention, and physician collaboration. At a metropolitan academic medical center, we examined nurses' perceptions of the ethical climate and relationships among ethical climate factors and nurse characteristics. We used a descriptive correlational design and nurses (N = 475) completed Olson's Hospital Ethical Climate Survey. Data were analyzed using STATA. Approvals by the Nursing Research Council and Institutional Review Board were obtained; participants' rights were protected. Nurses reported an ethical climate total mean score of 3.22 ± 0.65 that varied across factors; significant differences were found for ethical climate scores by nurses' age, race, and specialty area. These findings contribute to what is known about ethical climate and nurses' characteristics and provides the foundation to develop strategies to improve the ethical climate in work settings. © The Author(s) 2016.
Climate variability and causes: from the perspective of the Tharaka people of eastern Kenya
NASA Astrophysics Data System (ADS)
Recha, Charles W.; Makokha, George L.; Shisanya, Chris A.
2017-12-01
The study assessed community understanding of climate variability in semi-arid Tharaka sub-county, Kenya. The study used four focus group discussions (FGD) ( N = 48) and a household survey ( N = 326) to obtain information from four agro-ecological zones (AEZs). The results were synthesized and descriptively presented. People in Tharaka sub-county are familiar with the term climate change and associate it with environmental degradation. There are, however, misconceptions and gaps in understanding the causes of climate change. There was a mismatch between community and individual perception of onset and cessation of rainfall—evidence that analysis of the impact of climate change should take into account the scale of interaction. To improve climate change knowledge, there is a need for climate change education by scientific institutions—to provide information on local climatic conditions and global and regional drivers of climate change to local communities.
NASA Astrophysics Data System (ADS)
Aleman, A.; Olsen, L. M.; Ritz, S.; Stevens, T.; Morahan, M.; Grebas, S. K.
2011-12-01
NASA's Global Change Master Directory provides the scientific community with the ability to discover, access, and use Earth science data, data-related services, and climate diagnostics worldwide.The GCMD offers descriptions of Earth science data sets using the Directory Interchange Format (DIF) metadata standard; Earth science related data services are described using the Service Entry Resource Format (SERF); and climate visualizations are described using the Climate Diagnostic (CD) standard. The DIF, SERF and CD standards each capture data attributes used to determine whether a data set, service, or climate visualization is relevant to a user's needs.Metadata fields include: title, summary, science keywords, service keywords, data center, data set citation, personnel, instrument, platform, quality, related URL, temporal and spatial coverage, data resolution and distribution information.In addition, nine valuable sets of controlled vocabularies have been developed to assist users in normalizing the search for data descriptions. An update to the GCMD's search functionality is planned to further capitalize on the controlled vocabularies during database queries.By implementing a dynamic keyword "tree", users will have the ability to search for data sets by combining keywords in new ways.This will allow users to conduct more relevant and efficient database searches to support the free exchange and re-use of Earth science data.
AmeriFlux US-SCd Southern California Climate Gradient - Sonoran Desert
DOE Office of Scientific and Technical Information (OSTI.GOV)
Goulden, Mike
This is the AmeriFlux version of the carbon flux data for the site US-SCd Southern California Climate Gradient - Sonoran Desert. Site Description - Half hourly data are available at https://www.ess.uci.edu/~california/. This site is one of six Southern California Climate Gradient flux towers operated along an elevation gradient (sites are US-SCg, US-SCs, US-SCf, US-SCw, US-SCc, US-SCd). This site is a low desert site in Southern California's rain shadow; the climate is extremely dry and hot. The site has experience repeated droughts, with negligible rainfall during several years of the record.
NASA Astrophysics Data System (ADS)
Divíšek, Jan; Zelený, David; Culek, Martin; Št'astný, Karel
2014-08-01
Studies that explore species-environment relationships at a broad scale are usually limited by the availability of sufficient habitat description, which is often too coarse to differentiate natural habitat patches. Therefore, it is not well understood how the distribution of natural habitats affects broad-scale patterns in the distribution of animal species. In this study, we evaluate the role of field-mapped natural habitats, land-cover types derived from remote sensing and climate on the composition of assemblages of five distinct animal groups, namely non-volant mammals, birds, reptiles, amphibians and butterflies native to the Czech Republic. First, we used variation partitioning based on redundancy analysis to evaluate the extent to which the environmental variables and their spatial structure might underlie the observed spatial patterns in the composition of animal assemblages. Second, we partitioned variations explained by climate, natural habitats and land-cover to compare their relative importance. Finally, we tested the independent effects of each variable in order to evaluate the significance of their contributions to the environmental model. Our results showed that spatial patterns in the composition of assemblages of almost all the considered animal groups may be ascribed mostly to variations in the environment. Although the shared effects of climatic variables, natural habitats and land-cover types explained the largest proportion of variation in each animal group, the variation explained purely by natural habitats was always higher than the variation explained purely by climate or land-cover. We conclude that most spatial variation in the composition of assemblages of almost all animal groups probably arises from biological processes operating within a spatially structured environment and suggest that natural habitats are important to explain observed patterns because they often perform better than habitat descriptions based on remote sensing. This underlines the value of using appropriate habitat data, for which high-resolution and large-area field-mapping projects are necessary.
Randles, C A; Da Silva, A M; Buchard, V; Colarco, P R; Darmenov, A; Govindaraju, R; Smirnov, A; Holben, B; Ferrare, R; Hair, J; Shinozuka, Y; Flynn, C J
2017-09-01
The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) updates NASA's previous satellite era (1980 - onward) reanalysis system to include additional observations and improvements to the Goddard Earth Observing System, Version 5 (GEOS-5) Earth system model. As a major step towards a full Integrated Earth Systems Analysis (IESA), in addition to meteorological observations, MERRA-2 now includes assimilation of aerosol optical depth (AOD) from various ground- and space-based remote sensing platforms. Here, in the first of a pair of studies, we document the MERRA-2 aerosol assimilation, including a description of the prognostic model (GEOS-5 coupled to the GOCART aerosol module), aerosol emissions, and the quality control of ingested observations. We provide initial validation and evaluation of the analyzed AOD fields using independent observations from ground, aircraft, and shipborne instruments. We demonstrate the positive impact of the AOD assimilation on simulated aerosols by comparing MERRA-2 aerosol fields to an identical control simulation that does not include AOD assimilation. Having shown the AOD evaluation, we take a first look at aerosol-climate interactions by examining the shortwave, clear-sky aerosol direct radiative effect. In our companion paper, we evaluate and validate available MERRA-2 aerosol properties not directly impacted by the AOD assimilation (e.g. aerosol vertical distribution and absorption). Importantly, while highlighting the skill of the MERRA-2 aerosol assimilation products, both studies point out caveats that must be considered when using this new reanalysis product for future studies of aerosols and their interactions with weather and climate.
Community Intercomparison Suite (CIS) v1.4.0: a tool for intercomparing models and observations
NASA Astrophysics Data System (ADS)
Watson-Parris, Duncan; Schutgens, Nick; Cook, Nicholas; Kipling, Zak; Kershaw, Philip; Gryspeerdt, Edward; Lawrence, Bryan; Stier, Philip
2016-09-01
The Community Intercomparison Suite (CIS) is an easy-to-use command-line tool which has been developed to allow the straightforward intercomparison of remote sensing, in situ and model data. While there are a number of tools available for working with climate model data, the large diversity of sources (and formats) of remote sensing and in situ measurements necessitated a novel software solution. Developed by a professional software company, CIS supports a large number of gridded and ungridded data sources "out-of-the-box", including climate model output in NetCDF or the UK Met Office pp file format, CloudSat, CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), MODIS (MODerate resolution Imaging Spectroradiometer), Cloud and Aerosol CCI (Climate Change Initiative) level 2 satellite data and a number of in situ aircraft and ground station data sets. The open-source architecture also supports user-defined plugins to allow many other sources to be easily added. Many of the key operations required when comparing heterogenous data sets are provided by CIS, including subsetting, aggregating, collocating and plotting the data. Output data are written to CF-compliant NetCDF files to ensure interoperability with other tools and systems. The latest documentation, including a user manual and installation instructions, can be found on our website (http://cistools.net). Here, we describe the need which this tool fulfils, followed by descriptions of its main functionality (as at version 1.4.0) and plugin architecture which make it unique in the field.
Seventh Grade Students' Conceptions of Global Warming and Climate Change
ERIC Educational Resources Information Center
Shepardson, Daniel P.; Niyogi, Dev; Choi, Soyoung; Charusombat, Umarporn
2009-01-01
The purpose of this study was to investigate seventh grade students' conceptions of global warming and climate change. The study was descriptive in nature and involved the collection of qualitative data from 91 seventh grade students from three different schools in the Midwest, USA. An open response and draw and explain assessment instrument was…
ERIC Educational Resources Information Center
Biag, Manuelito D.; Sanchez, Monika A.
2016-01-01
Background/Context: Much of the literature on school-university research partnerships has focused on collaborations that address curriculum, instruction, and leadership. Less scholarly attention has been paid to how practitioners and academics work together to improve school climate. Purpose: We seek to deepen understanding of how educators and…
Perception of Transfer Climate Factors in the Macro and Micro Organizational Work Environment
ERIC Educational Resources Information Center
Diggs, Byron Kenneth
2011-01-01
This qualitative study was designed to provide insight on the perceived transfer climate factors in the macro and micro organizational work environment that may influence an employee's willingness to transfer what was learned in a training program to the job. More specifically, the purpose of the study was to delineate descriptive patterns and…
Navigating Climate Science in the Classroom: Teacher Preparation, Perceptions and Practices
ERIC Educational Resources Information Center
Sullivan, Susan M. Buhr; Ledley, Tamara Shapiro; Lynds, Susan E.; Gold, Anne U.
2014-01-01
Results from a series of surveys describe dimensions of middle and high school science teachers' preparation for and practices around climate science instruction in the classroom. Descriptions are drawn from 877 respondents to four surveys of US middle and high school science teachers from 2009-2011. Most respondents had engaged in self-directed…
NASA Astrophysics Data System (ADS)
Kutsch, W. L.; Falge, E. M.; Brümmer, C.; Mukwashi, K.; Schmullius, C.; Hüttich, C.; Odipo, V.; Scholes, R. J.; Mudau, A.; Midgley, G.; Stevens, N.; Hickler, T.; Scheiter, S.; Martens, C.; Twine, W.; Iiyambo, T.; Bradshaw, K.; Lück, W.; Lenfers, U.; Thiel-Clemen, T.; du Toit, J.
2015-12-01
Sub-Saharan Africa currently experiences rapidly growing human population, intrinsically tied to substantial changes in land use on shrubland, savanna and mixed woodland ecosystems due to over-exploitation. Significant conversions driving degradation, affecting fire frequency and water availability, and fueling climate change are expected to increase in the immediate future. However, measured data of greenhouse gas emissions as affected by land use change are scarce to entirely lacking from this region. The project 'Adaptive Resilience of Southern African Ecosystems' (ARS AfricaE) conducts research and develops scenarios of ecosystem development under climate change, for management support in conservation or for planning rural area development. This will be achieved by (1) creation of a network of research clusters (paired sites with natural and altered vegetation) along an aridity gradient in South Africa for ground-based micrometeorological in-situ measurements of energy and matter fluxes, (2) linking biogeochemical functions with ecosystem structure, and eco-physiological properties, (3) description of ecosystem disturbance (and recovery) in terms of ecosystem function such as carbon balance components and water use efficiency, (4) set-up of individual-based models to predict ecosystem dynamics under (post) disturbance managements, (5) combination with long-term landscape dynamic information derived from remote sensing and aerial photography, and (6) development of sustainable management strategies for disturbed ecosystems and land use change. Emphasis is given on validation (by a suite of field measurements) of estimates obtained from eddy covariance, model approaches and satellite derivations.
High-Resolution Regional Reanalysis in China: Evaluation of 1 Year Period Experiments
NASA Astrophysics Data System (ADS)
Zhang, Qi; Pan, Yinong; Wang, Shuyu; Xu, Jianjun; Tang, Jianping
2017-10-01
Globally, reanalysis data sets are widely used in assessing climate change, validating numerical models, and understanding the interactions between the components of a climate system. However, due to the relatively coarse resolution, most global reanalysis data sets are not suitable to apply at the local and regional scales directly with the inadequate descriptions of mesoscale systems and climatic extreme incidents such as mesoscale convective systems, squall lines, tropical cyclones, regional droughts, and heat waves. In this study, by using a data assimilation system of Gridpoint Statistical Interpolation, and a mesoscale atmospheric model of Weather Research and Forecast model, we build a regional reanalysis system. This is preliminary and the first experimental attempt to construct a high-resolution reanalysis for China main land. Four regional test bed data sets are generated for year 2013 via three widely used methods (classical dynamical downscaling, spectral nudging, and data assimilation) and a hybrid method with data assimilation coupled with spectral nudging. Temperature at 2 m, precipitation, and upper level atmospheric variables are evaluated by comparing against observations for one-year-long tests. It can be concluded that the regional reanalysis with assimilation and nudging methods can better produce the atmospheric variables from surface to upper levels, and regional extreme events such as heat waves, than the classical dynamical downscaling. Compared to the ERA-Interim global reanalysis, the hybrid nudging method performs slightly better in reproducing upper level temperature and low-level moisture over China, which improves regional reanalysis data quality.
Hay, Lauren E.; LaFontaine, Jacob H.; Markstrom, Steven
2014-01-01
The accuracy of statistically downscaled general circulation model (GCM) simulations of daily surface climate for historical conditions (1961–99) and the implications when they are used to drive hydrologic and stream temperature models were assessed for the Apalachicola–Chattahoochee–Flint River basin (ACFB). The ACFB is a 50 000 km2 basin located in the southeastern United States. Three GCMs were statistically downscaled, using an asynchronous regional regression model (ARRM), to ⅛° grids of daily precipitation and minimum and maximum air temperature. These ARRM-based climate datasets were used as input to the Precipitation-Runoff Modeling System (PRMS), a deterministic, distributed-parameter, physical-process watershed model used to simulate and evaluate the effects of various combinations of climate and land use on watershed response. The ACFB was divided into 258 hydrologic response units (HRUs) in which the components of flow (groundwater, subsurface, and surface) are computed in response to climate, land surface, and subsurface characteristics of the basin. Daily simulations of flow components from PRMS were used with the climate to simulate in-stream water temperatures using the Stream Network Temperature (SNTemp) model, a mechanistic, one-dimensional heat transport model for branched stream networks.The climate, hydrology, and stream temperature for historical conditions were evaluated by comparing model outputs produced from historical climate forcings developed from gridded station data (GSD) versus those produced from the three statistically downscaled GCMs using the ARRM methodology. The PRMS and SNTemp models were forced with the GSD and the outputs produced were treated as “truth.” This allowed for a spatial comparison by HRU of the GSD-based output with ARRM-based output. Distributional similarities between GSD- and ARRM-based model outputs were compared using the two-sample Kolmogorov–Smirnov (KS) test in combination with descriptive metrics such as the mean and variance and an evaluation of rare and sustained events. In general, precipitation and streamflow quantities were negatively biased in the downscaled GCM outputs, and results indicate that the downscaled GCM simulations consistently underestimate the largest precipitation events relative to the GSD. The KS test results indicate that ARRM-based air temperatures are similar to GSD at the daily time step for the majority of the ACFB, with perhaps subweekly averaging for stream temperature. Depending on GCM and spatial location, ARRM-based precipitation and streamflow requires averaging of up to 30 days to become similar to the GSD-based output.Evaluation of the model skill for historical conditions suggests some guidelines for use of future projections; while it seems correct to place greater confidence in evaluation metrics which perform well historically, this does not necessarily mean those metrics will accurately reflect model outputs for future climatic conditions. Results from this study indicate no “best” overall model, but the breadth of analysis can be used to give the product users an indication of the applicability of the results to address their particular problem. Since results for historical conditions indicate that model outputs can have significant biases associated with them, the range in future projections examined in terms of change relative to historical conditions for each individual GCM may be more appropriate.
Validation of extremes within the Perfect-Predictor Experiment of the COST Action VALUE
NASA Astrophysics Data System (ADS)
Hertig, Elke; Maraun, Douglas; Wibig, Joanna; Vrac, Mathieu; Soares, Pedro; Bartholy, Judith; Pongracz, Rita; Mares, Ileana; Gutierrez, Jose Manuel; Casanueva, Ana; Alzbutas, Robertas
2016-04-01
Extreme events are of widespread concern due to their damaging consequences on natural and anthropogenic systems. From science to applications the statistical attributes of rare and infrequent occurrence and low probability become connected with the socio-economic aspect of strong impact. Specific end-user needs regarding information about extreme events depend on the type of application, but as a joining element there is always the request for easily accessible climate change information with a clear description of their uncertainties and limitations. Within the Perfect-Predictor Experiment of the COST Action VALUE extreme indices modelled from a wide range of downscaling methods are compared to reference indices calculated from observational data. The experiment uses reference data from a selection of 86 weather stations representative of the different climates in Europe. Results are presented for temperature and precipitation extremes and include aspects of the marginal distribution as well as spell-length related aspects.
Collected Data of The Boreal Ecosystem and Atmosphere Study (BOREAS)
NASA Technical Reports Server (NTRS)
Newcomer, J. (Editor); Landis, D. (Editor); Conrad, S. (Editor); Curd, S. (Editor); Huemmrich, K. (Editor); Knapp, D. (Editor); Morrell, A. (Editor); Nickerson, J. (Editor); Papagno, A. (Editor); Rinker, D. (Editor)
2000-01-01
The Boreal Ecosystem-Atmosphere Study (BOREAS) was a large-scale international interdisciplinary climate-ecosystem interaction experiment in the northern boreal forests of Canada. Its goal was to improve our understanding of the boreal forests -- how they interact with the atmosphere, how much CO2 they can store, and how climate change will affect them. BOREAS wanted to learn to use satellite data to monitor the forests, and to improve computer simulation and weather models so scientists can anticipate the effects of global change. This BOREAS CD-ROM set is a set of 12 CD-ROMs containing the finalized point data sets and compressed image data from the BOREAS Project. All point data are stored in ASCII text files, and all image and GIS products are stored as binary images, compressed using GZip. Additional descriptions of the various data sets on this CD-ROM are available in other documents in the BOREAS series.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Munger, J. William; Foster, David R.; Richardson, Andrew D.
This report summarizes work to improve quantitative understanding of the terrestrial ecosystem processes that control carbon sequestration in unmanaged forests It builds upon the comprehensive long-term observations of CO2 fluxes, climate and forest structure and function at the Harvard Forest in Petersham, MA. This record includes the longest CO2 flux time series in the world. The site is a keystone for the AmeriFlux network. Project Description The project synthesizes observations made at the Harvard Forest HFEMS and Hemlock towers, which represent the dominant mixed deciduous and coniferous forest types in the northeastern United States. The 20+ year record of carbonmore » uptake at Harvard Forest and the associated comprehensive meteorological and biometric data, comprise one of the best data sets to challenge ecosystem models on time scales spanning hourly, daily, monthly, interannual and multi-decadal intervals, as needed to understand ecosystem change and climate feedbacks.« less
Hydroclimatological And Anthropogenic Drivers For Cholera Spreading
NASA Astrophysics Data System (ADS)
Righetto, Lorenzo; Bertuzzo, Enrico; Mari, Lorenzo; Casagrandi, Renato; Gatto, Marino; Rinaldo, Andrea
2010-05-01
The nature of waterborne diseases, among which cholera has a prominent importance, calls for a better understanding of the link between epidemic spreading, water and climate. To this end, we have developed a framework which involves a network-based description of a river system, connected with local communities which act as nodes of the network. This has allowed us to produce consistent simulations of real case studies. More recent investigations comprise the evaluation of the spreading velocity of an epidemic wave by means of a reaction-diffusion modeling approach. In particular, we have found that both transport processes and epidemiological quantities, such as the basic reproduction number, have a crucial effect in controlling the spreading of the epidemics. We first developed a description of bacterial movement along the network driven by advection and diffusion; afterward, we have included the movement of human populations. This latter model allowed us to establish the conditions that can trigger epidemic waves that start from the coastal region, where bacteria are autochthonous, and travel inland. In particular, our findings suggest that even relatively low values of human diffusion can have the epidemic propagate upstream. The interaction between climate, hydrology and epidemic events is still much debated, since no clear correlation between climatologic and epidemiological phenomena has emerged so far. However, a spatial assessment of hydrological and epidemiological mechanisms could be crucial to understand the evolution of cholera outbreaks. In particular, a hotly debated topic is the understanding of the mechanisms that can generate patterns of cholera incidence that exhibit an intra-annual double peak, as frequently observed in endemic region such as Bangladesh. One of the possible explanations proposed in the literature is that spring droughts cause bacteria concentration in water to rise dramatically, triggering the first peak. On the other hand similar mechanisms can occur during flood recessions in autumn together with major water sanitation system failures and higher population density. We show here the results of an ecohydrological model that couples the dynamics of the disease to a description of both the local water reservoir and of the local river section. The goal of this modeling exercise is to reproduce and understand the mechanisms behind intra-annual cholera incidence dynamics driven by hydrologic variability.
A design space of visualization tasks.
Schulz, Hans-Jörg; Nocke, Thomas; Heitzler, Magnus; Schumann, Heidrun
2013-12-01
Knowledge about visualization tasks plays an important role in choosing or building suitable visual representations to pursue them. Yet, tasks are a multi-faceted concept and it is thus not surprising that the many existing task taxonomies and models all describe different aspects of tasks, depending on what these task descriptions aim to capture. This results in a clear need to bring these different aspects together under the common hood of a general design space of visualization tasks, which we propose in this paper. Our design space consists of five design dimensions that characterize the main aspects of tasks and that have so far been distributed across different task descriptions. We exemplify its concrete use by applying our design space in the domain of climate impact research. To this end, we propose interfaces to our design space for different user roles (developers, authors, and end users) that allow users of different levels of expertise to work with it.
NASA Astrophysics Data System (ADS)
Kirk, K. B.; Manduca, C. A.; Myers, J. D.; Loxsom, F.
2009-12-01
Global climate change and energy use are among the most relevant and pressing issues in today’s science curriculum, yet they are also complex topics to teach. The underlying science spans multiple disciplines and is quickly evolving. Moreover, a comprehensive treatment of climate change and energy use must also delve into perspectives not typically addressed in geosciences courses, such as public policy and economics. Thus, faculty attempting to address these timely issues face many challenges. To support faculty in teaching these subjects, the On the Cutting Edge faculty development program has created a series of websites and workshop opportunities to provide faculty with information and resources for teaching about climate and energy. A web-based collection of teaching materials was developed in conjunction with the On the Cutting Edge workshops “Teaching about Energy in Geoscience Courses: Current Research and Pedagogy.” The website is designed to provide faculty with examples, references and ideas for either incorporating energy topics into existing geoscience courses or for designing or refining a course about energy. The website contains a collection of over 30 classroom and lab activities contributed by faculty and covering such diverse topics as renewable energy, energy policy and energy conservation. Course descriptions and syllabi for energy courses address audiences ranging from introductory courses to advanced seminars. Other materials available on the website include a collection of visualizations and animations, a catalog of recommended books, presentations and related references from the teaching energy workshops, and ideas for novel approaches or new topics for teaching about energy in the geosciences. The Teaching Climate Change website hosts large collections of teaching materials spanning many different topics within climate change, climatology and meteorology. Classroom activities highlight diverse pedagogic approaches such as role-playing, inquiry-based learning via online data sets, and the use of computer models. The website houses course descriptions and syllabi for both introductory-level and upper-level climate courses contributed by faculty. Collections of climate visualizations and recommended references help faculty navigate to online materials that are best suited for their classroom. The On the Cutting Edge program features a biennial workshop series about teaching climate change, held in conjunction with the American Quaternary Association. Presentations, teaching ideas and references from the 2006 and 2008 workshops are available, along with applications for the upcoming workshop to be held in August 2010. All of these materials can be found at http://serc.carleton.edu/NAGTWorkshops/energy and http://serc.carleton.edu/NAGTWorkshops/climatechange. Faculty are encouraged to submit their own teaching materials to the web collections via on-line forms for submitting information and uploading files.
Building Community Around Hydrologic Data Models Within CUAHSI
NASA Astrophysics Data System (ADS)
Maidment, D.
2007-12-01
The Consortium of Universities for the Advancement of Hydrologic Science, Inc (CUAHSI) has a Hydrologic Information Systems project which aims to provide better data access and capacity for data synthesis for the nation's water information, both that collected by academic investigators and that collected by water agencies. These data include observations of streamflow, water quality, groundwater levels, weather and climate and aquatic biology. Each water agency or research investigator has a unique method of formatting their data (syntactic heterogeneity) and describing their variables (semantic heterogeneity). The result is a large agglomeration of data in many formats and descriptions whose full content is hard to interpret and analyze. CUAHSI is helping to resolve syntactic heterogeneity through the development of WaterML, a standard XML markup language for communicating water observations data through web services, and a standard relational database structure for archiving data called the Observations Data Model. Variables in these data archiving and communicating systems are indexed against a controlled vocabulary of descriptive terms to provide the capacity to synthesize common data types from disparate data sources.
NASA Technical Reports Server (NTRS)
Reph, M. G.
1984-01-01
This document provides a summary of information available in the NASA Climate Data Catalog. The catalog provides scientific users with technical information about selected climate parameter data sets and the associated sensor measurements from which they are derived. It is an integral part of the Pilot Climate Data System (PCDS), an interactive, scientific management system for locating, obtaining, manipulating, and displaying climate research data. The catalog is maintained in a machine readable representation which can easily be accessed via the PCDS. The purposes, format and content of the catalog are discussed. Summarized information is provided about each of the data sets currently described in the catalog. Sample detailed descriptions are included for individual data sets or families of related data sets.
NASA Astrophysics Data System (ADS)
Dwivedi, R.; McIntosh, J. C.; Meixner, T.; Ferré, T. P. A.; Chorover, J.
2016-12-01
Mountain systems are critical sources of recharge to adjacent alluvial basins in dryland regions. Yet, mountain systems face poorly defined threats due to climate change in terms of reduced snowpack, precipitation changes, and increased temperatures. Fundamentally, the climate risks to mountain systems are uncertain due to our limited understanding of natural recharge processes. Our goal is to combine measurements and models to provide improved spatial and temporal descriptions of groundwater flow paths and transit times in a headwater catchment located in a sub-humid region. This information is important to quantifying groundwater age and, thereby, to providing more accurate assessments of the vulnerability of these systems to climate change. We are using: (a) combination of geochemical composition, along with 2H/18O and 3H isotopes to improve an existing conceptual model for mountain block recharge (MBR) for the Marshall Gulch Catchment (MGC) located within the Santa Catalina Mountains. The current model only focuses on shallow flow paths through the upper unconfined aquifer with no representation of the catchment's fractured-bedrock aquifer. Groundwater flow, solute transport, and groundwater age will be modeled throughout MGC using COMSOL Multiphysics® software. Competing models in terms of spatial distribution of required hydrologic parameters, e.g. hydraulic conductivity and porosity, will be proposed and these models will be used to design discriminatory data collection efforts based on multi-tracer methods. Initial end-member mixing results indicate that baseflow in MGC, if considered the same as the streamflow during the dry periods, is not represented by the chemistry of deep groundwater in the mountain system. In the ternary mixing space, most of the samples plot outside the mixing curve. Therefore, to further constrain the contributions of water from various reservoirs we are collecting stable water isotopes, tritium, and solute chemistry of precipitation, shallow groundwater, local spring water, MGC streamflow, and at a drainage location much lower than MGC outlet to better define and characterize each end-member of the ternary mixing model. Consequently, the end-member mixing results are expected to facilitate us in better understanding the MBR processes in and beyond MGC. Mountain systems are critical sources of recharge to adjacent alluvial basins in dryland regions. Yet, mountain systems face poorly defined threats due to climate change in terms of reduced snowpack, precipitation changes, and increased temperatures. Fundamentally, the climate risks to mountain systems are uncertain due to our limited understanding of natural recharge processes. Our goal is to combine measurements and models to provide improved spatial and temporal descriptions of groundwater flow paths and transit times in a headwater catchment located in a sub-humid region. This information is important to quantifying groundwater age and, thereby, to providing more accurate assessments of the vulnerability of these systems to climate change. We are using: (a) combination of geochemical composition, along with 2H/18O and 3H isotopes to improve an existing conceptual model for mountain block recharge (MBR) for the Marshall Gulch Catchment (MGC) located within the Santa Catalina Mountains. The current model only focuses on shallow flow paths through the upper unconfined aquifer with no representation of the catchment's fractured-bedrock aquifer. Groundwater flow, solute transport, and groundwater age will be modeled throughout MGC using COMSOL Multiphysics® software. Competing models in terms of spatial distribution of required hydrologic parameters, e.g. hydraulic conductivity and porosity, will be proposed and these models will be used to design discriminatory data collection efforts based on multi-tracer methods. Initial end-member mixing results indicate that baseflow in MGC, if considered the same as the streamflow during the dry periods, is not represented by the chemistry of deep groundwater in the mountain system. In the ternary mixing space, most of the samples plot outside the mixing curve. Therefore, to further constrain the contributions of water from various reservoirs we are collecting stable water isotopes, tritium, and solute chemistry of precipitation, shallow groundwater, local spring water, MGC streamflow, and at a drainage location much lower than MGC outlet to better define and characterize each end-member of the ternary mixing model. Consequently, the end-member mixing results are expected to facilitate us in better understanding the MBR processes in and beyond MGC.
Modeling behavioral thermoregulation in a climate change sentinel.
Moyer-Horner, Lucas; Mathewson, Paul D; Jones, Gavin M; Kearney, Michael R; Porter, Warren P
2015-12-01
When possible, many species will shift in elevation or latitude in response to rising temperatures. However, before such shifts occur, individuals will first tolerate environmental change and then modify their behavior to maintain heat balance. Behavioral thermoregulation allows animals a range of climatic tolerances and makes predicting geographic responses under future warming scenarios challenging. Because behavioral modification may reduce an individual's fecundity by, for example, limiting foraging time and thus caloric intake, we must consider the range of behavioral options available for thermoregulation to accurately predict climate change impacts on individual species. To date, few studies have identified mechanistic links between an organism's daily activities and the need to thermoregulate. We used a biophysical model, Niche Mapper, to mechanistically model microclimate conditions and thermoregulatory behavior for a temperature-sensitive mammal, the American pika (Ochotona princeps). Niche Mapper accurately simulated microclimate conditions, as well as empirical metabolic chamber data for a range of fur properties, animal sizes, and environmental parameters. Niche Mapper predicted pikas would be behaviorally constrained because of the need to thermoregulate during the hottest times of the day. We also showed that pikas at low elevations could receive energetic benefits by being smaller in size and maintaining summer pelage during longer stretches of the active season under a future warming scenario. We observed pika behavior for 288 h in Glacier National Park, Montana, and thermally characterized their rocky, montane environment. We found that pikas were most active when temperatures were cooler, and at sites characterized by high elevations and north-facing slopes. Pikas became significantly less active across a suite of behaviors in the field when temperatures surpassed 20°C, which supported a metabolic threshold predicted by Niche Mapper. In general, mechanistic predictions and empirical observations were congruent. This research is unique in providing both an empirical and mechanistic description of the effects of temperature on a mammalian sentinel of climate change, the American pika. Our results suggest that previously underinvestigated characteristics, specifically fur properties and body size, may play critical roles in pika populations' response to climate change. We also demonstrate the potential importance of considering behavioral thermoregulation and microclimate variability when predicting animal responses to climate change.
Castillo, Andrea G; Alò, Dominique; González, Benito A; Samaniego, Horacio
2018-01-01
The main goal of this contribution was to define the ecological niche of the guanaco ( Lama guanicoe ), to describe potential distributional changes, and to assess the relative importance of niche conservatism and divergence processes between the two lineages described for the species ( L.g. cacsilensis and L.g. guanicoe ). We used maximum entropy to model lineage's climate niche from 3,321 locations throughout continental Chile, and developed future niche models under climate change for two extreme greenhouse gas emission scenarios (RCP2.6 and RCP8.5). We evaluated changes of the environmental niche and future distribution of the largest mammal in the Southern Cone of South America. Evaluation of niche conservatism and divergence were based on identity and background similarity tests. We show that: (a) the current geographic distribution of lineages is associated with different climatic requirements that are related to the geographic areas where these lineages are located; (b) future distribution models predict a decrease in the distribution surface under both scenarios; (c) a 3% decrease of areal protection is expected if the current distribution of protected areas is maintained, and this is expected to occur at the expense of a large reduction of high quality habitats under the best scenario; (d) current and future distribution ranges of guanaco mostly adhere to phylogenetic niche divergence hypotheses between lineages. Associating environmental variables with species ecological niche seems to be an important aspect of unveiling the particularities of, both evolutionary patterns and ecological features that species face in a changing environment. We report specific descriptions of how these patterns may play out under the most extreme climate change predictions and provide a grim outlook of the future potential distribution of guanaco in Chile. From an ecological perspective, while a slightly smaller distribution area is expected, this may come with an important reduction of available quality habitats. From the evolutionary perspective, we describe the limitations of this taxon as it experiences forces imposed by climate change dynamics.
Castillo, Andrea G.; González, Benito A.
2018-01-01
Background The main goal of this contribution was to define the ecological niche of the guanaco (Lama guanicoe), to describe potential distributional changes, and to assess the relative importance of niche conservatism and divergence processes between the two lineages described for the species (L.g. cacsilensis and L.g. guanicoe). Methods We used maximum entropy to model lineage’s climate niche from 3,321 locations throughout continental Chile, and developed future niche models under climate change for two extreme greenhouse gas emission scenarios (RCP2.6 and RCP8.5). We evaluated changes of the environmental niche and future distribution of the largest mammal in the Southern Cone of South America. Evaluation of niche conservatism and divergence were based on identity and background similarity tests. Results We show that: (a) the current geographic distribution of lineages is associated with different climatic requirements that are related to the geographic areas where these lineages are located; (b) future distribution models predict a decrease in the distribution surface under both scenarios; (c) a 3% decrease of areal protection is expected if the current distribution of protected areas is maintained, and this is expected to occur at the expense of a large reduction of high quality habitats under the best scenario; (d) current and future distribution ranges of guanaco mostly adhere to phylogenetic niche divergence hypotheses between lineages. Discussion Associating environmental variables with species ecological niche seems to be an important aspect of unveiling the particularities of, both evolutionary patterns and ecological features that species face in a changing environment. We report specific descriptions of how these patterns may play out under the most extreme climate change predictions and provide a grim outlook of the future potential distribution of guanaco in Chile. From an ecological perspective, while a slightly smaller distribution area is expected, this may come with an important reduction of available quality habitats. From the evolutionary perspective, we describe the limitations of this taxon as it experiences forces imposed by climate change dynamics. PMID:29868293
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.
NASA Astrophysics Data System (ADS)
Alvanos, Michail; Christoudias, Theodoros
2017-10-01
This paper presents an application of GPU accelerators in Earth system modeling. We focus on atmospheric chemical kinetics, one of the most computationally intensive tasks in climate-chemistry model simulations. We developed a software package that automatically generates CUDA kernels to numerically integrate atmospheric chemical kinetics in the global climate model ECHAM/MESSy Atmospheric Chemistry (EMAC), used to study climate change and air quality scenarios. A source-to-source compiler outputs a CUDA-compatible kernel by parsing the FORTRAN code generated by the Kinetic PreProcessor (KPP) general analysis tool. All Rosenbrock methods that are available in the KPP numerical library are supported.Performance evaluation, using Fermi and Pascal CUDA-enabled GPU accelerators, shows achieved speed-ups of 4. 5 × and 20. 4 × , respectively, of the kernel execution time. A node-to-node real-world production performance comparison shows a 1. 75 × speed-up over the non-accelerated application using the KPP three-stage Rosenbrock solver. We provide a detailed description of the code optimizations used to improve the performance including memory optimizations, control code simplification, and reduction of idle time. The accuracy and correctness of the accelerated implementation are evaluated by comparing to the CPU-only code of the application. The median relative difference is found to be less than 0.000000001 % when comparing the output of the accelerated kernel the CPU-only code.The approach followed, including the computational workload division, and the developed GPU solver code can potentially be used as the basis for hardware acceleration of numerous geoscientific models that rely on KPP for atmospheric chemical kinetics applications.
NASA Astrophysics Data System (ADS)
Timuhins, Andrejs; Bethers, Uldis; Bethers, Peteris; Klints, Ilze; Sennikovs, Juris; Frishfelds, Vilnis
2017-04-01
In a changing climate it is essential to estimate its impacts on different economic fields. In our study we tried to create a framework for climate change assessment and climate change impact estimation for the territory of Latvia and to create results which are also understandable for non-scientists (stakeholder, media and public). This approach allowed us to more carefully assess the presentation and interpretation of results and their validation, for public viewing. For the presentation of our work a website was created (www.modlab.lv/klimats) containing two types of documents in a unified framework, meteorological parameter analysis of different easily interpretable derivative values. Both of these include analysis of the current situation as well as illustrate the projection for future time periods. Derivate values are calculated using two data sources: the bias corrected regional climate data and meteorological observation data. Derivative documents contain description of derived value, some interesting facts and conclusions. Additionally, all results may be viewed in temporal and spatial graphs and maps, for different time periods as well as different seasons. Bias correction (Sennikovs and Bethers, 2009) for the control period 1961-1990 is applied to RCM data series. Meteorological observation data of the Latvian Environment, Geology, and Meteorology Agency and ENSEMBLES project daily data of 13 RCM runs for the period 1960-2100 are used. All the documents are prepared in python notebooks, which allow for flexible changes. At the moment following derivative values have been published: forest fire risk index, wind energy, phenology (Degree days), road condition (friction, ice conditions), daily minimal meteorological visibility, headache occurrence rate, firs snow date and meteorological parameter analysis: temperature, precipitation, wind speed, relative humidity, and cloudiness. While creating these products RCM ability to represent the actual climate was analysed from different perspectives, for example, we found that forest fire index has qualitative differences depending on the data used in calculation either using observed data or RCM data, which could be caused by the differences in precipitation and temperature cross correlation (Bethers, P., Sennikovs, J. and Timuhins, A. 2011) The present work has been funded by the Latvian National Research Program on the "The value and dynamic of Latvia's ecosystems under changing climate" (EVIDEnT). References Sennikovs, J. and Bethers, U. (2009), Statistical downscaling method of regional climate model results for hydrological modelling. 18th World IMACS / MODSIM Congress, Cairns, Australia Bethers, P., Sennikovs, J. and Timuhins, A. (2011), Skill assessment of regional climate models:T/P correlations impacts on hydrological modeling. Geophysical Research Abstracts Vol. 13, EGU2011-7068, 2011 EGU General Assembly 2011
Role of the ocean in climate changes
NASA Technical Reports Server (NTRS)
Gulev, Sergey K.
1992-01-01
The present program aimed at the study of ocean climate change is prepared by a group of scientists from State Oceanographic Institute, Academy of Science of Russia, Academy of Science of Ukraine and Moscow State University. It appears to be a natural evolution of ideas and achievements that have been developed under national and international ocean research projects such as SECTIONS, WOCE, TOGA, JGOFS and others. The two primary goals are set in the program ROCC. (1) Quantitative description of the global interoceanic 'conveyor' and it's role in formation of the large scale anomalies in the North Atlantic. The objectives on the way to this goal are: to get the reliable estimates of year-to-year variations of heat and water exchange between the Atlantic Ocean and the atmosphere; to establish and understand the physics of long period variations in meridianal heat and fresh water transport (MHT and MFWT) in the Atlantic Ocean; to analyze the general mechanisms, that form the MHT and MFWT in low latitudes (Ekman flux), middle latitudes (western boundary currents) and high latitudes (deep convection) of the North Atlantic; to establish and to give quantitative description of the realization of global changes in SST, surface salinity, sea level and sea ice data. (2) Development of the observational system pointed at tracing the climate changes in the North Atlantic. This goal merges the following objectives: to find the proper sites that form the inter annual variations of MHT; to study the deep circulation in the 'key' points; to develop the circulation models reflecting the principle features of interoceanic circulation; and to define global and local response of the atmosphere circulation to large scale processes in the Atlantic Ocean.
Numminen, Olivia; Leino-Kilpi, Helena; Isoaho, Hannu; Meretoja, Riitta
2015-09-01
To study the relationships between newly graduated nurses' (NGNs') perceptions of their professional competence, and individual and organizational work-related factors. A multivariate, quantitative, descriptive, correlation design was applied. Data collection took place in November 2012 with a national convenience sample of 318 NGNs representing all main healthcare settings in Finland. Five instruments measured NGNs' perceptions of their professional competence, occupational commitment, empowerment, practice environment, and its ethical climate, with additional questions on turnover intentions, job satisfaction, and demographics. Descriptive statistics summarized the demographic data, and inferential statistics multivariate path analysis modeling estimated the relationships between the variables. The strongest relationship was found between professional competence and empowerment, competence explaining 20% of the variance of empowerment. The explanatory power of competence regarding practice environment, ethical climate of the work unit, and occupational commitment, and competence's associations with turnover intentions, job satisfaction, and age, were statistically significant but considerably weaker. Higher competence and satisfaction with quality of care were associated with more positive perceptions of practice environment and its ethical climate as well as higher empowerment and occupational commitment. Apart from its association with empowerment, competence seems to be a rather independent factor in relation to the measured work-related factors. Further exploration would deepen the knowledge of this relationship, providing support for planning educational and developmental programs. Research on other individual and organizational factors is warranted to shed light on factors associated with professional competence in providing high-quality and safe care as well as retaining new nurses in the workforce. The study sheds light on the strength and direction of the significantly associated work-related factors. Nursing professional bodies, managers, and supervisors can use the findings in planning orientation programs and other occupational interventions for NGNs. © 2015 Sigma Theta Tau International.
The terroir of vineyards - climatic variability in an Austrian wine-growing region
NASA Astrophysics Data System (ADS)
Gerersdorfer, T.
2010-09-01
The description of a terroir is a concept in viticulture that relates the sensory attributes of wine to the environmental conditions in which the grapes grow. Many factors are involved including climate, soil, cultivar, human practices and all these factors interact manifold. The study area of Carnuntum is a small wine-growing region in the eastern part of Austria. It is rich of Roman remains which play a major role in tourism and the marketing strategies of the wines as well. An interdisciplinary study on the environmental characteristics particularly with regard to growing conditions of grapes was started in this region. The study is concerned with the description of the physiogeographic properties of the region and with the investigation of the dominating viticultural functions. Grape-vines depend on climatic conditions to a high extent. Compared to other influencing factors like soil, climate plays a significant role. In the framework of this interdisciplinary project climatic variability within the Carnuntum wine-growing region is investigated. On the one hand microclimatic variations are influenced by soil type and by canopy management. On the other hand the variability is a result of the topoclimate (altitude, aspect and slope) and therefore relief is a major terroir factor. Results of microclimatic measurements and variations are presented with focus on the interpretation of the relationship between relief, structure of the vineyards and the climatic conditions within the course of a full year period.
This report was prepared by the Global Change Research Program (GCRP) in the National Center for Environmental Assessment (NCEA) of the Office of Research and Development (ORD) at the U.S. Environmental Protection Agency (EPA). This draft report is a description of the methods u...
Using synchronization in multi-model ensembles to improve prediction
NASA Astrophysics Data System (ADS)
Hiemstra, P.; Selten, F.
2012-04-01
In recent decades, many climate models have been developed to understand and predict the behavior of the Earth's climate system. Although these models are all based on the same basic physical principles, they still show different behavior. This is for example caused by the choice of how to parametrize sub-grid scale processes. One method to combine these imperfect models, is to run a multi-model ensemble. The models are given identical initial conditions and are integrated forward in time. A multi-model estimate can for example be a weighted mean of the ensemble members. We propose to go a step further, and try to obtain synchronization between the imperfect models by connecting the multi-model ensemble, and exchanging information. The combined multi-model ensemble is also known as a supermodel. The supermodel has learned from observations how to optimally exchange information between the ensemble members. In this study we focused on the density and formulation of the onnections within the supermodel. The main question was whether we could obtain syn-chronization between two climate models when connecting only a subset of their state spaces. Limiting the connected subspace has two advantages: 1) it limits the transfer of data (bytes) between the ensemble, which can be a limiting factor in large scale climate models, and 2) learning the optimal connection strategy from observations is easier. To answer the research question, we connected two identical quasi-geostrohic (QG) atmospheric models to each other, where the model have different initial conditions. The QG model is a qualitatively realistic simulation of the winter flow on the Northern hemisphere, has three layers and uses a spectral imple-mentation. We connected the models in the original spherical harmonical state space, and in linear combinations of these spherical harmonics, i.e. Empirical Orthogonal Functions (EOFs). We show that when connecting through spherical harmonics, we only need to connect 28% of the state variables to obtain synchronization. In addition, when connecting through EOFs, we can reduce this percentage even more to 12%. This reduction is caused by the more efficient description of the model state variables when using EOFs. The connected state variables center around the medium scale structures in the model. Small and large scale structures need not be connected in order to obtain synchronization. This could be related to the baroclinic instabilities in the QG model which are located in the medium scale structures of the model. The baroclinic instabilities are the main source of divergence between the two connected models.
NASA Astrophysics Data System (ADS)
Brook, Anna; Polinova, Maria; Housh, Mashor
2016-04-01
Agriculture and agricultural landscapes are increasingly under pressure to meet the demands of a constantly increasing human population and globally changing food patterns. At the same time, there is rising concern that climate change and food security will harm agriculture in many regions of the world (Nelson et al., 2009). Facing those treats, majority of Mediterranean countries had chosen irrigated agriculture. For crop plants water is one of the most important inputs, as it is responsible for crop growth, production and it ensures the efficiency of other inputs (e.g. seeds, fertilizers and pesticide) but its use is in competition with other local sectors (e.g. industry, urban human use). Thus, well-timed availability of water is vital to agriculture for ensured yields. The increasing demand for irrigation has necessitated the need for optimal irrigation scheduling techniques that coordinate the timing and amount of irrigation to optimally manage the water use in agriculture systems. The irrigation scheduling problem can be challenging as farmers try to deal with different conflicting objectives of maximizing their yield while minimizing irrigation water use. Another challenge in the irrigation scheduling problem is attributed to the uncertain factors involved in the plant growth process during the growing season. Most notable, the climatic factors such as evapotranspiration and rainfall, these uncertain factors add a third objective to the farmer perspective, namely, minimizing the risk associated with these uncertain factors. Nevertheless, advancements in weather forecasting reduced the uncertainty level associated with future climatic data. Thus, climatic forecasts can be reliably employed to guide optimal irrigation schedule scheme when coupled with stochastic optimization models (Housh et al., 2012). Many studies have concluded that optimal irrigation decisions can provide substantial economic value over conventional irrigation decisions (Wang and Cai 2009). These studies have only incorporated short-term (weekly) forecasts, missing the potential benefit of the mid-term (seasonal) climate forecasts The latest progress in new data acquisition technologies (mainly in the field of Earth observation by remote sensing and imaging spectroscopy systems) as well as the state-of-the-art achievements in the fields of geographical information systems (GIS), computer science and climate and climate impact modelling enable to develop both integrated modelling and realistic spatial simulations. The present method is the use of field spectroscopy technology to keep constant monitoring of the field. The majority of previously developed decision support systems use satellite remote sensing data that provide very limited capabilities (conventional and basic parameters). The alternative is to use a more progressive technology of hyperspectral airborne or ground-based imagery data that provide an exhaustive description of the field. Nevertheless, this alternative is known to be very costly and complex. As such, we will present a low-cost imaging spectroscopy technology supported by detailed and fine-resolution field spectroscopy as a cost effective option for near field real-time monitoring tool. In order to solve the soil water balance and to predict the water irrigation volume a pedological survey is realized in the evaluation study areas.The remote sensing and field spectroscopy were applied to integrate continuous feedbacks from the field (e.g. soil moisture, organic/inorganic carbon, nitrogen, salinity, fertilizers, sulphur acid, texture; crop water-stress, plant stage, LAI , chlorophyll, biomass, yield prediction applying PROSPECT+SILT ; Fraction of Absorbed Photosynthetically Active Radiation FAPAR) estimated based on remote sensing information to minimize the errors associated with crop simulation process. A stochastic optimization model will be formulated that take into account both mid-term seasonal probabilistic climate prediction and short-term weekly forecasts. In order to optimize the water resource use, the irrigation scheduling will be defined by use a simulation model of soil-plant and atmosphere system (e.g. SWAP model, Van Dam et al., 2008). The use of this tool is necessary to: i) take into account the soil spatial variability; ii) to predict the system behaviour under the forecasted climate; iii) define the optimized irrigation water volumes. Given this knowledge in the three domains of optimization under uncertainty, spectroscopy/remote sensing and climate forecasting, we will be presented as an integrated framework for deriving optimal irrigation decisions. References Nelson, Gerald C., et al. Climate change: Impact on agriculture and costs of adaptation. Vol. 21. Intl Food Policy Res Inst, 2009. Housh, Mashor, Avi Ostfeld, and Uri Shamir. "Seasonal multi-year optimal management of quantities and salinities in regional water supply systems." Environmental Modelling & Software 37 (2012): 55-67. Wang, Dingbao, and Ximing Cai. "Irrigation scheduling - Role of weather forecasting and farmers' behavior." Journal of Water Resources Planning and Management 135.5 (2009): 364-372. Van Dam, J. C., et al. SWAP version 3.2: Theory description and user manual. No. 1649. Wageningen, The Netherlands: Alterra, 2008.
Urban greening impacts on tropospheric ozone
NASA Astrophysics Data System (ADS)
Grote, R.; Churkina, G.; Butler, T. M.; Morfopoulos, C.
2013-12-01
Cities are characterized by elevated air temperatures as well as high anthropogenic emissions of air pollutants. Cities' greening in form of urban parks, street trees, and vegetation on roofs and walls of buildings is supposed to generally mitigate negative impacts on human health and well-being. However, high emissions of biogenic volatile organic compounds (BVOC) from certain popular urban plants in combination with the elevated concentrations of NOx have the potential to increase ground-level ozone concentrations - with negative impacts on health, agriculture, and climate. Policies targeting reduction of ground-level ozone in urban and suburban areas therefore must consider limiting BVOC emissions along with measures for decreasing NOx and VOC from anthropogenic sources. For this, integrated climate/ chemistry models are needed that take into account the species-specific physiological responses of urban plants which in turn drive their emission behavior. Current models of urban climate and air quality 1) do not account for the feedback between ozone concentrations, productivity, and BVOC emission and 2) do not distinguish different physiological properties of urban tree species. Instead environmental factors such as light, temperature, carbon dioxide, and water supply are applied disregarding interactions between such influences. Thus we may not yet be able to represent the impacts of air pollution under multiple changed conditions such as climate change, altered anthropogenic emission patterns, and new urban structures. We present here the implementation of the new BVOC emission model (Morfopolous et al., in press) that derives BVOC emissions directly from the electron production potential and consumption from photosynthesis calculation that is already supplied by the CLM land surface model. The new approach has the advantage that many environmental drivers of BVOC emissions are implicitly considered in the description of plant photosynthesis and phenology. We investigate the tradeoff between vegetation driven ozone -reduction and -formation processes in dependence on temperature, radiation, CO2 and O3 concentrations. We have parameterized suitable plant functional types for different urban greening structures, currently focusing on central European vegetation. The modified CLM model is applied in a global (CESM) and a regional climate/ air quality model (WRF-Chem) to calculate realistic ozone concentrations in the influence zones of urban conglomerations. BVOC emissions and their impacts are also calculated with the standard MEGAN2.1 approach for comparison. The simulation results are analyzed and discussed in view of the models suitability for air quality scenario estimates under simultaneously changing climate, anthropogenic emissions and plant species composition. References Morfopoulos, C., Prentice, I.C., Keenan T.F., Friedlingstein, P., Medlyn, B., Penuelas, J., Possel, M. (in press): A unifying conceptual model for the environmental responses of isoprene emission by plants. Annals of Botany
Climates of risk: a field analysis of global climate change in US media discourse, 1997-2004.
Sonnett, John
2010-11-01
How are industry and environmentalist discourses of climate risk related to dominant scientific and political discourses? This study operationalizes Bourdieu's concept of symbolic capital in order to map dimensions of risk description and prescription onto a journalistic field of industry, environmentalist, scientific, and political media. Results show that conventional definitions of risk mirror an opposition between scientific and political discourses. Prescriptions for action on risk are partly autonomous from definitions however. Environmentalist and scientific media feature more proactive discourse, and industry and political media feature more reactive discourse. Implications for future research on climate risk and relational studies of media discourse are discussed.
NASA Astrophysics Data System (ADS)
Varentsov, Mikhail; Verezemskaya, Polina; Baranyuk, Anastasia; Zabolotskikh, Elizaveta; Repina, Irina
2015-04-01
Polar lows (PL), high latitude marine mesoscale cyclones, are an enigmatic atmospheric phenomenon, which could result in windstorm damage of shipping and infrastructure in high latitudes. Because of their small spatial scales, short life times and their tendency to develop in remote data sparse regions (Zahn, Strorch, 2008), our knowledge of their behavior and climatology lags behind that of synoptic-scale cyclones. In case of continuing global warming (IPCC, 2013) and prospects of the intensification of economic activity and marine traffic in Arctic region, the problem of relevant simulation of this phenomenon by numerical models of the atmosphere, which could be used for weather and climate prediction, is especially important. The focus of this paper is researching the ability to simulate polar lows by two modern nonhydrostatic mesoscale numerical models, driven by realistic lateral boundary conditions from ERA-Interim reanalysis: regional climate model COSMO-CLM (Böhm et. al., 2009) and weather prediction and research model (WRF). Fields of wind, pressure and cloudiness, simulated by models, were compared with remote sensing data and ground meteorological observations for several cases, when polar lows were observed, in Norwegian, Kara and Laptev seas. Several types of satellite data were used: atmospheric water vapor, cloud liquid water content and surface wind fields were resampled by examining AMSR-E and AMSR-2 microwave radiometer data (MODIS Aqua, GCOM-W1), and wind fields were additionally extracted from QuickSCAT scatterometer. Infrared and visible pictures of cloud cover were obtained from MODIS (Aqua). Completed comparison shown that COSMO-CLM and WRF models could successfully reproduce evolution of polar lows and their most important characteristics such as size and wind speed in short experiments with WRF model and longer (up to half-year) experiments with COSMO-CLM model. Improvement of the quality of polar lows reproduction by these models in relation to source reanalysis fields were investigated. References: 1. Böhm U. et al. CLM - the climate version of LM: Brief description and long-term applications [Journal] // COSMO Newsletter. - 2006. - Vol. 6. 2. IPCC Fifth Assessment Report: Climate Change 2013 (AR5) Rep.,Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. 3. Zahn, M., and H. von Storch (2008), A long-term climatology of North Atlantic polar lows, Geophys. Res. Lett., 35, L22702
NASA Astrophysics Data System (ADS)
Palacios-Peña, Laura; Baró, Rocío; Jiménez-Guerrero, Pedro
2016-04-01
The changes in Earth's climate are produced by forcing agents such as greenhouse gases, clouds and atmospheric aerosols. The latter modify the Earth's radiative budget due to their optical, microphysical and chemical properties, and are considered to be the most uncertain forcing agent. There are two main approaches to the study of aerosols: (1) ground-based and remote sensing observations and (2) atmospheric modelling. With the aim of characterizing the uncertainties associated with these approaches, and estimating the radiative forcing caused by aerosols, the main objective of this work is to assess the representation of aerosol optical properties by different remote sensing sensors and online-coupled chemistry-climate models and to determine whether the inclusion of aerosol radiative feedbacks in this type of models improves the modelling outputs over Europe. Two case studies have been selected under the framework of the EuMetChem COST Action ES1004, when important aerosol episodes during 2010 over Europe took place: a Russian wildfires episode and a Saharan desert dust outbreak covering most of Europe. Model data comes from an ensemble of regional air quality-climate simulations performed by the working group 2 of EuMetChem, that investigates the importance of different processes and feedbacks in on-line coupled chemistry-climate models. These simulations are run for three different configurations for each model, differing in the inclusion (or not) of aerosol-radiation and aerosol-cloud interactions. The remote sensing data comes from three different sensors, MODIS (Moderate Resolution Imaging Spectroradiometer), OMI (Ozone Monitoring Instrument) and SeaWIFS (Sea-viewing Wide Field-of-view Sensor). The evaluation has been performed by using classical statistical metrics, comparing modelled and remotely sensed data versus a ground-based instrument network (AERONET). The evaluated variables are aerosol optical depth (AOD) and the Angström exponent (AE) at different wavelengths. Regarding the uncertainty in satellite representation of AOD, MODIS appears to have the best agreement with AERONET observations when compared to other satellite AOD observations. Focusing on the comparison between model output and MODIS and AERONET, results indicate a general slight improvement of AOD in the case of including the aerosol radiative effects in the model and a slight worsening for the Angström exponent for some stations and regions. Regarding the correlation coefficient, both episodes show similar values of this metric, which are higher for AOD. Generally, for the Angström exponent, models tend to underestimate the variability of this variable. Despite this , the improvement in the representation by on-line coupled chemistry-climate models of AOD reflected here may be of essential importance for a better description of aerosol-radiation-cloud interactions in regional climate models. On the other hand, the differences found between remote sensing sensors (which is of the same order of magnitude as the differences between the different members of the model ensemble) point out the uncertainty in the measurements and observations that have to be taken into account when the models are evaluated. Acknowledgments: the funding from REPAIR-CGL2014-59677-R projects (Spanish Ministry of Economy and Innovation, funded by the FEDER programme of the European Union). Special thanks to the EuMetChem COST ACTION ES1004.
NASA Astrophysics Data System (ADS)
Willkofer, Florian; Wood, Raul R.; Schmid, Josef; von Trentini, Fabian; Ludwig, Ralf
2016-04-01
The ClimEx project (Climate change and hydrological extreme events - risks and perspectives for water management in Bavaria and Québec) focuses on the effects of climate change on hydro-meteorological extreme events and their implications for water management in Bavaria and Québec. It builds on the conjoint analysis of a large ensemble of the CRCM5, driven by 50 members of the CanESM2, and the latest information provided through the CORDEX-initiative, to better assess the influence of natural climate variability and climatic change on the dynamics of extreme events. A critical point in the entire project is the preparation of a meteorological reference dataset with the required temporal (1-6h) and spatial (500m) resolution to be able to better evaluate hydrological extreme events in mesoscale river basins. For Bavaria a first reference data set (daily, 1km) used for bias-correction of RCM data was created by combining raster based data (E-OBS [1], HYRAS [2], MARS [3]) and interpolated station data using the meteorological interpolation schemes of the hydrological model WaSiM [4]. Apart from the coarse temporal and spatial resolution, this mosaic of different data sources is considered rather inconsistent and hence, not applicable for modeling of hydrological extreme events. Thus, the objective is to create a dataset with hourly data of temperature, precipitation, radiation, relative humidity and wind speed, which is then used for bias-correction of the RCM data being used as driver for hydrological modeling in the river basins. Therefore, daily data is disaggregated to hourly time steps using the 'Method of fragments' approach [5], based on available training stations. The disaggregation chooses fragments of daily values from observed hourly datasets, based on similarities in magnitude and behavior of previous and subsequent events. The choice of a certain reference station (hourly data, provision of fragments) for disaggregating daily station data (application of fragments) is crucial and several methods will be tested to achieve a profound spatial interpolation. This entire methodology shall be applicable for existing or newly developed datasets. References [1] Haylock, M.R., N. Hofstra, A.M.G. Klein Tank, E.J. Klok, P.D. Jones and M. New. A European daily high-resolution gridded dataset of surface temperature and precipitation. J. Geophys. Res (Atmospheres) (2008), 113, D20119, doi:10.1029/2008JD10201. [2] Rauthe, M., Steiner, H., Riediger, U., Mazurkiewicz, A. and A. Gratzki. A Central European precipitation climatology - Part I: Generation and validation of a high-resolution gridded daily data set (HYRAS). Meteorologische Zeitschrift (2013), 22/3, p.238-256. [3] MARS-AGRI4CAST. AGRI4CAST Interpolated Meteorological Data. http://mars.jrc.ec.europa.eu/mars/ About-us/AGRI4CAST/Data-distribution/AGRI4CAST-Interpolated-Meteorological-Data. 2007, last accessed May 10th, 2013. [4] Schulla, J. Model Description WaSiM - Water balance Simulation Model. 2015, available at: http://wasim.ch/en/products/wasim_description.htm. [5] Sharma, A. and S. Srikanthan. Continuous Rainfall Simulation: A Nonparametric Alternative. 30th Hydrology and Water Resources Symposium, Launceston, Tasmania, 4-7 December, 2006.
NASA Technical Reports Server (NTRS)
Aleman, Alicia; Olsen, Lola; Ritz, Scott; Morahan, Michael; Cepero, Laurel; Stevens, Tyler
2011-01-01
NASA's Global Change Master Directory provides the scientific community with the ability to discover, access, and use Earth science data, data-related services, and climate diagnostics worldwide. The GCMD offers descriptions of Earth science data sets using the Directory Interchange Format (DIF) metadata standard; Earth science related data services are described using the Service Entry Resource Format (SERF); and climate visualizations are described using the Climate Diagnostic (CD) standard. The DIF, SERF and CD standards each capture data attributes used to determine whether a data set, service, or climate visualization is relevant to a user's needs. Metadata fields include: title, summary, science keywords, service keywords, data center, data set citation, personnel, instrument, platform, quality, related URL, temporal and spatial coverage, data resolution and distribution information. In addition, nine valuable sets of controlled vocabularies have been developed to assist users in normalizing the search for data descriptions. An update to the GCMD's search functionality is planned to further capitalize on the controlled vocabularies during database queries. By implementing a dynamic keyword "tree", users will have the ability to search for data sets by combining keywords in new ways. This will allow users to conduct more relevant and efficient database searches to support the free exchange and re-use of Earth science data. http://gcmd.nasa.gov/
NASA Astrophysics Data System (ADS)
Haberlandt, U.; Gerten, D.; Schaphoff, S.; Lucht, W.
Dynamic global vegetation models are developed with the main purpose to describe the spatio-temporal dynamics of vegetation at the global scale. Increasing concern about climate change impacts has put the focus of recent applications on the sim- ulation of the global carbon cycle. Water is a prime driver of biogeochemical and biophysical processes, thus an appropriate representation of the water cycle is crucial for their proper simulation. However, these models usually lack thorough validation of the water balance they produce. Here we present a hydrological validation of the current version of the LPJ (Lund- Potsdam-Jena) model, a dynamic global vegetation model operating at daily time steps. Long-term simulated runoff and evapotranspiration are compared to literature values, results from three global hydrological models, and discharge observations from various macroscale river basins. It was found that the seasonal and spatial patterns of the LPJ-simulated average values correspond well both with the measurements and the results from the stand-alone hy- drological models. However, a general underestimation of runoff occurs, which may be attributable to the low input dynamics of precipitation (equal distribution within a month), to the simulated vegetation pattern (potential vegetation without anthro- pogenic influence), and to some generalizations of the hydrological components in LPJ. Future research will focus on a better representation of the temporal variability of climate forcing, improved description of hydrological processes, and on the consider- ation of anthropogenic land use.
The Southwest Pacific Ocean circulation and climate experiment (SPICE)
NASA Astrophysics Data System (ADS)
Ganachaud, A.; Cravatte, S.; Melet, A.; Schiller, A.; Holbrook, N. J.; Sloyan, B. M.; Widlansky, M. J.; Bowen, M.; Verron, J.; Wiles, P.; Ridgway, K.; Sutton, P.; Sprintall, J.; Steinberg, C.; Brassington, G.; Cai, W.; Davis, R.; Gasparin, F.; Gourdeau, L.; Hasegawa, T.; Kessler, W.; Maes, C.; Takahashi, K.; Richards, K. J.; Send, U.
2014-11-01
The Southwest Pacific Ocean Circulation and Climate Experiment (SPICE) is an international research program under the auspices of CLIVAR. The key objectives are to understand the Southwest Pacific Ocean circulation and the South Pacific Convergence Zone (SPCZ) dynamics, as well as their influence on regional and basin-scale climate patterns. South Pacific thermocline waters are transported in the westward flowing South Equatorial Current (SEC) toward Australia and Papua-New Guinea. On its way, the SEC encounters the numerous islands and straits of the Southwest Pacific and forms boundary currents and jets that eventually redistribute water to the equator and high latitudes. The transit in the Coral, Solomon, and Tasman Seas is of great importance to the climate system because changes in either the temperature or the amount of water arriving at the equator have the capability to modulate the El Niño-Southern Oscillation, while the southward transports influence the climate and biodiversity in the Tasman Sea. After 7 years of substantial in situ oceanic observational and modeling efforts, our understanding of the region has much improved. We have a refined description of the SPCZ behavior, boundary currents, pathways, and water mass transformation, including the previously undocumented Solomon Sea. The transports are large and vary substantially in a counter-intuitive way, with asymmetries and gating effects that depend on time scales. This paper provides a review of recent advancements and discusses our current knowledge gaps and important emerging research directions.
15 CFR 950.3 - National Climatic Center (NCC).
Code of Federal Regulations, 2014 CFR
2014-01-01
...; develops analytical and descriptive products to meet user requirements; and provides facilities for the... Meteorological Experiment meteorological data, Global Atmospheric Research Program basic data set, solar...
15 CFR 950.3 - National Climatic Center (NCC).
Code of Federal Regulations, 2012 CFR
2012-01-01
...; develops analytical and descriptive products to meet user requirements; and provides facilities for the... Meteorological Experiment meteorological data, Global Atmospheric Research Program basic data set, solar...
15 CFR 950.3 - National Climatic Center (NCC).
Code of Federal Regulations, 2010 CFR
2010-01-01
...; develops analytical and descriptive products to meet user requirements; and provides facilities for the... Meteorological Experiment meteorological data, Global Atmospheric Research Program basic data set, solar...
15 CFR 950.3 - National Climatic Center (NCC).
Code of Federal Regulations, 2013 CFR
2013-01-01
...; develops analytical and descriptive products to meet user requirements; and provides facilities for the... Meteorological Experiment meteorological data, Global Atmospheric Research Program basic data set, solar...
15 CFR 950.3 - National Climatic Center (NCC).
Code of Federal Regulations, 2011 CFR
2011-01-01
...; develops analytical and descriptive products to meet user requirements; and provides facilities for the... Meteorological Experiment meteorological data, Global Atmospheric Research Program basic data set, solar...
NASA Astrophysics Data System (ADS)
Ganachaud, A. S.; Sprintall, J.; Lin, X.; Ando, K.
2016-02-01
The Southwest Pacific Ocean Circulation and Climate Experiment (SPICE) is an international research program under the auspices of CLIVAR (Climate Variability and Predictability). The key objectives are to understand the Southwest Pacific Ocean circulation and Convergence Zone (SPCZ) dynamics, as well as their influence on regional and basin-scale climate patterns. It was designed to measure and monitor the ocean circulation, and to validate and improve numerical models. South Pacific oceanic waters are carried from the subtropical gyre centre in the westward flowing South Equatorial Current (SEC), towards the southwest Pacific-a major circulation pathway that redistributes water from the subtropics to the equator and Southern Ocean. Water transit through the Coral and Solomon Seas is potentially of great importance to tropical climate prediction because changes in either the temperature or the amount of water arriving at the equator have the capability to modulate ENSO and produce basin-scale climate feedbacks. On average, the oceanic circulation is driven by the Trade Winds, and subject to substantial variability, related with the SPCZ position and intensity. The circulation is complex, with the SEC splitting into zonal jets upon encountering island archipelagos, before joining either the East Australian Current or the New Guinea Costal UnderCurrent towards the equator. SPICE included large, coordinated in situ measurement programs and high resolution numerical simulations of the area. After 8 years of substantial in situ oceanic observational and modeling efforts, our understanding of the region has much improved. We have a refined description of the SPCZ behavior, boundary currents, pathways, and water mass transformation, including the previously undocumented Solomon Sea. The transports are large and vary substantially in a counter-intuitive way, with asymmetries and gating effects that depend on time scales. We will review the recent advancements and discuss our current knowledge gaps and important emerging research directions. In particular we will discuss how SPICE, along with the Northwestern Pacific Ocean Circulation and Climate Experiment (NPOCE) and Indonesian ThroughFlow (ITF) programs could evolve toward an integrative observing system under CLIVAR coordination.
Approaches to local climate action in Colorado
NASA Astrophysics Data System (ADS)
Huang, Y. D.
2011-12-01
Though climate change is a global problem, the impacts are felt on the local scale; it follows that the solutions must come at the local level. Fortunately, many cities and municipalities are implementing climate mitigation (or climate action) policies and programs. However, they face many procedural and institutional barriers to their efforts, such of lack of expertise or data, limited human and financial resources, and lack of community engagement (Krause 2011). To address the first obstacle, thirteen in-depth case studies were done of successful model practices ("best practices") of climate action programs carried out by various cities, counties, and organizations in Colorado, and one outside Colorado, and developed into "how-to guides" for other municipalities to use. Research was conducted by reading documents (e.g. annual reports, community guides, city websites), email correspondence with program managers and city officials, and via phone interviews. The information gathered was then compiled into a series of reports containing a narrative description of the initiative; an overview of the plan elements (target audience and goals); implementation strategies and any indicators of success to date (e.g. GHG emissions reductions, cost savings); and the adoption or approval process, as well as community engagement efforts and marketing or messaging strategies. The types of programs covered were energy action plans, energy efficiency programs, renewable energy programs, and transportation and land use programs. Between the thirteen case studies, there was a range of approaches to implementing local climate action programs, examined along two dimensions: focus on climate change (whether it was direct/explicit or indirect/implicit) and extent of government authority. This benchmarking exercise affirmed the conventional wisdom propounded by Pitt (2010), that peer pressure (that is, the presence of neighboring jurisdictions with climate initiatives), the level of community engagement and enthusiasm, and most importantly staff members dedicated to the area of climate planning have a significant effect on climate mitigation policy adoption. In addition, it supported the claim asserted by Toly (2008) that an emphasis on economic co-benefits perpetuates the principle that economic growth need not be compromised when addressing climate change and weakens our capacity to shift toward a bolder paradigm in what is politically achievable in climate legislation.
Ying, Liu; Kunaviktikul, Wipada; Tonmukayakal, Ouyporn
2007-09-01
Nursing competency is important to ensure patient safety and improve the quality of nursing care. Based on competency-based human resource management strategies, the organizational climate can positively influence nursing competency. However, a review of the literature indicated that there were no studies about the relationship between nursing competency and organizational climate in the People's Republic of China. This descriptive, correlational study examined the relationship between nursing competency and the organizational climate. The sample consisted of 243 staff nurses who completed the questionnaire worked at one university hospital in Liao Ning Province. The findings showed that there was a significantly moderate positive relationship between nursing competency and organizational climate. The study results suggested that Chinese nurse managers should maintain and provide a positive organizational climate to improve nursing competency.
NASA Astrophysics Data System (ADS)
Stisen, S.; Højberg, A. L.; Troldborg, L.; Refsgaard, J. C.; Christensen, B. S. B.; Olsen, M.; Henriksen, H. J.
2012-11-01
Precipitation gauge catch correction is often given very little attention in hydrological modelling compared to model parameter calibration. This is critical because significant precipitation biases often make the calibration exercise pointless, especially when supposedly physically-based models are in play. This study addresses the general importance of appropriate precipitation catch correction through a detailed modelling exercise. An existing precipitation gauge catch correction method addressing solid and liquid precipitation is applied, both as national mean monthly correction factors based on a historic 30 yr record and as gridded daily correction factors based on local daily observations of wind speed and temperature. The two methods, named the historic mean monthly (HMM) and the time-space variable (TSV) correction, resulted in different winter precipitation rates for the period 1990-2010. The resulting precipitation datasets were evaluated through the comprehensive Danish National Water Resources model (DK-Model), revealing major differences in both model performance and optimised model parameter sets. Simulated stream discharge is improved significantly when introducing the TSV correction, whereas the simulated hydraulic heads and multi-annual water balances performed similarly due to recalibration adjusting model parameters to compensate for input biases. The resulting optimised model parameters are much more physically plausible for the model based on the TSV correction of precipitation. A proxy-basin test where calibrated DK-Model parameters were transferred to another region without site specific calibration showed better performance for parameter values based on the TSV correction. Similarly, the performances of the TSV correction method were superior when considering two single years with a much dryer and a much wetter winter, respectively, as compared to the winters in the calibration period (differential split-sample tests). We conclude that TSV precipitation correction should be carried out for studies requiring a sound dynamic description of hydrological processes, and it is of particular importance when using hydrological models to make predictions for future climates when the snow/rain composition will differ from the past climate. This conclusion is expected to be applicable for mid to high latitudes, especially in coastal climates where winter precipitation types (solid/liquid) fluctuate significantly, causing climatological mean correction factors to be inadequate.
NASA Astrophysics Data System (ADS)
Naudts, Kim; Ryder, James; McGrath, Matthew J.; Otto, Juliane; Chen, Yiying; Valade, Aude; Bellasen, Valentin; Ghattas, Josefine; Haverd, Vanessa; MacBean, Natasha; Maignan, Fabienne; Peylin, Philippe; Pinty, Bernard; Solyga, Didier; Vuichard, Nicolas; Luyssaert, Sebastiaan
2015-04-01
Since 70% of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land surface models used in Earth system models, and therefore none of today's predictions of future climate, account for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrizing a version of the land surface model ORCHIDEE to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new model called ORCHIDEE-CAN and the standard version of ORCHIDEE are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes towards a better process representation occurred for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrization was revisited after introducing twelve new parameter sets that represent specific tree species or genera rather than a group of unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, GPP, albedo and evapotranspiration over Europe. For all tested variables ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92% chance to reproduce the spatial and temporal variability of the validation data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Randles, C. A.; da Silva, A. M.; Buchard, V.
The Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) updates NASA’s previous satellite era (1980 – onward) reanalysis system to include additional observations and improvements to the Goddard Earth Observing System, Version 5 (GEOS-5) Earth system model. As a major step towards a full Integrated Earth Systems Analysis (IESA), in addition to meteorological observations, MERRA-2 now includes assimila-tion of aerosol optical depth (AOD) from various ground- and space-based remote sensing platforms. Here, in the first of a pair of studies, we document the MERRA-2 aerosol assimilation, including a description of the prognostic model (GEOS-5 coupled to the GOCARTmore » aerosol module), aerosol emissions, and the quality control of ingested observations. We provide initial validation and evaluation of the analyzed AOD fields using independent observations rom ground, aircraft, and shipborne instruments. We demonstrate the pos-itive impact of the AOD assimilation on simulated aerosols by comparing MERRA-2 aerosol fields to an identical control simulation that does not in-clude AOD assimilation. Having shown the AOD evaluation, we take a first look at aerosol-climate interactions by examining the shortwave, clear-sky aerosol direct radiative effect. In our companion paper, we evaluate and validate available MERRA-2 aerosol properties not directly impacted by the AOD assimilation (e.g. aerosol vertical distribution and absorption). Importantly, while highlighting the skill of the MERRA-2 aerosol assimilation products, both studies point out caveats that must be considered when using this new reanalysis product for future studies of aerosols and their interactions with weather and climate.« less
NASA Astrophysics Data System (ADS)
McPhee, James; Mengual, Sebastian; MacDonell, Shelley
2017-04-01
Seasonal snowpack melt constitutes the main water source for large portions of extratropical South America, including central Chile and Western Argentina. The properties and distribution of snow in the Andes are threatened by rapid climate change, characterised by warming and drying. This study provides a first attempt at detailed description of the energy balance of the seasonal snowpack and its variability along a latitudinal gradient, which is also correlated with an elevation and precipitation gradient, in the Andes Cordillera. The Snowpack model was validated at semi-arid, Mediterranean and temperate humid sites, where meteorological and snowpack properties have been observed since year 2013. Site elevations decrease from north to south, whereas precipitation climatology increases with latitude. Results show that turbulent energy exchange becomes relatively more important in periods of low snow accumulation, with sensible heat fluxes having a greater effect in cooling the snowpack at the high-altitude, low latitude site. Likewise, daily melt-freeze cycles are important in maintaining positive cold contents throughout the accumulation season at this site, and contribute to extending the duration of snow cover despite low accumulation and high radiation loads. In contrast, the southernmost, lowest elevation site shows smaller daily temperature amplitude and a much more preponderant radiation component to the energy balance. This modelling exercise highlights the nonlinearities of snow dynamics at different geographical settings in a sparsely monitored mountain area of the world, as well as the need for further understanding in order to evaluate the sensitivity of snow-dominated watersheds to global warming and climate change.
Mediterranean Cyclones in a changing climate. First statistical results
NASA Astrophysics Data System (ADS)
Tous, M.; Genoves, A.; Campins, J.; Picornell, M. A.; Jansa, A.; Mizuta, R.
2009-09-01
The Mediterranean storms play an important role in weather and climate. Their influence in determining the local weather is known; heavy precipitation systems and strong wind cases are often related to the presence of a cyclone in the Mediterranean. From a large-scale point of view, the Mediterranean storm track has importance in the vertical and horizontal transfers of heat and water vapour towards the Eastern regions. For all of these reasons, any future change related to the intensity, frequency or tracks of these storms can be important for both the local weather and local climate, at least, in the countries around the basin. The Mediterranean cyclones constitute a study subject of increasing interest. Some climatologies from long series of re-analyses, like ERA15, NCEP/NCAR and ERA40, or from operational and high resolution analysis systems, like HIRLAM_INM and ECMWF, have allowed to define the main characteristics of these storms. Generally speaking, the Mediterranean storms have the characteristics of extratropical storms, showing smaller sizes and shorter life cycles than those ones developed in other maritime areas of the world. Moreover, the influence of the land areas and high mountains around the basin and the large-scale heat releases have been revealed as key factors for understanding their genesis and rates of development. In spite of the fact that probably the existing automatic procedures include some large scale assumptions, which may not the best for the correct detection and tracking the Mediterranean storms, these procedures can provide a first and almost necessary step, from a statistical/climatological point of view, specially taking into account both the current resolution of the existent global re-analysis series and global climatic models and the state-of-the art about Mediterranean cyclones. A cyclone detection and tracking procedure, originally designed for the description of Mediterranean storms, has been applied to the low resolution (1.5 degrees lat-lon) outputs of the JMA-GSM climate general circulation model. Preliminary results are here presented. Two different periods have been analysed. The first period, covering 1979-2002 has been compared with the previously computed ERA-40 climatology of cyclones. Results agree reasonably well with those obtained from ERA-40, providing confidence to the current climate simulation of JMA-GSM. Once validated the model from the perspective of cyclonic climatology under current climate conditions, the same procedure is applied to a scenario period (2075-2099) to investigate possible changes in cyclonic activity linked to climate change.
Qualitative properties of the minimal model of carbon circulation in the biosphere
NASA Astrophysics Data System (ADS)
Pestunov, Aleksandr; Fedotov, Anatoliy; Medvedev, Sergey
2014-05-01
Substantial changes in the biosphere during recent decades have caused legitimate concern in the international community. The fact that feedbacks between the atmospheric CO2 concentration, global temperature, permafrost, ocean CO2 concentration and air humidity increases the risk of catastrophic phenomena on the planetary scale. The precautionary principle allows us to consider greenhouse effect using the mathematical models of the biosphere-climate system. Minimal models do not allow us to make a quantitative description of the "biosphere-climate" system dynamics, which is determined by the aggregate effect of the set of known climatic and biosphere processes. However, the study of such models makes it possible to understand the qualitative mechanisms of biosphere processes and to evaluate their possible consequences. The global minimal model of long-term dynamics of carbon in biosphere is considered basing on assumption that anthropogenous carbon emissions in atmosphere are absent [1]. Qualitative analysis of the model shows that there exists a set of model parameters (taken from the current estimation ranges), such that the system becomes unstable. It is also shown that external influences on the carbon circulation can lead either to degradation of the biosphere or to global temperature change [2]. This work is aimed at revealing the conditions under which the biosphere model can become unstable, which can result in catastrophic changes in the Earth's biogeocenoses. The minimal model of the biosphere-climate system describes an improbable, but, nevertheless, a possible worst-case scenario of the biosphere evolution takes into consideration only the most dangerous biosphere mechanisms and ignores some climate feedbacks (such as transpiration). This work demonstrates the possibility of implementing the trigger mode in the biosphere, which can lead to dramatic changes in the state of the biosphere even without additional burning of fossil fuels. This mode implementation is possible under parameter values of the biosphere, lying within the ranges of their existing estimates. Hence a potential hazard of any drastic change of the biosphere conditions that may speed up possible shift of the biosphere to a new stable state. References 1. Bartsev S.I., Degermendzhi A.G., Fedotov A.M., Medvedev S.B., Pestunov A.I., Pestunov I.A. The Biosphere Trigger Mechanism in the Minimal Model for the Global Carbon Cycle of the Earth // Doklady Earth Sciences, 2012, Vol. 443, Part 2, pp. 489-492. © Pleiades Publishing, Ltd., 2012. 2. Fedotov A.M., Medvedev S.B., Pestunov A.I., Pestunov I.A., Bartsev S.I., Degermendzhi A.G. Qualitative analysis of the minimal model of carbon dynamics in the biosphere // Computational Technologies. 2012. Vol. 17. N 3. pp. 91-108 (in Russian).
NASA Astrophysics Data System (ADS)
Kleinschmitt, Christoph; Boucher, Olivier; Bekki, Slimane; Lott, François; Platt, Ulrich
2017-09-01
Stratospheric aerosols play an important role in the climate system by affecting the Earth's radiative budget as well as atmospheric chemistry, and the capabilities to simulate them interactively within global models are continuously improving. It is important to represent accurately both aerosol microphysical and atmospheric dynamical processes because together they affect the size distribution and the residence time of the aerosol particles in the stratosphere. The newly developed LMDZ-S3A model presented in this article uses a sectional approach for sulfate particles in the stratosphere and includes the relevant microphysical processes. It allows full interaction between aerosol radiative effects (e.g. radiative heating) and atmospheric dynamics, including e.g. an internally generated quasi-biennial oscillation (QBO) in the stratosphere. Sulfur chemistry is semi-prescribed via climatological lifetimes. LMDZ-S3A reasonably reproduces aerosol observations in periods of low (background) and high (volcanic) stratospheric sulfate loading, but tends to overestimate the number of small particles and to underestimate the number of large particles. Thus, it may serve as a tool to study the climate impacts of volcanic eruptions, as well as the deliberate anthropogenic injection of aerosols into the stratosphere, which has been proposed as a method of geoengineering to abate global warming.
NASA Astrophysics Data System (ADS)
Ballinas, R.; Versini, P.-A.; Sempere, D.; Escaler, I.
2009-09-01
Any long-term change in the patterns of average weather in a global or regional scale is called climate change. It may cause a progressive increase of atmospheric temperature and consequently may change the amount, frequency and intensity of precipitation. All these changes of meteorological parameters may modify the water cycle: run-off, infiltration, aquifer recharge, etc. Recent studies in Catalonia foresee changes in hydrological systems caused by climate change. This will lead to alterations in the hydrological cycle that could impact in land use, in the regimen of water extractions, in the hydrological characteristics of the territory and reduced groundwater recharge. Besides, can expect a loss of flow in rivers. In addition to possible increases in the frequency of extreme rainfall, being necessary to modify the design of infrastructure. Because this, it work focuses on studying the impacts of climate change in one of the most important basins in Catalonia, the Llobregat River Basin. The basin is the hub of the province of Barcelona. It is a highly populated and urbanized catchment, where water resources are used for different purposes, as drinking water production, agricultural irrigation, industry and hydro-electrical energy production. In consequence, many companies and communities depend on these resources. To study the impact of climate change in the Llobregat basin, storms (frequency, intensity) mainly, we will need regional climate change information. A regional climate is determined by interactions at large, regional and local scales. The general circulation models (GCMs) are run at too coarse resolution to permit accurate description of these regional and local interactions. So far, they have been unable to provide consistent estimates of climate change on a local scale. Several regionalization techniques have been developed to bridge the gap between the large-scale information provided by GCMs and fine spatial scales required for regional and environmental impact studies. Downscaling methods to assess the effect of large-scale circulations on local parameters have. Statistical downscaling methods are based on the view that regional climate can be conditioned by two factors: large-scale climatic state and regional/local features. Local climate information is derived by first developing a statistical model which relates large-scale variables or "predictors" for which GCMs are trustable to regional or local surface "predictands" for which models are less skilful. The main advantage of these methods is that they are computationally inexpensive, and can be applied to outputs from different GCM experiments. Three statistical downscaling methods are applied: Analogue method, Delta Change and Direct Forcing. These methods have been used to determine daily precipitation projections at rain gauge location to study the intensity, frequency and variability of storms in a context of climate change in the Llobregat River Basin in Catalonia, Spain. This work is part of the European project "Water Change" (included in the LIFE + Environment Policy and Governance program). It deals with Medium and long term water resources modelling as a tool for planning and global change adaptation. Two stakeholders involved in the project provided the historical time series: Catalan Water Agency (ACA) and the State Meteorological Agency (AEMET).
NASA Astrophysics Data System (ADS)
Varentsov, Mikhail; Wouters, Hendrik; Trusilova, Kristina; Samsonov, Timofey; Konstantinov, Pavel
2017-04-01
In this study we present the application of the regional climate model COSMO-CLM to simulate urban heat island (UHI) phenomenon for Moscow megacity, which is the biggest agglomeration in Europe (with modern population of more than 17 million people). Significant differences of Moscow from the cities of Western Europe are related with much more continental climate with higher diurnal and annual temperature variations, and with specific building features such as its high density and almost total predominance of high-rise and low-rise blocks of flats on the private low-rise houses. Because of these building and climate features, the UHI of Moscow megacity is stronger than UHIs of many other cities of the similar size, with a mean intensity is about 2 °C and maximum intensity reaching up to 13 °C (Lokoschenko, 2014). Such a pronounced UHI together with the existence of an extensive observation network (more than 50 weather and air quality monitoring stations and few microwave temperature profilers) within the city and its surrounding make Moscow an especially interesting place for urban climate researches and good testbed for urban canopy models. In our numerical experiments, regional climate model firstly was adapted for investigated region with aim to improve quality of its simulations of rural areas. Then, to take into account urban canopy effects on thermal regime of the urbanized areas, we used two different versions of COSMO-CLM model. First is coupled with TEB (Town Energy Balance) single layer urban canopy model (Trusilova, 2013), and second is extended with bulk urban canopy scheme TERRA_URB using the Semi-empircal URban-canopY dependency parametriation SURY (Wouters et. al, 2016). Numerical experiments with these two versions of the model were run with spatial resolution about 1 km for several summer and winter months. To provide specific parameters, required for urban parameterizations, such as urban fraction, building height and street canyon aspect ratio, we used originally technology of GIS-based processing of realistic OpenStreetMap data, which includes size and shape of the most of the in the city (Samsonov et al., 2015). Our testbed allows to make more detailed comparison between the modelling approaches, and also reveals the importance of correct definition of the of turbulent mixing in the ABL in the atmospheric model, and the realistic specification of the building morphology parameters and anthropogenic heat fluxes. In addition, strong seasonal variation of the importance of different factors, responsible for UHI appearance, was shown. Moreover, the framework allows to identify and solve issues regarding the different model approaches: detailed analysis of spatial and temporal variations of modelled urban temperature anomalies and their vertical extent has shown that version of COSMO-CLM model with TERRA-URB scheme simulate UHI effect in more realistic way. Research was supported by Russian Foundation for Basic Research (RFBR) and Russian Geographic Society (RGS): RFBR projects № 16-35-00474, 15-35-21129 and 16-05-00704 A, RGS-RFBR project № 13-05-41306. References: 1. Lokoshchenko, M. A. (2014). Urban 'heat island' in Moscow. Urban Climate, 10, 550-562. 2. Samsonov, T. E., Konstantinov, P. I., & Varentsov, M. I. (2015). Object-oriented approach to urban canyon analysis and its applications in meteorological modeling. Urban Climate, 13, 122-139. 3. Trusilova K., Früh, B., Brienen, S., Walter, A., Masson, V., Pigeon, G., Becker, P. Implementation of an Urban Parameterization Scheme into the Regional Climate Model COSMO-CLM// Journal of Applied Meteorology and Climatology. 2013. Vol. 52. P. 2296-2311. 4. Wouters, H., Demuzere, M., Blahak, U., Fortuniak, K., Maiheu, B., Camps, J., & van Lipzig, N. P. (2016). The efficient urban canopy dependency parametrization (SURY) v1.0 for atmospheric modelling: description and application with the COSMO-CLM model for a Belgian summer. Geoscientific Model Development, 9(9), 3027-3054.
Haider, Khadija; Khokhar, Muhammad Fahim; Chishtie, Farrukh; RazzaqKhan, Waseem; Hakeem, Khalid Rehman
2017-03-01
Like other developing countries, Pakistan is also facing changes in temperature per decade and other climatic abnormalities like droughts and torrential rains. In order to assess and identify the extent of temperature change over Pakistan, the whole Pakistan was divided into five climatic zones ranging from very cold to hot and dry climates. Similarly, seasons in Pakistan are defined on the basis of monsoon variability as winter, pre-monsoon, monsoon, and post-monsoon. This study primarily focuses on the comparison of surface temperature observations from Pakistan Meteorological Department (PMD) network with PRECIS (Providing Regional Climates for Impacts Studies) model simulations. Results indicate that PRECIS underestimates the temperature in Northern Pakistan and during the winter season. However, there exists a fair agreement between PRECIS output and observed datasets in the lower plain and hot areas of the country. An absolute increase of 0.07 °C is observed in the mean temperature over Pakistan during the time period of 1951-2010. Especially, the increase is more significant (0.7 °C) during the last 14 years (1997-2010). Moreover, SCIAMACHY observations were used to explore the evolution of atmospheric CO 2 levels in comparison to temperature over Pakistan. CO 2 levels have shown an increasing trend during the first decade of the twenty-first century.
Monsoons: Processes, predictability, and the prospects for prediction
NASA Astrophysics Data System (ADS)
Webster, P. J.; Magaña, V. O.; Palmer, T. N.; Shukla, J.; Thomas, R. A.; Yanai, M.; Yasunari, T.
1998-06-01
The Tropical Ocean-Global Atmosphere (TOGA) program sought to determine the predictability of the coupled ocean-atmosphere system. The World Climate Research Programme's (WCRP) Global Ocean-Atmosphere-Land System (GOALS) program seeks to explore predictability of the global climate system through investigation of the major planetary heat sources and sinks, and interactions between them. The Asian-Australian monsoon system, which undergoes aperiodic and high amplitude variations on intraseasonal, annual, biennial and interannual timescales is a major focus of GOALS. Empirical seasonal forecasts of the monsoon have been made with moderate success for over 100 years. More recent modeling efforts have not been successful. Even simulation of the mean structure of the Asian monsoon has proven elusive and the observed ENSO-monsoon relationships has been difficult to replicate. Divergence in simulation skill occurs between integrations by different models or between members of ensembles of the same model. This degree of spread is surprising given the relative success of empirical forecast techniques. Two possible explanations are presented: difficulty in modeling the monsoon regions and nonlinear error growth due to regional hydrodynamical instabilities. It is argued that the reconciliation of these explanations is imperative for prediction of the monsoon to be improved. To this end, a thorough description of observed monsoon variability and the physical processes that are thought to be important is presented. Prospects of improving prediction and some strategies that may help achieve improvement are discussed.
Advantages and applicability of commonly used homogenisation methods for climate data
NASA Astrophysics Data System (ADS)
Ribeiro, Sara; Caineta, Júlio; Henriques, Roberto; Soares, Amílcar; Costa, Ana Cristina
2014-05-01
Homogenisation of climate data is a very relevant subject since these data are required as an input in a wide range of studies, such as atmospheric modelling, weather forecasting, climate change monitoring, or hydrological and environmental projects. Often, climate data series include non-natural irregularities which have to be detected and removed prior to their use, otherwise it would generate biased and erroneous results. Relocation of weather stations or changes in the measuring instruments are amongst the most relevant causes for these inhomogeneities. Depending on the climate variable, its temporal resolution and spatial continuity, homogenisation methods can be more or less effective. For example, due to its natural variability, precipitation is identified as a very challenging variable to be homogenised. During the last two decades, numerous methods have been proposed to homogenise climate data. In order to compare, evaluate and develop those methods, the European project COST Action ES0601, Advances in homogenisation methods of climate series: an integrated approach (HOME), was released in 2008. Existing homogenisation methods were improved based on the benchmark exercise issued by this project. A recent approach based on Direct Sequential Simulation (DSS), not yet evaluated by the benchmark exercise, is also presented as an innovative methodology for homogenising climate data series. DSS already proved to be a successful geostatistical method in environmental and hydrological studies, and it provides promising results for the homogenisation of climate data. Since DSS is a geostatistical stochastic approach, it accounts for the joint spatial and temporal dependence between observations, as well as the relative importance of stations both in terms of distance and correlation. This work presents a chronological review of the most commonly used homogenisation methods for climate data and available software packages. A short description and classification is provided for each method. Their advantages and applicability are discussed based on literature review and on the results of the HOME project. Acknowledgements: The authors gratefully acknowledge the financial support of "Fundação para a Ciência e Tecnologia" (FCT), Portugal, through the research project PTDC/GEO-MET/4026/2012 ("GSIMCLI - Geostatistical simulation with local distributions for the homogenization and interpolation of climate data").
The Integration of SMOS Soil Moisture in a Consistent Soil Moisture Climate Record
NASA Astrophysics Data System (ADS)
de Jeu, Richard; Kerr, Yann; Wigneron, Jean Pierre; Rodriguez-Fernandez, Nemesio; Al-Yaari, Amen; van der Schalie, Robin; Dolman, Han; Drusch, Matthias; Mecklenburg, Susanne
2015-04-01
Recently, a study funded by the European Space Agency (ESA) was set up to provide guidelines for the development of a global soil moisture climate record with a special emphasis on the integration of SMOS. Three different data fusion approaches were designed and implemented on 10 year passive microwave data (2003-2013) from two different satellite sensors; the ESA Soil Moisture Ocean Salinity Mission (SMOS) and the NASA/JAXA Advanced Scanning Microwave Radiometer (AMSR-E). The AMSR-E data covered the period from January 2003 until Oct 2011 and SMOS data covered the period from June 2010 until the end of 2013. The fusion approaches included a neural network approach (Rodriguez-Fernandez et al., this conference session HS6.4), a regression approach (Wigneron et al., 2004), and an approach based on the baseline algorithm of ESAs current Climate Change Initiative soil moisture program, the Land Parameter Retrieval Model (Van der Schalie et al., this conference session HS6.4). With this presentation we will show the first results from this study including a description of the different approaches and the validation activities using both globally covered modeled datasets and ground observations from the international soil moisture network. The statistical validation analyses will give us information on the temporal and spatial performance of the three different approaches. Based on these results we will then discuss the next steps towards a seamless integration of SMOS in a consistent soil moisture climate record. References Wigneron J.-P., J.-C. Calvet, P. de Rosnay, Y. Kerr, P. Waldteufel, K. Saleh, M. J. Escorihuela, A. Kruszewski, 'Soil Moisture Retrievals from Bi-Angular L-band Passive Microwave Observations', IEEE Trans. Geosc. Remote Sens. Let., vol 1, no. 4, 277-281, 2004.
NASA Technical Reports Server (NTRS)
Swartz, W. H.; Stolarski, R. S.; Oman, L. D.; Fleming, E. L.; Jackman, C. H.
2012-01-01
The 11-year solar cycle in solar spectral irradiance (SSI) inferred from measurements by the SOlar Radiation & Climate Experiment (SORCE) suggests a much larger variation in the ultraviolet than previously accepted. We present middle atmosphere ozone and temperature responses to the solar cycles in SORCE SSI and the ubiquitous Naval Research Laboratory (NRL) SSI reconstruction using the Goddard Earth Observing System chemistry-climate model (GEOS CCM). The results are largely consistent with other recent modeling studies. The modeled ozone response is positive throughout the stratosphere and lower mesosphere using the NRL SSI, while the SORCE SSI produces a response that is larger in the lower stratosphere but out of phase with respect to total solar irradiance above 45 km. The modeled responses in total ozone are similar to those derived from satellite and ground-based measurements, 3-6 Dobson Units per 100 units of 10.7-cm radio flux (F10.7) in the tropics. The peak zonal mean tropical temperature response 50 using the SORCE SSI is nearly 2 K per 100 units 3 times larger than the simulation using the NRL SSI. The GEOS CCM and the Goddard Space Flight Center (GSFC) 2-D coupled model are used to examine how the SSI solar cycle affects the atmosphere through direct solar heating and photolysis processes individually. Middle atmosphere ozone is affected almost entirely through photolysis, whereas the solar cycle in temperature is caused both through direct heating and photolysis feedbacks, processes that are mostly linearly separable. Further, the net ozone response results from the balance of ozone production at wavelengths less than 242 nm and destruction at longer wavelengths, coincidentally corresponding to the wavelength regimes of the SOLar STellar Irradiance Comparison Experiment (SOLSTICE) and Spectral Irradiance Monitor (SIM) on SORCE, respectively. A higher wavelength-resolution analysis of the spectral response could allow for a better prediction of the atmospheric response to arbitrary SSI variations.
NASA Astrophysics Data System (ADS)
Hanzer, F.; Marke, T.; Steiger, R.; Strasser, U.
2012-04-01
Tourism and particularly winter tourism is a key factor for the Austrian economy. Judging from currently available climate simulations, the Austrian Alps show a particularly high vulnerability to climatic changes. To reduce the exposure of ski areas towards changes in natural snow conditions as well as to generally enhance snow conditions at skiing sites, technical snowmaking is widely utilized across Austrian ski areas. While such measures result in better snow conditions at the skiing sites and are important for the local skiing industry, its economic efficiency has also to be taken into account. The current work emerges from the project CC-Snow II, where improved future climate scenario simulations are used to determine future natural and artificial snow conditions and their effects on tourism and economy in the Austrian Alps. In a first step, a simple technical snowmaking approach is incorporated into the process based snow model AMUNDSEN, which operates at a spatial resolution of 10-50 m and a temporal resolution of 1-3 hours. Locations of skiing slopes within a ski area in Styria, Austria, were digitized and imported into the model environment. During a predefined time frame in the beginning of the ski season, the model produces a maximum possible amount of technical snow and distributes the associated snow on the slopes, whereas afterwards, until to the end of the ski season, the model tries to maintain a certain snow depth threshold value on the slopes. Due to only few required input parameters, this approach is easily transferable to other ski areas. In our poster contribution, we present first results of this snowmaking approach and give an overview of the data and methodology applied. In a further step in CC-Snow, this simple bulk approach will be extended to consider actual snow cannon locations and technical specifications, which will allow a more detailed description of technical snow production as well as cannon-based recordings of water and energy consumption.
Teaching Climate Change Using System Models: An Understanding Global Change Project Pilot Study
NASA Astrophysics Data System (ADS)
Bean, J. R.; Stuhlsatz, M.; Bracey, Z. B.; Marshall, C. R.
2017-12-01
Teaching and learning about historical and anthropogenic climate change in the classroom requires integrating instructional resources that address physical, chemical, and biological processes. The Understanding Global Change (UGC) framework and system models developed at the University of California Museum of Paleontology (UCMP) provide visualizations of the relationships and feedbacks between Earth system processes, and the consequences of anthropogenic activities on global climate. This schema provides a mechanism for developing pedagogic narratives that are known to support comprehension and retention of information and relationships. We designed a nine-day instructional unit for middle and high school students that includes a sequence of hands-on, inquiry-based, data rich activities combined with conceptual modeling exercises intended to foster students' development of systems thinking and their understanding of human influences on Earth system processes. The pilot unit, Sea Level Rise in the San Francisco Bay Area, addresses the human causes and consequences of sea level rise and related Earth system processes (i.e., the water cycle and greenhouse effect). Most of the content is not Bay Area specific, and could be used to explore sea level rise in any coastal region. Students completed pre and post assessments, which included questions about the connectedness of components of the Earth system and probed their attitudes towards participating in environmental stewardship activities. Students sequentially drew models representing the content explored in the activities and wrote short descriptions of their system diagrams that were collected by teachers for analysis. We also randomly assigned classes to engage in a very short additional intervention that asked students to think about the role that humans play in the Earth system and to draw themselves into the models. The study will determine if these students have higher stewardship scores and more frequently discuss their personal impact on the Earth system in their writing tasks. The results from this pilot will inform the design of future resources using UGC system models.
The biogeophysical climatic impacts of anthropogenic land use change during the Holocene
NASA Astrophysics Data System (ADS)
Smith, M. C.; Singarayer, J. S.; Valdes, P. J.; Kaplan, J. O.; Branch, N. P.
2015-10-01
The first agricultural societies were established around 10 ka BP and had spread across much of Europe and southern Asia by 5.5 ka BP with resultant anthropogenic deforestation for crop and pasture land. Various studies have attempted to assess the biogeochemical implications for Holocene climate in terms of increased carbon dioxide and methane emissions. However, less work has been done to examine the biogeophysical impacts of this early land use change. In this study, global climate model simulations with HadCM3 were used to examine the biogeophysical effects of Holocene land cover change on climate, both globally and regionally, from the early Holocene (8 ka BP) to the early industrial era (1850 CE). Two experiments were performed with alternative descriptions of past vegetation: (i) potential natural vegetation simulated by TRIFFID but no land-use changes, and (ii) where the anthropogenic land use model, KK10 (Kaplan et al., 2009, 2011) has been used to set the HadCM3 crop regions. Snapshot simulations have been run at 1000 year intervals to examine when the first signature of anthropogenic climate change can be detected both regionally, in the areas of land use change, and globally. Results indicate that in regions of early land disturbance such as Europe and S.E. Asia detectable temperature changes, outside the normal range of variability, are encountered in the model as early as 7 ka BP in the June/July/August (JJA) season and throughout the entire annual cycle by 2-3 ka BP. Areas outside the regions of land disturbance are also affected, with virtually the whole globe experiencing significant temperature changes (predominantly cooling) by the early industrial period. Large-scale precipitation features such as the Indian monsoon, the intertropical convergence zone (ITCZ), and the North Atlantic storm track are also impacted by local land use and remote teleconnections. We investigated how advection by surface winds, mean sea level pressure (MSLP) anomalies, and tropospheric stationary wave train disturbances in the mid- to high-latitudes led to remote teleconnections.
Probabilistic description of probable maximum precipitation
NASA Astrophysics Data System (ADS)
Ben Alaya, Mohamed Ali; Zwiers, Francis W.; Zhang, Xuebin
2017-04-01
Probable Maximum Precipitation (PMP) is the key parameter used to estimate probable Maximum Flood (PMF). PMP and PMF are important for dam safety and civil engineering purposes. Even if the current knowledge of storm mechanisms remains insufficient to properly evaluate limiting values of extreme precipitation, PMP estimation methods are still based on deterministic consideration, and give only single values. This study aims to provide a probabilistic description of the PMP based on the commonly used method, the so-called moisture maximization. To this end, a probabilistic bivariate extreme values model is proposed to address the limitations of traditional PMP estimates via moisture maximization namely: (i) the inability to evaluate uncertainty and to provide a range PMP values, (ii) the interpretation that a maximum of a data series as a physical upper limit (iii) and the assumption that a PMP event has maximum moisture availability. Results from simulation outputs of the Canadian Regional Climate Model CanRCM4 over North America reveal the high uncertainties inherent in PMP estimates and the non-validity of the assumption that PMP events have maximum moisture availability. This later assumption leads to overestimation of the PMP by an average of about 15% over North America, which may have serious implications for engineering design.
Climate is changing, everything is flowing, stationarity is immortal
NASA Astrophysics Data System (ADS)
Koutsoyiannis, Demetris; Montanari, Alberto
2015-04-01
There is no doubt that climate is changing -- and ever has been. The environment is also changing and in the last decades, as a result of demographic change and technological advancement, environmental change has been accelerating. These affect also the hydrological processes, whose changes in connection with rapidly changing human systems have been the focus of the new scientific decade 2013-2022 of the International Association of Hydrological Sciences, entitled "Panta Rhei - Everything Flows". In view of the changing systems, it has recently suggested that, when dealing with water management and hydrological extremes, stationarity is no longer a proper assumption. Hence, it was proposed that hydrological processes should be treated as nonstationary. Two main reasons contributed to this perception. First, the climate models project a future hydroclimate that will be different from the current one. Second, as streamflow record become longer, they indicate the presence of upward or downward trends. However, till now hydroclimatic projections made in the recent past have not been verified. At the same time, evidence from quite longer records, instrumental or proxy, suggest that local trends are omnipresent but not monotonic; rather at some time upward trends turn to downward ones and vice versa. These observations suggest that improvident dismiss of stationarity and adoption of nonstationary descriptions based either on climate model outputs or observed trends may entail risks. The risks stem from the facts that the future can be different from what was deterministically projected, that deterministic projections are associated with an illusion of decreased uncertainty, as well as that nonstationary models fitted on observed data may have lower predictive capacity than simpler stationary ones. In most of the cases, what is actually needed is to revisit the concept of stationarity and try to apply it carefully, making it consistent with the presence of local trends, possibly incorporating information from deterministic predictions, whenever these prove to be reliable, and estimating the total predictive uncertainty.
NASA Astrophysics Data System (ADS)
Inbar, Assaf; Nyman, Petter; Lane, Patrick; Sheridan, Gary
2016-04-01
Water and radiation are unevenly distributed across the landscape due to variations in topography, which in turn causes water availability differences on the terrain according to elevation and aspect orientation. These differences in water availability can cause differential distribution of vegetation types and indirectly influence the development of soil and even landform, as expressed in hillslope asymmetry. While most of the research on the effects of climate on the vegetation and soil development and landscape evolution has been concentrated in drier semi-arid areas, temperate forested areas has been poorly studied, particularly in South Eastern Australia. This study uses soil profile descriptions and data on soil depth and landform across climatic gradients to explore the degrees to which coevolution of vegetation, soils and landform are controlled by radiative forcing and rainfall. Soil depth measurements were made on polar and equatorial facing hillslopes located at 3 sites along a climatic gradient (mean annual rainfall between 700 - 1800 mm yr-1) in the Victorian Highlands, where forest types range from dry open woodland to closed temperate rainforest. Profile descriptions were taken from soil pits dag on planar hillslopes (50 m from ridge), and samples were taken from each horizon for physical and chemical properties analysis. Hillslope asymmetry in different precipitation regimes of the study region was quantified from Digital Elevation Models (DEMs). Significant vegetation differences between aspects were noted in lower and intermediate rainfall sites, where polar facing aspects expressed higher overall biomass than the drier equatorial slope. Within the study domain, soil depth was strongly correlated with forest type and above ground biomass. Soil depths and chemical properties varied between topographic aspects and along the precipitation gradient, where wetter conditions facilitate deeper and more weathered soils. Furthermore, soil depths showed different patterns as a function of contributing area. While soils on the polar facing slope became deeper, soils on the equatorial facing slope kept a uniform depth with increasing contributing area, pointing to different governing geomorphic processes at work. Using slope-area relationships analysis, polar facing slopes were found to be generally steeper and with longer distance to channel initiation point (if existent) than that of the equatorial facing slopes, strengthening the evidence of climate-affected differential geomorphic processes shaping the hillslope form. The results point out to the effect of climate on the development and coevolution of soil, vegetation and landform in the temperate part of Australia.
This dataset represents climate observations throughout the years 2008-09 within individual local NHDPlusV2 catchments and upstream, contributing watersheds based on the Composite Topographic Index (See Supplementary Info for Glossary of Terms). PRISM is a set of monthly, yearly, and single-event gridded data products of mean temperature and precipitation, max/min temperatures, and dewpoints, primarily for the United States. In-situ point measurements are ingested into the PRISM (Parameter elevation Regression on Independent Slopes Model) statistical mapping system. The PRISM products use a weighted regression scheme to account for complex climate regimes associated with orography, rain shadows, temperature inversions, slope aspect, coastal proximity, and other factors. (see Data Sources for links to NHDPlusV2 data and USGS Data) These data were summarized to produce local catchment-level and watershed-level metrics as a continuous data type (see Data Structure and Attribute Information for a description).
Mohamadzadeh Nojehdehi, Maryam; Ashgholi Farahani, Mansoureh; Rafii, Forough; Bahrani, Nasser
2015-05-01
Human resource is the most important factor of performance, success and better revelation of excellence goals of each organization. By performing excellence plan, healthcare organizations improve their organizational climate and play a valuable role in retaining nurses and improving the quality of their services to patients. The aim of this study was to compare hospital organizational climate and intention to leave among working nurses in hospitals performing the excellence plan and other hospitals of Tehran University of Medical Sciences. This was a cross-sectional descriptive comparison study. Its population included 248 nurses of the hospitals performing the excellence plan and other hospitals of Tehran University of Medical Sciences in Iran selected by random sampling. The used instrument had three parts: the first part was related to personal characteristics, the second part was the Munn's organizational climate questionnaire and the third part was Hinshaw's questionnaire of "anticipated turnover scale". Data was analyzed using SPSS software, version 17 and indices of descriptive statistics and inferential statistics. The results of the mean and standard deviation for organizational climate and intention to leave in both performing and non-performing hospitals of the organizational excellence plan were respectively (65.28 ± 19.31 and 56.42 ± 21.36) and (33.64 ± 5.58 and 35.59 ± 4.94). Independent T test revealed a significant difference between the mean scores for organizational climate in both performing and non-performing hospitals, and also a significant difference between the mean scores for intention to leave in both performing and non-performing hospitals (P = 0.004). Moreover, Pearson Correlation test showed a reverse significant correlation between organizational climate and intention to leave in performing hospitals of the organizational excellence plan (r = -0.337) and non-performing hospitals (r = -0.282) (P = 0.001). Performing quality improvement pattern such as organization's excellence plan improves organizational climate of healthcare sectors, it can reduce nurses' intentions to leave and retain human resources.
Orsini, C; Binnie, V; Wilson, S; Villegas, M J
2018-05-01
The aim of this study was to test the mediating role of the satisfaction of dental students' basic psychological needs of autonomy, competence and relatedness on the association between learning climate, feedback and student motivation. The latter was based on the self-determination theory's concepts of differentiation of autonomous motivation, controlled motivation and amotivation. A cross-sectional correlational study was conducted where 924 students completed self-reported questionnaires measuring motivation, perception of the learning climate, feedback and basic psychological needs satisfaction. Descriptive statistics, Cronbach's alpha scores and bivariate correlations were computed. Mediation of basic needs on each predictor-outcome association was tested based on a series of regression analyses. Finally, all variables were integrated into one structural equation model, controlling for the effects of age, gender and year of study. Cronbach's alpha scores were acceptable (.655 to .905). Correlation analyses showed positive and significant associations between both an autonomy-supportive learning climate and the quantity and quality of feedback received, and students' autonomous motivation, which decreased and became negative when correlated with controlled motivation and amotivation, respectively. Regression analyses revealed that these associations were indirect and mediated by how these predictors satisfied students' basic psychological needs. These results were corroborated by the structural equation analysis, in which data fit the model well and regression paths were in the expected direction. An autonomy-supportive learning climate and the quantity and quality of feedback were positive predictors of students' autonomous motivation and negative predictors of amotivation. However, this was an indirect association mediated by the satisfaction of students' basic psychological needs. Consequently, supporting students' needs of autonomy, competence and relatedness might lead to optimal types of motivation, which has an important influence on dental education. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
The natural and radiatively perturbed troposphere. CIAP monograph 4. Final report
DOE Office of Scientific and Technical Information (OSTI.GOV)
Not Available
1975-09-01
The Climatic Impact Assessment Program (CIAP) of the U.S. Department of Transportation is charged with the 'assessment' of the impact of future aircraft fleets and other vehicles operating in, or transiting through, the stratosphere. Monograph 4 considers the perturbations of the UV radiation and the climate at the earth's surface, which could be caused by the emissions of engine effluents from a potential, large-scale operation of aircraft in the lower stratosphere. Perturbation of the UV radiation depends primarily on the magnitude of the NOx emission index (i.e., g of NO/sub 2//kg of fuel), since the NOx effluents would produce anmore » ozone column decrease and, therefore, a UV radiation increase at the earth's surface. Monograph 4 treats the problem of the UV radiation increase from solutions of the radiative transfer equation for clear sky conditions. These solutions yield the maximum increase in the direct and diffuse components of UV radiation as a function of wavelength, solar zenith angle, and ozone decrease. Perturbations of the earth's climate would depend on the magnitude of the NOx, SO2, and H2O engine effluents. In contrast to predicting UV radiation changes, it is impossible to conclusively predict the climate perturbations at the present time: the current understanding of the processes controlling the variability of the earth's climate, i.e., the general circulations of air in the atmosphere and sea water in the oceans, is limited. Considerations of climate perturbations are restricted to partial descriptions of geophysical phenomena, involving the use of mechanistic models to describe the temperature radiation couplings in time scales of decades, which seems to be appropriate for CIAP. (GRA)« less
Paradoxical Behavior of Granger Causality
NASA Astrophysics Data System (ADS)
Witt, Annette; Battaglia, Demian; Gail, Alexander
2013-03-01
Granger causality is a standard tool for the description of directed interaction of network components and is popular in many scientific fields including econometrics, neuroscience and climate science. For time series that can be modeled as bivariate auto-regressive processes we analytically derive an expression for spectrally decomposed Granger Causality (SDGC) and show that this quantity depends only on two out of four groups of model parameters. Then we present examples of such processes whose SDGC expose paradoxical behavior in the sense that causality is high for frequency ranges with low spectral power. For avoiding misinterpretations of Granger causality analysis we propose to complement it by partial spectral analysis. Our findings are illustrated by an example from brain electrophysiology. Finally, we draw implications for the conventional definition of Granger causality. Bernstein Center for Computational Neuroscience Goettingen
GEWEX Cloud Systems Study (GCSS)
NASA Technical Reports Server (NTRS)
Moncrieff, Mitch
1993-01-01
The Global Energy and Water Cycle Experiment (GEWEX) Cloud Systems Study (GCSS) program seeks to improve the physical understanding of sub-grid scale cloud processes and their representation in parameterization schemes. By improving the description and understanding of key cloud system processes, GCSS aims to develop the necessary parameterizations in climate and numerical weather prediction (NWP) models. GCSS will address these issues mainly through the development and use of cloud-resolving or cumulus ensemble models to generate realizations of a set of archetypal cloud systems. The focus of GCSS is on mesoscale cloud systems, including precipitating convectively-driven cloud systems like MCS's and boundary layer clouds, rather than individual clouds, and on their large-scale effects. Some of the key scientific issues confronting GCSS that particularly relate to research activities in the central U.S. are presented.
The Copernicus Climate Change Service (C3S): A European Answer to Climate Change
NASA Astrophysics Data System (ADS)
Thepaut, Jean-Noel
2016-04-01
Copernicus is the European Commission's flagship Earth observation programme that delivers freely accessible operational data and information services. ECMWF has been entrusted to operate two key parts of the Copernicus programme, which will bring a consistent standard to the measurement, forecasting and prediction of atmospheric conditions and climate change: • The Copernicus Atmosphere Monitoring Service, CAMS, provides daily forecasts detailing the makeup composition of the atmosphere from the ground up to the stratosphere. • The Copernicus Climate Change Service (C3S) (in development) will routinely monitor and analyse more than 20 essential climate variables to build a global picture of our climate, from the past to the future, as well as developing customisable climate indicators for relevant economic sectors, such as energy, water management, agriculture, insurance, health…. C3S has now taken off and a number of proof-of-concept sectoral climate services have been initiated. This paper will focus on the description and expected outcome of these proof-of-concept activities as well as the definition of a roadmap towards a fully operational European Climate Change Service.
NASA Astrophysics Data System (ADS)
Chen, Yiying; Ryder, James; Bastrikov, Vladislav; McGrath, Matthew J.; Naudts, Kim; Otto, Juliane; Ottlé, Catherine; Peylin, Philippe; Polcher, Jan; Valade, Aude; Black, Andrew; Elbers, Jan A.; Moors, Eddy; Foken, Thomas; van Gorsel, Eva; Haverd, Vanessa; Heinesch, Bernard; Tiedemann, Frank; Knohl, Alexander; Launiainen, Samuli; Loustau, Denis; Ogée, Jérôme; Vessala, Timo; Luyssaert, Sebastiaan
2016-09-01
Canopy structure is one of the most important vegetation characteristics for land-atmosphere interactions, as it determines the energy and scalar exchanges between the land surface and the overlying air mass. In this study we evaluated the performance of a newly developed multi-layer energy budget in the ORCHIDEE-CAN v1.0 land surface model (Organising Carbon and Hydrology In Dynamic Ecosystems - CANopy), which simulates canopy structure and can be coupled to an atmospheric model using an implicit coupling procedure. We aim to provide a set of acceptable parameter values for a range of forest types. Top-canopy and sub-canopy flux observations from eight sites were collected in order to conduct this evaluation. The sites crossed climate zones from temperate to boreal and the vegetation types included deciduous, evergreen broad-leaved and evergreen needle-leaved forest with a maximum leaf area index (LAI; all-sided) ranging from 3.5 to 7.0. The parametrization approach proposed in this study was based on three selected physical processes - namely the diffusion, advection, and turbulent mixing within the canopy. Short-term sub-canopy observations and long-term surface fluxes were used to calibrate the parameters in the sub-canopy radiation, turbulence, and resistance modules with an automatic tuning process. The multi-layer model was found to capture the dynamics of sub-canopy turbulence, temperature, and energy fluxes. The performance of the new multi-layer model was further compared against the existing single-layer model. Although the multi-layer model simulation results showed few or no improvements to both the nighttime energy balance and energy partitioning during winter compared with a single-layer model simulation, the increased model complexity does provide a more detailed description of the canopy micrometeorology of various forest types. The multi-layer model links to potential future environmental and ecological studies such as the assessment of in-canopy species vulnerability to climate change, the climate effects of disturbance intensities and frequencies, and the consequences of biogenic volatile organic compound (BVOC) emissions from the terrestrial ecosystem.
NASA Astrophysics Data System (ADS)
Gampe, David; Ludwig, Ralf
2013-04-01
According to current climate projections, Mediterranean countries are at high risk for an even pronounced susceptibility to changes in the hydrological budget and extremes. While there is scientific consensus that climate induced changes on the hydrology of Mediterranean regions are presently occurring and are projected to amplify in the future, very little knowledge is available about the quantification of these changes, which is hampered by a lack of suitable and cost effective hydrological monitoring and modeling systems. The European FP7-project CLIMB is aiming to analyze climate induced changes on the hydrology of the Mediterranean Basins by investigating seven test sites located in the countries Italy, France, Turkey, Tunisia, Gaza and Egypt. CLIMB employs a combination of novel geophysical field monitoring concepts, remote sensing techniques and integrated hydrologic modeling to improve process descriptions and understanding and to quantify existing uncertainties in climate change impact analysis. One of those seven sites is the Gaza Strip, located in the Eastern Mediterranean and part of the Palestinian Autonomous Area, covers an area of 365km² with a length of 35km and 6 to 12km in width. Elevation ranges from sea level up to 104m in the East of the test site. Mean annual precipitation varies from 235mm in the South to 420mm in the North of the area. The inter annual variability of rainfall and the rapid population growth in an highly agricultural used area represent the major challenges in this area. The physically based Water Simulation Model WaSiM Vers. 2 (Schulla & Jasper (1999)) is setup to model current and projected future hydrological conditions. The availability of measured meteorological and hydrological data is poor as common to many Mediterranean catchments. The lack of available measured input data hampers the calibration of the model setup and the validation of model outputs. WaSiM was driven with meteorological forcing taken from 4 different ENSEMBLES climate projections for a reference (1971-2000) and a future (2041-2070) times series. State of the art remote sensing techniques and field measuring techniques were applied to improve the quality of hydrological input parameters. For the parameterization of the vegetation the Leaf Area Index (LAI) is a crucial component. However, the LAI is difficult to access at field scale, hence a simple remote sensing approach, using the Normalized Difference Vegetation Index (NDVI) and MODIS LAI information, was applied for the parameterization in WaSiM. As no permanent streams, hence no discharge measurements, exist in the Gaza Strip, the actual evapotranspiration (ETact) outputs of the model were used for model validation. Landsat TM images were applied to calculate the actual monthly mean ETact rates using the triangle method (Jiang and Islam, 1999). Simulated spatial ETact patterns and those derived from remote sensing show a good fit especially for the growing season.
Evaluation of TOPLATS on three Mediterranean catchments
NASA Astrophysics Data System (ADS)
Loizu, Javier; Álvarez-Mozos, Jesús; Casalí, Javier; Goñi, Mikel
2016-08-01
Physically based hydrological models are complex tools that provide a complete description of the different processes occurring on a catchment. The TOPMODEL-based Land-Atmosphere Transfer Scheme (TOPLATS) simulates water and energy balances at different time steps, in both lumped and distributed modes. In order to gain insight on the behavior of TOPLATS and its applicability in different conditions a detailed evaluation needs to be carried out. This study aimed to develop a complete evaluation of TOPLATS including: (1) a detailed review of previous research works using this model; (2) a sensitivity analysis (SA) of the model with two contrasted methods (Morris and Sobol) of different complexity; (3) a 4-step calibration strategy based on a multi-start Powell optimization algorithm; and (4) an analysis of the influence of simulation time step (hourly vs. daily). The model was applied on three catchments of varying size (La Tejeria, Cidacos and Arga), located in Navarre (Northern Spain), and characterized by different levels of Mediterranean climate influence. Both Morris and Sobol methods showed very similar results that identified Brooks-Corey Pore Size distribution Index (B), Bubbling pressure (ψc) and Hydraulic conductivity decay (f) as the three overall most influential parameters in TOPLATS. After calibration and validation, adequate streamflow simulations were obtained in the two wettest catchments, but the driest (Cidacos) gave poor results in validation, due to the large climatic variability between calibration and validation periods. To overcome this issue, an alternative random and discontinuous method of cal/val period selection was implemented, improving model results.
Wilkinson, Sarah; Ogée, Jérôme; Domec, Jean-Christophe; Rayment, Mark; Wingate, Lisa
2015-03-01
Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus pinaster (L.) Aït.) stand exposed to seasonal droughts. Intra-annual variations in tracheid anatomy and wood density were identified through image analysis and X-ray densitometry on stem cores covering the growth period 1999-2010. A cambial growth model was integrated with modelled plant water status and sugar availability from the soil-plant-atmosphere transfer model MuSICA to generate estimates of cell number, cell volume, cell mass and wood density on a weekly time step. The model successfully predicted inter-annual variations in cell number, ring width and maximum wood density. The model was also able to predict the occurrence of special anatomical features such as intra-annual density fluctuations (IADFs) in growth rings. Since cell wall thickness remained surprisingly constant within and between growth rings, variations in wood density were primarily the result of variations in lumen diameter, both in the model and anatomical data. In the model, changes in plant water status were identified as the main driver of the IADFs through a direct effect on cell volume. The anatomy data also revealed that a trade-off existed between hydraulic safety and hydraulic efficiency. Although a simplified description of cambial physiology is presented, this integrated modelling approach shows potential value for identifying universal patterns of tree-ring growth and anatomical features over a broad climatic gradient. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
McIver, Lachlan; Kim, Rokho; Woodward, Alistair; Hales, Simon; Spickett, Jeffery; Katscherian, Dianne; Hashizume, Masahiro; Honda, Yasushi; Kim, Ho; Iddings, Steven; Naicker, Jyotishma; Bambrick, Hilary; McMichael, Anthony J; Ebi, Kristie L
2016-11-01
Between 2010 and 2012, the World Health Organization Division of Pacific Technical Support led a regional climate change and health vulnerability assessment and adaptation planning project, in collaboration with health sector partners, in 13 Pacific island countries-Cook Islands, Federated States of Micronesia, Fiji, Kiribati, Marshall Islands, Nauru, Niue, Palau, Samoa, Solomon Islands, Tonga, Tuvalu, and Vanuatu. We assessed the vulnerabilities of Pacific island countries to the health impacts of climate change and planned adaptation strategies to minimize such threats to health. This assessment involved a combination of quantitative and qualitative techniques. The former included descriptive epidemiology, time series analyses, Poisson regression, and spatial modeling of climate and climate-sensitive disease data, in the few instances where this was possible; the latter included wide stakeholder consultations, iterative consensus building, and expert opinion. Vulnerabilities were ranked using a "likelihood versus impact" matrix, and adaptation strategies were prioritized and planned accordingly. The highest-priority climate-sensitive health risks in Pacific island countries included trauma from extreme weather events, heat-related illnesses, compromised safety and security of water and food, vector-borne diseases, zoonoses, respiratory illnesses, psychosocial ill-health, non-communicable diseases, population pressures, and health system deficiencies. Adaptation strategies relating to these climate change and health risks could be clustered according to categories common to many countries in the Pacific region. Pacific island countries are among the most vulnerable in the world to the health impacts of climate change. This vulnerability is a function of their unique geographic, demographic, and socioeconomic characteristics combined with their exposure to changing weather patterns associated with climate change, the health risks entailed, and the limited capacity of the countries to manage and adapt in the face of such risks. Citation: McIver L, Kim R, Woodward A, Hales S, Spickett J, Katscherian D, Hashizume M, Honda Y, Kim H, Iddings S, Naicker J, Bambrick H, McMichael AJ, Ebi KL. 2016. Health impacts of climate change in Pacific island countries: a regional assessment of vulnerabilities and adaptation priorities. Environ Health Perspect 124:1707-1714; http://dx.doi.org/10.1289/ehp.1509756.
McIver, Lachlan; Kim, Rokho; Woodward, Alistair; Hales, Simon; Spickett, Jeffery; Katscherian, Dianne; Hashizume, Masahiro; Honda, Yasushi; Kim, Ho; Iddings, Steven; Naicker, Jyotishma; Bambrick, Hilary; McMichael, Anthony J.; Ebi, Kristie L.
2015-01-01
Background: Between 2010 and 2012, the World Health Organization Division of Pacific Technical Support led a regional climate change and health vulnerability assessment and adaptation planning project, in collaboration with health sector partners, in 13 Pacific island countries—Cook Islands, Federated States of Micronesia, Fiji, Kiribati, Marshall Islands, Nauru, Niue, Palau, Samoa, Solomon Islands, Tonga, Tuvalu, and Vanuatu. Objective: We assessed the vulnerabilities of Pacific island countries to the health impacts of climate change and planned adaptation strategies to minimize such threats to health. Methods: This assessment involved a combination of quantitative and qualitative techniques. The former included descriptive epidemiology, time series analyses, Poisson regression, and spatial modeling of climate and climate-sensitive disease data, in the few instances where this was possible; the latter included wide stakeholder consultations, iterative consensus building, and expert opinion. Vulnerabilities were ranked using a “likelihood versus impact” matrix, and adaptation strategies were prioritized and planned accordingly. Results: The highest-priority climate-sensitive health risks in Pacific island countries included trauma from extreme weather events, heat-related illnesses, compromised safety and security of water and food, vector-borne diseases, zoonoses, respiratory illnesses, psychosocial ill-health, non-communicable diseases, population pressures, and health system deficiencies. Adaptation strategies relating to these climate change and health risks could be clustered according to categories common to many countries in the Pacific region. Conclusion: Pacific island countries are among the most vulnerable in the world to the health impacts of climate change. This vulnerability is a function of their unique geographic, demographic, and socioeconomic characteristics combined with their exposure to changing weather patterns associated with climate change, the health risks entailed, and the limited capacity of the countries to manage and adapt in the face of such risks. Citation: McIver L, Kim R, Woodward A, Hales S, Spickett J, Katscherian D, Hashizume M, Honda Y, Kim H, Iddings S, Naicker J, Bambrick H, McMichael AJ, Ebi KL. 2016. Health impacts of climate change in Pacific island countries: a regional assessment of vulnerabilities and adaptation priorities. Environ Health Perspect 124:1707–1714; http://dx.doi.org/10.1289/ehp.1509756 PMID:26645102
Zhao, M.; Golaz, J.-C.; Held, I. M.; Guo, H.; Balaji, V.; Benson, R.; Chen, J.-H.; Chen, X.; Donner, L. J.; Dunne, J. P.; Dunne, Krista A.; Durachta, J.; Fan, S.-M.; Freidenreich, S. M.; Garner, S. T.; Ginoux, P.; Harris, L. M.; Horowitz, L. W.; Krasting, J. P.; Langenhorst, A. R.; Liang, Z.; Lin, P.; Lin, S.-J.; Malyshev, S. L.; Mason, E.; Milly, Paul C.D.; Ming, Y.; Naik, V.; Paulot, F.; Paynter, D.; Phillipps, P.; Radhakrishnan, A.; Ramaswamy, V.; Robinson, T.; Schwarzkopf, D.; Seman, C. J.; Shevliakova, E.; Shen, Z.; Shin, H.; Silvers, L.; Wilson, J. R.; Winton, M.; Wittenberg, A. T.; Wyman, B.; Xiang, B.
2018-01-01
In Part 2 of this two‐part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.
Zhao, Ming; Golaz, J. -C.; Held, I. M.; ...
2018-02-19
Here, in Part 2 of this two–part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken tomore » tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.« less
NASA Astrophysics Data System (ADS)
Zhao, M.; Golaz, J.-C.; Held, I. M.; Guo, H.; Balaji, V.; Benson, R.; Chen, J.-H.; Chen, X.; Donner, L. J.; Dunne, J. P.; Dunne, K.; Durachta, J.; Fan, S.-M.; Freidenreich, S. M.; Garner, S. T.; Ginoux, P.; Harris, L. M.; Horowitz, L. W.; Krasting, J. P.; Langenhorst, A. R.; Liang, Z.; Lin, P.; Lin, S.-J.; Malyshev, S. L.; Mason, E.; Milly, P. C. D.; Ming, Y.; Naik, V.; Paulot, F.; Paynter, D.; Phillipps, P.; Radhakrishnan, A.; Ramaswamy, V.; Robinson, T.; Schwarzkopf, D.; Seman, C. J.; Shevliakova, E.; Shen, Z.; Shin, H.; Silvers, L. G.; Wilson, J. R.; Winton, M.; Wittenberg, A. T.; Wyman, B.; Xiang, B.
2018-03-01
In Part 2 of this two-part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken to tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhao, Ming; Golaz, J. -C.; Held, I. M.
Here, in Part 2 of this two–part paper, documentation is provided of key aspects of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). The quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode has been provided in Part 1. Part 2 provides documentation of key components and some sensitivities to choices of model formulation and values of parameters, highlighting the convection parameterization and orographic gravity wave drag. The approach taken tomore » tune the model's clouds to observations is a particular focal point. Care is taken to describe the extent to which aerosol effective forcing and Cess sensitivity have been tuned through the model development process, both of which are relevant to the ability of the model to simulate the evolution of temperatures over the last century when coupled to an ocean model.« less
Terraforming planet Dune: Climate-vegetation interactions on a sandy planet
NASA Astrophysics Data System (ADS)
Cresto Aleina, F.; Baudena, M.; D'Andrea, F.; Provenzale, A.
2012-04-01
The climate and the biosphere of planet Earth interact in multiple, complicated ways and on many spatial and temporal scales. Some of these processes can be studied with the help of simple mathematical models, as done for the effects of vegetation on albedo in desert areas and for the mechanisms by which terrestrial vegetation affects water fluxes in arid environments. Conceptual models of this kind do not attempt at providing quantitative descriptions of the climate-biosphere interaction, but rather to explore avenues and mechanisms which can play a role in the real system, providing inspiration for further research. In this work, we develop a simple conceptual box model in the spirit illustrated above, to explore whether and how vegetation affects the planetary hydrologic cycle. We imagine a planet with no oceans and whose surface is entirely covered with sand, quite similar to planet Dune of the science-fiction series by Frank Herbert (1965). We suppose that water is entirely in the sand, below the surface. Without vegetation, only evaporation takes place, affecting the upper sand layer for a maximum depth of a few cm. The amount of water that is evaporated in the atmosphere is relatively small, and not sufficient to trigger a full hydrologic cycle. The question is what happens to this planet when vegetation is introduced: the root depth can reach a meter or more, and plant transpiration can then transfer a much larger amount of water to the atmosphere. One may wonder whether the presence of vegetation is sufficient to trigger a hydrologic cycle with enough precipitation to sustain the vegetation itself and, if the answer is positive, what is the minimum vegetation cover that is required to maintain the cycle active. In more precise terms, we want to know whether the introduction of vegetation and of the evapotranspiration feedback allows for the existence of multiple equilibria (or solutions) in the soil-vegetation-atmosphere system. Although the box model introduced here is best formulated in terms of a hypothetical sandy planet, the results can be used to study the hydrologic cycle on wide continental regions of the Earth. On the other hand, our findings show how the definition of a habitable climate may also depend on surface characteristics, and in particular on biosphere and climate interactions.
NASA Astrophysics Data System (ADS)
Arnold, J.; Wider-Lewis, F.; Miller-Jenkins, A.
2017-12-01
This poster is a description of the challenges and success of implementing climate studies lessons for pre-service teachers to engage student teaching pedagogy and content skill based learning. Edward Waters College is a historical black college with an elementary education teacher program focused on urban elementary school teaching and learning. Pre-Service Elementary Educator Students often have difficulty with science and mathematics content and pedagogy. This poster will highlight the barriers and successes of using climate studies lessons to develop and enhance pre-service teachers' knowledge of elementary science principles particularly related to climate studies, physical and earth space science.
Sukhovol'skiĭ, V G; Ovchinnikova, T M; Baboĭ, S D
2014-01-01
As a description of altitude-belt zonality of wood vegetation, a model of ecological second-order transitions is proposed. Objects of the study have been chosen to be forest cenoses of the northern slope of Kulumyss Ridge (the Sayan Mauntains), while the results are comprised by the altitude profiles of wood vegetation. An ecological phase transition can be considered as the transition of cenoses at different altitudes from the state of presence of certain tree species within the studied territory to the state of their absence. By analogy with the physical model of second-order, phase transitions the order parameter is introduced (i.e., the area portion occupied by a single tree species at the certain altitude) as well as the control variable (i.e., the altitude of the wood vegetation belt). As the formal relation between them, an analog of the Landau's equation for phase transitions in physical systems is obtained. It is shown that the model is in a good accordance with the empirical data. Thus, the model can be used for estimation of upper and lower boundaries of altitude belts for individual tree species (like birch, aspen, Siberian fir, Siberian pine) as well as the breadth of their ecological niches with regard to altitude. The model includes also the parameters that describe numerically the interactions between different species of wood vegetation. The approach versatility allows to simplify description and modeling of wood vegetation altitude zonality, and enables assessment of vegetation cenoses response to climatic changes.
Romañach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.
2014-01-01
Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.
Modeling Modern Methane Emissions from Natural Wetlands. 1; Model Description and Results
NASA Technical Reports Server (NTRS)
Walter, Bernadette P.; Heimann, Martin; Matthews, Elaine
2001-01-01
Methane is an important greenhouse gas which contributes about 22 percent to the present greenhouse effect. Natural wetlands currently constitute the biggest methane source and were the major source in preindustrial times. Wetland emissions depend highly on the climate, i.e., on soil temperature and water table. To investigate the response of methane emissions from natural wetlands to climate variations, a process-based model that derives methane emissions from natural wetlands as a function of soil temperature, water table, and net primary productivity is used. For its application on the global scale, global data sets for all model parameters are generated. In addition, a simple hydrologic model is developed in order to simulate the position of the water table in wetlands. The hydrologic model is tested against data from different wetland sites, and the sensitivity of the hydrologic model to changes in precipitation is examined. The global methane hydrology model constitutes a tool to study temporal and spatial variations in methane emissions from natural wetlands. The model is applied using high-frequency atmospheric forcing fields from European Center for Medium-range Weather Forecasts (ECMWF) re-analyses of the period from 1982 to 1993. We calculate global annual methane emissions from wetlands to be 260 teragrams per year. Twenty-five percent of these methane emissions originate from wetlands north of 30 degrees North Latitude. Only 60 percent of the produced methane is emitted, while the rest is re-oxidized. A comparison of zonal integrals of simulated global wetland emissions and results obtained by an inverse modeling approach shows good agreement. In a test with data from two wetlands the seasonality of simulated and observed methane emissions agrees well.
NASA Astrophysics Data System (ADS)
Herbst, M.; Hellebrand, H. J.; Bauer, J.; Vanderborght, J.; Vereecken, H.
2006-12-01
The modelling of soil respiration plays an important role in the prediction of climate change. Soil respiration is usually divided in autotrophic and heterotrophic fractions orginating from root respiration and microbial decomposition of soil organic carbon, respectively. We report on the coupling of a one dimensional water, heat and CO2 flux model (SOILCO2) with a model of carbon turnover (RothC) for the prediction of soil heterotrophic respiration. The coupled model was tested using soil temperature, soil moisture, and CO2 flux measurements in a bare soil experimental plot located in Bornim, Germany. A seven year record of soil and CO2 measurements covering a broad range of atmospheric and soil conditions was availabe to evaluate the model performance. After calibrating the decomposition rate constant of the humic fraction pool, the overall model performance on CO2 efflux prediction was acceptable. The root mean square error for the CO2 efflux prediction was 0.12 cm ³/cm ²/d. During the severe summer draught of 2003 very high CO2 efluxes were measured, which could not be explained by the model. Those high fluxes were attributed to a pressure pumping effect. The soil temperature dependency of CO2 production was well described by th e model, whereas the biggest opportunity for improvement is seen in a better description of the soil moisture dependency of CO2 production. The calibration of the humus decomposition rate constant revealed a value of 0.09 1/d, which is higher than the original value suggested by the RothC model developers but within the range of literature values.
NASA Astrophysics Data System (ADS)
Jex, C.; Phipps, S. J.; Baker, A.; Bradley, C.; Scholz, D.
2012-12-01
Speleothem δ18O (δ18Ospel) is arguably one of the best proxies for understanding seasonal groundwater recharge dynamics on all timescales, and therefore for inferring past changes in regional hydroclimate. Statistical relationships between δ18Ospel and the amount of seasonally effective precipitation or its isotopic composition may be demonstrated at cave sites where there is a reliable seasonally distinct composition of δ18O of precipitation (δ18Opptn). This is often the case where recharge is driven by spring snow-melt, seasonal soil moisture excess, or in monsoonal regimes with distinct changes in moisture source. We suggest that there are also three main areas of uncertainty that need to be addressed with any individual record of δ18Ospel. Here we present the results of a multi-model-proxy comparison using a published record of δ18Ospel from Turkey that has grown over the last 500 years in order to quantify these three main areas of uncertainty. First, we assess the stability of previously observed relationships between local climate parameters and regional circulation dynamics over the last 1ka using the CSIRO Mk3L climate system model [Phipps et al., 2011] in order to estimate the variability of δ18Opptn that could be explained by internal climate variability alone. Second, we estimate the variability in δ18Odw that could be explained by storage and routing of water in the karst aquifer over the last 1 ka using the temperature and precipitation output of a three-member ensemble of transient simulations and synthetic δ18Opptn for this location, to drive the KarstFor karst systems model [Baker et al., 2012]. Finally, we estimate the variability in δ18Ospel that may be attributed to kinetic fractionation processes associated with non-equilibrium CaCO3 formation for this cave system [Scholz et al., 2009]. Baker, A., C. Bradley, S. J. Phipps, M. Fischer, I. J. Fairchild, L. Fuller, C. Spötl, and C. Azcurra (2012), Millennial-length forward models and pseudoproxies of stalagmite δ18O: an example from NW Scotland, Clim. Past Discuss, 8, 869-907. Phipps, S. J., L. D. Rotstayn, H. B. Gordon, J. L. Roberts, A. C. Hirst, and W. F. Budd (2011), The CSIRO Mk3L climate system model version 1.0 - Part 1: Description and evaluation, Geoscientific Model Development, 4, 483-509. Scholz, D., C. Mühlinghaus, and A. Mangini (2009), Modelling δ18C and δ18O in the solution layer on stalagmite surfaces, Geochimica et Cosmochimica Acta, 73(9), 2592-2602.
HYDROSCAPE: A SCAlable and ParallelizablE Rainfall Runoff Model for Hydrological Applications
NASA Astrophysics Data System (ADS)
Piccolroaz, S.; Di Lazzaro, M.; Zarlenga, A.; Majone, B.; Bellin, A.; Fiori, A.
2015-12-01
In this work we present HYDROSCAPE, an innovative streamflow routing method based on the travel time approach, and modeled through a fine-scale geomorphological description of hydrological flow paths. The model is designed aimed at being easily coupled with weather forecast or climate models providing the hydrological forcing, and at the same time preserving the geomorphological dispersion of the river network, which is kept unchanged independently on the grid size of rainfall input. This makes HYDROSCAPE particularly suitable for multi-scale applications, ranging from medium size catchments up to the continental scale, and to investigate the effects of extreme rainfall events that require an accurate description of basin response timing. Key feature of the model is its computational efficiency, which allows performing a large number of simulations for sensitivity/uncertainty analyses in a Monte Carlo framework. Further, the model is highly parsimonious, involving the calibration of only three parameters: one defining the residence time of hillslope response, one for channel velocity, and a multiplicative factor accounting for uncertainties in the identification of the potential maximum soil moisture retention in the SCS-CN method. HYDROSCAPE is designed with a simple and flexible modular structure, which makes it particularly prone to massive parallelization, customization according to the specific user needs and preferences (e.g., rainfall-runoff model), and continuous development and improvement. Finally, the possibility to specify the desired computational time step and evaluate streamflow at any location in the domain, makes HYDROSCAPE an attractive tool for many hydrological applications, and a valuable alternative to more complex and highly parametrized large scale hydrological models. Together with model development and features, we present an application to the Upper Tiber River basin (Italy), providing a practical example of model performance and characteristics.
TopoSCALE v.1.0: downscaling gridded climate data in complex terrain
NASA Astrophysics Data System (ADS)
Fiddes, J.; Gruber, S.
2014-02-01
Simulation of land surface processes is problematic in heterogeneous terrain due to the the high resolution required of model grids to capture strong lateral variability caused by, for example, topography, and the lack of accurate meteorological forcing data at the site or scale it is required. Gridded data products produced by atmospheric models can fill this gap, however, often not at an appropriate spatial resolution to drive land-surface simulations. In this study we describe a method that uses the well-resolved description of the atmospheric column provided by climate models, together with high-resolution digital elevation models (DEMs), to downscale coarse-grid climate variables to a fine-scale subgrid. The main aim of this approach is to provide high-resolution driving data for a land-surface model (LSM). The method makes use of an interpolation of pressure-level data according to topographic height of the subgrid. An elevation and topography correction is used to downscale short-wave radiation. Long-wave radiation is downscaled by deriving a cloud-component of all-sky emissivity at grid level and using downscaled temperature and relative humidity fields to describe variability with elevation. Precipitation is downscaled with a simple non-linear lapse and optionally disaggregated using a climatology approach. We test the method in comparison with unscaled grid-level data and a set of reference methods, against a large evaluation dataset (up to 210 stations per variable) in the Swiss Alps. We demonstrate that the method can be used to derive meteorological inputs in complex terrain, with most significant improvements (with respect to reference methods) seen in variables derived from pressure levels: air temperature, relative humidity, wind speed and incoming long-wave radiation. This method may be of use in improving inputs to numerical simulations in heterogeneous and/or remote terrain, especially when statistical methods are not possible, due to lack of observations (i.e. remote areas or future periods).
NASA Astrophysics Data System (ADS)
Naudts, K.; Ryder, J.; McGrath, M. J.; Otto, J.; Chen, Y.; Valade, A.; Bellasen, V.; Berhongaray, G.; Bönisch, G.; Campioli, M.; Ghattas, J.; De Groote, T.; Haverd, V.; Kattge, J.; MacBean, N.; Maignan, F.; Merilä, P.; Penuelas, J.; Peylin, P.; Pinty, B.; Pretzsch, H.; Schulze, E. D.; Solyga, D.; Vuichard, N.; Yan, Y.; Luyssaert, S.
2015-07-01
Since 70 % of global forests are managed and forests impact the global carbon cycle and the energy exchange with the overlying atmosphere, forest management has the potential to mitigate climate change. Yet, none of the land-surface models used in Earth system models, and therefore none of today's predictions of future climate, accounts for the interactions between climate and forest management. We addressed this gap in modelling capability by developing and parametrising a version of the ORCHIDEE land-surface model to simulate the biogeochemical and biophysical effects of forest management. The most significant changes between the new branch called ORCHIDEE-CAN (SVN r2290) and the trunk version of ORCHIDEE (SVN r2243) are the allometric-based allocation of carbon to leaf, root, wood, fruit and reserve pools; the transmittance, absorbance and reflectance of radiation within the canopy; and the vertical discretisation of the energy budget calculations. In addition, conceptual changes were introduced towards a better process representation for the interaction of radiation with snow, the hydraulic architecture of plants, the representation of forest management and a numerical solution for the photosynthesis formalism of Farquhar, von Caemmerer and Berry. For consistency reasons, these changes were extensively linked throughout the code. Parametrisation was revisited after introducing 12 new parameter sets that represent specific tree species or genera rather than a group of often distantly related or even unrelated species, as is the case in widely used plant functional types. Performance of the new model was compared against the trunk and validated against independent spatially explicit data for basal area, tree height, canopy structure, gross primary production (GPP), albedo and evapotranspiration over Europe. For all tested variables, ORCHIDEE-CAN outperformed the trunk regarding its ability to reproduce large-scale spatial patterns as well as their inter-annual variability over Europe. Depending on the data stream, ORCHIDEE-CAN had a 67 to 92 % chance to reproduce the spatial and temporal variability of the validation data.
NASA Astrophysics Data System (ADS)
Squire, O. J.; Archibald, A. T.; Griffiths, P. T.; Jenkin, M. E.; Smith, D.; Pyle, J. A.
2015-05-01
Isoprene is a~precursor to tropospheric ozone, a key pollutant and greenhouse gas. Anthropogenic activity over the coming century is likely to cause large changes in atmospheric CO2 levels, climate and land use, all of which will alter the global vegetation distribution leading to changes in isoprene emissions. Previous studies have used global chemistry-climate models to assess how possible changes in climate and land use could affect isoprene emissions and hence tropospheric ozone. The chemistry of isoprene oxidation, which can alter the concentration of ozone, is highly complex, therefore it must be parameterised in these models. In this work, we compare the effect of four different reduced isoprene chemical mechanisms, all currently used in Earth system models, on tropospheric ozone. Using a box model we compare ozone in these reduced schemes to that in a more explicit scheme (the Master Chemical Mechanism) over a range of NOx and isoprene emissions, through the use of O3 isopleths. We find that there is some variability, especially at high isoprene emissions, caused by differences in isoprene-derived NOx reservoir species. A global model is then used to examine how the different reduced schemes respond to potential future changes in climate, isoprene emissions, anthropogenic emissions and land use change. We find that, particularly in isoprene-rich regions, the response of the schemes varies considerably. The wide-ranging response is due to differences in the model descriptions of the peroxy radical chemistry, particularly their relative rates of reaction towards NO, leading to ozone formation, or HO2, leading to termination. Also important is the yield of isoprene nitrates and peroxyacyl nitrate precursors from isoprene oxidation. Those schemes that produce less of these NOx reservoir species, tend to produce more ozone locally and less away from the source region. We also note changes in other key oxidants such as NO3 and OH (due to the inclusion of additional isoprene-derived HOx recycling pathways). These have implications for secondary organic aerosol formation, as does the inclusion of an epoxide formation pathway in one of the mechanisms. By combining the emissions and O3 data from all of the global model integrations, we are able to construct isopleth plots comparable to those from the box model analysis. We find that the global and box model isopleths show good qualitative agreement, suggesting that comparing chemical mechanisms with a box model in this framework is a useful tool for assessing mechanistic performance in complex global models. We conclude that as the choice of reduced isoprene mechanism may alter both the magnitude and sign of the ozone response, how isoprene chemistry is parameterised in perturbation experiments such as these is a crucially important consideration. More measurements and laboratory studies are needed to validate these reduced mechanisms especially under high-volatile-organic-compound, low-NOx conditions.
Pragmatic service development and customisation with the CEDA OGC Web Services framework
NASA Astrophysics Data System (ADS)
Pascoe, Stephen; Stephens, Ag; Lowe, Dominic
2010-05-01
The CEDA OGC Web Services framework (COWS) emphasises rapid service development by providing a lightweight layer of OGC web service logic on top of Pylons, a mature web application framework for the Python language. This approach gives developers a flexible web service development environment without compromising access to the full range of web application tools and patterns: Model-View-Controller paradigm, XML templating, Object-Relational-Mapper integration and authentication/authorization. We have found this approach useful for exploring evolving standards and implementing protocol extensions to meet the requirements of operational deployments. This paper outlines how COWS is being used to implement customised WMS, WCS, WFS and WPS services in a variety of web applications from experimental prototypes to load-balanced cluster deployments serving 10-100 simultaneous users. In particular we will cover 1) The use of Climate Science Modeling Language (CSML) in complex-feature aware WMS, WCS and WFS services, 2) Extending WMS to support applications with features specific to earth system science and 3) A cluster-enabled Web Processing Service (WPS) supporting asynchronous data processing. The COWS WPS underpins all backend services in the UK Climate Projections User Interface where users can extract, plot and further process outputs from a multi-dimensional probabilistic climate model dataset. The COWS WPS supports cluster job execution, result caching, execution time estimation and user management. The COWS WMS and WCS components drive the project-specific NCEO and QESDI portals developed by the British Atmospheric Data Centre. These portals use CSML as a backend description format and implement features such as multiple WMS layer dimensions and climatology axes that are beyond the scope of general purpose GIS tools and yet vital for atmospheric science applications.
Impacts of weighting climate models for hydro-meteorological climate change studies
NASA Astrophysics Data System (ADS)
Chen, Jie; Brissette, François P.; Lucas-Picher, Philippe; Caya, Daniel
2017-06-01
Weighting climate models is controversial in climate change impact studies using an ensemble of climate simulations from different climate models. In climate science, there is a general consensus that all climate models should be considered as having equal performance or in other words that all projections are equiprobable. On the other hand, in the impacts and adaptation community, many believe that climate models should be weighted based on their ability to better represent various metrics over a reference period. The debate appears to be partly philosophical in nature as few studies have investigated the impact of using weights in projecting future climate changes. The present study focuses on the impact of assigning weights to climate models for hydrological climate change studies. Five methods are used to determine weights on an ensemble of 28 global climate models (GCMs) adapted from the Coupled Model Intercomparison Project Phase 5 (CMIP5) database. Using a hydrological model, streamflows are computed over a reference (1961-1990) and future (2061-2090) periods, with and without post-processing climate model outputs. The impacts of using different weighting schemes for GCM simulations are then analyzed in terms of ensemble mean and uncertainty. The results show that weighting GCMs has a limited impact on both projected future climate in term of precipitation and temperature changes and hydrology in terms of nine different streamflow criteria. These results apply to both raw and post-processed GCM model outputs, thus supporting the view that climate models should be considered equiprobable.
PIMMS tools for capturing metadata about simulations
NASA Astrophysics Data System (ADS)
Pascoe, Charlotte; Devine, Gerard; Tourte, Gregory; Pascoe, Stephen; Lawrence, Bryan; Barjat, Hannah
2013-04-01
PIMMS (Portable Infrastructure for the Metafor Metadata System) provides a method for consistent and comprehensive documentation of modelling activities that enables the sharing of simulation data and model configuration information. The aim of PIMMS is to package the metadata infrastructure developed by Metafor for CMIP5 so that it can be used by climate modelling groups in UK Universities. PIMMS tools capture information about simulations from the design of experiments to the implementation of experiments via simulations that run models. PIMMS uses the Metafor methodology which consists of a Common Information Model (CIM), Controlled Vocabularies (CV) and software tools. PIMMS software tools provide for the creation and consumption of CIM content via a web services infrastructure and portal developed by the ES-DOC community. PIMMS metadata integrates with the ESGF data infrastructure via the mapping of vocabularies onto ESGF facets. There are three paradigms of PIMMS metadata collection: Model Intercomparision Projects (MIPs) where a standard set of questions is asked of all models which perform standard sets of experiments. Disciplinary level metadata collection where a standard set of questions is asked of all models but experiments are specified by users. Bespoke metadata creation where the users define questions about both models and experiments. Examples will be shown of how PIMMS has been configured to suit each of these three paradigms. In each case PIMMS allows users to provide additional metadata beyond that which is asked for in an initial deployment. The primary target for PIMMS is the UK climate modelling community where it is common practice to reuse model configurations from other researchers. This culture of collaboration exists in part because climate models are very complex with many variables that can be modified. Therefore it has become common practice to begin a series of experiments by using another climate model configuration as a starting point. Usually this other configuration is provided by a researcher in the same research group or by a previous collaborator with whom there is an existing scientific relationship. Some efforts have been made at the university department level to create documentation but there is a wide diversity in the scope and purpose of this information. The consistent and comprehensive documentation enabled by PIMMS will enable the wider sharing of climate model data and configuration information. The PIMMS methodology assumes an initial effort to document standard model configurations. Once these descriptions have been created users need only describe the specific way in which their model configuration is different from the standard. Thus the documentation burden on the user is specific to the experiment they are performing and fits easily into the workflow of doing their science. PIMMS metadata is independent of data and as such is ideally suited for documenting model development. PIMMS provides a framework for sharing information about failed model configurations for which data are not kept, the negative results that don't appear in scientific literature. PIMMS is a UK project funded by JISC, The University of Reading, The University of Bristol and STFC.
The Monash University Interactive Simple Climate Model
NASA Astrophysics Data System (ADS)
Dommenget, D.
2013-12-01
The Monash university interactive simple climate model is a web-based interface that allows students and the general public to explore the physical simulation of the climate system with a real global climate model. It is based on the Globally Resolved Energy Balance (GREB) model, which is a climate model published by Dommenget and Floeter [2011] in the international peer review science journal Climate Dynamics. The model simulates most of the main physical processes in the climate system in a very simplistic way and therefore allows very fast and simple climate model simulations on a normal PC computer. Despite its simplicity the model simulates the climate response to external forcings, such as doubling of the CO2 concentrations very realistically (similar to state of the art climate models). The Monash simple climate model web-interface allows you to study the results of more than a 2000 different model experiments in an interactive way and it allows you to study a number of tutorials on the interactions of physical processes in the climate system and solve some puzzles. By switching OFF/ON physical processes you can deconstruct the climate and learn how all the different processes interact to generate the observed climate and how the processes interact to generate the IPCC predicted climate change for anthropogenic CO2 increase. The presentation will illustrate how this web-base tool works and what are the possibilities in teaching students with this tool are.
AmeriFlux US-SCf Southern California Climate Gradient - Oak/Pine Forest
DOE Office of Scientific and Technical Information (OSTI.GOV)
Goulden, Mike
This is the AmeriFlux version of the carbon flux data for the site US-SCf Southern California Climate Gradient - Oak/Pine Forest. Site Description - Half hourly data are available at https://www.ess.uci.edu/~california/. This site is one of six Southern California Climate Gradient flux towers operated along an elevation gradient (sites are US-SCg, US-SCs, US-SCf, US-SCw, US-SCc, US-SCd). This site is a mixed oak/pine forest. The site experiences episodic severe drought and mortality, and has also experienced occasional logging and wildfire. Drought and mortality was especially severe in the early 2000s.
Toward a loss of functional diversity in stream fish assemblages under climate change.
Buisson, Laëtitia; Grenouillet, Gaël; Villéger, Sébastien; Canal, Julie; Laffaille, Pascal
2013-02-01
The assessment of climate change impacts on biodiversity has so far been biased toward the taxonomic identification of the species likely either to benefit from climate modifications or to experience overall declines. There have still been few studies intended to correlate the characteristics of species to their sensitivity to climate change, even though it is now recognized that functional trait-based approaches are promising tools for addressing challenges related to global changes. In this study, two functional indices (originality and uniqueness) were first measured for 35 fish species occurring in French streams. They were then combined to projections of range shifts in response to climate change derived from species distribution models. We set out to investigate: (1) the relationship between the degrees of originality and uniqueness of fish species, and their projected response to future climate change; and (2) the consequences of individual responses of species for the functional diversity of fish assemblages. After accounting for phylogenetic relatedness among species, we have demonstrated that the two indices used measure two complementary facets of the position of fish species in a functional space. We have also rejected the hypothesis that the most original and/or less redundant species would necessarily experience the greatest declines in habitat suitability as a result of climate change. However, individual species range shifts could lead simultaneously both to a severe decline in the functional diversity of fish assemblages, and to an increase in the functional similarity among assemblages, supporting the hypothesis that disturbance favors communities with combination of common traits and biotic homogenization as well. Our findings therefore emphasize the importance of going beyond the simple taxonomic description of diversity to provide a better assessment of the likely future effects of environmental changes on biodiversity, thus helping to design more effective conservation and management measures. © 2012 Blackwell Publishing Ltd.
EnviroAtlas - Minimum Temperature 1950 - 2099 for the Conterminous United States
The EnviroAtlas Climate Scenarios were generated from NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) ensemble averages (the average of over 30 available climate models) for each of the four representative concentration pathways (RCP) for the contiguous U.S. at 30 arc-second (approx. 800 m2) spatial resolution. NEX-DCP30 mean monthly minimum temperature for the 4 RCPs (2.6, 4.5, 6.0, 8.5) were organized by season (Winter, Spring, Summer, and Fall) and annually for the years 2006 00e2?? 2099. Additionally, mean monthly minimum temperature for the ensemble average of all historic runs is organized similarly for the years 1950 00e2?? 2005. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
EnviroAtlas - Precipitation 1950 - 2099 for the Conterminous United States
The EnviroAtlas Climate Scenarios were generated from NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) ensemble averages (the average of over 30 available climate models) for each of the four representative concentration pathways (RCP) for the contiguous U.S. at 30 arc-second (approx. 800 m2) spatial resolution. NEX-DCP30 mean monthly precipitation rate for the 4 RCPs (2.6, 4.5, 6.0, 8.5) were organized by season (Winter, Spring, Summer, and Fall) and annually for the years 2006 00e2?? 2099. Additionally, mean monthly precipitation rate for the ensemble average of all historic runs is organized similarly for the years 1950 00e2?? 2005. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
EnviroAtlas - Maximum Temperature 1950 - 2099 for the Conterminous United States
The EnviroAtlas Climate Scenarios were generated from NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) ensemble averages (the average of over 30 available climate models) for each of the four representative concentration pathways (RCP) for the contiguous U.S. at 30 arc-second (approx. 800 m2) spatial resolution. NEX-DCP30 mean monthly maximum temperature for the 4 RCPs (2.6, 4.5, 6.0, 8.5) were organized by season (Winter, Spring, Summer, and Fall) and annually for the years 2006 00e2?? 2099. Additionally, mean monthly maximum temperature for the ensemble average of all historic runs is organized similarly for the years 1950 00e2?? 2005. This dataset was produced by the US EPA to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data (https://edg.epa.gov/data/Public/ORD/EnviroAtlas) or as an EnviroAtlas map service. Additional descriptive information about each attribute in this dataset can be found in its associated EnviroAtlas Fact Sheet (https://www.epa.gov/enviroatlas/enviroatlas-fact-sheets).
Stillman, Jonathon H; Tagmount, Abderrahmane
2009-10-01
Central predictions of climate warming models include increased climate variability and increased severity of heat waves. Physiological acclimatization in populations across large-scale ecological gradients in habitat temperature fluctuation is an important factor to consider in detecting responses to climate change related increases in thermal fluctuation. We measured in vivo cardiac thermal maxima and used microarrays to profile transcriptome heat and cold stress responses in cardiac tissue of intertidal zone porcelain crabs across biogeographic and seasonal gradients in habitat temperature fluctuation. We observed acclimatization dependent induction of heat shock proteins, as well as unknown genes with heat shock protein-like expression profiles. Thermal acclimatization had the largest effect on heat stress responses of extensin-like, beta tubulin, and unknown genes. For these genes, crabs acclimatized to thermally variable sites had higher constitutive expression than specimens from low variability sites, but heat stress dramatically induced expression in specimens from low variability sites and repressed expression in specimens from highly variable sites. Our application of ecological transcriptomics has yielded new biomarkers that may represent sensitive indicators of acclimatization to habitat temperature fluctuation. Our study also has identified novel genes whose further description may yield novel understanding of cellular responses to thermal acclimatization or thermal stress.
Campbell, Timothy L; Lewis, Patrick J; Thies, Monte L; Williams, Justin K
2012-11-01
GOALS OF THIS STUDY WERE TO: (1) develop distributional maps of modern rodent genera throughout the countries of South Africa, Lesotho, and Swaziland by georeferencing museum specimens; (2) assess habitat preferences for genera by cross-referencing locality position with South African vegetation; and (3) identify mean annual precipitation and temperature range where the genera are located. Conterminous South Africa including the countries of Lesotho and Swaziland Digital databases of rodent museum specimens housed in the Ditsong National Museum of Natural History, South Africa (DM), and the Division of Mammals, National Museum of Natural History, Smithsonian Institution, United States (NMNH), were acquired and then sorted into a subset of specimens with associated coordinate data. The coordinate data were then used to develop distributional maps for the rodent genera present within the study area. Percent habitat occupation and descriptive statistics for six climatic variables were then determined for each genus by cross-referencing locality positions with vegetation and climatic maps. This report presents a series of maps illustrating the distribution of 35 rodent genera based on 19,471 geo-referenced specimens obtained from two major collections. Inferred habitat use by taxon is provided for both locality and specimen percent occurrence at three hierarchical habitat levels: biome, bioregion, and vegetation unit. Descriptive statistics for six climatic variables are also provided for each genus based on locality and specimen percent incidence. As rodent faunas are commonly used in paleoenvironmental reconstructions, an accurate assessment of rodent environmental tolerance ranges is necessary before confidence can be placed in an actualistic model. While the data presented here represent only a subset of the modern geographic distributions for many of the taxa examined, a wide range of environmental regimes are observed, suggesting that more research is necessary in order to accurately reconstruct an environmental signature when these taxa are found in the fossil record.
An Overview of Climatic Elements
NASA Technical Reports Server (NTRS)
Crutcher, H. L.; Johnson, D. L.
2007-01-01
This Technical Publication (TP) addresses some climatic elements with emphasis on atmospheric composition, including gas radiative characteristics. Solar radiation is discussed with considerable information on the mathematical and statistical formulae. On a worldwide basis, temperature and precipitation for the globe are discussed along with interaction in drought. Also included is the simultaneous interaction with winds, humidity, and solar radiation. Volcanology gets minimum treatment. The oceans and seas are treated in chart form along with the interrelationship of oceanic currents and El Nino and La Nina, and ENSO phenomena. Upper air circulations are discussed. Various cloud formations up to 85-95 km altitude are described. Information on tornadoes and hurricanes is also included. One section is devoted to the climate physical-chemical elements. A short discussion is given on the importance for the quality of data and/or information in descriptions of the climate. This TP presents only an overview or survey of these and other various climatic elements.
Definition of temperature thresholds: the example of the French heat wave warning system.
Pascal, Mathilde; Wagner, Vérène; Le Tertre, Alain; Laaidi, Karine; Honoré, Cyrille; Bénichou, Françoise; Beaudeau, Pascal
2013-01-01
Heat-related deaths should be somewhat preventable. In France, some prevention measures are activated when minimum and maximum temperatures averaged over three days reach city-specific thresholds. The current thresholds were computed based on a descriptive analysis of past heat waves and on local expert judgement. We tested whether a different method would confirm these thresholds. The study was set in the six cities of Paris, Lyon, Marseille, Nantes, Strasbourg and Limoges between 1973 and 2003. For each city, we estimated the excess in mortality associated with different temperature thresholds, using a generalised additive model, controlling for long-time trends, seasons and days of the week. These models were used to compute the mortality predicted by different percentiles of temperatures. The thresholds were chosen as the percentiles associated with a significant excess mortality. In all cities, there was a good correlation between current thresholds and the thresholds derived from the models, with 0°C to 3°C differences for averaged maximum temperatures. Both set of thresholds were able to anticipate the main periods of excess mortality during the summers of 1973 to 2003. A simple method relying on descriptive analysis and expert judgement is sufficient to define protective temperature thresholds and to prevent heat wave mortality. As temperatures are increasing along with the climate change and adaptation is ongoing, more research is required to understand if and when thresholds should be modified.
NASA Astrophysics Data System (ADS)
Will, Andreas; Akhtar, Naveed; Brauch, Jennifer; Breil, Marcus; Davin, Edouard; Ho-Hagemann, Ha T. M.; Maisonnave, Eric; Thürkow, Markus; Weiher, Stefan
2017-04-01
We developed a coupled regional climate system model based on the CCLM regional climate model. Within this model system, using OASIS3-MCT as a coupler, CCLM can be coupled to two land surface models (the Community Land Model (CLM) and VEG3D), the NEMO-MED12 regional ocean model for the Mediterranean Sea, two ocean models for the North and Baltic seas (NEMO-NORDIC and TRIMNP+CICE) and the MPI-ESM Earth system model.We first present the different model components and the unified OASIS3-MCT interface which handles all couplings in a consistent way, minimising the model source code modifications and defining the physical and numerical aspects of the couplings. We also address specific coupling issues like the handling of different domains, multiple usage of the MCT library and exchange of 3-D fields.We analyse and compare the computational performance of the different couplings based on real-case simulations over Europe. The usage of the LUCIA tool implemented in OASIS3-MCT enables the quantification of the contributions of the coupled components to the overall coupling cost. These individual contributions are (1) cost of the model(s) coupled, (2) direct cost of coupling including horizontal interpolation and communication between the components, (3) load imbalance, (4) cost of different usage of processors by CCLM in coupled and stand-alone mode and (5) residual cost including i.a. CCLM additional computations.Finally a procedure for finding an optimum processor configuration for each of the couplings was developed considering the time to solution, computing cost and parallel efficiency of the simulation. The optimum configurations are presented for sequential, concurrent and mixed (sequential+concurrent) coupling layouts. The procedure applied can be regarded as independent of the specific coupling layout and coupling details.We found that the direct cost of coupling, i.e. communications and horizontal interpolation, in OASIS3-MCT remains below 7 % of the CCLM stand-alone cost for all couplings investigated. This is in particular true for the exchange of 450 2-D fields between CCLM and MPI-ESM. We identified remaining limitations in the coupling strategies and discuss possible future improvements of the computational efficiency.
NASA Astrophysics Data System (ADS)
Hartmann, Jean-Michel; Tran, Ha; Armante, Raymond; Boulet, Christian; Campargue, Alain; Forget, François; Gianfrani, Livio; Gordon, Iouli; Guerlet, Sandrine; Gustafsson, Magnus; Hodges, Joseph T.; Kassi, Samir; Lisak, Daniel; Thibault, Franck; Toon, Geoffrey C.
2018-07-01
We review progress, since publication of the book ``Collisional effects on molecular spectra: Laboratory experiments and models, consequences for applications" (Elsevier, Amsterdam, 2008), on measuring, modeling and predicting the influence of pressure (ie of intermolecular collisions) on the spectra of gas molecules. We first introduce recently developed experimental techniques of high accuracy and sensitivity. We then complement the aforementioned book by presenting the theoretical approaches, results and data proposed (mostly) in the last decade on the topics of isolated line shapes, line-broadening and -shifting, line-mixing, the far wings and associated continua, and collision-induced absorption. Examples of recently demonstrated consequences of the progress in the description of spectral shapes for some practical applications (metrology, probing of gas media, climate predictions) are then given. Remaining issues and directions for future research are finally discussed.
A CPT for Improving Turbulence and Cloud Processes in the NCEP Global Models
NASA Astrophysics Data System (ADS)
Krueger, S. K.; Moorthi, S.; Randall, D. A.; Pincus, R.; Bogenschutz, P.; Belochitski, A.; Chikira, M.; Dazlich, D. A.; Swales, D. J.; Thakur, P. K.; Yang, F.; Cheng, A.
2016-12-01
Our Climate Process Team (CPT) is based on the premise that the NCEP (National Centers for Environmental Prediction) global models can be improved by installing an integrated, self-consistent description of turbulence, clouds, deep convection, and the interactions between clouds and radiative and microphysical processes. The goal of our CPT is to unify the representation of turbulence and subgrid-scale (SGS) cloud processes and to unify the representation of SGS deep convective precipitation and grid-scale precipitation as the horizontal resolution decreases. We aim to improve the representation of small-scale phenomena by implementing a PDF-based SGS turbulence and cloudiness scheme that replaces the boundary layer turbulence scheme, the shallow convection scheme, and the cloud fraction schemes in the GFS (Global Forecast System) and CFS (Climate Forecast System) global models. We intend to improve the treatment of deep convection by introducing a unified parameterization that scales continuously between the simulation of individual clouds when and where the grid spacing is sufficiently fine and the behavior of a conventional parameterization of deep convection when and where the grid spacing is coarse. We will endeavor to improve the representation of the interactions of clouds, radiation, and microphysics in the GFS/CFS by using the additional information provided by the PDF-based SGS cloud scheme. The team is evaluating the impacts of the model upgrades with metrics used by the NCEP short-range and seasonal forecast operations.
Managing critical materials with a technology-specific stocks and flows model.
Busch, Jonathan; Steinberger, Julia K; Dawson, David A; Purnell, Phil; Roelich, Katy
2014-01-21
The transition to low carbon infrastructure systems required to meet climate change mitigation targets will involve an unprecedented roll-out of technologies reliant upon materials not previously widespread in infrastructure. Many of these materials (including lithium and rare earth metals) are at risk of supply disruption. To ensure the future sustainability and resilience of infrastructure, circular economy policies must be crafted to manage these critical materials effectively. These policies can only be effective if supported by an understanding of the material demands of infrastructure transition and what reuse and recycling options are possible given the future availability of end-of-life stocks. This Article presents a novel, enhanced stocks and flows model for the dynamic assessment of material demands resulting from infrastructure transitions. By including a hierarchical, nested description of infrastructure technologies, their components, and the materials they contain, this model can be used to quantify the effectiveness of recovery at both a technology remanufacturing and reuse level and a material recycling level. The model's potential is demonstrated on a case study on the roll-out of electric vehicles in the UK forecast by UK Department of Energy and Climate Change scenarios. The results suggest policy action should be taken to ensure Li-ion battery recycling infrastructure is in place by 2025 and NdFeB motor magnets should be designed for reuse. This could result in a reduction in primary demand for lithium of 40% and neodymium of 70%.
Designing water demand management schemes using a socio-technical modelling approach.
Baki, Sotiria; Rozos, Evangelos; Makropoulos, Christos
2018-05-01
Although it is now widely acknowledged that urban water systems (UWSs) are complex socio-technical systems and that a shift towards a socio-technical approach is critical in achieving sustainable urban water management, still, more often than not, UWSs are designed using a segmented modelling approach. As such, either the analysis focuses on the description of the purely technical sub-system, without explicitly taking into account the system's dynamic socio-economic processes, or a more interdisciplinary approach is followed, but delivered through relatively coarse models, which often fail to provide a thorough representation of the urban water cycle and hence cannot deliver accurate estimations of the hydrosystem's responses. In this work we propose an integrated modelling approach for the study of the complete socio-technical UWS that also takes into account socio-economic and climatic variability. We have developed an integrated model, which is used to investigate the diffusion of household water conservation technologies and its effects on the UWS, under different socio-economic and climatic scenarios. The integrated model is formed by coupling a System Dynamics model that simulates the water technology adoption process, and the Urban Water Optioneering Tool (UWOT) for the detailed simulation of the urban water cycle. The model and approach are tested and demonstrated in an urban redevelopment area in Athens, Greece under different socio-economic scenarios and policy interventions. It is suggested that the proposed approach can establish quantifiable links between socio-economic change and UWS responses and therefore assist decision makers in designing more effective and resilient long-term strategies for water conservation. Copyright © 2017 Elsevier B.V. All rights reserved.
Control vocabulary software designed for CMIP6
NASA Astrophysics Data System (ADS)
Nadeau, D.; Taylor, K. E.; Williams, D. N.; Ames, S.
2016-12-01
The Coupled Model Intercomparison Project Phase 6 (CMIP6) coordinates a number of intercomparison activities and includes many more experiments than its predecessor, CMIP5. In order to organize and facilitate use of the complex collection of expected CMIP6 model output, a standard set of descriptive information has been defined, which must be stored along with the data. This standard information enables automated machine interpretation of the contents of all model output files. The standard metadata is stored in compliance with the Climate and Forecast (CF) standard, which ensures that it can be interpreted and visualized by many standard software packages. Additional attributes (not standardized by CF) are required by CMIP6 to enhance identification of models and experiments, and to provide additional information critical for interpreting the model results. To ensure that CMIP6 data complies with the standards, a python program called "PrePARE" (Pre-Publication Attribute Reviewer for the ESGF) has been developed to check the model output prior to its publication and release for analysis. If, for example, a required attribute is missing or incorrect (e.g., not included in the reference CMIP6 controlled vocabularies), then PrePare will prevent publication. In some circumstances, missing attributes can be created or incorrect attributes can be replaced automatically by PrePARE, and the program will warn users about the changes that have been made. PrePARE provides a final check on model output assuring adherence to a baseline conformity across the output from all CMIP6 models which will facilitate analysis by climate scientists. PrePARE is flexible and can be easily modified for use by similar projects that have a well-defined set of metadata and controlled vocabularies.
NASA Astrophysics Data System (ADS)
Guimberteau, Matthieu; Zhu, Dan; Maignan, Fabienne; Huang, Ye; Yue, Chao; Dantec-Nédélec, Sarah; Ottlé, Catherine; Jornet-Puig, Albert; Bastos, Ana; Laurent, Pierre; Goll, Daniel; Bowring, Simon; Chang, Jinfeng; Guenet, Bertrand; Tifafi, Marwa; Peng, Shushi; Krinner, Gerhard; Ducharne, Agnès; Wang, Fuxing; Wang, Tao; Wang, Xuhui; Wang, Yilong; Yin, Zun; Lauerwald, Ronny; Joetzjer, Emilie; Qiu, Chunjing; Kim, Hyungjun; Ciais, Philippe
2018-01-01
The high-latitude regions of the Northern Hemisphere are a nexus for the interaction between land surface physical properties and their exchange of carbon and energy with the atmosphere. At these latitudes, two carbon pools of planetary significance - those of the permanently frozen soils (permafrost), and of the great expanse of boreal forest - are vulnerable to destabilization in the face of currently observed climatic warming, the speed and intensity of which are expected to increase with time. Improved projections of future Arctic and boreal ecosystem transformation require improved land surface models that integrate processes specific to these cold biomes. To this end, this study lays out relevant new parameterizations in the ORCHIDEE-MICT land surface model. These describe the interactions between soil carbon, soil temperature and hydrology, and their resulting feedbacks on water and CO2 fluxes, in addition to a recently developed fire module. Outputs from ORCHIDEE-MICT, when forced by two climate input datasets, are extensively evaluated against (i) temperature gradients between the atmosphere and deep soils, (ii) the hydrological components comprising the water balance of the largest high-latitude basins, and (iii) CO2 flux and carbon stock observations. The model performance is good with respect to empirical data, despite a simulated excessive plant water stress and a positive land surface temperature bias. In addition, acute model sensitivity to the choice of input forcing data suggests that the calibration of model parameters is strongly forcing-dependent. Overall, we suggest that this new model design is at the forefront of current efforts to reliably estimate future perturbations to the high-latitude terrestrial environment.
Assessment of Seasonal Water Balance Components over India Using Macroscale Hydrological Model
NASA Astrophysics Data System (ADS)
Joshi, S.; Raju, P. V.; Hakeem, K. A.; Rao, V. V.; Yadav, A.; Issac, A. M.; Diwakar, P. G.; Dadhwal, V. K.
2016-12-01
Hydrological models provide water balance components which are useful for water resources assessment and for capturing the seasonal changes and impact of anthropogenic interventions and climate change. The study under description is a national level modeling framework for country India using wide range of geo-spatial and hydro-meteorological data sets for estimating daily Water Balance Components (WBCs) at 0.15º grid resolution using Variable Infiltration Capacity model. The model parameters were optimized through calibration of model computed stream flow with field observed yielding Nash-Sutcliffe efficiency between 0.5 to 0.7. The state variables, evapotranspiration (ET) and soil moisture were also validated, obtaining R2 values of 0.57 and 0.69, respectively. Using long-term meteorological data sets, model computation were carried to capture hydrological extremities. During 2013, 2014 and 2015 monsoon seasons, WBCs were estimated and were published in web portal with 2-day time lag. In occurrence of disaster events, weather forecast was ingested, high surface runoff zones were identified for forewarning and disaster preparedness. Cumulative monsoon season rainfall of 2013, 2014 and 2015 were 105, 89 and 91% of long period average (LPA) respectively (Source: India Meteorological Department). Analysis of WBCs indicated that corresponding seasonal surface runoff was 116, 81 and 86% LPA and evapotranspiration was 109, 104 and 90% LPA. Using the grid-wise data, the spatial variation in WBCs among river basins/administrative regions was derived to capture the changes in surface runoff, ET between the years and in comparison with LPA. The model framework is operational and is providing periodic account of national level water balance fluxes which are useful for quantifying spatial and temporal variation in basin/sub-basin scale water resources, periodical water budgeting to form vital inputs for studies on water resources and climate change.
NASA Astrophysics Data System (ADS)
Blanc, Elisabeth; Le Pichon, Alexis; Ceranna, Lars; Pilger, Christoph; Charlton Perez, Andrew; Smets, Pieter
2016-04-01
The International Monitoring System (IMS) developed for the verification of the Comprehensive nuclear-Test-Ban Treaty (CTBT) provides a unique global description of atmospheric disturbances generating infrasound such as extreme events (e.g. meteors, volcanoes, earthquakes, and severe weather) or human activity (e.g. explosions and supersonic airplanes). The analysis of the detected signals, recorded at global scales and over near 15 years at some stations, demonstrates that large-scale atmospheric disturbances strongly affect infrasound propagation. Their time scales vary from several tens of minutes to hours and days. Their effects are in average well resolved by the current model predictions; however, accurate spatial and temporal description is lacking in both weather and climate models. This study reviews recent results using the infrasound technology to characterize these large scale disturbances, including (i) wind fluctuations induced by gravity waves generating infrasound partial reflections and modifications of the infrasound waveguide, (ii) convection from thunderstorms and mountain waves generating gravity waves, (iii) stratospheric warming events which yield wind inversions in the stratosphere, (iv)planetary waves which control the global atmospheric circulation. Improved knowledge of these disturbances and assimilation in future models is an important objective of the ARISE (Atmospheric dynamics Research InfraStructure in Europe) project. This is essential in the context of the future verification of the CTBT as enhanced atmospheric models are necessary to assess the IMS network performance in higher resolution, reduce source location errors, and improve characterization methods.
Dynamics of the middle atmosphere as observed by the ARISE project
NASA Astrophysics Data System (ADS)
Blanc, Elisabeth
2015-04-01
The atmosphere is a complex system submitted to disturbances in a wide range of scales, including high frequency sources as volcanoes, thunderstorms, tornadoes and at larger scales, gravity waves from deep convection or wind over mountains, atmospheric tides and planetary waves. These waves affect the different atmospheric layers submitted to different temperature and wind systems which strongly control the general atmospheric circulation. The full description of gravity and planetary waves constitutes a challenge for the development of future models of atmosphere and climate. The objective of this paper is to present a review of recent advances obtained in this topic, especially in the framework of the ARISE (Atmospheric dynamics Research InfraStructure in Europe) project
NASA Astrophysics Data System (ADS)
Raz-Yaseef, N.; Sonnentag, O.; Kobayashi, H.; Chen, J. M.; Verfaillie, J. G.; Ma, S.; Baldocchi, D. D.
2011-12-01
Semi-arid climates experience large seasonal and inter-annual variability in radiation and precipitation, creating natural conditions adequate to study how year-to-year changes affect atmosphere-biosphere fluxes. Especially, savanna ecosystems, that combine tree and below-canopy components, create a unique environment in which phenology dramatically changes between seasons. We used a 10-year flux database in order to define seasonal and interannual variability of climatic inputs and fluxes, and evaluate model capability to reproduce observed variability. This is based on the perception that model capability to construct the deviation, and not the average, is important in order to correctly predict ecosystem sensitivity to climate change. Our research site is a low density and low LAI (0.8) semi-arid savanna, located at Tonzi Ranch, Northern California. In this system, trees are active during the warm season (Mar - Oct), and grasses are active during the wet season (Dec - May). Measurements of carbon and water fluxes above and below the tree canopy using eddy covariance and supplementary measurements have been made since 2001. Fluxes were simulated using bio-meteorological process-oriented ecosystem models: BEPS and 3D-CAONAK. Models were partly capable of reproducing fluxes on daily scales (R2=0.66). We then compared model outputs for different ecosystem components and seasons, and found distinct seasons with high correlations while other seasons were purely represented. Comparison was much higher for ET than for GPP. The understory was better simulated than the overstory. CANOAK overestimated spring understory fluxes, probably due to the capability to directly calculated 3D radiative transfer. BEPS underestimated spring understory fluxes, following the pre-description of grass die-off. Both models underestimated peak spring overstory fluxes. During winter tree dormant, modeled fluxes were null, but occasional high fluxes of both ET and GPP were measured following precipitation events, likely produced by an adverse measurement effect. This analysis enabled to pinpoint specific areas where models break, and stress that model capability to reproduce fluxes vary among seasons and ecosystem components. The combined response was such, that comparison decreases when ecosystem fluxes were partitioned between overstory and understory fluxes. Model performance decreases with time scale; while performance was high for some seasons, models were less capable of reproducing the high variability in understory fluxes vs. the conservative overstory fluxes on annual scales. Discrepancies were not always a result of models' faults; comparison largely improved when measurements of overstory fluxes during precipitation events were excluded. Conclusions raised from this research enable to answer the critical question of the level and type of details needed in order to correctly predict ecosystem respond to environmental and climatic change.
Vaughan, Catherine; Dessai, Suraje
2014-01-01
Climate services involve the generation, provision, and contextualization of information and knowledge derived from climate research for decision making at all levels of society. These services are mainly targeted at informing adaptation to climate variability and change, widely recognized as an important challenge for sustainable development. This paper reviews the development of climate services, beginning with a historical overview, a short summary of improvements in climate information, and a description of the recent surge of interest in climate service development including, for example, the Global Framework for Climate Services, implemented by the World Meteorological Organization in October 2012. It also reviews institutional arrangements of selected emerging climate services across local, national, regional, and international scales. By synthesizing existing literature, the paper proposes four design elements of a climate services evaluation framework. These design elements include: problem identification and the decision-making context; the characteristics, tailoring, and dissemination of the climate information; the governance and structure of the service, including the process by which it is developed; and the socioeconomic value of the service. The design elements are intended to serve as a guide to organize future work regarding the evaluation of when and whether climate services are more or less successful. The paper concludes by identifying future research questions regarding the institutional arrangements that support climate services and nascent efforts to evaluate them. PMID:25798197
Vaughan, Catherine; Dessai, Suraje
2014-09-01
Climate services involve the generation, provision, and contextualization of information and knowledge derived from climate research for decision making at all levels of society. These services are mainly targeted at informing adaptation to climate variability and change, widely recognized as an important challenge for sustainable development. This paper reviews the development of climate services, beginning with a historical overview, a short summary of improvements in climate information, and a description of the recent surge of interest in climate service development including, for example, the Global Framework for Climate Services, implemented by the World Meteorological Organization in October 2012. It also reviews institutional arrangements of selected emerging climate services across local, national, regional, and international scales. By synthesizing existing literature, the paper proposes four design elements of a climate services evaluation framework. These design elements include: problem identification and the decision-making context; the characteristics, tailoring, and dissemination of the climate information; the governance and structure of the service, including the process by which it is developed; and the socioeconomic value of the service. The design elements are intended to serve as a guide to organize future work regarding the evaluation of when and whether climate services are more or less successful. The paper concludes by identifying future research questions regarding the institutional arrangements that support climate services and nascent efforts to evaluate them.
The Art and Science of Climate Model Tuning
Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew; ...
2017-03-31
The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less
The Art and Science of Climate Model Tuning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hourdin, Frederic; Mauritsen, Thorsten; Gettelman, Andrew
The process of parameter estimation targeting a chosen set of observations is an essential aspect of numerical modeling. This process is usually named tuning in the climate modeling community. In climate models, the variety and complexity of physical processes involved, and their interplay through a wide range of spatial and temporal scales, must be summarized in a series of approximate submodels. Most submodels depend on uncertain parameters. Tuning consists of adjusting the values of these parameters to bring the solution as a whole into line with aspects of the observed climate. Tuning is an essential aspect of climate modeling withmore » its own scientific issues, which is probably not advertised enough outside the community of model developers. Optimization of climate models raises important questions about whether tuning methods a priori constrain the model results in unintended ways that would affect our confidence in climate projections. Here, we present the definition and rationale behind model tuning, review specific methodological aspects, and survey the diversity of tuning approaches used in current climate models. We also discuss the challenges and opportunities in applying so-called objective methods in climate model tuning. Here, we discuss how tuning methodologies may affect fundamental results of climate models, such as climate sensitivity. The article concludes with a series of recommendations to make the process of climate model tuning more transparent.« less
Peak water from glaciers: advances and challenges in a global perspective
NASA Astrophysics Data System (ADS)
Huss, M.; Hock, R.
2014-12-01
Mountain glaciers show a high sensitivity to changes in climate forcing. In a global perspective, their anticipated retreat will pose far-reaching challenges to the management of fresh water resources and will raise sea levels significantly within only a few decades. Different model frameworks have been applied to simulate melt water contributions of glaciers outside the two ice sheets for the recent IPCC report. However, these models depend on strongly simplified, and often empirical descriptions of the driving processes hampering the reliability of the results. Thus, a transition from the physically-based mass balance-ice flow models developed for single glaciers to the application at the global scale is urgently needed. The challenges are manifold but can be tackled with the new data sets, methods and process-understanding that have emerged during the last years. Here, we present a novel glacier model for calculating the response of surface mass balance and 3D glacier geometry for each individual glacier around the globe. Our approach accounts for feedbacks due to glacier retreat and includes models for mass loss due to frontal ablation and refreezing of water in the snow/firn. This allows the calculation of the components of proglacial runoff for each individual glacier in a process-based way. The current surface geometry and thickness distribution for each of the world's roughly 200'000 glaciers is extracted from the Randolph Glacier Inventory v3.3 and terrain models. Our simulations are driven with 14 Global Circulation Models from the CMIP5 project using the RCP4.5, RCP8.5 and RCP2.6 scenarios. We focus on the timing of peak water from glacierized catchments in all climatic regions of the earth and the corresponding importance of these regime changes on hydrological stress. Peak water represents a crucial tipping point for sustained water supply even for regions with only a minor glacier coverage, and is relevant to the dynamics of sea level rise. The maximum rate of water release from glacial storage is subject to a high spatio-temporal variability depending on the glacier-specific geometry and its transient response to climatic change.
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.
Selection of climate change scenario data for impact modelling.
Sloth Madsen, M; Maule, C Fox; MacKellar, N; Olesen, J E; Christensen, J Hesselbjerg
2012-01-01
Impact models investigating climate change effects on food safety often need detailed climate data. The aim of this study was to select climate change projection data for selected crop phenology and mycotoxin impact models. Using the ENSEMBLES database of climate model output, this study illustrates how the projected climate change signal of important variables as temperature, precipitation and relative humidity depends on the choice of the climate model. Using climate change projections from at least two different climate models is recommended to account for model uncertainty. To make the climate projections suitable for impact analysis at the local scale a weather generator approach was adopted. As the weather generator did not treat all the necessary variables, an ad-hoc statistical method was developed to synthesise realistic values of missing variables. The method is presented in this paper, applied to relative humidity, but it could be adopted to other variables if needed.
Gupta, Himangana; Kohli, Ravinder Kumar; Ahluwalia, Amrik Singh
2015-10-01
India's position on climate change negotiations is likely to have far reaching implications for the success of global climate cooperation. Since the beginning of negotiations, the principle of equity and common but differentiated responsibilities (CBDR) remained the centerpiece of India's stand. The stand started to evolve at the 15th Conference of Parties to the United Nations Framework Convention on Climate Change at Copenhagen in 2009, when India accepted voluntary commitments to reduce emission intensity. Though India still swears by CBDR, status of the principle in the negotiations has become doubtful after the Durban Climate Conference in 2011 committed all parties to take emission targets. This paper traces major transition points in India's negotiating position over the years and provides a descriptive context of its climate-related concerns. It analyzes the interview responses of 15 top scientists, experts, and negotiators to build upon core areas of climate change issues in India, its future role, and position in negotiations. Interviewees, in general, were in favor of protecting the carbon space for the poor who had very low emissions.
Telling the Climate Change Story: Framing and Messaging
NASA Astrophysics Data System (ADS)
Hassol, S. J.
2011-12-01
Scientists have important roles to play in communicating climate change, yet most scientists are not well versed in important aspects of communication. Scientists can improve their communication by helping to develop and deliver effectively framed messages. Research suggests that effective messages about climate change should include science-based descriptions of the risks posed by human-induced warming as well as information about solutions for a better future. Thus, telling the climate change story effectively involves clearly stating that human-induced climate change is happening now and having impacts on society, while also showing that it is not too late to make a difference for the future. For example, framing and messaging should include the fact that lower emissions pathways lead to less severe climate change and fewer impacts than higher emissions pathways. It also involves communicating that there is much we can do to alter our emissions pathway, and that doing these things has other benefits, for example, for human health and the economy. Scientists telling the climate change story should make the threats tangible and the opportunities clear.
NASA Astrophysics Data System (ADS)
Slovic, S.
2015-12-01
I will highlight the following teaching strategies in my presentation: 1) the decision of include climate-related works at the end of syllabi for courses in subjects like "The Literature of Energy" in order to complicate and contextualize readings from earlier in the courses and to delay the climate topic until I feel students are ready to face it; 2) breaking down climate into an array of specific, graspable sub-issues (food, water, transportation, architecture) in courses on sustainability literature; and 3) appreciating the psychology of "numbers and nerves" in course design for topics such as genocide and climate change that seem to require quantitative description (for instance, psychic numbing, pseudoinefficacy, the prominence effect, the asymmetry of trust, and the trans-scalar imaginary). This presentation will briefly describe my own experiences teaching climate change literature at the University of Nevada, Reno, and the University of Idaho and will also draw from my forthcoming book, with psychologist Paul Slovic, titled Numbers and Nerves: Information, Emotion, and Meaning in a World of Data (Oregon State University Press, October 2015).
Pezeshki, Z; Tafazzoli-Shadpour, M; Mansourian, A; Eshrati, B; Omidi, E; Nejadqoli, I
2012-10-01
Cholera is spread by drinking water or eating food that is contaminated by bacteria, and is related to climate changes. Several epidemics have occurred in Iran, the most recent of which was in 2005 with 1133 cases and 12 deaths. This study investigated the incidence of cholera over a 10-year period in Chabahar district, a region with one of the highest incidence rates of cholera in Iran. Descriptive retrospective study on data of patients with Eltor and NAG cholera reported to the Iranian Centre of Disease Control between 1997 and 2006. Data on the prevalence of cholera were gathered through a surveillance system, and a spatial database was developed using geographic information systems (GIS) to describe the relation of spatial and climate variables to cholera incidences. Fuzzy clustering (fuzzy C) method and statistical analysis based on logistic regression were used to develop a model of cholera dissemination. The variables were demographic characteristics, specifications of cholera infection, climate conditions and some geographical parameters. The incidence of cholera was found to be significantly related to higher temperature and humidity, lower precipitation, shorter distance to the eastern border of Iran and local health centres, and longer distance to the district health centre. The fuzzy C means algorithm showed that clusters were geographically distributed in distinct regions. In order to plan, manage and monitor any public health programme, GIS provide ideal platforms for the convergence of disease-specific information, analysis and computation of new data for statistical analysis. Copyright © 2012 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
Improving Climate Projections Using "Intelligent" Ensembles
NASA Technical Reports Server (NTRS)
Baker, Noel C.; Taylor, Patrick C.
2015-01-01
Recent changes in the climate system have led to growing concern, especially in communities which are highly vulnerable to resource shortages and weather extremes. There is an urgent need for better climate information to develop solutions and strategies for adapting to a changing climate. Climate models provide excellent tools for studying the current state of climate and making future projections. However, these models are subject to biases created by structural uncertainties. Performance metrics-or the systematic determination of model biases-succinctly quantify aspects of climate model behavior. Efforts to standardize climate model experiments and collect simulation data-such as the Coupled Model Intercomparison Project (CMIP)-provide the means to directly compare and assess model performance. Performance metrics have been used to show that some models reproduce present-day climate better than others. Simulation data from multiple models are often used to add value to projections by creating a consensus projection from the model ensemble, in which each model is given an equal weight. It has been shown that the ensemble mean generally outperforms any single model. It is possible to use unequal weights to produce ensemble means, in which models are weighted based on performance (called "intelligent" ensembles). Can performance metrics be used to improve climate projections? Previous work introduced a framework for comparing the utility of model performance metrics, showing that the best metrics are related to the variance of top-of-atmosphere outgoing longwave radiation. These metrics improve present-day climate simulations of Earth's energy budget using the "intelligent" ensemble method. The current project identifies several approaches for testing whether performance metrics can be applied to future simulations to create "intelligent" ensemble-mean climate projections. It is shown that certain performance metrics test key climate processes in the models, and that these metrics can be used to evaluate model quality in both current and future climate states. This information will be used to produce new consensus projections and provide communities with improved climate projections for urgent decision-making.
Steele, Madeline O.; Chang, Heejun; Reusser, Deborah A.; Brown, Cheryl A.; Jung, Il-Won
2012-01-01
As part of a larger investigation into potential effects of climate change on estuarine habitats in the Pacific Northwest, we estimated changes in freshwater inputs into four estuaries: Coquille River estuary, South Slough of Coos Bay, and Yaquina Bay in Oregon, and Willapa Bay in Washington. We used the U.S. Geological Survey's Precipitation Runoff Modeling System (PRMS) to model watershed hydrological processes under current and future climatic conditions. This model allowed us to explore possible shifts in coastal hydrologic regimes at a range of spatial scales. All modeled watersheds are located in rainfall-dominated coastal areas with relatively insignificant base flow inputs, and their areas vary from 74.3 to 2,747.6 square kilometers. The watersheds also vary in mean elevation, ranging from 147 meters in the Willapa to 1,179 meters in the Coquille. The latitudes of watershed centroids range from 43.037 degrees north latitude in the Coquille River estuary to 46.629 degrees north latitude in Willapa Bay. We calibrated model parameters using historical climate grid data downscaled to one-sixteenth of a degree by the Climate Impacts Group, and historical runoff from sub-watersheds or neighboring watersheds. Nash Sutcliffe efficiency values for daily flows in calibration sub-watersheds ranged from 0.71 to 0.89. After calibration, we forced the PRMS models with four North American Regional Climate Change Assessment Program climate models: Canadian Regional Climate Model-(National Center for Atmospheric Research) Community Climate System Model version 3, Canadian Regional Climate Model-Canadian Global Climate Model version 3, Hadley Regional Model version 3-Hadley Centre Climate Model version 3, and Regional Climate Model-Canadian Global Climate Model version 3. These are global climate models (GCMs) downscaled with regional climate models that are embedded within the GCMs, and all use the A2 carbon emission scenario developed by the Intergovernmental Panel on Climate Change. With these climate-forcing outputs, we derived the mean change in flow from the period encompassing the 1980s (1971-1995) to the period encompassing the 2050s (2041-2065). Specifically, we calculated percent change in mean monthly flow rate, coefficient of variation, top 5 percent of flow, and 7-day low flow. The trends with the most agreement among climate models and among watersheds were increases in autumn mean monthly flows, especially in October and November, decreases in summer monthly mean flow, and increases in the top 5 percent of flow. We also estimated variance in PRMS outputs owing to parameter uncertainty and the selection of climate model using Latin hypercube sampling. This analysis showed that PRMS low-flow simulations are more uncertain than medium or high flow simulations, and that variation among climate models was a larger source of uncertainty than the hydrological model parameters. These results improve our understanding of how climate change may affect the saltwater-freshwater balance in Pacific Northwest estuaries, with implications for their sensitive ecosystems.
NASA Astrophysics Data System (ADS)
Dave, Eshan V.
Asphalt concrete pavements are inherently graded viscoelastic structures. Oxidative aging of asphalt binder and temperature cycling due to climatic conditions being the major cause of non-homogeneity. Current pavement analysis and simulation procedures dwell on the use of layered approach to account for these non-homogeneities. The conventional finite-element modeling (FEM) technique discretizes the problem domain into smaller elements, each with a unique constitutive property. However the assignment of unique material property description to an element in the FEM approach makes it an unattractive choice for simulation of problems with material non-homogeneities. Specialized elements such as "graded elements" allow for non-homogenous material property definitions within an element. This dissertation describes the development of graded viscoelastic finite element analysis method and its application for analysis of asphalt concrete pavements. Results show that the present research improves efficiency and accuracy of simulations for asphalt pavement systems. Some of the practical implications of this work include the new technique's capability for accurate analysis and design of asphalt pavements and overlay systems and for the determination of pavement performance with varying climatic conditions and amount of in-service age. Other application areas include simulation of functionally graded fiber-reinforced concrete, geotechnical materials, metal and metal composites at high temperatures, polymers, and several other naturally existing and engineered materials.
AASC Recommendations for the Education of an Applied Climatologist
NASA Astrophysics Data System (ADS)
Nielsen-Gammon, J. W.; Stooksbury, D.; Akyuz, A.; Dupigny-Giroux, L.; Hubbard, K. G.; Timofeyeva, M. M.
2011-12-01
The American Association of State Climatologists (AASC) has developed curricular recommendations for the education of future applied and service climatologists. The AASC was founded in 1976. Membership of the AASC includes state climatologists and others who work in state climate offices; climate researchers in academia and educators; applied climatologists in NOAA and other federal agencies; and the private sector. The AASC is the only professional organization dedicated solely to the growth and development of applied and service climatology. The purpose of the recommendations is to offer a framework for existing and developing academic climatology programs. These recommendations are intended to serve as a road map and to help distinguish the educational needs for future applied climatologists from those of operational meteorologists or other scientists and practitioners. While the home department of climatology students may differ from one program to the next, the most essential factor is that students can demonstrate a breadth and depth of understanding in the knowledge and tools needed to be an applied climatologist. Because the training of an applied climatologist requires significant depth and breadth, the Masters degree is recommended as the minimum level of education needed. This presentation will highlight the AASC recommendations. These include a strong foundation in: - climatology (instrumentation and data collection, climate dynamics, physical climatology, synoptic and regional climatology, applied climatology, climate models, etc.) - basic natural sciences and mathematics including calculus, physics, chemistry, and biology/ecology - fundamental atmospheric sciences (atmospheric dynamics, atmospheric thermodynamics, atmospheric radiation, and weather analysis/synoptic meteorology) and - data analysis and spatial analysis (descriptive statistics, statistical methods, multivariate statistics, geostatistics, GIS, etc.). The recommendations also include a secondary area of concentration (agriculture, economics, geography, hydrology, marine sciences, natural resources, policy, etc.) and a major applied climate research component.
Dasgupta, Aritra; Poco, Jorge; Wei, Yaxing; ...
2015-03-16
Evaluation methodologies in visualization have mostly focused on how well the tools and techniques cater to the analytical needs of the user. While this is important in determining the effectiveness of the tools and advancing the state-of-the-art in visualization research, a key area that has mostly been overlooked is how well established visualization theories and principles are instantiated in practice. This is especially relevant when domain experts, and not visualization researchers, design visualizations for analysis of their data or for broader dissemination of scientific knowledge. There is very little research on exploring the synergistic capabilities of cross-domain collaboration between domainmore » experts and visualization researchers. To fill this gap, in this paper we describe the results of an exploratory study of climate data visualizations conducted in tight collaboration with a pool of climate scientists. The study analyzes a large set of static climate data visualizations for identifying their shortcomings in terms of visualization design. The outcome of the study is a classification scheme that categorizes the design problems in the form of a descriptive taxonomy. The taxonomy is a first attempt for systematically categorizing the types, causes, and consequences of design problems in visualizations created by domain experts. We demonstrate the use of the taxonomy for a number of purposes, such as, improving the existing climate data visualizations, reflecting on the impact of the problems for enabling domain experts in designing better visualizations, and also learning about the gaps and opportunities for future visualization research. We demonstrate the applicability of our taxonomy through a number of examples and discuss the lessons learnt and implications of our findings.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dasgupta, Aritra; Poco, Jorge; Wei, Yaxing
Evaluation methodologies in visualization have mostly focused on how well the tools and techniques cater to the analytical needs of the user. While this is important in determining the effectiveness of the tools and advancing the state-of-the-art in visualization research, a key area that has mostly been overlooked is how well established visualization theories and principles are instantiated in practice. This is especially relevant when domain experts, and not visualization researchers, design visualizations for analysis of their data or for broader dissemination of scientific knowledge. There is very little research on exploring the synergistic capabilities of cross-domain collaboration between domainmore » experts and visualization researchers. To fill this gap, in this paper we describe the results of an exploratory study of climate data visualizations conducted in tight collaboration with a pool of climate scientists. The study analyzes a large set of static climate data visualizations for identifying their shortcomings in terms of visualization design. The outcome of the study is a classification scheme that categorizes the design problems in the form of a descriptive taxonomy. The taxonomy is a first attempt for systematically categorizing the types, causes, and consequences of design problems in visualizations created by domain experts. We demonstrate the use of the taxonomy for a number of purposes, such as, improving the existing climate data visualizations, reflecting on the impact of the problems for enabling domain experts in designing better visualizations, and also learning about the gaps and opportunities for future visualization research. We demonstrate the applicability of our taxonomy through a number of examples and discuss the lessons learnt and implications of our findings.« less
Designing ecological climate change impact assessments to reflect key climatic drivers
Sofaer, Helen R.; Barsugli, Joseph J.; Jarnevich, Catherine S.; Abatzoglou, John T.; Talbert, Marian; Miller, Brian W.; Morisette, Jeffrey T.
2017-01-01
Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive – such as means or extremes – can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the ‘model space’ approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling.
Designing ecological climate change impact assessments to reflect key climatic drivers.
Sofaer, Helen R; Barsugli, Joseph J; Jarnevich, Catherine S; Abatzoglou, John T; Talbert, Marian K; Miller, Brian W; Morisette, Jeffrey T
2017-07-01
Identifying the climatic drivers of an ecological system is a key step in assessing its vulnerability to climate change. The climatic dimensions to which a species or system is most sensitive - such as means or extremes - can guide methodological decisions for projections of ecological impacts and vulnerabilities. However, scientific workflows for combining climate projections with ecological models have received little explicit attention. We review Global Climate Model (GCM) performance along different dimensions of change and compare frameworks for integrating GCM output into ecological models. In systems sensitive to climatological means, it is straightforward to base ecological impact assessments on mean projected changes from several GCMs. Ecological systems sensitive to climatic extremes may benefit from what we term the 'model space' approach: a comparison of ecological projections based on simulated climate from historical and future time periods. This approach leverages the experimental framework used in climate modeling, in which historical climate simulations serve as controls for future projections. Moreover, it can capture projected changes in the intensity and frequency of climatic extremes, rather than assuming that future means will determine future extremes. Given the recent emphasis on the ecological impacts of climatic extremes, the strategies we describe will be applicable across species and systems. We also highlight practical considerations for the selection of climate models and data products, emphasizing that the spatial resolution of the climate change signal is generally coarser than the grid cell size of downscaled climate model output. Our review illustrates how an understanding of how climate model outputs are derived and downscaled can improve the selection and application of climatic data used in ecological modeling. © 2017 John Wiley & Sons Ltd.
Mohamadzadeh Nojehdehi, Maryam; Ashgholi Farahani, Mansoureh; Rafii, Forough; Bahrani, Nasser
2015-01-01
Background: Human resource is the most important factor of performance, success and better revelation of excellence goals of each organization. By performing excellence plan, healthcare organizations improve their organizational climate and play a valuable role in retaining nurses and improving the quality of their services to patients. Objectives: The aim of this study was to compare hospital organizational climate and intention to leave among working nurses in hospitals performing the excellence plan and other hospitals of Tehran University of Medical Sciences. Patients and Methods: This was a cross-sectional descriptive comparison study. Its population included 248 nurses of the hospitals performing the excellence plan and other hospitals of Tehran University of Medical Sciences in Iran selected by random sampling. The used instrument had three parts: the first part was related to personal characteristics, the second part was the Munn’s organizational climate questionnaire and the third part was Hinshaw’s questionnaire of “anticipated turnover scale”. Data was analyzed using SPSS software, version 17 and indices of descriptive statistics and inferential statistics. Results: The results of the mean and standard deviation for organizational climate and intention to leave in both performing and non-performing hospitals of the organizational excellence plan were respectively (65.28 ± 19.31 and 56.42 ± 21.36) and (33.64 ± 5.58 and 35.59 ± 4.94). Independent T test revealed a significant difference between the mean scores for organizational climate in both performing and non-performing hospitals, and also a significant difference between the mean scores for intention to leave in both performing and non-performing hospitals (P = 0.004). Moreover, Pearson Correlation test showed a reverse significant correlation between organizational climate and intention to leave in performing hospitals of the organizational excellence plan (r = -0.337) and non-performing hospitals (r = -0.282) (P = 0.001). Conclusions: Performing quality improvement pattern such as organization’s excellence plan improves organizational climate of healthcare sectors, it can reduce nurses’ intentions to leave and retain human resources. PMID:26082850
The Effects of Climate Model Similarity on Local, Risk-Based Adaptation Planning
NASA Astrophysics Data System (ADS)
Steinschneider, S.; Brown, C. M.
2014-12-01
The climate science community has recently proposed techniques to develop probabilistic projections of climate change from ensemble climate model output. These methods provide a means to incorporate the formal concept of risk, i.e., the product of impact and probability, into long-term planning assessments for local systems under climate change. However, approaches for pdf development often assume that different climate models provide independent information for the estimation of probabilities, despite model similarities that stem from a common genealogy. Here we utilize an ensemble of projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to develop probabilistic climate information, with and without an accounting of inter-model correlations, and use it to estimate climate-related risks to a local water utility in Colorado, U.S. We show that the tail risk of extreme climate changes in both mean precipitation and temperature is underestimated if model correlations are ignored. When coupled with impact models of the hydrology and infrastructure of the water utility, the underestimation of extreme climate changes substantially alters the quantification of risk for water supply shortages by mid-century. We argue that progress in climate change adaptation for local systems requires the recognition that there is less information in multi-model climate ensembles than previously thought. Importantly, adaptation decisions cannot be limited to the spread in one generation of climate models.
Integrated approaches to climate-crop modelling: needs and challenges.
Betts, Richard A
2005-11-29
This paper discusses the need for a more integrated approach to modelling changes in climate and crops, and some of the challenges posed by this. While changes in atmospheric composition are expected to exert an increasing radiative forcing of climate change leading to further warming of global mean temperatures and shifts in precipitation patterns, these are not the only climatic processes which may influence crop production. Changes in the physical characteristics of the land cover may also affect climate; these may arise directly from land use activities and may also result from the large-scale responses of crops to seasonal, interannual and decadal changes in the atmospheric state. Climate models used to drive crop models may, therefore, need to consider changes in the land surface, either as imposed boundary conditions or as feedbacks from an interactive climate-vegetation model. Crops may also respond directly to changes in atmospheric composition, such as the concentrations of carbon dioxide (CO2), ozone (03) and compounds of sulphur and nitrogen, so crop models should consider these processes as well as climate change. Changes in these, and the responses of the crops, may be intimately linked with meteorological processes so crop and climate models should consider synergies between climate and atmospheric chemistry. Some crop responses may occur at scales too small to significantly influence meteorology, so may not need to be included as feedbacks within climate models. However, the volume of data required to drive the appropriate crop models may be very large, especially if short-time-scale variability is important. Implementation of crop models within climate models would minimize the need to transfer large quantities of data between separate modelling systems. It should also be noted that crop responses to climate change may interact with other impacts of climate change, such as hydrological changes. For example, the availability of water for irrigation may be affected by changes in runoff as a direct consequence of climate change, and may also be affected by climate-related changes in demand for water for other uses. It is, therefore, necessary to consider the interactions between the responses of several impacts sectors to climate change. Overall, there is a strong case for a much closer coupling between models of climate, crops and hydrology, but this in itself poses challenges arising from issues of scale and errors in the models. A strategy is proposed whereby the pursuit of a fully coupled climate-chemistry-crop-hydrology model is paralleled by continued use of separate climate and land surface models but with a focus on consistency between the models.
What Determines Water Temperature Dynamics in the San Francisco Bay-Delta System?
NASA Astrophysics Data System (ADS)
Vroom, J.; van der Wegen, M.; Martyr-Koller, R. C.; Lucas, L. V.
2017-11-01
Water temperature is an important factor determining estuarine species habitat conditions. Water temperature is mainly governed by advection (e.g., from rivers) and atmospheric exchange processes varying strongly over time (day-night, seasonally) and the spatial domain. On a long time scale, climate change will impact water temperature in estuarine systems due to changes in river flow regimes, air temperature, and sea level rise. To determine which factors govern estuarine water temperature and its sensitivity to changes in its forcing, we developed a process-based numerical model (Delft3D Flexible Mesh) and applied it to a well-monitored estuarine system (the San Francisco Estuary) for validation. The process-based approach allows for detailed process description and a physics-based analysis of governing processes. The model was calibrated for water year 2011 and incorporated 3-D hydrodynamics, salinity intrusion, water temperature dynamics, and atmospheric coupling. Results show significant skill in reproducing temperature observations on daily, seasonal, and yearly time scales. In North San Francisco Bay, thermal stratification is present, enhanced by salinity stratification. The temperature of the upstream, fresh water Delta area is captured well in 2-D mode, although locally—on a small scale—vertical processes (e.g., stratification) may be important. The impact of upstream river temperature and discharge and atmospheric forcing on water temperatures differs throughout the Delta, possibly depending on dispersion and residence times. Our modeling effort provides a sound basis for future modeling studies including climate change impact on water temperature and associated ecological modeling, e.g., clam and fish habitat and phytoplankton dynamics.
The Met Office Global Coupled Model 3.0 and 3.1 (GC3.0 and GC3.1) Configurations
NASA Astrophysics Data System (ADS)
Williams, K. D.; Copsey, D.; Blockley, E. W.; Bodas-Salcedo, A.; Calvert, D.; Comer, R.; Davis, P.; Graham, T.; Hewitt, H. T.; Hill, R.; Hyder, P.; Ineson, S.; Johns, T. C.; Keen, A. B.; Lee, R. W.; Megann, A.; Milton, S. F.; Rae, J. G. L.; Roberts, M. J.; Scaife, A. A.; Schiemann, R.; Storkey, D.; Thorpe, L.; Watterson, I. G.; Walters, D. N.; West, A.; Wood, R. A.; Woollings, T.; Xavier, P. K.
2018-02-01
The Global Coupled 3 (GC3) configuration of the Met Office Unified Model is presented. Among other applications, GC3 is the basis of the United Kingdom's submission to the Coupled Model Intercomparison Project 6 (CMIP6). This paper documents the model components that make up the configuration (although the scientific descriptions of these components are in companion papers) and details the coupling between them. The performance of GC3 is assessed in terms of mean biases and variability in long climate simulations using present-day forcing. The suitability of the configuration for predictability on shorter time scales (weather and seasonal forecasting) is also briefly discussed. The performance of GC3 is compared against GC2, the previous Met Office coupled model configuration, and against an older configuration (HadGEM2-AO) which was the submission to CMIP5. In many respects, the performance of GC3 is comparable with GC2, however, there is a notable improvement in the Southern Ocean warm sea surface temperature bias which has been reduced by 75%, and there are improvements in cloud amount and some aspects of tropical variability. Relative to HadGEM2-AO, many aspects of the present-day climate are improved in GC3 including tropospheric and stratospheric temperature structure, most aspects of tropical and extratropical variability and top-of-atmosphere and surface fluxes. A number of outstanding errors are identified including a residual asymmetric sea surface temperature bias (cool northern hemisphere, warm Southern Ocean), an overly strong global hydrological cycle and insufficient European blocking.
Evaluation and Quality Control for the Copernicus Seasonal Forecast Systems
NASA Astrophysics Data System (ADS)
Manubens, N.; Hunter, A.; Bedia, J.; Bretonnière, P. A.; Bhend, J.; Doblas-Reyes, F. J.
2017-12-01
The EU funded Copernicus Climate Change Service (C3S) will provide authoritative information about past, current and future climate for a wide range of users, from climate scientists to stakeholders from a wide range of sectors including insurance, energy or transport. It has been recognized that providing information about the products' quality and provenance is paramount to establish trust in the service and allow users to make best use of the available information. This presentation outlines the work being conducted within the Quality Assurance for Multi-model Seasonal Forecast Products project (QA4Seas). The aim of QA4Seas is to develop a strategy for the evaluation and quality control (EQC) of the multi-model seasonal forecasts provided by C3S. First, we present the set of guidelines the data providers must comply with, ensuring the data is fully traceable and harmonized across data sets. Second, we discuss the ongoing work on defining a provenance and metadata model that is able to encode such information, and that can be extended to describe the steps followed to obtain the final verification products such as maps and time series of forecast quality measures. The metadata model is based on the Resource Description Framework W3C standard, being thus extensible and reusable. It benefits from widely adopted vocabularies to describe data provenance and workflows, as well as from expert consensus and community-support for the development of the verification and downscaling specific ontologies. Third, we describe the open source software being developed to generate fully reproducible and certifiable seasonal forecast products, which also attaches provenance and metadata information to the verification measures and enables the user to visually inspect the quality of the C3S products. QA4Seas is seeking collaboration with similar initiatives, as well as extending the discussion to interested parties outside the C3S community to share experiences and establish global common guidelines or best practices regarding data provenance.
An enhanced model of land water and energy for global hydrologic and earth-system studies
Milly, Paul C.D.; Malyshev, Sergey L.; Shevliakova, Elena; Dunne, Krista A.; Findell, Kirsten L.; Gleeson, Tom; Liang, Zhi; Phillips, Peter; Stouffer, Ronald J.; Swenson, Sean
2014-01-01
LM3 is a new model of terrestrial water, energy, and carbon, intended for use in global hydrologic analyses and as a component of earth-system and physical-climate models. It is designed to improve upon the performance and to extend the scope of the predecessor Land Dynamics (LaD) and LM3V models by better quantifying the physical controls of climate and biogeochemistry and by relating more directly to components of the global water system that touch human concerns. LM3 includes multilayer representations of temperature, liquid water content, and ice content of both snowpack and macroporous soil–bedrock; topography-based description of saturated area and groundwater discharge; and transport of runoff to the ocean via a global river and lake network. Sensible heat transport by water mass is accounted throughout for a complete energy balance. Carbon and vegetation dynamics and biophysics are represented as in LM3V. In numerical experiments, LM3 avoids some of the limitations of the LaD model and provides qualitatively (though not always quantitatively) reasonable estimates, from a global perspective, of observed spatial and/or temporal variations of vegetation density, albedo, streamflow, water-table depth, permafrost, and lake levels. Amplitude and phase of annual cycle of total water storage are simulated well. Realism of modeled lake levels varies widely. The water table tends to be consistently too shallow in humid regions. Biophysical properties have an artificial stepwise spatial structure, and equilibrium vegetation is sensitive to initial conditions. Explicit resolution of thick (>100 m) unsaturated zones and permafrost is possible, but only at the cost of long (≫300 yr) model spinup times.
David E. Rupp,
2016-05-05
The 20th century climate for the Southeastern United States and surrounding areas as simulated by global climate models used in the Coupled Model Intercomparison Project Phase 5 (CMIP5) was evaluated. A suite of statistics that characterize various aspects of the regional climate was calculated from both model simulations and observation-based datasets. CMIP5 global climate models were ranked by their ability to reproduce the observed climate. Differences in the performance of the models between regions of the United States (the Southeastern and Northwestern United States) warrant a regional-scale assessment of CMIP5 models.
Making Sense of Complexity with FRE, a Scientific Workflow System for Climate Modeling (Invited)
NASA Astrophysics Data System (ADS)
Langenhorst, A. R.; Balaji, V.; Yakovlev, A.
2010-12-01
A workflow is a description of a sequence of activities that is both precise and comprehensive. Capturing the workflow of climate experiments provides a record which can be queried or compared, and allows reproducibility of the experiments - sometimes even to the bit level of the model output. This reproducibility helps to verify the integrity of the output data, and enables easy perturbation experiments. GFDL's Flexible Modeling System Runtime Environment (FRE) is a production-level software project which defines and implements building blocks of the workflow as command line tools. The scientific, numerical and technical input needed to complete the workflow of an experiment is recorded in an experiment description file in XML format. Several key features add convenience and automation to the FRE workflow: ● Experiment inheritance makes it possible to define a new experiment with only a reference to the parent experiment and the parameters to override. ● Testing is a basic element of the FRE workflow: experiments define short test runs which are verified before the main experiment is run, and a set of standard experiments are verified with new code releases. ● FRE is flexible enough to support short runs with mere megabytes of data, to high-resolution experiments that run on thousands of processors for months, producing terabytes of output data. Experiments run in segments of model time; after each segment, the state is saved and the model can be checkpointed at that level. Segment length is defined by the user, but the number of segments per system job is calculated to fit optimally in the batch scheduler requirements. FRE provides job control across multiple segments, and tools to monitor and alter the state of long-running experiments. ● Experiments are entered into a Curator Database, which stores query-able metadata about the experiment and the experiment's output. ● FRE includes a set of standardized post-processing functions as well as the ability to incorporate user-level functions. FRE post-processing can take us all the way to the preparing of graphical output for a scientific audience, and publication of data on a public portal. ● Recent FRE development includes incorporating a distributed workflow to support remote computing.
NASA Astrophysics Data System (ADS)
Tsimpidi, A.; Karydis, V.; Pandis, S. N.; Lelieveld, J.
2016-12-01
Hygroscopicity is an important property of aerosols which describes their propensity to absorb water vapor. The hygroscopicity of organic aerosol (OA) can change during its atmospheric aging affecting the total aerosol hygroscopicity. A more hygroscopic particle will grow more rapidly under humid conditions, scatter incident sunlight more efficiently; and it will more likely form cloud droplets. Both phenomena strongly influence the radiative forcing of climate through the direct and indirect effects of aerosols. Therefore, taking into account the hygrscopicity changes of OA during its atmospheric aging is of prime importance to accurately estimate the aerosol climatic impact. Here, we use a computationally efficient module for the description of OA composition and evolution in the atmosphere (ORACLE) (Tsimpidi et al., 2014) in the frame of the global chemistry climate model EMAC to simulate the global distribution of the OA oxidation state and hygroscopicity. To track the evolution of the OA oxidation state during its atmospheric aging, ORACLE is modified to include the description of the OA oxygen content change when mass from any OA surrogate species reacts with the OH radical. Subsequently, it is assumed that the cloud condensation nuclei (CCN) activity of OA, expressed in the form of the hygroscopicity parameter κ, will increase with increasing oxygen content (expressed by the oxygen per carbon ratio, O:C) and will range from κ = 0 (for O:C ≤ 0.2) to κ = 0.35 (for O:C = 1). The exact relationship between O:C and κ is determined based on aerosol mass spectrometer (AMS) and continuous flow CCN (CCNC) measurements of SOA (Lambe et al., 2011). Following a straightforward mixing rule, the hygroscopicity and oxygen content of total OA is calculated based on the hygroscopicities of the individual OA compounds and their degree of oxidation. A global dataset of O:C measurements is used to validate the model results. ReferencesLambe, A. T., et al. : Laboratory studies of the chemical composition and cloud condensation nuclei (CCN) activity of secondary organic aerosol (SOA) and oxidized primary organic aerosol (OPOA), Atmos. Chem. Phys., 11, 8913-8928, 2011. Tsimpidi, A. P., et al. : ORACLE (v1.0): module to simulate the organic aerosol composition and evolution in the atmosphere, Geo. Mod. Devel., 7, 3153-3172, 2014.
Zhao, M.; Golaz, J.-C.; Held, I. M.; Guo, H.; Balaji, V.; Benson, R.; Chen, J.-H.; Chen, X.; Donner, L. J.; Dunne, J. P.; Dunne, Krista A.; Durachta, J.; Fan, S.-M.; Freidenreich, S. M.; Garner, S. T.; Ginoux, P.; Harris, L. M.; Horowitz, L. W.; Krasting, J. P.; Langenhorst, A. R.; Liang, Z.; Lin, P.; Lin, S.-J.; Malyshev, S. L.; Mason, E.; Milly, Paul C.D.; Ming, Y.; Naik, V.; Paulot, F.; Paynter, D.; Phillipps, P.; Radhakrishnan, A.; Ramaswamy, V.; Robinson, T.; Schwarzkopf, D.; Seman, C. J.; Shevliakova, E.; Shen, Z.; Shin, H.; Silvers, L.; Wilson, J. R.; Winton, M.; Wittenberg, A. T.; Wyman, B.; Xiang, B.
2018-01-01
In this two‐part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed sea surface temperatures (SSTs) and sea‐ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top‐of‐atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhao, Ming; Golaz, J. -C.; Held, I. M.
In this two–part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed seamore » surface temperatures (SSTs) and sea–ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. Here, the model's Cess sensitivity (response in the top–of–atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.« less
Zhao, Ming; Golaz, J. -C.; Held, I. M.; ...
2018-02-19
In this two–part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a “light” chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed seamore » surface temperatures (SSTs) and sea–ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. Here, the model's Cess sensitivity (response in the top–of–atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.« less
NASA Astrophysics Data System (ADS)
Zhao, M.; Golaz, J.-C.; Held, I. M.; Guo, H.; Balaji, V.; Benson, R.; Chen, J.-H.; Chen, X.; Donner, L. J.; Dunne, J. P.; Dunne, K.; Durachta, J.; Fan, S.-M.; Freidenreich, S. M.; Garner, S. T.; Ginoux, P.; Harris, L. M.; Horowitz, L. W.; Krasting, J. P.; Langenhorst, A. R.; Liang, Z.; Lin, P.; Lin, S.-J.; Malyshev, S. L.; Mason, E.; Milly, P. C. D.; Ming, Y.; Naik, V.; Paulot, F.; Paynter, D.; Phillipps, P.; Radhakrishnan, A.; Ramaswamy, V.; Robinson, T.; Schwarzkopf, D.; Seman, C. J.; Shevliakova, E.; Shen, Z.; Shin, H.; Silvers, L. G.; Wilson, J. R.; Winton, M.; Wittenberg, A. T.; Wyman, B.; Xiang, B.
2018-03-01
In this two-part paper, a description is provided of a version of the AM4.0/LM4.0 atmosphere/land model that will serve as a base for a new set of climate and Earth system models (CM4 and ESM4) under development at NOAA's Geophysical Fluid Dynamics Laboratory (GFDL). This version, with roughly 100 km horizontal resolution and 33 levels in the vertical, contains an aerosol model that generates aerosol fields from emissions and a "light" chemistry mechanism designed to support the aerosol model but with prescribed ozone. In Part 1, the quality of the simulation in AMIP (Atmospheric Model Intercomparison Project) mode—with prescribed sea surface temperatures (SSTs) and sea-ice distribution—is described and compared with previous GFDL models and with the CMIP5 archive of AMIP simulations. The model's Cess sensitivity (response in the top-of-atmosphere radiative flux to uniform warming of SSTs) and effective radiative forcing are also presented. In Part 2, the model formulation is described more fully and key sensitivities to aspects of the model formulation are discussed, along with the approach to model tuning.
AmeriFlux US-SCs Southern California Climate Gradient - Coastal Sage
DOE Office of Scientific and Technical Information (OSTI.GOV)
Goulden, Mike
This is the AmeriFlux version of the carbon flux data for the site US-SCs Southern California Climate Gradient - Coastal Sage. Site Description - Half hourly data are available at https://www.ess.uci.edu/~california/. This site is one of six Southern California Climate Gradient flux towers operated along an elevation gradient (sites are US-SCg, US-SCs, US-SCf, US-SCw, US-SCc, US-SCd). This site is a coastal sage shrubland. Coastal sage is a small stature, closed canopy vegetation dominated by drought deciduous shrubs. The site has historically burned every 10-20 years, with the wild fire in October 2007. The tower data sets includes this recovery process.
The biogeophysical climatic impacts of anthropogenic land use change during the Holocene
NASA Astrophysics Data System (ADS)
Smith, M. Clare; Singarayer, Joy S.; Valdes, Paul J.; Kaplan, Jed O.; Branch, Nicholas P.
2016-04-01
The first agricultural societies were established around 10 ka BP and had spread across much of Europe and southern Asia by 5.5 ka BP with resultant anthropogenic deforestation for crop and pasture land. Various studies (e.g. Joos et al., 2004; Kaplan et al., 2011; Mitchell et al., 2013) have attempted to assess the biogeochemical implications for Holocene climate in terms of increased carbon dioxide and methane emissions. However, less work has been done to examine the biogeophysical impacts of this early land use change. In this study, global climate model simulations with Hadley Centre Coupled Model version 3 (HadCM3) were used to examine the biogeophysical effects of Holocene land cover change on climate, both globally and regionally, from the early Holocene (8 ka BP) to the early industrial era (1850 CE). Two experiments were performed with alternative descriptions of past vegetation: (i) one in which potential natural vegetation was simulated by Top-down Representation of Interactive Foliage and Flora Including Dynamics (TRIFFID) but without land use changes and (ii) one where the anthropogenic land use model Kaplan and Krumhardt 2010 (KK10; Kaplan et al., 2009, 2011) was used to set the HadCM3 crop regions. Snapshot simulations were run at 1000-year intervals to examine when the first signature of anthropogenic climate change can be detected both regionally, in the areas of land use change, and globally. Results from our model simulations indicate that in regions of early land disturbance such as Europe and south-east Asia detectable temperature changes, outside the normal range of variability, are encountered in the model as early as 7 ka BP in the June-July-August (JJA) season and throughout the entire annual cycle by 2-3 ka BP. Areas outside the regions of land disturbance are also affected, with virtually the whole globe experiencing significant temperature changes (predominantly cooling) by the early industrial period. The global annual mean temperature anomalies found in our single model simulations were -0.22 at 1850 CE, -0.11 at 2 ka BP, and -0.03 °C at 7 ka BP. Regionally, the largest temperature changes were in Europe with anomalies of -0.83 at 1850 CE, -0.58 at 2 ka BP, and -0.24 °C at 7 ka BP. Large-scale precipitation features such as the Indian monsoon, the Intertropical Convergence Zone (ITCZ), and the North Atlantic storm track are also impacted by local land use and remote teleconnections. We investigated how advection by surface winds, mean sea level pressure (MSLP) anomalies, and tropospheric stationary wave train disturbances in the mid- to high latitudes led to remote teleconnections.
Wetland Ecohydrology: stochastic description of water level fluctuations across the soil surface
NASA Astrophysics Data System (ADS)
Tamea, S.; Muneepeerakul, R.; Laio, F.; Ridolfi, L.; Rodriguez-Iturbe, I.
2009-12-01
Wetlands provide a suite of social and ecological critical functions such as being habitats of disease-carrying vectors, providing buffer zones against hurricanes, controlling sediment transport, filtering nutrients and contaminants, and a repository of great biological diversity. More recently, wetlands have also been recognized as crucial for carbon storage in the context of global climate change. Despite such importance, quantitative approaches to many aspects of wetlands are far from adequate. Therefore, improving our quantitative understanding of wetlands is necessary to our ability to maintain, manage, and restore these invaluable environments. In wetlands, hydrologic factors and ecosystem processes interplay and generate unique characteristics and a delicate balance between biotic and abiotic elements. The main hydrologic driver of wetland ecosystems is the position of the water level that, being above or below ground, determines the submergence or exposure of soil. When the water level is above the soil surface, soil saturation and lack of oxygen causes hypoxia, anaerobic functioning of microorganisms and anoxic stress in plants, that might lead to the death of non-adapted organisms. When the water level lies below the soil surface, the ecosystem becomes groundwater-dependent, and pedological and physiological aspects play their role in the soil water balance. We propose here a quantitative description of wetland ecohydrology, through a stochastic process-based water balance, driven by a marked compound Poisson noise representing rainfall events. The model includes processes such as rainfall infiltration, evapotranspiration, capillary rise, and the contribution of external water bodies, which are quantified in a simple yet realistic way. The semi-analytical steady-state probability distributions of water level spanning across the soil surface are validated with data from the Everglades (Florida, USA). The model and its results allow for a quantitative analysis of the long term behavior of biotic and abiotic factors which depend on the position of the water level and enable the assessment of impacts of climate changes on the wetland ecosystem.
A 50-year precipitation analysis over Europe at 5.5km within the UERRA project
NASA Astrophysics Data System (ADS)
Bazile, Eric; Abida, Rachid; Soci, Cornel; Verrelle, Antoine; Szczypta, Camille; Le Moigne, Patrick
2017-04-01
The UERRA project is a 4-year project (2014-2017) financed by the European Union under its 7th Framework Programme SPACE. One of its main objectives is to provide a 50-year reanalysis dataset of surface essential climate variables (ECV) at 5.5km grid at European scale, together with, as much as possible, uncertainty estimates. One of the ECV is the precipitation and this variable is of essential interest in weather forecasting, climate study and to "drive" hydrological model for water management, or agrometeorology. After a brief description of the method used for the precipitation analysis (Soci et al. 2016)during this project, the preliminary results will be presented. The estimation of uncertainties will be also discussed associated with the problem of the evolution of the observation density network and its impact on the long term series. Additional information about the UERRA project can be found at http://www.uerra.eu The research leading to these results has received funding from the European Union, Seventh Framework Programme (FP7-SPACE-2013-1) under grant agreement no 607193.
This dataset represents climate observations within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. (See Supplementary Info for Glossary of Terms) PRISM is a set of monthly, yearly, and single-event gridded data products of mean temperature and precipitation, max/min temperatures, and dewpoints, primarily for the United States. In-situ point measurements are ingested into the PRISM (Parameter elevation Regression on Independent Slopes Model) statistical mapping system. The PRISM products use a weighted regression scheme to account for complex climate regimes associated with orography, rain shadows, temperature inversions, slope aspect, coastal proximity, and other factors. (see Data Sources for links to NHDPlusV2 data and USGS Data) These data are summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type (see Data Structure and Attribute Information for a description).
This dataset represents climate observations within individual, local NHDPlusV2 catchments and upstream, contributing watersheds. Attributes of the landscape layer were calculated for every local NHDPlusV2 catchment and accumulated to provide watershed-level metrics. (See Supplementary Info for Glossary of Terms) PRISM is a set of monthly, yearly, and single-event gridded data products of mean temperature and precipitation, max/min temperatures, and dewpoints, primarily for the United States. In-situ point measurements are ingested into the PRISM (Parameter elevation Regression on Independent Slopes Model) statistical mapping system. The PRISM products use a weighted regression scheme to account for complex climate regimes associated with orography, rain shadows, temperature inversions, slope aspect, coastal proximity, and other factors. (see Data Sources for links to NHDPlusV2 data and USGS Data) These data are summarized by local catchment and by watershed to produce local catchment-level and watershed-level metrics as a continuous data type (see Data Structure and Attribute Information for a description).
The Realm of Physical Geography.
ERIC Educational Resources Information Center
Rea, Patrick S.
This secondary education student geography book contains chapters on climate, landforms, oceans, world vegetation, water resources, and population. Each chapter provides an introduction that describes the unit's topics, descriptive and instructional materials, learning activities, and questions. A glossary of geography-related terms and an…
Beauregard, Frieda; de Blois, Sylvie
2014-01-01
Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential for non-climate aspects of the environment to pose a constraint to range expansion under climate change. PMID:24658097
Beauregard, Frieda; de Blois, Sylvie
2014-01-01
Both climatic and edaphic conditions determine plant distribution, however many species distribution models do not include edaphic variables especially over large geographical extent. Using an exceptional database of vegetation plots (n = 4839) covering an extent of ∼55,000 km2, we tested whether the inclusion of fine scale edaphic variables would improve model predictions of plant distribution compared to models using only climate predictors. We also tested how well these edaphic variables could predict distribution on their own, to evaluate the assumption that at large extents, distribution is governed largely by climate. We also hypothesized that the relative contribution of edaphic and climatic data would vary among species depending on their growth forms and biogeographical attributes within the study area. We modelled 128 native plant species from diverse taxa using four statistical model types and three sets of abiotic predictors: climate, edaphic, and edaphic-climate. Model predictive accuracy and variable importance were compared among these models and for species' characteristics describing growth form, range boundaries within the study area, and prevalence. For many species both the climate-only and edaphic-only models performed well, however the edaphic-climate models generally performed best. The three sets of predictors differed in the spatial information provided about habitat suitability, with climate models able to distinguish range edges, but edaphic models able to better distinguish within-range variation. Model predictive accuracy was generally lower for species without a range boundary within the study area and for common species, but these effects were buffered by including both edaphic and climatic predictors. The relative importance of edaphic and climatic variables varied with growth forms, with trees being more related to climate whereas lower growth forms were more related to edaphic conditions. Our study identifies the potential for non-climate aspects of the environment to pose a constraint to range expansion under climate change.
Validation of individual and aggregate global flood hazard models for two major floods in Africa.
NASA Astrophysics Data System (ADS)
Trigg, M.; Bernhofen, M.; Whyman, C.
2017-12-01
A recent intercomparison of global flood hazard models undertaken by the Global Flood Partnership shows that there is an urgent requirement to undertake more validation of the models against flood observations. As part of the intercomparison, the aggregated model dataset resulting from the project was provided as open access data. We compare the individual and aggregated flood extent output from the six global models and test these against two major floods in the African Continent within the last decade, namely severe flooding on the Niger River in Nigeria in 2012, and on the Zambezi River in Mozambique in 2007. We test if aggregating different number and combination of models increases model fit to the observations compared with the individual model outputs. We present results that illustrate some of the challenges of comparing imperfect models with imperfect observations and also that of defining the probability of a real event in order to test standard model output probabilities. Finally, we propose a collective set of open access validation flood events, with associated observational data and descriptions that provide a standard set of tests across different climates and hydraulic conditions.
Wildhaber, Mark L.; Wikle, Christopher K.; Anderson, Christopher J.; Franz, Kristie J.; Moran, Edward H.; Dey, Rima; Mader, Helmut; Kraml, Julia
2012-01-01
Climate change operates over a broad range of spatial and temporal scales. Understanding its effects on ecosystems requires multi-scale models. For understanding effects on fish populations of riverine ecosystems, climate predicted by coarse-resolution Global Climate Models must be downscaled to Regional Climate Models to watersheds to river hydrology to population response. An additional challenge is quantifying sources of uncertainty given the highly nonlinear nature of interactions between climate variables and community level processes. We present a modeling approach for understanding and accomodating uncertainty by applying multi-scale climate models and a hierarchical Bayesian modeling framework to Midwest fish population dynamics and by linking models for system components together by formal rules of probability. The proposed hierarchical modeling approach will account for sources of uncertainty in forecasts of community or population response. The goal is to evaluate the potential distributional changes in an ecological system, given distributional changes implied by a series of linked climate and system models under various emissions/use scenarios. This understanding will aid evaluation of management options for coping with global climate change. In our initial analyses, we found that predicted pallid sturgeon population responses were dependent on the climate scenario considered.
CM-DataONE: A Framework for collaborative analysis of climate model output
NASA Astrophysics Data System (ADS)
Xu, Hao; Bai, Yuqi; Li, Sha; Dong, Wenhao; Huang, Wenyu; Xu, Shiming; Lin, Yanluan; Wang, Bin
2015-04-01
CM-DataONE is a distributed collaborative analysis framework for climate model data which aims to break through the data access barriers of increasing file size and to accelerate research process. As data size involved in project such as the fifth Coupled Model Intercomparison Project (CMIP5) has reached petabytes, conventional methods for analysis and diagnosis of model outputs have been rather time-consuming and redundant. CM-DataONE is developed for data publishers and researchers from relevant areas. It can enable easy access to distributed data and provide extensible analysis functions based on tools such as NCAR Command Language, NetCDF Operators (NCO) and Climate Data Operators (CDO). CM-DataONE can be easily installed, configured, and maintained. The main web application has two separate parts which communicate with each other through APIs based on HTTP protocol. The analytic server is designed to be installed in each data node while a data portal can be configured anywhere and connect to a nearest node. Functions such as data query, analytic task submission, status monitoring, visualization and product downloading are provided to end users by data portal. Data conform to CMIP5 Model Output Format in each peer node can be scanned by the server and mapped to a global information database. A scheduler included in the server is responsible for task decomposition, distribution and consolidation. Analysis functions are always executed where data locate. Analysis function package included in the server has provided commonly used functions such as EOF analysis, trend analysis and time series. Functions are coupled with data by XML descriptions and can be easily extended. Various types of results can be obtained by users for further studies. This framework has significantly decreased the amount of data to be transmitted and improved efficiency in model intercomparison jobs by supporting online analysis and multi-node collaboration. To end users, data query is therefore accelerated and the size of data to be downloaded is reduced. Methodology can be easily shared among scientists, avoiding unnecessary replication. Currently, a prototype of CM-DataONE has been deployed on two data nodes of Tsinghua University.
Meze-Hausken, Elisabeth
2007-10-01
This paper is a portrayal of aspects of weather and climate as front-page news in Europe's rainiest city, Bergen, Norway. It descriptively explores the coverage and different contextualization of weather and climate. By asking the simple question of what actually constitutes a good or bad weather day in Bergen, short-lived weather descriptions in the news are compared with climatological data. The study reveals a complex picture with different annotations of good and bad weather depending on the season. It is found that, while the amount of sunshine is important for defining a good weather day during winter, it is temperature that determines a good summer day. In spring, holidays and the anticipation of the summer result in a lower sunshine threshold for what to call a good weather day. The conspicuousness of rainfall is shown by both the number of articles and the various contexts in which bad weather is presented in the newspaper. It is suggested here that it is not the amount of rainfall that creates headlines, but rather the context of the surrounding event, as well as the weather of the previous period. Human perceptions cannot be read off meteorological stations. Nevertheless, they can strengthen measurements and, therefore, have a value in themselves. As a result, perceptions of seasonal or daily weather anomalies may well play a role in how society in Bergen will think about and experience a probable climate change with a projected increase in rainfall.
Atmospheric, Climatic, and Environmental Research
NASA Technical Reports Server (NTRS)
Broecker, Wallace S.; Gornitz, Vivien M.
1994-01-01
The climate and atmospheric modeling project involves analysis of basic climate processes, with special emphasis on studies of the atmospheric CO2 and H2O source/sink budgets and studies of the climatic role Of CO2, trace gases and aerosols. These studies are carried out, based in part on use of simplified climate models and climate process models developed at GISS. The principal models currently employed are a variable resolution 3-D general circulation model (GCM), and an associated "tracer" model which simulates the advection of trace constituents using the winds generated by the GCM.
Assessing NARCCAP climate model effects using spatial confidence regions.
French, Joshua P; McGinnis, Seth; Schwartzman, Armin
2017-01-01
We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference.
NASA Astrophysics Data System (ADS)
Cailleret, Maxime; Snell, Rebecca; von Waldow, Harald; Kotlarski, Sven; Bugmann, Harald
2015-04-01
Different levels of uncertainty should be considered in climate impact projections by Dynamic Vegetation Models (DVMs), particularly when it comes to managing climate risks. Such information is useful to detect the key processes and uncertainties in the climate model - impact model chain and may be used to support recommendations for future improvements in the simulation of both climate and biological systems. In addition, determining which uncertainty source is dominant is an important aspect to recognize the limitations of climate impact projections by a multi-model ensemble mean approach. However, to date, few studies have clarified how each uncertainty source (baseline climate data, greenhouse gas emission scenario, climate model, and DVM) affects the projection of ecosystem properties. Focusing on one greenhouse gas emission scenario, we assessed the uncertainty in the projections of a forest landscape model (LANDCLIM) and a stand-scale forest gap model (FORCLIM) that is caused by linking climate data with an impact model. LANDCLIM was used to assess the uncertainty in future landscape properties of the Visp valley in Switzerland that is due to (i) the use of different 'baseline' climate data (gridded data vs. data from weather stations), and (ii) differences in climate projections among 10 GCM-RCM chains. This latter point was also considered for the projections of future forest properties by FORCLIM at several sites along an environmental gradient in Switzerland (14 GCM-RCM chains), for which we also quantified the uncertainty caused by (iii) the model chain specific statistical properties of the climate time-series, and (iv) the stochasticity of the demographic processes included in the model, e.g., the annual number of saplings that establish, or tree mortality. Using methods of variance decomposition analysis, we found that (i) The use of different baseline climate data strongly impacts the prediction of forest properties at the lowest and highest, but not so much at medium elevations. (ii) Considering climate change, the variability that is due to the GCM-RCM chains is much greater than the variability induced by the uncertainty in the initial climatic conditions. (iii) The uncertainties caused by the intrinsic stochasticity in the DVMs and by the random generation of the climate time-series are negligible. Overall, our results indicate that DVMs are quite sensitive to the climate data, highlighting particularly (1) the limitations of using one single multi-model average climate change scenario in climate impact studies and (2) the need to better consider the uncertainty in climate model outputs for projecting future vegetation changes.
Climate Vulnerability and Human Migration in Global Perspective.
Grecequet, Martina; DeWaard, Jack; Hellmann, Jessica J; Abel, Guy J
2017-05-01
The relationship between climate change and human migration is not homogenous and depends critically on the differential vulnerability of population and places. If places and populations are not vulnerable, or susceptible, to climate change, then the climate-migration relationship may not materialize. The key to understanding and, from a policy perspective, planning for whether and how climate change will impact future migration patterns is therefore knowledge of the link between climate vulnerability and migration. However, beyond specific case studies, little is known about this association in global perspective. We therefore provide a descriptive, country-level portrait of this relationship. We show that the negative association between climate vulnerability and international migration holds only for countries least vulnerable to climate change, which suggests the potential for trapped populations in more vulnerable countries. However, when analyzed separately by life supporting sector (food, water, health, ecosystem services, human habitat, and infrastructure) and vulnerability dimension (exposure, sensitivity, and adaptive capacity), we detect evidence of a relationship among more, but not the most, vulnerable countries. The bilateral (i.e., country-to-country) migration show that, on average, people move from countries of higher vulnerability to lower vulnerability, reducing global risk by 15%. This finding is consistent with the idea that migration is a climate adaptation strategy. Still, ~6% of bilateral migration is maladaptive with respect to climate change, with some movement toward countries with greater climate change vulnerability.
NASA Astrophysics Data System (ADS)
Jauregui, Yakelyn R.; Takahashi, Ken
2018-03-01
The observed nonlinear relationship between tropical sea surface temperature (T_s) and precipitation ( P) on climate timescales, by which a threshold (T_c) must be exceeded by T_s in order for deep convection to occur, is the basis of a physical-empirical model (PEM) that we fitted to observational data and CMIP5 climate model output and used to show that, with essentially only two constant parameters (T_c and the sensitivity a_1 of P to T_s>T_c), it provides a useful first-order description of the climatological and interannual variability of the large-scale distribution of tropical P given T_s, as well as of the biases of the Global Climate Models (GCMs). A substantial limitation is its underestimation of the peak P in the convergence zones, as the necessary processes associated with the atmospheric circulation are not considered. The pattern of the intermodel correlation between the mean T_s-T_c for each GCM and the average P distribution is in agreement with the double ITCZ bias, featuring roughly zonally-symmetric off-equatorial maxima, rather than being regionally or hemispherically restricted. The inter-comparison of GCMs indicates a relationship between T_c with the near-equatorial low-level (850 hPa) tropospheric temperature, consistent with the interpretation that it is a measure of the convective inhibition (CIN). The underestimation of T_c is linked to the cold free tropospheric bias in the GCMs. However, the discrepancy among the observational datasets is a limitation for assessing the GCM biases from the PEM framework quantitatively. Under the RCP4.5 climate change scenario, T_c increases slightly more than the mean tropical T_s, implying a stabilizing trend consistent with the amplified free tropospheric warming relative to the surface. However, since a_1 increases by 10-50%/°C with the surface warming, its effect dominates and results in generally positive precipitation change (Δ P) in the equatorial regions. In the equatorial eastern-central Pacific cold tongue, Δ (T_s-T_c) is positive, but the absolute T_s-T_c remains small, which explains the double band pattern of Δ P along the equatorial flanks of the spuriously strong double ITCZs. When the GCM biases are corrected in the PEM, the positive Δ P in the southeast Pacific and Atlantic oceans is substantially reduced.
Understanding Global Change: Frameworks and Models for Teaching Systems Thinking
NASA Astrophysics Data System (ADS)
Bean, J. R.; Mitchell, K.; Zoehfeld, K.; Oshry, A.; Menicucci, A. J.; White, L. D.; Marshall, C. R.
2017-12-01
The scientific and education communities must impart to teachers, students, and the public an understanding of how the various factors that drive climate and global change operate, and why the rates and magnitudes of these changes related to human perturbation of Earth system processes today are cause for deep concern. Even though effective educational modules explaining components of the Earth and climate system exist, interdisciplinary learning tools are necessary to conceptually link the causes and consequences of global changes. To address this issue, the Understanding Global Change Project at the University of California Museum of Paleontology (UCMP) at UC Berkeley developed an interdisciplinary framework that organizes global change topics into three categories: (1) causes of climate change, both human and non-human (e.g., burning of fossil fuels, deforestation, Earth's tilt and orbit), (2) Earth system processes that shape the way the Earth works (e.g., Earth's energy budget, water cycle), and (3) the measurable changes in the Earth system (e.g., temperature, precipitation, ocean acidification). To facilitate student learning about the Earth as a dynamic, interacting system, a website will provide visualizations of Earth system models and written descriptions of how each framework topic is conceptually linked to other components of the framework. These visualizations and textual summarizations of relationships and feedbacks in the Earth system are a unique and crucial contribution to science communication and education, informed by a team of interdisciplinary scientists and educators. The system models are also mechanisms by which scientists can communicate how their own work informs our understanding of the Earth system. Educators can provide context and relevancy for authentic datasets and concurrently can assess student understanding of the interconnectedness of global change phenomena. The UGC resources will be available through a web-based platform and scalable professional development programming to facilitate systemic changes in the teaching and learning about climate and global change. We are establishing a diverse community of scientists and educators across the country that are using these tools, and plan to create local networks supported by UGC staff and partners.
NASA Astrophysics Data System (ADS)
Liu, X.; Ma, P.-L.; Wang, H.; Tilmes, S.; Singh, B.; Easter, R. C.; Ghan, S. J.; Rasch, P. J.
2016-02-01
Atmospheric carbonaceous aerosols play an important role in the climate system by influencing the Earth's radiation budgets and modifying the cloud properties. Despite the importance, their representations in large-scale atmospheric models are still crude, which can influence model simulated burden, lifetime, physical, chemical and optical properties, and the climate forcing of carbonaceous aerosols. In this study, we improve the current three-mode version of the Modal Aerosol Module (MAM3) in the Community Atmosphere Model version 5 (CAM5) by introducing an additional primary carbon mode to explicitly account for the microphysical ageing of primary carbonaceous aerosols in the atmosphere. Compared to MAM3, the four-mode version of MAM (MAM4) significantly increases the column burdens of primary particulate organic matter (POM) and black carbon (BC) by up to 40 % in many remote regions, where in-cloud scavenging plays an important role in determining the aerosol concentrations. Differences in the column burdens for other types of aerosol (e.g., sulfate, secondary organic aerosols, mineral dust, sea salt) are less than 1 %. Evaluating the MAM4 simulation against in situ surface and aircraft observations, we find that MAM4 significantly improves the simulation of seasonal variation of near-surface BC concentrations in the polar regions, by increasing the BC concentrations in all seasons and particularly in cold seasons. However, it exacerbates the overestimation of modeled BC concentrations in the upper troposphere in the Pacific regions. The comparisons suggest that, to address the remaining model POM and BC biases, future improvements are required related to (1) in-cloud scavenging and vertical transport in convective clouds and (2) emissions of anthropogenic and biomass burning aerosols.
Liu, X.; Ma, P. -L.; Wang, H.; ...
2016-02-08
Atmospheric carbonaceous aerosols play an important role in the climate system by influencing the Earth's radiation budgets and modifying the cloud properties. Despite the importance, their representations in large-scale atmospheric models are still crude, which can influence model simulated burden, lifetime, physical, chemical and optical properties, and the climate forcing of carbonaceous aerosols. In this study, we improve the current three-mode version of the Modal Aerosol Module (MAM3) in the Community Atmosphere Model version 5 (CAM5) by introducing an additional primary carbon mode to explicitly account for the microphysical ageing of primary carbonaceous aerosols in the atmosphere. Compared to MAM3,more » the four-mode version of MAM (MAM4) significantly increases the column burdens of primary particulate organic matter (POM) and black carbon (BC) by up to 40 % in many remote regions, where in-cloud scavenging plays an important role in determining the aerosol concentrations. Differences in the column burdens for other types of aerosol (e.g., sulfate, secondary organic aerosols, mineral dust, sea salt) are less than 1 %. Evaluating the MAM4 simulation against in situ surface and aircraft observations, we find that MAM4 significantly improves the simulation of seasonal variation of near-surface BC concentrations in the polar regions, by increasing the BC concentrations in all seasons and particularly in cold seasons. However, it exacerbates the overestimation of modeled BC concentrations in the upper troposphere in the Pacific regions. As a result, the comparisons suggest that, to address the remaining model POM and BC biases, future improvements are required related to (1) in-cloud scavenging and vertical transport in convective clouds and (2) emissions of anthropogenic and biomass burning aerosols.« less
What’s Needed from Climate Modeling to Advance Actionable Science for Water Utilities?
NASA Astrophysics Data System (ADS)
Barsugli, J. J.; Anderson, C. J.; Smith, J. B.; Vogel, J. M.
2009-12-01
“…perfect information on climate change is neither available today nor likely to be available in the future, but … over time, as the threats climate change poses to our systems grow more real, predicting those effects with greater certainty is non-discretionary. We’re not yet at a level at which climate change projections can drive climate change adaptation.” (Testimony of WUCA Staff Chair David Behar to the House Committee on Science and Technology, May 5, 2009) To respond to this challenge, the Water Utility Climate Alliance (WUCA) has sponsored a white paper titled “Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change. ” This report concerns how investments in the science of climate change, and in particular climate modeling and downscaling, can best be directed to help make climate projections more actionable. The meaning of “model improvement” can be very different depending on whether one is talking to a climate model developer or to a water manager trying to incorporate climate projections in to planning. We first surveyed the WUCA members on present and potential uses of climate model projections and on climate inputs to their various system models. Based on those surveys and on subsequent discussions, we identified four dimensions along which improvement in modeling would make the science more “actionable”: improved model agreement on change in key parameters; narrowing the range of model projections; providing projections at spatial and temporal scales that match water utilities system models; providing projections that water utility planning horizons. With these goals in mind we developed four options for improving global-scale climate modeling and three options for improving downscaling that will be discussed. However, there does not seem to be a single investment - the proverbial “magic bullet” -- which will substantially reduce the range of model projections at the scales at which utility planning is conducted. In the near term we feel strongly that water utilities and climate scientists should work together to leverage the upcoming Coupled Model Intercomparison Project, Phase 5 (CMIP5; a coordinated set climate model experiments that will be used to support the upcoming IPCC Fifth Assessment) to better benefit water utilities. In the longer term, even with model and downscaling improvements, it is very likely that substantial uncertainty about future climate change at the desired spatial and temporal scales will remain. Nonetheless, there is no doubt the climate is changing, and the challenge is to work with what we have, or what we can reasonably expect to have in the coming years to make the best decisions we can.
NASA Astrophysics Data System (ADS)
Khodayari, Arezoo; Wuebbles, Donald J.; Olsen, Seth C.; Fuglestvedt, Jan S.; Berntsen, Terje; Lund, Marianne T.; Waitz, Ian; Wolfe, Philip; Forster, Piers M.; Meinshausen, Malte; Lee, David S.; Lim, Ling L.
2013-08-01
This study evaluates the capabilities of the carbon cycle and energy balance treatments relative to the effect of aviation CO2 emissions on climate in several existing simplified climate models (SCMs) that are either being used or could be used for evaluating the effects of aviation on climate. Since these models are used in policy-related analyses, it is important that the capabilities of such models represent the state of understanding of the science. We compare the Aviation Environmental Portfolio Management Tool (APMT) Impacts climate model, two models used at the Center for International Climate and Environmental Research-Oslo (CICERO-1 and CICERO-2), the Integrated Science Assessment Model (ISAM) model as described in Jain et al. (1994), the simple Linear Climate response model (LinClim) and the Model for the Assessment of Greenhouse-gas Induced Climate Change version 6 (MAGICC6). In this paper we select scenarios to illustrate the behavior of the carbon cycle and energy balance models in these SCMs. This study is not intended to determine the absolute and likely range of the expected climate response in these models but to highlight specific features in model representations of the carbon cycle and energy balance models that need to be carefully considered in studies of aviation effects on climate. These results suggest that carbon cycle models that use linear impulse-response-functions (IRF) in combination with separate equations describing air-sea and air-biosphere exchange of CO2 can account for the dominant nonlinearities in the climate system that would otherwise not have been captured with an IRF alone, and hence, produce a close representation of more complex carbon cycle models. Moreover, results suggest that an energy balance model with a 2-box ocean sub-model and IRF tuned to reproduce the response of coupled Earth system models produces a close representation of the globally-averaged temperature response of more complex energy balance models.
Historical Time Series of Extreme Convective Weather in Finland
NASA Astrophysics Data System (ADS)
Laurila, T. K.; Mäkelä, A.; Rauhala, J.; Olsson, T.; Jylhä, K.
2016-12-01
Thunderstorms, lightning, tornadoes, downbursts, large hail and heavy precipitation are well-known for their impacts to human life. In the high latitudes as in Finland, these hazardous warm season convective weather events are focused in the summer season, roughly from May to September with peak in the midsummer. The position of Finland between the maritime Atlantic and the continental Asian climate zones makes possible large variability in weather in general which reflects also to the occurrence of severe weather; the hot, moist and extremely unstable air masses sometimes reach Finland and makes possible for the occurrence of extreme and devastating weather events. Compared to lower latitudes, the Finnish climate of severe convection is "moderate" and contains a large year-to-year variation; however, behind the modest annual average is hidden the climate of severe weather events that practically every year cause large economical losses and sometimes even losses of life. Because of the increased vulnerability of our modern society, these episodes have gained recently plenty of interest. During the decades, the Finnish Meteorological Institute (FMI) has collected observations and damage descriptions of severe weather episodes in Finland; thunderstorm days (1887-present), annual number of lightning flashes (1960-present), tornados (1796-present), large hail (1930-present), heavy rainfall (1922-present). The research findings show e.g. that a severe weather event may occur practically anywhere in the country, although in general the probability of occurrence is smaller in the Northern Finland. This study, funded by the Finnish Research Programme on Nuclear Power Plant Safety (SAFIR), combines the individual Finnish severe weather time series' and examines their trends, cross-correlation and correlations with other atmospheric parameters. Furthermore, a numerical weather model (HARMONIE) simulation is performed for a historical severe weather case for analyzing how well the present state-of-the-art models grasp these small-scale weather phenomena. Our results give important background for estimating the Finnish severe weather climate in the future.
Adaptive developmental delay in Chagas disease vectors: an evolutionary ecology approach.
Menu, Frédéric; Ginoux, Marine; Rajon, Etienne; Lazzari, Claudio R; Rabinovich, Jorge E
2010-05-25
The developmental time of vector insects is important in population dynamics, evolutionary biology, epidemiology and in their responses to global climatic change. In the triatomines (Triatominae, Reduviidae), vectors of Chagas disease, evolutionary ecology concepts, which may allow for a better understanding of their biology, have not been applied. Despite delay in the molting in some individuals observed in triatomines, no effort was made to explain this variability. We applied four methods: (1) an e-mail survey sent to 30 researchers with experience in triatomines, (2) a statistical description of the developmental time of eleven triatomine species, (3) a relationship between development time pattern and climatic inter-annual variability, (4) a mathematical optimization model of evolution of developmental delay (diapause). 85.6% of responses informed on prolonged developmental times in 5(th) instar nymphs, with 20 species identified with remarkable developmental delays. The developmental time analysis showed some degree of bi-modal pattern of the development time of the 5(th) instars in nine out of eleven species but no trend between development time pattern and climatic inter-annual variability was observed. Our optimization model predicts that the developmental delays could be due to an adaptive risk-spreading diapause strategy, only if survival throughout the diapause period and the probability of random occurrence of "bad" environmental conditions are sufficiently high. Developmental delay may not be a simple non-adaptive phenotypic plasticity in development time, and could be a form of adaptive diapause associated to a physiological mechanism related to the postponement of the initiation of reproduction, as an adaptation to environmental stochasticity through a spreading of risk (bet-hedging) strategy. We identify a series of parameters that can be measured in the field and laboratory to test this hypothesis. The importance of these findings is discussed in terms of global climatic change and epidemiological consequences.
An Investigation on the Sensitivity of the Parameters of Urban Flood Model
NASA Astrophysics Data System (ADS)
M, A. B.; Lohani, B.; Jain, A.
2015-12-01
Global climatic change has triggered weather patterns which lead to heavy and sudden rainfall in different parts of world. The impact of heavy rainfall is severe especially on urban areas in the form of urban flooding. In order to understand the effect of heavy rainfall induced flooding, it is necessary to model the entire flooding scenario more accurately, which is now becoming possible with the availability of high resolution airborne LiDAR data and other real time observations. However, there is not much understanding on the optimal use of these data and on the effect of other parameters on the performance of the flood model. This study aims at developing understanding on these issues. In view of the above discussion, the aim of this study is to (i) understand that how the use of high resolution LiDAR data improves the performance of urban flood model, and (ii) understand the sensitivity of various hydrological parameters on urban flood modelling. In this study, modelling of flooding in urban areas due to heavy rainfall is carried out considering Indian Institute of Technology (IIT) Kanpur, India as the study site. The existing model MIKE FLOOD, which is accepted by Federal Emergency Management Agency (FEMA), is used along with the high resolution airborne LiDAR data. Once the model is setup it is made to run by changing the parameters such as resolution of Digital Surface Model (DSM), manning's roughness, initial losses, catchment description, concentration time, runoff reduction factor. In order to realize this, the results obtained from the model are compared with the field observations. The parametric study carried out in this work demonstrates that the selection of catchment description plays a very important role in urban flood modelling. Results also show the significant impact of resolution of DSM, initial losses and concentration time on urban flood model. This study will help in understanding the effect of various parameters that should be part of a flood model for its accurate performance.
The Development in modeling Tibetan Plateau Land/Climate Interaction
NASA Astrophysics Data System (ADS)
Xue, Yongkang; Liu, Ye; li, qian; Maheswor Shrestha, Maheswor; Ma, Hsi-Yen; Cox, Peter; Sun, shufen; Koike, Toshio
2015-04-01
Tibetan Plateau (TP) plays an important role in influencing the continental and planetary scale climate, including East Asian and South Asian monsoon, circulation and precipitation over West Pacific and Indian Oceans. The numerical study has identified TP as the area with strongest land/atmosphere interactions over the midlatitude land. The land degradation there has also affected the monsoon precipitation in TP along the monsoon pathway. The water cycle there affects water sources for major Asian river systems, which include the Tarim, Amu Darya, Indus, Ganges, Brahmaputra, Irrawaddy, Salween, Mekong, Yellow, and Yangtze Rivers. Despite the importance of TP land process in the climate system, the TP land surface processes are poorly modeled due to lack of data available for model validation. To better understand, simulate, and project the role of Tibetan Plateau land surface processes, better parameterization of the Tibetan Land surface processes have been developed and evaluated. The recently available field measurement there and satellite observation have greatly helped this development. This paper presents these new developments and preliminary results using the newly developed biophysical/dynamic vegetation model, frozen soil model, and glacier model. In recent CMIP5 simulation, the CMIP5 models with dynamic vegetation model show poor performance in simulating the TP vegetation and climate. To better simulate the TP vegetation condition and its interaction with climate, we have developed biophysical/dynamic vegetation model, the Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), based on water, carbon, and energy balance. The simulated vegetation variables are updates, driven by carbon assimilation, allocation, and accumulation, as well as competition between plant functional types. The model has been validated with the station data, including those measured over the TP. The offline SSiB4/TRIFFID is integrated using the observed precipitation and reanalysis-based meteorological forcing from 1948 to 2008 with 1 degree horizontal resolution. The simulated vegetation conditions and surface hydrology are compared well with observational data with some bias, and shows strong decadal and interannual variabilities with a linear trend associated with the global warming. The TP region is covered by both discontinuous and sporadic permafrost with irregular snow layers above. A frozen soil model is developed to take the coupling effect of mass and heat transport into consideration and includes a detailed description of mass balances of volumetric liquid water, ice, as well as vapor content. It also considers contributions' of heat conduction to the energy balance. The model has been extensively tested using a number of TP station data, which included soil temperature and soil water measurements. The results suggest that it is important to include the frozen sol process to adequately simulate the surface energy balance during the freezing and thawing periods and surface temperature variability, including its diurnal variation. Issues in simulating permafrost process will also be addressed. To better understand the glacier variations under climate change scenarios, an integrated modeling system with an energy budget-based multilayer scheme for clean glaciers, a single-layer scheme for debris-covered glaciers and multilayer scheme for seasonal snow over glacier, soil and forest are developed within a distributed biosphere hydrological modeling framework (WEB-DHM-S model). Discharge simulations using this model show good agreement with observations for Hunza River Basin (13,733 km2) in the Karakoram region of Pakistan for three hydrologic years (2002-2004). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt) and suggests that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu-Kush-Karakoram-Himalaya region.
The Arctic Climate Modeling Program: K-12 Geoscience Professional Development for Rural Educators
NASA Astrophysics Data System (ADS)
Bertram, K. B.
2009-12-01
Helping teachers and students connect with scientists is the heart of the Arctic Climate Modeling Program (ACMP), funded from 2005-09 by the National Science Foundation’s Innovative Technology Experience for Students and Teachers. ACMP offered progressive yearlong science, technology and math (STM) professional development that prepared teachers to train youth in workforce technologies used in Arctic research. ACMP was created for the Bering Strait School District, a geographically isolated area with low standardized test scores, high dropout rates, and poverty. Scientists from around the globe have converged in this region and other areas of the Arctic to observe and measure changes in climate that are significant, accelerating, and unlike any in recorded history. Climate literacy (the ability to understand Earth system science and to make scientifically informed decisions about climate changes) has become essential for this population. Program resources were designed in collaboration with scientists to mimic the processes used to study Arctic climate. Because the Bering Strait School District serves a 98 percent Alaska Native student population, ACMP focused on best practices shown to increase the success of minority students. Significant research indicates that Alaska Native students succeed academically at higher rates when instruction addresses topics of local interest, links education to the students’ physical and cultural environment, uses local knowledge and culture in the curriculum, and incorporates hands-on, inquiry-based lessons in the classroom. A seven-partner consortium of research institutes and Alaska Native corporations created ACMP to help teachers understand their role in nurturing STM talent and motivating students to explore geoscience careers. Research underscores the importance of increasing school emphasis in content areas, such as climate, that facilitate global awareness and civic responsibility, and that foster critical thinking and other 21st century learning skills. Climate studies offer insight into a broad cross-section of STM careers, and provide a natural forum for helping students develop problem-solving skills inherent in STM research. Climate research involves sophisticated technology, a complex set of 21st century skills, and the ability to collaborate with an international community. Professional development that trains teachers in these skills is essential considering that recent research shows 90 percent of U.S. secondary students are taught Earth and physical science by a teacher lacking STM certification. ACMP summative evaluation posed three questions: 1) Did ACMP training meet teachers’ needs? 2) Did ACMP involvement result in more effective teachers and teaching? 3) Did participation in ACMP result in higher Bering Strait School District student achievement? Teachers and students were evaluated using a mixed method design incorporating descriptive components with a before/after design to measure what teachers and students learned. Community members, 165 teachers, and 1,738 individual students participated in the program, which was successful in its goals overall.
Global-scale combustion sources of organic aerosols: sensitivity to formation and removal mechanisms
NASA Astrophysics Data System (ADS)
Tsimpidi, Alexandra P.; Karydis, Vlassis A.; Pandis, Spyros N.; Lelieveld, Jos
2017-06-01
Organic compounds from combustion sources such as biomass burning and fossil fuel use are major contributors to the global atmospheric load of aerosols. We analyzed the sensitivity of model-predicted global-scale organic aerosols (OA) to parameters that control primary emissions, photochemical aging, and the scavenging efficiency of organic vapors. We used a computationally efficient module for the description of OA composition and evolution in the atmosphere (ORACLE) of the global chemistry-climate model EMAC (ECHAM/MESSy Atmospheric Chemistry). A global dataset of aerosol mass spectrometer (AMS) measurements was used to evaluate simulated primary (POA) and secondary (SOA) OA concentrations. Model results are sensitive to the emission rates of intermediate-volatility organic compounds (IVOCs) and POA. Assuming enhanced reactivity of semi-volatile organic compounds (SVOCs) and IVOCs with OH substantially improved the model performance for SOA. The use of a hybrid approach for the parameterization of the aging of IVOCs had a small effect on predicted SOA levels. The model performance improved by assuming that freshly emitted organic compounds are relatively hydrophobic and become increasingly hygroscopic due to oxidation.
NASA Astrophysics Data System (ADS)
Russo, E.; Mauri, A.; Davis, B. A. S.; Cubasch, U.
2017-12-01
The evolution of the Mediterranean region's climate during the Holocene has been the subject of long-standing debate within the paleoclimate community. Conflicting hypotheses have emerged from the analysis of different climate reconstructions based on proxy records and climate models outputs.In particular, pollen-based reconstructions of cooler summer temperatures during the Holocene have been criticized based on a hypothesis that the Mediterranean vegetation is mainly limited by effective precipitation and not summer temperature. This criticism is important because climate models show warmer summer temperatures during the Holocene over the Mediterranean region, in direct contradiction of the pollen-based evidence. Here we investigate this problem using a high resolution model simulation of the climate of the Mediterranean region during the mid-to-late Holocene, which we compare against pollen-based reconstructions using two different approaches.In the first, we compare the simulated climate from the model directly with the climate derived from the pollen data. In the second, we compare the simulated vegetation from the model directly with the vegetation from the pollen data.Results show that the climate model is unable to simulate neither the climate nor the vegetation shown by the pollen-data. The pollen data indicates an expansion in cool temperate vegetation in the mid-Holocene while the model suggests an expansion in warm arid vegetation. This suggests that the data-model discrepancy is more likely the result of bias in climate models, and not bias in the pollen-climate calibration transfer-function.
How does the sensitivity of climate affect stratospheric solar radiation management?
NASA Astrophysics Data System (ADS)
Ricke, K.; Rowlands, D. J.; Ingram, W.; Keith, D.; Morgan, M. G.
2011-12-01
If implementation of proposals to engineer the climate through solar radiation management (SRM) ever occurs, it is likely to be contingent upon climate sensitivity. Despite this, no modeling studies have examined how the effectiveness of SRM forcings differs between the typical Atmosphere-Ocean General Circulation Models (AOGCMs) with climate sensitivities close to the Coupled Model Intercomparison Project (CMIP) mean and ones with high climate sensitivities. Here, we use a perturbed physics ensemble modeling experiment to examine variations in the response of climate to SRM under different climate sensitivities. When SRM is used as a substitute for mitigation its ability to maintain the current climate state gets worse with increased climate sensitivity and with increased concentrations of greenhouse gases. However, our results also demonstrate that the potential of SRM to slow climate change, even at the regional level, grows with climate sensitivity. On average, SRM reduces regional rates of temperature change by more than 90 percent and rates of precipitation change by more than 50 percent in these higher sensitivity model configurations. To investigate how SRM might behave in models with high climate sensitivity that are also consistent with recent observed climate change we perform a "perturbed physics" ensemble (PPE) modelling experiment with the climateprediction.net (cpdn) version of the HadCM3L AOGCM. Like other perturbed physics climate modelling experiments, we simulate past and future climate scenarios using a wide range of model parameter combinations that both reproduce past climate within a specified level of accuracy and simulate future climates with a wide range of climate sensitivities. We chose 43 members ("model versions") from a subset of the 1,550 from the British Broadcasting Corporation (BBC) climateprediction.net project that have data that allow restarts. We use our results to explore how much assessments of SRM that use best-estimate models, and so near-median climate sensitivity, may be ignoring important contingencies associated with implementing SRM in reality. A primary motivation for studying SRM via the injection of aerosols in the stratosphere is to evaluate its potential effectiveness as "insurance" in the case of higher-than-expected climate response to global warming. We find that this is precisely when SRM appears to be least effective in returning regional climates to their baseline states and reducing regional rates of precipitation change. On the other hand, given the very high regional temperature anomalies associated with rising greenhouse gas concentrations in high sensitivity models, it is also where SRM is most effective in reducing rates of change relative to a no SRM alternative.
Majda, Andrew J; Abramov, Rafail; Gershgorin, Boris
2010-01-12
Climate change science focuses on predicting the coarse-grained, planetary-scale, longtime changes in the climate system due to either changes in external forcing or internal variability, such as the impact of increased carbon dioxide. The predictions of climate change science are carried out through comprehensive, computational atmospheric, and oceanic simulation models, which necessarily parameterize physical features such as clouds, sea ice cover, etc. Recently, it has been suggested that there is irreducible imprecision in such climate models that manifests itself as structural instability in climate statistics and which can significantly hamper the skill of computer models for climate change. A systematic approach to deal with this irreducible imprecision is advocated through algorithms based on the Fluctuation Dissipation Theorem (FDT). There are important practical and computational advantages for climate change science when a skillful FDT algorithm is established. The FDT response operator can be utilized directly for multiple climate change scenarios, multiple changes in forcing, and other parameters, such as damping and inverse modelling directly without the need of running the complex climate model in each individual case. The high skill of FDT in predicting climate change, despite structural instability, is developed in an unambiguous fashion using mathematical theory as guidelines in three different test models: a generic class of analytical models mimicking the dynamical core of the computer climate models, reduced stochastic models for low-frequency variability, and models with a significant new type of irreducible imprecision involving many fast, unstable modes.
Geographic trend of bud hardiness response in Vitis riparia
USDA-ARS?s Scientific Manuscript database
A major goal of grapevine breeding efforts for production outside of Mediterranean climates is the production of varieties that have cold tolerance phenotypes. Typically, grapevine breeders use midwinter bud hardiness measures as the descriptive phenotype for cold tolerance. Historical practices of...
Novel GIS approaches to watershed science and management: Description, prediction, and integration
Spatial data and geographic information systems (GIS) are playing an increasingly important role in watershed science and management, particularly in the face of increasing climate uncertainty and demand for water resources. Concomitantly, scientists and managers are presented wi...
Integrated approaches to climate–crop modelling: needs and challenges
A. Betts, Richard
2005-01-01
This paper discusses the need for a more integrated approach to modelling changes in climate and crops, and some of the challenges posed by this. While changes in atmospheric composition are expected to exert an increasing radiative forcing of climate change leading to further warming of global mean temperatures and shifts in precipitation patterns, these are not the only climatic processes which may influence crop production. Changes in the physical characteristics of the land cover may also affect climate; these may arise directly from land use activities and may also result from the large-scale responses of crops to seasonal, interannual and decadal changes in the atmospheric state. Climate models used to drive crop models may, therefore, need to consider changes in the land surface, either as imposed boundary conditions or as feedbacks from an interactive climate–vegetation model. Crops may also respond directly to changes in atmospheric composition, such as the concentrations of carbon dioxide (CO2), ozone (O3) and compounds of sulphur and nitrogen, so crop models should consider these processes as well as climate change. Changes in these, and the responses of the crops, may be intimately linked with meteorological processes so crop and climate models should consider synergies between climate and atmospheric chemistry. Some crop responses may occur at scales too small to significantly influence meteorology, so may not need to be included as feedbacks within climate models. However, the volume of data required to drive the appropriate crop models may be very large, especially if short-time-scale variability is important. Implementation of crop models within climate models would minimize the need to transfer large quantities of data between separate modelling systems. It should also be noted that crop responses to climate change may interact with other impacts of climate change, such as hydrological changes. For example, the availability of water for irrigation may be affected by changes in runoff as a direct consequence of climate change, and may also be affected by climate-related changes in demand for water for other uses. It is, therefore, necessary to consider the interactions between the responses of several impacts sectors to climate change. Overall, there is a strong case for a much closer coupling between models of climate, crops and hydrology, but this in itself poses challenges arising from issues of scale and errors in the models. A strategy is proposed whereby the pursuit of a fully coupled climate–chemistry–crop–hydrology model is paralleled by continued use of separate climate and land surface models but with a focus on consistency between the models. PMID:16433093
Implementation of an Online Chemistry Model to a Large Eddy Simulation Model (PALM-4U0
NASA Astrophysics Data System (ADS)
Mauder, M.; Khan, B.; Forkel, R.; Banzhaf, S.; Russo, E. E.; Sühring, M.; Kanani-Sühring, F.; Raasch, S.; Ketelsen, K.
2017-12-01
Large Eddy Simulation (LES) models permit to resolve relevant scales of turbulent motion, so that these models can capture the inherent unsteadiness of atmospheric turbulence. However, LES models are so far hardly applied for urban air quality studies, in particular chemical transformation of pollutants. In this context, BMBF (Bundesministerium für Bildung und Forschung) funded a joint project, MOSAIK (Modellbasierte Stadtplanung und Anwendung im Klimawandel / Model-based city planning and application in climate change) with the main goal to develop a new highly efficient urban climate model (UCM) that also includes atmospheric chemical processes. The state-of-the-art LES model PALM; Maronga et al, 2015, Geosci. Model Dev., 8, doi:10.5194/gmd-8-2515-2015), has been used as a core model for the new UCM named as PALM-4U. For the gas phase chemistry, a fully coupled 'online' chemistry model has been implemented into PALM. The latest version of the Kinetic PreProcessor (KPP) Version 2.3, has been utilized for the numerical integration of chemical species. Due to the high computational demands of the LES model, compromises in the description of chemical processes are required. Therefore, a reduced chemistry mechanism, which includes only major pollutants namely O3, NO, NO2, CO, a highly simplified VOC chemistry and a small number of products have been implemented. This work shows preliminary results of the advection, and chemical transformation of atmospheric pollutants. Non-cyclic boundaries have been used for inflow and outflow in east-west directions while periodic boundary conditions have been implemented to the south-north lateral boundaries. For practical applications, our approach is to go beyond the simulation of single street canyons to chemical transformation, advection and deposition of air pollutants in the larger urban canopy. Tests of chemistry schemes and initial studies of chemistry-turbulence, transport and transformations are presented.
A New CCI ECV Release (v2.0) to Accurately Measure the Sea Level Change (1993-2015)
NASA Astrophysics Data System (ADS)
Legeais, J.; Cazenave, A. A.; Ablain, M.; Gilles, G.; Johannessen, J. A.; Scharffenberg, M. G.; Timms, G.; Andersen, O. B.; Cipollini, P.; Roca, M.; Rudenko, S.; Fernandes, J.; Balmaseda, M.; Quartly, G.; Fenoglio Marc, L.; Meyssignac, B.; Benveniste, J.; Ambrozio, A.; Restano, M.
2016-12-01
Accurate monitoring of the sea level is required to better understand its variability and changes. Sea level is one of the Essential Climate Variables (ECV) selected in the frame of the ESA Climate Change Initiative (CCI) program. It aims at providing a long-term homogeneous and accurate sea level record. The needs and feedback of the climate research community have been collected and a first version of the sea level ECV product has been generated with the best algorithms and altimeter standards. This record (1993-2014) has been validated by the climate research community. Within phase II (2014-2016), the 15 partner consortium has prepared the production of a new reprocessed homogeneous and accurate altimeter sea level record which will be distributed in Autumn 2016. New level 2 altimeter standards developed and tested within the project as well as external contributions have been identified, processed and evaluated by comparison with a reference for different altimeter missions (TOPEX/Poseidon, Jason-1 & 2, ERS-1 & 2, Envisat and GFO). The main evolutions are associated with the wet troposphere correction (based on the GPD+ algorithm including inter calibration with respect to external sensors) but also to the orbit solutions (POE-E and GFZ15), the ERA-Interim based atmospheric corrections and the FES2014 ocean tide model. A new pole tide solution is used and anomalies are referenced to the MSS DTU15. The presentation will focus on the main achievements of the ESA CCI Sea Level project and on the description of the new SL_cci ECV release covering 1993-2015. The major steps required to produce the reprocessed 23 year climate time series will be described. The impacts of the selected level 2 altimeter standards on the SL_cci ECV have been assessed on different spatial scales (global, regional, mesoscale) and temporal scales (long-term, inter-annual, periodic). A significant improvement is expected compared to the current v1.1, with the main impacts observed on the long-term evolution on decadal time scale, on global and regional scales, and for mesoscale signals. The results from product validation, carried out by several groups of the ocean and climate modeling community will be also presented.
Documenting Climate Models and Simulations: the ES-DOC Ecosystem in Support of CMIP
NASA Astrophysics Data System (ADS)
Pascoe, C. L.; Guilyardi, E.
2017-12-01
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 non-specialists 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. Here we describe the ES-DOC community-govern project to collect and make available documentation of climate models and their simulations for the internationally coordinated modeling activity CMIP6 (Coupled Model Intercomparison Project, Phase 6). An overview of the underlying standards, key properties and features, the evolution from CMIP5, the underlying tools and workflows as well as what modelling groups should expect and how they should engage with the documentation of their contribution to CMIP6 is also presented.
Assessing NARCCAP climate model effects using spatial confidence regions
French, Joshua P.; McGinnis, Seth; Schwartzman, Armin
2017-01-01
We assess similarities and differences between model effects for the North American Regional Climate Change Assessment Program (NARCCAP) climate models using varying classes of linear regression models. Specifically, we consider how the average temperature effect differs for the various global and regional climate model combinations, including assessment of possible interaction between the effects of global and regional climate models. We use both pointwise and simultaneous inference procedures to identify regions where global and regional climate model effects differ. We also show conclusively that results from pointwise inference are misleading, and that accounting for multiple comparisons is important for making proper inference. PMID:28936474
Linking models of human behaviour and climate alters projected climate change
Beckage, Brian; Gross, Louis J.; Lacasse, Katherine; ...
2018-01-01
Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4–6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with themore » largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Lastly, our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.« less
Linking models of human behaviour and climate alters projected climate change
NASA Astrophysics Data System (ADS)
Beckage, Brian; Gross, Louis J.; Lacasse, Katherine; Carr, Eric; Metcalf, Sara S.; Winter, Jonathan M.; Howe, Peter D.; Fefferman, Nina; Franck, Travis; Zia, Asim; Kinzig, Ann; Hoffman, Forrest M.
2018-01-01
Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4-6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with the largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.
Linking models of human behaviour and climate alters projected climate change
DOE Office of Scientific and Technical Information (OSTI.GOV)
Beckage, Brian; Gross, Louis J.; Lacasse, Katherine
Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4–6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with themore » largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Lastly, our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.« less
Climate Change and Projected Impacts in Agriculture: an Example on Mediterranean Crops
NASA Astrophysics Data System (ADS)
Ferrise, R.; Moriondo, M.; Bindi, M.
2009-04-01
Recently, the availability of multi-model ensemble prediction methods has permitted the assignment of likelihoods to future climate projections. This allowed moving from the scenario-based approach to the risk-based approach in assessing the effects of climate change, thus providing more useful information for decision-makers that, as reported by Schneider (2001), need probability estimates to assess the seriousness of the projected impacts. The probabilistic approach to evaluate crop response to climate change mainly consists in applying an impact model (such as crop growth model) to a very large number of climate projections so to provide a probabilistic distribution of the variable selected to evaluate the impact. By comparing the outputs of the multi-simulation with a critical threshold (such as minimum yield below which it is not admissible to fall), it is possible to evaluate the risk related to future climate conditions. Unfortunately, such an approach is a time-consuming process due to the large number of model runs needed for such a procedure. An alternative method relies on the set up of impact response surfaces (RS) with respect to key climatic variables on which a probabilistic representation of projected changes in the same climatic variables may be overlaid (Fronzek et al. 2008). This approach was exploited within the ENSEMBLES EU Project aiming at assessing climate change impact on typical Mediterranean crops. This work presents the results of the project with a particular concerning about the assessment of risk, of durum wheat (T. turgidum L. subsp. durum (Desf.) Husn) and grapevine (Vitis vinifera L.) yield falling below fixed thresholds, using probabilistic information about future climate. Methodology The simple mechanistic crop growth models, SIRIUS Quality (Jamieson et al., 1998) and VITE-model (Bindi et al., 1997a,b), were selected to respectively simulate durum wheat and grapevine yields in present and future scenarios. SIRIUS Quality is a wheat simulation model that calculates biomass production from photosynthetically active radiation and grain growth from simple partition rules. VITE-model is a model that uses a simplified mechanistic approach based on the accumulated degree days, the radiation use efficiency and the fruit biomass index to simulate the main processes regulating grapevine development, growth and yield. The selected crop growth models were adopted to create yield RSs of both crops over the suitable cultivated area in the Mediterranean Basin. Yield RSs were calculated performing a scenario sensitivity analysis by altering the baseline climate with respect to temperature and precipitation changes. The baseline climate consisted of 30 years (1975-2005) of daily minimum and maximum temperatures, rainfall and global radiation. Meteorological data were extracted from the MARS JRC Archive and are referred to a grid with a spatial resolution of 50 Km x 50 Km covering the whole European area. The sensitivity analysis was performed for precipitation changes (from -40% to 20%) and temperature changes (from 0°C to +8°C), uniformly applied across all the year. To take in account for the effect of rising CO2, the yield RSs for future periods, were produced considering CO2 air concentration level according to the A1B SRES emission scenario. For each rainfall and temperature combination the average yield over the 30-years period was calculated. The probabilistic distribution of future yields was estimated by applying a bilinear interpolative method to overlap, onto the RSs, the data from perturbed physics experiment of Hadley Centre for future scenarios (joint distribution of annual temperature and rainfall changes). Critical thresholds of impact were determined by calculating, for each grid cell, the distribution of the 30-years average yield according to the joint distribution data for present period (1990-2010) and selecting the values that correspond to the 20th percentile of the cumulative distribution. Finally, future yields were compared with yield threshold to assess the risk of yield shortfall that, in each time period, was defined as the percentage of projected yields that not overcome the selected threshold. Results Maps of durum wheat and grapevine low productivity risk were generated for the next century over the Mediterranean Basin. For durum wheat, with the exception of Portugal and Southern Spain, in the next 30 years risk of low crop productivity shows an overall reduction, due to the fertilizing effect of CO2 increase that counterbalances for the negative impact of rising temperature and reducing rainfall. Thereafter, these latter negative effects become greater and the risk progressively increases starting from lower latitudes. Maximum risk was estimated in 2060 when strong reductions in yield were accounted all over the study area. The smaller reductions in risk, estimated for the end of the next century, may be explained by the greater uncertainty in climate projections. South Portugal, South Spain and Peloponnesus resulted the most vulnerable areas showing increase in risk probability up to 50%, while risk in Galicia, Slovenia, Croatia and central-southern France always resulted lower then present time. As regard grapevine, in the great part of the case study area, the yield seems to have beneficial effect from future climate change. In Central-Western Europe and at lower latitudes the projected yields never fall below the risk threshold, indicating a prevailing effect of CO2 fertilisation. By the other hand, Central-Northern Italy and North of Greece result the most vulnerable areas. In these regions the likelihood of reduced yields quickly rises and remains very high (>50%) until the end of the century, denoting a greater negative effect of temperature and rainfall. Conclusions From these results it may be argued that the impact of future climate change on crop yields is the resultant of the contrasting effects of changes in temperature and precipitation, CO2 increase and uncertainty in climate projections. The intensity of these effects is very site and crop dependent and may vary with time, differently affecting the assessment of risk. As a consequence, the patterns of risk of low crop productivity will change depending on which of these effects will prevail. References Bindi M. et al., 1997a "A simple model for simulation of growth and development in grapevine (Vitis vinifera L.). I. Model description". Vitis 36:67-71 Bindi M. et al., 1997b "A simple model for simulation of growth and development in grapevine (Vitis vinifera L.). II. Model validation". Vitis 36:73-76 Carter T. et al., 2006 "". Fronzek S. et al 2008 "Applying probabilistic projections of climate change with impact models: a case study for sub-arctic palsa mires in Fennoscandia". Climatic Change (submitted) Jamieson et al., 1998 "Sirius: a mechanistic model of wheat response to environmental variation". Eur. J. Agron. 8:161-179. Schneider S. 2001 "What is ‘dangerous' climate change?". Nature 411:17-19
Impact of ethical factors on job satisfaction among Korean nurses.
Jang, Yujin; Oh, Younjae
2017-01-01
Although numerous studies on job satisfaction among nurses have been conducted, there is a lack of research considering the ethical perspectives of leadership and organizational climate in job satisfaction. The purpose of this study was to clarify the impact of the ethical climate and ethical leadership as perceived by nurses on job satisfaction in South Korea. A descriptive and correlational study was conducted with a convenience sample of 263 nurses from four general hospitals in South Korea. Ethical considerations: This study was approved by the Institute Review Board of Hallym University before data collection. Job satisfaction was positively correlated with ethical climate and ethical leadership. The ethical climate in relationship with hospitals and people orientation leadership were influential factors in the level of job satisfaction among nurses. Organizations in the nursing environment should pay attention to improving the ethical climate with acceptable ethical norms in the workplace and nurse leaders should respect, support and genuinely care about their nurses in ethical concerns.
Determing Credibility of Regional Simulations of Future Climate
NASA Astrophysics Data System (ADS)
Mearns, L. O.
2009-12-01
Climate models have been evaluated or validated ever since they were first developed. Establishing that a climate model can reproduce (some) aspects of the current climate of the earth on various spatial and temporal scales has long been a standard procedure for providing confidence in the model's ability to simulate future climate. However, direct links between the successes and failures of models in reproducing the current climate with regard to what future climates the models simulate has been largely lacking. This is to say that the model evaluation process has been largely divorced from the projections of future climate that the models produce. This is evidenced in the separation in the Intergovernmental Panel on Climate Change (IPCC) WG1 report of the chapter on evaluation of models from the chapter on future climate projections. There has also been the assumption of 'one model, one vote, that is, that each model projection is given equal weight in any multi-model ensemble presentation of the projections of future climate. There have been various attempts at determing measures of credibility that would avoid the 'ultrademocratic' assumption of the IPCC. Simple distinctions between models were made by research such as in Giorgi and Mearns (2002), Tebaldi et al., (2005), and Greene et al., (2006). But the metrics used were rather simplistic. More ambitous means of discriminating among the quality of model simulations have been made through the production of complex multivariate metrics, but insufficent work has been produced to verify that the metrics successfully discriminate in meaningful ways. Indeed it has been suggested that we really don't know what a model must successfully model to establish confidence in its regional-scale projections (Gleckler et al., 2008). Perhaps a more process oriented regional expert judgment approach is needed to understand which errors in climate models really matter for the model's response to future forcing. Such an approach is being attempted in the North American Climate Change Assessment Program (NARCCAP) whereby multiple global models are used to drive multiple regional models for the current period and the mid-21st century over the continent. Progress in this endeavor will be reported.
NASA Astrophysics Data System (ADS)
Handayani, W.; Ananda, M. R.; Esariti, L.; Anggraeni, M.
2018-03-01
Mainly due to its complexity, the effort to mainstream gender in addressing climate change issues has been far from the satisfying result. However, there is an urgent call to accommodate gender lens issues and to become more gender sensitive in an attempt to have an effective intervention in responding climate change impact. To enrich the reports on gender and climate change adaptation in city-based case, this paper aims to elaborate climate change adaptation in Tanjung Mas – Semarang city focusing on the gender perspective analysis in male- and female-headed households. The quantitative descriptive method is applied to carry out the analyses, including adaptive strategy and gender role analyses. The research result indicates there are not any significant differences in the climate change adaptation strategies applied in male- and female-headed households. This shows that women in the female-headed households, with their double burden, performed well in managing their roles. Therefore, in particular perspective, it may not be relevant to state that woman and female-headed households are likely to be more vulnerable compared with their counterparts.
Climate data induced uncertainty in model-based estimations of terrestrial primary productivity
NASA Astrophysics Data System (ADS)
Wu, Zhendong; Ahlström, Anders; Smith, Benjamin; Ardö, Jonas; Eklundh, Lars; Fensholt, Rasmus; Lehsten, Veiko
2017-06-01
Model-based estimations of historical fluxes and pools of the terrestrial biosphere differ substantially. These differences arise not only from differences between models but also from differences in the environmental and climatic data used as input to the models. Here we investigate the role of uncertainties in historical climate data by performing simulations of terrestrial gross primary productivity (GPP) using a process-based dynamic vegetation model (LPJ-GUESS) forced by six different climate datasets. We find that the climate induced uncertainty, defined as the range among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 11 Pg C yr-1 globally (9% of mean GPP). We also assessed a hypothetical maximum climate data induced uncertainty by combining climate variables from different datasets, which resulted in significantly larger uncertainties of 41 Pg C yr-1 globally or 32% of mean GPP. The uncertainty is partitioned into components associated to the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (climate data range) and the apparent sensitivity of the modeled GPP to the driver (apparent model sensitivity). We find that LPJ-GUESS overestimates GPP compared to empirically based GPP data product in all land cover classes except for tropical forests. Tropical forests emerge as a disproportionate source of uncertainty in GPP estimation both in the simulations and empirical data products. The tropical forest uncertainty is most strongly associated with shortwave radiation and precipitation forcing, of which climate data range contributes higher to overall uncertainty than apparent model sensitivity to forcing. Globally, precipitation dominates the climate induced uncertainty over nearly half of the vegetated land area, which is mainly due to climate data range and less so due to the apparent model sensitivity. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than apparent model sensitivity to forcing. Our study highlights the need to better constrain tropical climate, and demonstrates that uncertainty caused by climatic forcing data must be considered when comparing and evaluating carbon cycle model results and empirical datasets.
The Agricultural Model Intercomparison and Improvement Project (AgMIP): Protocols and Pilot Studies
NASA Technical Reports Server (NTRS)
Rosenzweig, C.; Jones, J. W.; Hatfield, J. L.; Ruane, A. C.; Boote, K. J.; Thorburn, P.; Antle, J. M.; Nelson, G. C.; Porter, C.; Janssen, S.;
2012-01-01
The Agricultural Model Intercomparison and Improvement Project (AgMIP) is a major international effort linking the climate, crop, and economic modeling communities with cutting-edge information technology to produce improved crop and economic models and the next generation of climate impact projections for the agricultural sector. The goals of AgMIP are to improve substantially the characterization of world food security due to climate change and to enhance adaptation capacity in both developing and developed countries. Analyses of the agricultural impacts of climate variability and change require a transdisciplinary effort to consistently link state-of-the-art climate scenarios to crop and economic models. Crop model outputs are aggregated as inputs to regional and global economic models to determine regional vulnerabilities, changes in comparative advantage, price effects, and potential adaptation strategies in the agricultural sector. Climate, Crop Modeling, Economics, and Information Technology Team Protocols are presented to guide coordinated climate, crop modeling, economics, and information technology research activities around the world, along with AgMIP Cross-Cutting Themes that address uncertainty, aggregation and scaling, and the development of Representative Agricultural Pathways (RAPs) to enable testing of climate change adaptations in the context of other regional and global trends. The organization of research activities by geographic region and specific crops is described, along with project milestones. Pilot results demonstrate AgMIP's role in assessing climate impacts with explicit representation of uncertainties in climate scenarios and simulations using crop and economic models. An intercomparison of wheat model simulations near Obregón, Mexico reveals inter-model differences in yield sensitivity to [CO2] with model uncertainty holding approximately steady as concentrations rise, while uncertainty related to choice of crop model increases with rising temperatures. Wheat model simulations with midcentury climate scenarios project a slight decline in absolute yields that is more sensitive to selection of crop model than to global climate model, emissions scenario, or climate scenario downscaling method. A comparison of regional and national-scale economic simulations finds a large sensitivity of projected yield changes to the simulations' resolved scales. Finally, a global economic model intercomparison example demonstrates that improvements in the understanding of agriculture futures arise from integration of the range of uncertainty in crop, climate, and economic modeling results in multi-model assessments.
A transient stochastic weather generator incorporating climate model uncertainty
NASA Astrophysics Data System (ADS)
Glenis, Vassilis; Pinamonti, Valentina; Hall, Jim W.; Kilsby, Chris G.
2015-11-01
Stochastic weather generators (WGs), which provide long synthetic time series of weather variables such as rainfall and potential evapotranspiration (PET), have found widespread use in water resources modelling. When conditioned upon the changes in climatic statistics (change factors, CFs) predicted by climate models, WGs provide a useful tool for climate impacts assessment and adaption planning. The latest climate modelling exercises have involved large numbers of global and regional climate models integrations, designed to explore the implications of uncertainties in the climate model formulation and parameter settings: so called 'perturbed physics ensembles' (PPEs). In this paper we show how these climate model uncertainties can be propagated through to impact studies by testing multiple vectors of CFs, each vector derived from a different sample from a PPE. We combine this with a new methodology to parameterise the projected time-evolution of CFs. We demonstrate how, when conditioned upon these time-dependent CFs, an existing, well validated and widely used WG can be used to generate non-stationary simulations of future climate that are consistent with probabilistic outputs from the Met Office Hadley Centre's Perturbed Physics Ensemble. The WG enables extensive sampling of natural variability and climate model uncertainty, providing the basis for development of robust water resources management strategies in the context of a non-stationary climate.
[Lake eutrophication modeling in considering climatic factors change: a review].
Su, Jie-Qiong; Wang, Xuan; Yang, Zhi-Feng
2012-11-01
Climatic factors are considered as the key factors affecting the trophic status and its process in most lakes. Under the background of global climate change, to incorporate the variations of climatic factors into lake eutrophication models could provide solid technical support for the analysis of the trophic evolution trend of lake and the decision-making of lake environment management. This paper analyzed the effects of climatic factors such as air temperature, precipitation, sunlight, and atmosphere on lake eutrophication, and summarized the research results about the lake eutrophication modeling in considering in considering climatic factors change, including the modeling based on statistical analysis, ecological dynamic analysis, system analysis, and intelligent algorithm. The prospective approaches to improve the accuracy of lake eutrophication modeling with the consideration of climatic factors change were put forward, including 1) to strengthen the analysis of the mechanisms related to the effects of climatic factors change on lake trophic status, 2) to identify the appropriate simulation models to generate several scenarios under proper temporal and spatial scales and resolutions, and 3) to integrate the climatic factors change simulation, hydrodynamic model, ecological simulation, and intelligent algorithm into a general modeling system to achieve an accurate prediction of lake eutrophication under climatic change.
Managing Critical Materials with a Technology-Specific Stocks and Flows Model
2013-01-01
The transition to low carbon infrastructure systems required to meet climate change mitigation targets will involve an unprecedented roll-out of technologies reliant upon materials not previously widespread in infrastructure. Many of these materials (including lithium and rare earth metals) are at risk of supply disruption. To ensure the future sustainability and resilience of infrastructure, circular economy policies must be crafted to manage these critical materials effectively. These policies can only be effective if supported by an understanding of the material demands of infrastructure transition and what reuse and recycling options are possible given the future availability of end-of-life stocks. This Article presents a novel, enhanced stocks and flows model for the dynamic assessment of material demands resulting from infrastructure transitions. By including a hierarchical, nested description of infrastructure technologies, their components, and the materials they contain, this model can be used to quantify the effectiveness of recovery at both a technology remanufacturing and reuse level and a material recycling level. The model’s potential is demonstrated on a case study on the roll-out of electric vehicles in the UK forecast by UK Department of Energy and Climate Change scenarios. The results suggest policy action should be taken to ensure Li-ion battery recycling infrastructure is in place by 2025 and NdFeB motor magnets should be designed for reuse. This could result in a reduction in primary demand for lithium of 40% and neodymium of 70%. PMID:24328245
Uncertainty and the Social Cost of Methane Using Bayesian Constrained Climate Models
NASA Astrophysics Data System (ADS)
Errickson, F. C.; Anthoff, D.; Keller, K.
2016-12-01
Social cost estimates of greenhouse gases are important for the design of sound climate policies and are also plagued by uncertainty. One major source of uncertainty stems from the simplified representation of the climate system used in the integrated assessment models that provide these social cost estimates. We explore how uncertainty over the social cost of methane varies with the way physical processes and feedbacks in the methane cycle are modeled by (i) coupling three different methane models to a simple climate model, (ii) using MCMC to perform a Bayesian calibration of the three coupled climate models that simulates direct sampling from the joint posterior probability density function (pdf) of model parameters, and (iii) producing probabilistic climate projections that are then used to calculate the Social Cost of Methane (SCM) with the DICE and FUND integrated assessment models. We find that including a temperature feedback in the methane cycle acts as an additional constraint during the calibration process and results in a correlation between the tropospheric lifetime of methane and several climate model parameters. This correlation is not seen in the models lacking this feedback. Several of the estimated marginal pdfs of the model parameters also exhibit different distributional shapes and expected values depending on the methane model used. As a result, probabilistic projections of the climate system out to the year 2300 exhibit different levels of uncertainty and magnitudes of warming for each of the three models under an RCP8.5 scenario. We find these differences in climate projections result in differences in the distributions and expected values for our estimates of the SCM. We also examine uncertainty about the SCM by performing a Monte Carlo analysis using a distribution for the climate sensitivity while holding all other climate model parameters constant. Our SCM estimates using the Bayesian calibration are lower and exhibit less uncertainty about extremely high values in the right tail of the distribution compared to the Monte Carlo approach. This finding has important climate policy implications and suggests previous work that accounts for climate model uncertainty by only varying the climate sensitivity parameter may overestimate the SCM.
The future of energy and climate
Steinberger, Jack
2018-04-26
The talk will review some of the basic facts about the history and present status of the use of energy and its climatic consequences. It is clear that the world will have to change its way of energy production, the sooner the better. Because of the difficulty of storing electric energy, by far the best energy source for the future is thermal solar from the deserts, with overnight thermal storage. I will give some description of the present status of the technologies involved and end up with a pilot project for Europe and North Africa.
The Swedish Regional Climate Modelling Programme, SWECLIM: a review.
Rummukainen, Markku; Bergström, Sten; Persson, Gunn; Rodhe, Johan; Tjernström, Michael
2004-06-01
The Swedish Regional Climate Modelling Programme, SWECLIM, was a 6.5-year national research network for regional climate modeling, regional climate change projections and hydrological impact assessment and information to a wide range of stakeholders. Most of the program activities focussed on the regional climate system of Northern Europe. This led to the establishment of an advanced, coupled atmosphere-ocean-hydrology regional climate model system, a suite of regional climate change projections and progress on relevant data and process studies. These were, in turn, used for information and educational purposes, as a starting point for impact analyses on different societal sectors and provided contributions also to international climate research.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gao, W.
High-resolution satellite data provide detailed, quantitative descriptions of land surface characteristics over large areas so that objective scale linkage becomes feasible. With the aid of satellite data, Sellers et al. and Wood and Lakshmi examined the linearity of processes scaled up from 30 m to 15 km. If the phenomenon is scale invariant, then the aggregated value of a function or flux is equivalent to the function computed from aggregated values of controlling variables. The linear relation may be realistic for limited land areas having no large surface contrasts to cause significant horizontal exchange. However, for areas with sharp surfacemore » contrasts, horizontal exchange and different dynamics in the atmospheric boundary may induce nonlinear interactions, such as at interfaces of land-water, forest-farm land, and irrigated crops-desert steppe. The linear approach, however, represents the simplest scenario, and is useful for developing an effective scheme for incorporating subgrid land surface processes into large-scale models. Our studies focus on coupling satellite data and ground measurements with a satellite-data-driven land surface model to parameterize surface fluxes for large-scale climate models. In this case study, we used surface spectral reflectance data from satellite remote sensing to characterize spatial and temporal changes in vegetation and associated surface parameters in an area of about 350 {times} 400 km covering the southern Great Plains (SGP) Cloud and Radiation Testbed (CART) site of the US Department of Energy`s Atmospheric Radiation Measurement (ARM) Program.« less