External validity of a generic safety climate scale for lone workers across different industries and companies.

PubMed

Lee, Jin; Huang, Yueng-hsiang; Robertson, Michelle M; Murphy, Lauren A; Garabet, Angela; Chang, Wen-Ruey

2014-02-01

The goal of this study was to examine the external validity of a 12-item generic safety climate scale for lone workers in order to evaluate the appropriateness of generalized use of the scale in the measurement of safety climate across various lone work settings. External validity evidence was established by investigating the measurement equivalence (ME) across different industries and companies. Confirmatory factor analysis (CFA)-based and item response theory (IRT)-based perspectives were adopted to examine the ME of the generic safety climate scale for lone workers across 11 companies from the trucking, electrical utility, and cable television industries. Fairly strong evidence of ME was observed for both organization- and group-level generic safety climate sub-scales. Although significant invariance was observed in the item intercepts across the different lone work settings, absolute model fit indices remained satisfactory in the most robust step of CFA-based ME testing. IRT-based ME testing identified only one differentially functioning item from the organization-level generic safety climate sub-scale, but its impact was minimal and strong ME was supported. The generic safety climate scale for lone workers reported good external validity and supported the presence of a common feature of safety climate among lone workers. The scale can be used as an effective safety evaluation tool in various lone work situations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs: Supplemental Material

NASA Technical Reports Server (NTRS)

Glotter, Michael J.; Ruane, Alex C.; Moyer, Elisabeth J.; Elliott, Joshua W.

2015-01-01

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled and observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources reanalysis, reanalysis that is bias corrected with observed climate, and a control dataset and compared with observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by non-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. Some issues persist for all choices of climate inputs: crop yields appear to be oversensitive to precipitation fluctuations but under sensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves.

Evaluating the sensitivity of agricultural model performance to different climate inputs

PubMed Central

Glotter, Michael J.; Moyer, Elisabeth J.; Ruane, Alex C.; Elliott, Joshua W.

2017-01-01

Projections of future food production necessarily rely on models, which must themselves be validated through historical assessments comparing modeled to observed yields. Reliable historical validation requires both accurate agricultural models and accurate climate inputs. Problems with either may compromise the validation exercise. Previous studies have compared the effects of different climate inputs on agricultural projections, but either incompletely or without a ground truth of observed yields that would allow distinguishing errors due to climate inputs from those intrinsic to the crop model. This study is a systematic evaluation of the reliability of a widely-used crop model for simulating U.S. maize yields when driven by multiple observational data products. The parallelized Decision Support System for Agrotechnology Transfer (pDSSAT) is driven with climate inputs from multiple sources – reanalysis, reanalysis bias-corrected with observed climate, and a control dataset – and compared to observed historical yields. The simulations show that model output is more accurate when driven by any observation-based precipitation product than when driven by un-bias-corrected reanalysis. The simulations also suggest, in contrast to previous studies, that biased precipitation distribution is significant for yields only in arid regions. However, some issues persist for all choices of climate inputs: crop yields appear oversensitive to precipitation fluctuations but undersensitive to floods and heat waves. These results suggest that the most important issue for agricultural projections may be not climate inputs but structural limitations in the crop models themselves. PMID:29097985

Validation of a model with climatic and flow scenario analysis: case of Lake Burrumbeet in southeastern Australia.

PubMed

Yihdego, Yohannes; Webb, John

2016-05-01

Forecast evaluation is an important topic that addresses the development of reliable hydrological probabilistic forecasts, mainly through the use of climate uncertainties. Often, validation has no place in hydrology for most of the times, despite the parameters of a model are uncertain. Similarly, the structure of the model can be incorrectly chosen. A calibrated and verified dynamic hydrologic water balance spreadsheet model has been used to assess the effect of climate variability on Lake Burrumbeet, southeastern Australia. The lake level has been verified to lake level, lake volume, lake surface area, surface outflow and lake salinity. The current study aims to increase lake level confidence model prediction through historical validation for the year 2008-2013, under different climatic scenario. Based on the observed climatic condition (2008-2013), it fairly matches with a hybridization of scenarios, being the period interval (2008-2013), corresponds to both dry and wet climatic condition. Besides to the hydrologic stresses uncertainty, uncertainty in the calibrated model is among the major drawbacks involved in making scenario simulations. In line with this, the uncertainty in the calibrated model was tested using sensitivity analysis and showed that errors in the model can largely be attributed to erroneous estimates of evaporation and rainfall, and surface inflow to a lesser. The study demonstrates that several climatic scenarios should be analysed, with a combination of extreme climate, stream flow and climate change instead of one assumed climatic sequence, to improve climate variability prediction in the future. Performing such scenario analysis is a valid exercise to comprehend the uncertainty with the model structure and hydrology, in a meaningful way, without missing those, even considered as less probable, ultimately turned to be crucial for decision making and will definitely increase the confidence of model prediction for management of the water resources.

Workforce Perceptions of Hospital Safety Culture: Development and Validation of the Patient Safety Climate in Healthcare Organizations Survey

PubMed Central

Singer, Sara; Meterko, Mark; Baker, Laurence; Gaba, David; Falwell, Alyson; Rosen, Amy

2007-01-01

Objective To describe the development of an instrument for assessing workforce perceptions of hospital safety culture and to assess its reliability and validity. Data Sources/Study Setting Primary data collected between March 2004 and May 2005. Personnel from 105 U.S. hospitals completed a 38-item paper and pencil survey. We received 21,496 completed questionnaires, representing a 51 percent response rate. Study Design Based on review of existing safety climate surveys, we developed a list of key topics pertinent to maintaining a culture of safety in high-reliability organizations. We developed a draft questionnaire to address these topics and pilot tested it in four preliminary studies of hospital personnel. We modified the questionnaire based on experience and respondent feedback, and distributed the revised version to 42,249 hospital workers. Data Collection We randomly divided respondents into derivation and validation samples. We applied exploratory factor analysis to responses in the derivation sample. We used those results to create scales in the validation sample, which we subjected to multitrait analysis (MTA). Principal Findings We identified nine constructs, three organizational factors, two unit factors, three individual factors, and one additional factor. Constructs demonstrated substantial convergent and discriminant validity in the MTA. Cronbach's α coefficients ranged from 0.50 to 0.89. Conclusions It is possible to measure key salient features of hospital safety climate using a valid and reliable 38-item survey and appropriate hospital sample sizes. This instrument may be used in further studies to better understand the impact of safety climate on patient safety outcomes. PMID:17850530

The Psychometric Properties of the Perceived Motivational Climate in Exercise Questionnaire

ERIC Educational Resources Information Center

Brown, Theresa C.; Fry, Mary D.; Little, Todd D.

2013-01-01

Given the potential benefits of understanding how climate may influence individuals' motivational outcomes, there exists a need for instrumentation measuring exercise setting climates. The purpose of this study was to validate further the psychometric properties of the Perceived Motivational Climate in Exercise Questionnaire (Huddleston, Fry &…

The Meriden School Climate Survey-Student Version: Preliminary Evidence of Reliability and Validity

ERIC Educational Resources Information Center

Gage, Nicholas A.; Larson, Alvin; Chafouleas, Sandra M.

2016-01-01

School climate has been linked with myriad positive student outcomes and the measurement of school climate is widely advocated at the national and state level. However, districts have little guidance about how to define and measure school climate. This study examines the psychometric properties of a district-developed school climate measure that…

Climate Change Impacts for Conterminous USA: An Integrated Assessment Part 2. Models and Validation

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

Thomson, Allison M.; Rosenberg, Norman J.; Izaurralde, R Cesar C.

As CO{sub 2} and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how a changing climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using a suite of climate change predictions from General Circulation Models (GCMs) as described in Part 1. Here we describe the agriculture model EPIC and the HUMUS water model and validate them with historical crop yields and streamflow data. We compare EPIC simulated grainmore » and forage crop yields with historical crop yields from the US Department of Agriculture and find an acceptable level of agreement for this study. The validation of HUMUS simulated streamflow with estimates of natural streamflow from the US Geological Survey shows that the model is able to reproduce significant relationships and capture major trends.« less

School Climate: Historical Review, Instrument Development, and School Assessment

ERIC Educational Resources Information Center

Zullig, Keith J.; Koopman, Tommy M.; Patton, Jon M.; Ubbes, Valerie A.

2010-01-01

This study's purpose is to examine the existing school climate literature in an attempt to constitute its definition from a historical context and to create a valid and reliable student-reported school climate instrument. Five historically common school climate domains and five measurement tools were identified, combined, and previewed by the…

Multilevel Factor Structure, Concurrent Validity, and Test-Retest Reliability of the High School Teacher Version of the Authoritative School Climate Survey

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2016-01-01

Although school climate has long been recognized as an important factor in the school improvement process, there are few psychometrically supported measures based on teacher perspectives. The current study replicated and extended the factor structure, concurrent validity, and test-retest reliability of the teacher version of the Authoritative…

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

PubMed

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

2016-09-01

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

A practical scale for Multi-Faceted Organizational Health Climate Assessment.

PubMed

Zweber, Zandra M; Henning, Robert A; Magley, Vicki J

2016-04-01

The current study sought to develop a practical scale to measure 3 facets of workplace health climate from the employee perspective as an important component of a healthy organization. The goal was to create a short, usable yet comprehensive scale that organizations and occupational health professionals could use to determine if workplace health interventions were needed. The proposed Multi-faceted Organizational Health Climate Assessment (MOHCA) scale assesses facets that correspond to 3 organizational levels: (a) workgroup, (b) supervisor, and (c) organization. Ten items were developed and tested on 2 distinct samples, 1 cross-organization and 1 within-organization. Exploratory and confirmatory factor analyses yielded a 9-item, hierarchical 3-factor structure. Tests confirmed MOHCA has convergent validity with related constructs, such as perceived organizational support and supervisor support, as well as discriminant validity with safety climate. Lastly, criterion-related validity was found between MOHCA and health-related outcomes. The multi-faceted nature of MOHCA provides a scale that has face validity and can be easily translated into practice, offering a means for diagnosing the shortcomings of an organization or workgroup's health climate to better plan health and well-being interventions. (c) 2016 APA, all rights reserved).

Validating the Implementation Climate Scale (ICS) in Child Welfare Organizations

PubMed Central

Ehrhart, Mark G.; Torres, Elisa M.; Wright, Lisa A.; Martinez, Sandra Y.; Aarons, Gregory A.

2015-01-01

There is increasing emphasis on the use of evidence-based practices (EBPs) in child welfare settings and growing recognition of the importance of the organizational environment, and the organization’s climate in particular, for how employees perceive and support EBP implementation. Recently, Ehrhart, Aarons, and Farahnak (2014) reported on the development and validation of a measure of EBP implementation climate, the Implementation Climate Scale (ICS), in a sample of mental health clinicians. The ICS consists of 18 items and measures six critical dimensions of implementation climate: focus on EBP, educational support for EBP, recognition for EBP, rewards for EBP, selection or EBP, and selection for openness. The goal of the current study is to extend this work by providing evidence for the factor structure, reliability, and validity of the ICS in a sample of child welfare service providers. Survey data were collected from 215 child welfare providers across three states, 12 organizations, and 43 teams. Confirmatory factor analysis demonstrated good fit to the six-factor model and the alpha reliabilities for the overall measure and its subscales was acceptable. In addition, there was general support for the invariance of the factor structure across the child welfare and mental health sectors. In conclusion, this study provides evidence for the factor structure, reliability, and validity of the ICS measure for use in child welfare service organizations. PMID:26563643

Validating the Implementation Climate Scale (ICS) in child welfare organizations.

PubMed

Ehrhart, Mark G; Torres, Elisa M; Wright, Lisa A; Martinez, Sandra Y; Aarons, Gregory A

2016-03-01

There is increasing emphasis on the use of evidence-based practices (EBPs) in child welfare settings and growing recognition of the importance of the organizational environment, and the organization's climate in particular, for how employees perceive and support EBP implementation. Recently, Ehrhart, Aarons, and Farahnak (2014) reported on the development and validation of a measure of EBP implementation climate, the Implementation Climate Scale (ICS), in a sample of mental health clinicians. The ICS consists of 18 items and measures six critical dimensions of implementation climate: focus on EBP, educational support for EBP, recognition for EBP, rewards for EBP, selection or EBP, and selection for openness. The goal of the current study is to extend this work by providing evidence for the factor structure, reliability, and validity of the ICS in a sample of child welfare service providers. Survey data were collected from 215 child welfare providers across three states, 12 organizations, and 43 teams. Confirmatory factor analysis demonstrated good fit to the six-factor model and the alpha reliabilities for the overall measure and its subscales was acceptable. In addition, there was general support for the invariance of the factor structure across the child welfare and mental health sectors. In conclusion, this study provides evidence for the factor structure, reliability, and validity of the ICS measure for use in child welfare service organizations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Workforce perceptions of hospital safety culture: development and validation of the patient safety climate in healthcare organizations survey.

PubMed

Singer, Sara; Meterko, Mark; Baker, Laurence; Gaba, David; Falwell, Alyson; Rosen, Amy

2007-10-01

To describe the development of an instrument for assessing workforce perceptions of hospital safety culture and to assess its reliability and validity. Primary data collected between March 2004 and May 2005. Personnel from 105 U.S. hospitals completed a 38-item paper and pencil survey. We received 21,496 completed questionnaires, representing a 51 percent response rate. Based on review of existing safety climate surveys, we developed a list of key topics pertinent to maintaining a culture of safety in high-reliability organizations. We developed a draft questionnaire to address these topics and pilot tested it in four preliminary studies of hospital personnel. We modified the questionnaire based on experience and respondent feedback, and distributed the revised version to 42,249 hospital workers. We randomly divided respondents into derivation and validation samples. We applied exploratory factor analysis to responses in the derivation sample. We used those results to create scales in the validation sample, which we subjected to multitrait analysis (MTA). We identified nine constructs, three organizational factors, two unit factors, three individual factors, and one additional factor. Constructs demonstrated substantial convergent and discriminant validity in the MTA. Cronbach's alpha coefficients ranged from 0.50 to 0.89. It is possible to measure key salient features of hospital safety climate using a valid and reliable 38-item survey and appropriate hospital sample sizes. This instrument may be used in further studies to better understand the impact of safety climate on patient safety outcomes.

Multilevel model of safety climate for furniture industries.

PubMed

Rodrigues, Matilde A; Arezes, Pedro M; Leão, Celina P

2015-01-01

Furniture companies can analyze their safety status using quantitative measures. However, the data needed are not always available and the number of accidents is under-reported. Safety climate scales may be an alternative. However, there are no validated Portuguese scales that account for the specific attributes of the furniture sector. The current study aims to develop and validate an instrument that uses a multilevel structure to measure the safety climate of the Portuguese furniture industry. The Safety Climate in Wood Industries (SCWI) model was developed and applied to the safety climate analysis using three different scales: organizational, group and individual. A multilevel exploratory factor analysis was performed to analyze the factorial structure. The studied companies' safety conditions were also analyzed. Different factorial structures were found between and within levels. In general, the results show the presence of a group-level safety climate. The scores of safety climates are directly and positively related to companies' safety conditions; the organizational scale is the one that best reflects the actual safety conditions. The SCWI instrument allows for the identification of different safety climates in groups that comprise the same furniture company and it seems to reflect those groups' safety conditions. The study also demonstrates the need for a multilevel analysis of the studied instrument.

Development and initial validation of an Aviation Safety Climate Scale.

PubMed

Evans, Bronwyn; Glendon, A Ian; Creed, Peter A

2007-01-01

A need was identified for a consistent set of safety climate factors to provide a basis for aviation industry benchmarking. Six broad safety climate themes were identified from the literature and consultations with industry safety experts. Items representing each of the themes were prepared and administered to 940 Australian commercial pilots. Data from half of the sample (N=468) were used in an exploratory factor analysis that produced a 3-factor model of Management commitment and communication, Safety training and equipment, and Maintenance. A confirmatory factor analysis on the remaining half of the sample showed the 3-factor model to be an adequate fit to the data. The results of this study have produced a scale of safety climate for aviation that is both reliable and valid. This study developed a tool to assess the level of perceived safety climate, specifically of pilots, but may also, with minor modifications, be used to assess other groups' perceptions of safety climate.

Cross-cultural adaptation and validation of the teamwork climate scale

PubMed Central

Silva, Mariana Charantola; Peduzzi, Marina; Sangaleti, Carine Teles; da Silva, Dirceu; Agreli, Heloise Fernandes; West, Michael A; Anderson, Neil R

2016-01-01

ABSTRACT OBJECTIVE To adapt and validate the Team Climate Inventory scale, of teamwork climate measurement, for the Portuguese language, in the context of primary health care in Brazil. METHODS Methodological study with quantitative approach of cross-cultural adaptation (translation, back-translation, synthesis, expert committee, and pretest) and validation with 497 employees from 72 teams of the Family Health Strategy in the city of Campinas, SP, Southeastern Brazil. We verified reliability by the Cronbach’s alpha, construct validity by the confirmatory factor analysis with SmartPLS software, and correlation by the job satisfaction scale. RESULTS We problematized the overlap of items 9, 11, and 12 of the “participation in the team” factor and the “team goals” factor regarding its definition. The validation showed no overlapping of items and the reliability ranged from 0.92 to 0.93. The confirmatory factor analysis indicated suitability of the proposed model with distribution of the 38 items in the four factors. The correlation between teamwork climate and job satisfaction was significant. CONCLUSIONS The version of the scale in Brazilian Portuguese was validated and can be used in the context of primary health care in the Country, constituting an adequate tool for the assessment and diagnosis of teamwork. PMID:27556966

Validation of an organizational communication climate assessment toolkit.

PubMed

Wynia, Matthew K; Johnson, Megan; McCoy, Thomas P; Griffin, Leah Passmore; Osborn, Chandra Y

2010-01-01

Effective communication is critical to providing quality health care and can be affected by a number of modifiable organizational factors. The authors performed a prospective multisite validation study of an organizational communication climate assessment tool in 13 geographically and ethnically diverse health care organizations. Communication climate was measured across 9 discrete domains. Patient and staff surveys with matched items in each domain were developed using a national consensus process, which then underwent psychometric field testing and assessment of domain coherence. The authors found meaningful within-site and between-site performance score variability in all domains. In multivariable models, most communication domains were significant predictors of patient-reported quality of care and trust. The authors conclude that these assessment tools provide a valid empirical assessment of organizational communication climate in 9 domains. Assessment results may be useful to track organizational performance, to benchmark, and to inform tailored quality improvement interventions.

A global validation of ERA-Interim integrated water vapor estimates using ground-based GNSS observations

NASA Astrophysics Data System (ADS)

Ahmed, F.; Dousa, J.; Hunegnaw, A.; Teferle, F. N.; Bingley, R.

2017-12-01

Integrated water vapor (IWV) derived from climate reanalysis models, such as the European Centre for Medium-range Weather Forecasts (ECMWF) ReAnalysis-Interim (ERA-Interim), is widely used in many atmospheric applications. Therefore, it is of interest to assess the quality of this reanalysis product using available observations. Observations from Global Navigation Satellite Systems (GNSS) are, as of now, available for a period of over 2 decades and their global availability makes it possible to validate the IWV obtained from climate reanalysis models in different geographical and climatic regions. In this study, primarily, three 5-year long homogeneously reprocessed GNSS-derived IWV datasets containing over 400 globally distributed ground-based GNSS stations have been used to validate the IWV estimates obtained from the ERA-Interim climate reanalysis model in 25 different climate zones. The IWV from ERA-Interim has been obtained by vertically integrating the specific humidity at all model levels above the locations of GNSS stations. It has been studied how the difference between the ERA-Interim IWV and the GNSS-derived IWV varies with respect to the different climate zones as well as with respect to the difference in the model orography and latitude. The results show a dependence of the ability of ERA-Interim to model the IWV on difference in climate types and latitude. This dependence, however, is dictated by the concentration of water vapor in different climate zones and at different latitudes. Furthermore, as a secondary focus of this study, the weighted mean atmospheric temperature (Tm) obtained from ERA-Interim has been compared to its equivalent obtained using two widely used approximations globally.

Simulation of Climate Change Impacts on Wheat-Fallow Cropping Systems

USDA-ARS?s Scientific Manuscript database

Agricultural system simulation models are predictive tools for assessing climate change impacts on crop production. In this study, RZWQM2 that contains the DSSAT 4.0-CERES model was evaluated for simulating climate change impacts on wheat growth. The model was calibrated and validated using data fro...

Global precipitation measurements for validating climate models

NASA Astrophysics Data System (ADS)

Tapiador, F. J.; Navarro, A.; Levizzani, V.; García-Ortega, E.; Huffman, G. J.; Kidd, C.; Kucera, P. A.; Kummerow, C. D.; Masunaga, H.; Petersen, W. A.; Roca, R.; Sánchez, J.-L.; Tao, W.-K.; Turk, F. J.

2017-11-01

The advent of global precipitation data sets with increasing temporal span has made it possible to use them for validating climate models. In order to fulfill the requirement of global coverage, existing products integrate satellite-derived retrievals from many sensors with direct ground observations (gauges, disdrometers, radars), which are used as reference for the satellites. While the resulting product can be deemed as the best-available source of quality validation data, awareness of the limitations of such data sets is important to avoid extracting wrong or unsubstantiated conclusions when assessing climate model abilities. This paper provides guidance on the use of precipitation data sets for climate research, including model validation and verification for improving physical parameterizations. The strengths and limitations of the data sets for climate modeling applications are presented, and a protocol for quality assurance of both observational databases and models is discussed. The paper helps elaborating the recent IPCC AR5 acknowledgment of large observational uncertainties in precipitation observations for climate model validation.

Developing and Validating a New Classroom Climate Observation Assessment Tool

PubMed Central

Leff, Stephen S.; Thomas, Duane E.; Shapiro, Edward S.; Paskewich, Brooke; Wilson, Kim; Necowitz-Hoffman, Beth; Jawad, Abbas F.

2011-01-01

The climate of school classrooms, shaped by a combination of teacher practices and peer processes, is an important determinant for children’s psychosocial functioning and is a primary factor affecting bullying and victimization. Given that there are relatively few theoretically-grounded and validated assessment tools designed to measure the social climate of classrooms, our research team developed an observation tool through participatory action research (PAR). This article details how the assessment tool was designed and preliminarily validated in 18 third-, fourth-, and fifth-grade classrooms in a large urban public school district. The goals of this study are to illustrate the feasibility of a PAR paradigm in measurement development, ascertain the psychometric properties of the assessment tool, and determine associations with different indices of classroom levels of relational and physical aggression. PMID:21643447

Developing and Validating a New Classroom Climate Observation Assessment Tool.

PubMed

Leff, Stephen S; Thomas, Duane E; Shapiro, Edward S; Paskewich, Brooke; Wilson, Kim; Necowitz-Hoffman, Beth; Jawad, Abbas F

2011-01-01

The climate of school classrooms, shaped by a combination of teacher practices and peer processes, is an important determinant for children's psychosocial functioning and is a primary factor affecting bullying and victimization. Given that there are relatively few theoretically-grounded and validated assessment tools designed to measure the social climate of classrooms, our research team developed an observation tool through participatory action research (PAR). This article details how the assessment tool was designed and preliminarily validated in 18 third-, fourth-, and fifth-grade classrooms in a large urban public school district. The goals of this study are to illustrate the feasibility of a PAR paradigm in measurement development, ascertain the psychometric properties of the assessment tool, and determine associations with different indices of classroom levels of relational and physical aggression.

The predictive validity of safety climate.

PubMed

Johnson, Stephen E

2007-01-01

Safety professionals have increasingly turned their attention to social science for insight into the causation of industrial accidents. One social construct, safety climate, has been examined by several researchers [Cooper, M. D., & Phillips, R. A. (2004). Exploratory analysis of the safety climate and safety behavior relationship. Journal of Safety Research, 35(5), 497-512; Gillen, M., Baltz, D., Gassel, M., Kirsch, L., & Vacarro, D. (2002). Perceived safety climate, job Demands, and coworker support among union and nonunion injured construction workers. Journal of Safety Research, 33(1), 33-51; Neal, A., & Griffin, M. A. (2002). Safety climate and safety behaviour. Australian Journal of Management, 27, 66-76; Zohar, D. (2000). A group-level model of safety climate: Testing the effect of group climate on microaccidents in manufacturing jobs. Journal of Applied Psychology, 85(4), 587-596; Zohar, D., & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group-level climates. Journal of Applied Psychology, 90(4), 616-628] who have documented its importance as a factor explaining the variation of safety-related outcomes (e.g., behavior, accidents). Researchers have developed instruments for measuring safety climate and have established some degree of psychometric reliability and validity. The problem, however, is that predictive validity has not been firmly established, which reduces the credibility of safety climate as a meaningful social construct. The research described in this article addresses this problem and provides additional support for safety climate as a viable construct and as a predictive indicator of safety-related outcomes. This study used 292 employees at three locations of a heavy manufacturing organization to complete the 16 item Zohar Safety Climate Questionnaire (ZSCQ) [Zohar, D., & Luria, G. (2005). A multilevel model of safety climate: Cross-level relationships between organization and group-level climates. Journal of Applied Psychology, 90(4), 616-628]. In addition, safety behavior and accident experience data were collected for 5 months following the survey and were statistically analyzed (structural equation modeling, confirmatory factor analysis, exploratory factor analysis, etc.) to identify correlations, associations, internal consistency, and factorial structures. Results revealed that the ZSCQ: (a) was psychometrically reliable and valid, (b) served as an effective predictor of safety-related outcomes (behavior and accident experience), and (c) could be trimmed to an 11 item survey with little loss of explanatory power. Practitioners and researchers can use the ZSCQ with reasonable certainty of the questionnaire's reliability and validity. This provides a solid foundation for the development of meaningful organizational interventions and/or continued research into social factors affecting industrial accident experience.

Validation of Nurse Practitioner Primary Care Organizational Climate Questionnaire: A New Tool to Study Nurse Practitioner Practice Settings.

PubMed

Poghosyan, Lusine; Chaplin, William F; Shaffer, Jonathan A

2017-04-01

Favorable organizational climate in primary care settings is necessary to expand the nurse practitioner (NP) workforce and promote their practice. Only one NP-specific tool, the Nurse Practitioner Primary Care Organizational Climate Questionnaire (NP-PCOCQ), measures NP organizational climate. We confirmed NP-PCOCQ's factor structure and established its predictive validity. A crosssectional survey design was used to collect data from 314 NPs in Massachusetts in 2012. Confirmatory factor analysis and regression models were used. The 4-factor model characterized NP-PCOCQ. The NP-PCOCQ score predicted job satisfaction (beta = .36; p < .001) and intent to leave job (odds ratio = .28; p = .011). NP-PCOCQ can be used by researchers to produce new evidence and by administrators to assess organizational climate in their clinics. Further testing of NP-PCOCQ is needed.

The Development and Validation of the Online Learning Climate Scale (OLCS)

ERIC Educational Resources Information Center

Kaufmann, Renee; Sellnow, Deanna D.; Frisby, Brandi N.

2016-01-01

With the increasing popularity of online learning in higher education comes a need to examine students' perceptions about classroom climate in these environments. This two-part study proposes the online learning climate scale (OLCS) for doing so. Informed by both instructional communication and education, the scale consists of several variables…

Delineation of climate regions in the Northeastern United States

Treesearch

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...

Psychometric assessment of the Spiritual Climate Scale Arabic version for nurses in Saudi Arabia.

PubMed

Cruz, Jonas Preposi; Albaqawi, Hamdan Mohammad; Alharbi, Sami Melbes; Alicante, Jerico G; Vitorino, Luciano M; Abunab, Hamzeh Y

2017-12-07

To assess the psychometric properties of the Spiritual Climate Scale Arabic version for Saudi nurses. Evidence showed that a high level of spiritual climate in the workplace is associated with increased productivity and performance, enhanced emotional intelligence, organisational commitment and job satisfaction among nurses. A convenient sample of 165 Saudi nurses was surveyed in this descriptive, cross-sectional study. Cronbach's α and intraclass correlation coefficient of the 2 week test-retest scores were computed to establish reliability. Exploratory factor analysis was performed to support the validity of the Spiritual Climate Scale Arabic version. The Spiritual Climate Scale Arabic version manifested excellent content validity. Exploratory factor analysis supported a single factor with an explained variance of 73.2%. The Cronbach's α values of the scale ranged from .79 to .88, while the intraclass correlation coefficient value was .90. The perceived spiritual climate was associated with the respondents' hospital, gender, age and years of experience. Findings of this study support the sound psychometric properties of the Spiritual Climate Scale Arabic version. The Spiritual Climate Scale Arabic version can be used by nurse managers to assess the nurses' perception of the spiritual climate in any clinical area. This process can lead to spiritually centred interventions, thereby ensuring a clinical climate that accepts and respects different spiritual beliefs and practices. © 2017 John Wiley & Sons Ltd.

Development and Validation of an Instrument for Assessing Climate Change Knowledge and Perceptions: The Climate Stewardship Survey (CSS)

ERIC Educational Resources Information Center

Walker, Scott L.; McNeal, Karen S.

2013-01-01

The Climate Stewardship Survey (CSS) was developed to measure knowledge and perceptions of global climate change, while also considering information sources that respondents 'trust.' The CSS was drafted using a three-stage approach: development of salient scales, writing individual items, and field testing and analyses. Construct validity and…

Modelling exploration of non-stationary hydrological system

NASA Astrophysics Data System (ADS)

Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei

2015-04-01

Traditional hydrological modelling assumes that the catchment does not change with time (i.e., stationary conditions) which means the model calibrated for the historical period is valid for the future period. However, in reality, due to change of climate and catchment conditions this stationarity assumption may not be valid in the future. It is a challenge to make the hydrological model adaptive to the future climate and catchment conditions that are not observable at the present time. In this study a lumped conceptual rainfall-runoff model called IHACRES was applied to a catchment in southwest England. Long observation data from 1961 to 2008 were used and seasonal calibration (in this study only summer period is further explored because it is more sensitive to climate and land cover change than the other three seasons) has been done since there are significant seasonal rainfall patterns. We expect that the model performance can be improved by calibrating the model based on individual seasons. The data is split into calibration and validation periods with the intention of using the validation period to represent the future unobserved situations. The success of the non-stationary model will depend not only on good performance during the calibration period but also the validation period. Initially, the calibration is based on changing the model parameters with time. Methodology is proposed to adapt the parameters using the step forward and backward selection schemes. However, in the validation both the forward and backward multiple parameter changing models failed. One problem is that the regression with time is not reliable since the trend may not be in a monotonic linear relationship with time. The second issue is that changing multiple parameters makes the selection process very complex which is time consuming and not effective in the validation period. As a result, two new concepts are explored. First, only one parameter is selected for adjustment while the other parameters are set as constant. Secondly, regression is made against climate condition instead of against time. It has been found that such a new approach is very effective and this non-stationary model worked very well both in the calibration and validation period. Although the catchment is specific in southwest England and the data are for only the summer period, the methodology proposed in this study is general and applicable to other catchments. We hope this study will stimulate the hydrological community to explore a variety of sites so that valuable experiences and knowledge could be gained to improve our understanding of such a complex modelling issue in climate change impact assessment.

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…

Organisational Climate as a Predictor of Workforce Performance in the Malaysian Higher Education Institutions

ERIC Educational Resources Information Center

Musah, Mohammed Borhandden; Ali, Hairuddin Mohd; al-Hudawi, Shafeeq Hussain Vazhathodi; Tahir, Lokman Mohd; Binti Daud, Khadijah; Bin Said, Hamdan; Kamil, Naail Mohammed

2016-01-01

Purpose: This study aims to investigate whether organisational climate (OC) predicts academic staff performance at Malaysian higher education institutions (HEIs). The study equally aims at validating the psychometric properties of OC and workforce performance (WFP) constructs. Design/methodology/approach: Survey questionnaires were administered to…

Development of a Work Climate Scale in Emergency Health Services

PubMed Central

Sanduvete-Chaves, Susana; Lozano-Lozano, José A.; Chacón-Moscoso, Salvador; Holgado-Tello, Francisco P.

2018-01-01

An adequate work climate fosters productivity in organizations and increases employee satisfaction. Workers in emergency health services (EHS) have an extremely high degree of responsibility and consequent stress. Therefore, it is essential to foster a good work climate in this context. Despite this, scales with a full study of their psychometric properties (i.e., validity evidence based on test content, internal structure and relations to other variables, and reliability) are not available to measure work climate in EHS specifically. For this reason, our objective was to develop a scale to measure the quality of work climates in EHS. We carried out three studies. In Study 1, we used a mixed-method approach to identify the latent conceptual structure of the construct work climate. Thus, we integrated the results found in (a) a previous study, where a content analysis of seven in-depth interviews obtained from EHS professionals in two hospitals in Gibraltar Countryside County was carried out; and (b) the factor analysis of the responses given by 113 EHS professionals from these same centers to 18 items that measured the work climate in health organizations. As a result, we obtained 56 items grouped into four factors (work satisfaction, productivity/achievement of aims, interpersonal relationships, and performance at work). In Study 2, we presented validity evidence based on test content through experts' judgment. Fourteen experts from the methodology and health fields evaluated the representativeness, utility, and feasibility of each of the 56 items with respect to their factor (theoretical dimension). Forty items met the inclusion criterion, which was to obtain an Osterlind index value greater than or equal to 0.5 in the three aspects assessed. In Study 3, 201 EHS professionals from the same centers completed the resulting 40-item scale. This new instrument produced validity evidence based on the internal structure in a second-order factor model with four components (RMSEA = 0.079, GFI = 0.97, AGFI = 0.97, CFI = 0.97; NFI = 0.95, and NNFI = 0.97); absence of Differential Item Functioning (DIF) in 80% of the items; reliability (α = 0.96); and validity evidence based on relations to other variables, specifically the test-criterion relationship (ρ = 0.680). Finally, we discuss further developments of the instrument and its possible implications for EHS workers. PMID:29403417

Development of a Work Climate Scale in Emergency Health Services.

PubMed

Sanduvete-Chaves, Susana; Lozano-Lozano, José A; Chacón-Moscoso, Salvador; Holgado-Tello, Francisco P

2018-01-01

An adequate work climate fosters productivity in organizations and increases employee satisfaction. Workers in emergency health services (EHS) have an extremely high degree of responsibility and consequent stress. Therefore, it is essential to foster a good work climate in this context. Despite this, scales with a full study of their psychometric properties (i.e., validity evidence based on test content, internal structure and relations to other variables, and reliability) are not available to measure work climate in EHS specifically. For this reason, our objective was to develop a scale to measure the quality of work climates in EHS. We carried out three studies. In Study 1, we used a mixed-method approach to identify the latent conceptual structure of the construct work climate . Thus, we integrated the results found in (a) a previous study, where a content analysis of seven in-depth interviews obtained from EHS professionals in two hospitals in Gibraltar Countryside County was carried out; and (b) the factor analysis of the responses given by 113 EHS professionals from these same centers to 18 items that measured the work climate in health organizations. As a result, we obtained 56 items grouped into four factors (work satisfaction, productivity/achievement of aims, interpersonal relationships, and performance at work). In Study 2, we presented validity evidence based on test content through experts' judgment. Fourteen experts from the methodology and health fields evaluated the representativeness, utility, and feasibility of each of the 56 items with respect to their factor (theoretical dimension). Forty items met the inclusion criterion, which was to obtain an Osterlind index value greater than or equal to 0.5 in the three aspects assessed. In Study 3, 201 EHS professionals from the same centers completed the resulting 40-item scale. This new instrument produced validity evidence based on the internal structure in a second-order factor model with four components ( RMSEA = 0.079, GFI = 0.97, AGFI = 0.97, CFI = 0.97; NFI = 0.95, and NNFI = 0.97); absence of Differential Item Functioning (DIF) in 80% of the items; reliability (α = 0.96); and validity evidence based on relations to other variables, specifically the test-criterion relationship (ρ = 0.680). Finally, we discuss further developments of the instrument and its possible implications for EHS workers.

Some Further Notes on the OCDQ

ERIC Educational Resources Information Center

Hoy, Wayne K.

1972-01-01

A validity study of the OCD Questionnaire instrument for assessing organizational climate in the schools concludes that (1) the prototypic profile is not useful, and (2) subtests of the OCDQ tap and measure important aspects of the organizational climate of secondary schools. (Author)

Development and validation of safety climate scales for mobile remote workers using utility/electrical workers as exemplar.

PubMed

Huang, Yueng-Hsiang; Zohar, Dov; Robertson, Michelle M; Garabet, Angela; Murphy, Lauren A; Lee, Jin

2013-10-01

The objective of this study was to develop and test the reliability and validity of a new scale designed for measuring safety climate among mobile remote workers, using utility/electrical workers as exemplar. The new scale employs perceived safety priority as the metric of safety climate and a multi-level framework, separating the measurement of organization- and group-level safety climate items into two sub-scales. The question of the emergence of shared perceptions among remote workers was also examined. For the initial survey development, several items were adopted from a generic safety climate scale and new industry-specific items were generated based on an extensive literature review, expert judgment, 15-day field observations, and 38 in-depth individual interviews with subject matter experts (i.e., utility industry electrical workers, trainers and supervisors of electrical workers). The items were revised after 45 cognitive interviews and a pre-test with 139 additional utility/electrical workers. The revised scale was subsequently implemented with a total of 2421 workers at two large US electric utility companies (1560 participants for the pilot company and 861 for the second company). Both exploratory (EFA) and confirmatory factor analyses (CFA) were adopted to finalize the items and to ensure construct validity. Reliability of the scale was tested based on Cronbach's α. Homogeneity tests examined whether utility/electrical workers' safety climate perceptions were shared within the same supervisor group. This was followed by an analysis of the criterion-related validity, which linked the safety climate scores to self-reports of safety behavior and injury outcomes (i.e., recordable incidents, missing days due to work-related injuries, vehicle accidents, and near misses). Six dimensions (Safety pro-activity, General training, Trucks and equipment, Field orientation, Financial Investment, and Schedule flexibility) with 29 items were extracted from the EFA to measure the organization-level safety climate. Three dimensions (Supervisory care, Participation encouragement, and Safety straight talk) with 19 items were extracted to measure the group-level safety climate. Acceptable ranges of internal consistency statistics for the sub-scales were observed. Whether or not to aggregate these multi-dimensions of safety climate into a single higher-order construct (overall safety climate) was discussed. CFAs confirmed the construct validity of the developed safety climate scale for utility/electrical workers. Homogeneity tests showed that utility/electrical workers' safety climate perceptions were shared within the same supervisor group. Both the organization- and group-level safety climate scores showed a statistically significant relationship with workers' self-reported safety behaviors and injury outcomes. A valid and reliable instrument to measure the essential elements of safety climate for utility/electrical workers in the remote working situation has been introduced. The scale can provide an in-depth understanding of safety climate based on its key dimensions and show where improvements can be made at both group and organization levels. As such, it may also offer a valuable starting point for future safety interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Psychometric support of the school climate measure in a large, diverse sample of adolescents: a replication and extension.

PubMed

Zullig, Keith J; Collins, Rani; Ghani, Nadia; Patton, Jon M; Scott Huebner, E; Ajamie, Jean

2014-02-01

The School Climate Measure (SCM) was developed and validated in 2010 in response to a dearth of psychometrically sound school climate instruments. This study sought to further validate the SCM on a large, diverse sample of Arizona public school adolescents (N = 20,953). Four SCM domains (positive student-teacher relationships, academic support, order and discipline, and physical environment) were available for the analysis. Confirmatory factor analysis and structural equation modeling were established to construct validity, and criterion-related validity was assessed via selected Youth Risk Behavior Survey (YRBS) school safety items and self-reported grade (GPA) point average. Analyses confirmed the 4 SCM school climate domains explained approximately 63% of the variance (factor loading range .45-.92). Structural equation models fit the data well χ(2) = 14,325 (df = 293, p < .001), comparative fit index (CFI) = .951, Tuker-Lewis index (TLI) = .952, root mean square error of approximation (RMSEA) = .05). The goodness-of-fit index was .940. Coefficient alphas ranged from .82 to .93. Analyses of variance with post hoc comparisons suggested the SCM domains related in hypothesized directions with the school safety items and GPA. Additional evidence supports the validity and reliability of the SCM. Measures, such as the SCM, can facilitate data-driven decisions and may be incorporated into evidenced-based processes designed to improve student outcomes. © 2014, American School Health Association.

The Relationship of Bureaucratic Structure to School Climate: An Exploratory Factor Analysis of Construct Validity

ERIC Educational Resources Information Center

Lennon, Patricia A.

2010-01-01

This researcher examined the relationship of bureaucratic structure to school climate by means of an exploratory factor analysis of a measure of bureaucracy developed by Hoy and Sweetland (2000) and the four dimensional measure of climate developed by Hoy, Smith, and Sweetland (2002). Since there had been no other empirical studies whose authors…

Measuring Sports Class Learning Climates: The Development of the Sports Class Environment Scale

ERIC Educational Resources Information Center

Dowdell, Trevor; Tomson, L. Mich; Davies, Michael

2011-01-01

The development and validation of a new and unique learning climate instrument, the Sports Class Environment Scale (SCES), was the focus of this study. We began with a consolidation of the dimensions and items of the Perceived Motivational Climate in Sport Questionnaire-2 and the Classroom Environment Scale. Field-testing of the SCES involved 204…

Development and psychometric testing of the Nurse Practitioner Primary Care Organizational Climate Questionnaire.

PubMed

Poghosyan, Lusine; Nannini, Angela; Finkelstein, Stacey R; Mason, Emanuel; Shaffer, Jonathan A

2013-01-01

Policy makers and healthcare organizations are calling for expansion of the nurse practitioner (NP) workforce in primary care settings to assure timely access and high-quality care for the American public. However, many barriers, including those at the organizational level, exist that may undermine NP workforce expansion and their optimal utilization in primary care. This study developed a new NP-specific survey instrument, Nurse Practitioner Primary Care Organizational Climate Questionnaire (NP-PCOCQ), to measure organizational climate in primary care settings and conducted its psychometric testing. Using instrument development design, the organizational climate domain pertinent for primary care NPs was identified. Items were generated from the evidence and qualitative data. Face and content validity were established through two expert meetings. Content validity index was computed. The 86-item pool was reduced to 55 items, which was pilot tested with 81 NPs using mailed surveys and then field-tested with 278 NPs in New York State. SPSS 18 and Mplus software were used for item analysis, reliability testing, and maximum likelihood exploratory factor analysis. Nurse Practitioner Primary Care Organizational Climate Questionnaire had face and content validity. The content validity index was .90. Twenty-nine items loaded on four subscale factors: professional visibility, NP-administration relations, NP-physician relations, and independent practice and support. The subscales had high internal consistency reliability. Cronbach's alphas ranged from.87 to .95. Having a strong instrument is important to promote future research. Also, administrators can use it to assess organizational climate in their clinics and propose interventions to improve it, thus promoting NP practice and the expansion of NP workforce.

Safety compliance and safety climate: A repeated cross-sectional study in the oil and gas industry.

PubMed

Kvalheim, Sverre A; Dahl, Øyvind

2016-12-01

Violations of safety rules and procedures are commonly identified as a causal factor in accidents in the oil and gas industry. Extensive knowledge on effective management practices related to improved compliance with safety procedures is therefore needed. Previous studies of the causal relationship between safety climate and safety compliance demonstrate that the propensity to act in accordance with prevailing rules and procedures is influenced to a large degree by workers' safety climate. Commonly, the climate measures employed differ from one study to another and identical measures of safety climate are seldom tested repeatedly over extended periods of time. This research gap is addressed in the present study. The study is based on a survey conducted four times among sharp-end workers of the Norwegian oil and gas industry (N=31,350). This is done by performing multiple tests (regression analysis) over a period of 7years of the causal relationship between safety climate and safety compliance. The safety climate measure employed is identical across the 7-year period. Taking all periods together, the employed safety climate model explained roughly 27% of the variance in safety compliance. The causal relationship was found to be stable across the period, thereby increasing the reliability and the predictive validity of the factor structure. The safety climate factor that had the most powerful effect on safety compliance was work pressure. The factor structure employed shows high predictive validity and should therefore be relevant to organizations seeking to improve safety in the petroleum sector. The findings should also be relevant to other high-hazard industries where safety rules and procedures constitute a central part of the approach to managing safety. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.

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

EPA Science Inventory

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

Actor groups, related needs, and challenges at the climate downscaling interface

NASA Astrophysics Data System (ADS)

Rössler, Ole; Benestad, Rasmus; Diamando, Vlachogannis; Heike, Hübener; Kanamaru, Hideki; Pagé, Christian; Margarida Cardoso, Rita; Soares, Pedro; Maraun, Douglas; Kreienkamp, Frank; Christodoulides, Paul; Fischer, Andreas; Szabo, Peter

2016-04-01

At the climate downscaling interface, numerous downscaling techniques and different philosophies compete on being the best method in their specific terms. Thereby, it remains unclear to what extent and for which purpose these downscaling techniques are valid or even the most appropriate choice. A common validation framework that compares all the different available methods was missing so far. The initiative VALUE closes this gap with such a common validation framework. An essential part of a validation framework for downscaling techniques is the definition of appropriate validation measures. The selection of validation measures should consider the needs of the stakeholder: some might need a temporal or spatial average of a certain variable, others might need temporal or spatial distributions of some variables, still others might need extremes for the variables of interest or even inter-variable dependencies. Hence, a close interaction of climate data providers and climate data users is necessary. Thus, the challenge in formulating a common validation framework mirrors also the challenges between the climate data providers and the impact assessment community. This poster elaborates the issues and challenges at the downscaling interface as it is seen within the VALUE community. It suggests three different actor groups: one group consisting of the climate data providers, the other two groups being climate data users (impact modellers and societal users). Hence, the downscaling interface faces classical transdisciplinary challenges. We depict a graphical illustration of actors involved and their interactions. In addition, we identified four different types of issues that need to be considered: i.e. data based, knowledge based, communication based, and structural issues. They all may, individually or jointly, hinder an optimal exchange of data and information between the actor groups at the downscaling interface. Finally, some possible ways to tackle these issues are discussed.

Predicting the Impacts of Climate Change on Runoff and Sediment Processes in Agricultural Watersheds: A Case Study from the Sunflower Watershed in the Lower Mississippi Basin

NASA Astrophysics Data System (ADS)

Elkadiri, R.; Momm, H.; Yasarer, L.; Armour, G. L.

2017-12-01

Climatic conditions play a major role in physical processes impacting soil and agrochemicals detachment and transportation from/in agricultural watersheds. In addition, these climatic conditions are projected to significantly vary spatially and temporally in the 21st century, leading to vast uncertainties about the future of sediment and non-point source pollution transport in agricultural watersheds. In this study, we selected the sunflower basin in the lower Mississippi River basin, USA to contribute in the understanding of how climate change affects watershed processes and the transport of pollutant loads. The climate projections used in this study were retrieved from the archive of World Climate Research Programme's (WCRP) Coupled Model Intercomparison Phase 5 (CMIP5) project. The CMIP5 dataset was selected because it contains the most up-to-date spatially downscaled and bias corrected climate projections. A subset of ten GCMs representing a range in projected climate were spatially downscaled for the sunflower watershed. Statistics derived from downscaled GCM output representing the 2011-2040, 2041-2070 and 2071-2100 time periods were used to generate maximum/minimum temperature and precipitation on a daily time step using the USDA Synthetic Weather Generator, SYNTOR. These downscaled climate data were then utilized as inputs to run in the Annualized Agricultural Non-Point Source (AnnAGNPS) pollution watershed model to estimate time series of runoff, sediment, and nutrient loads produced from the watershed. For baseline conditions a validated simulation of the watershed was created and validated using historical data from 2000 until 2015.

Identification of core objectives for teaching sustainable healthcare education.

PubMed

Teherani, Arianne; Nishimura, Holly; Apatira, Latifat; Newman, Thomas; Ryan, Susan

2017-01-01

Physicians will be called upon to care for patients who bear the burden of disease from the impact of climate change and ecologically irresponsible practices which harm ecosystems and contribute to climate change. However, physicians must recognize the connection between the climate, ecosystems, sustainability, and health and their responsibility and capacity in changing the status quo. Sustainable healthcare education (SHE), defined as education about the impact of climate change and ecosystem alterations on health and the impact of the healthcare industry on the aforementioned, is vital to prevention of adverse health outcomes due to the changing climate and environment. To systematically determine which and when a set of SHE objectives should be included in the medical education continuum. Fifty-two SHE experts participated in a two-part modified-Delphi study. A survey was developed based on 21 SHE objectives. Respondents rated the importance of each objective and when each objective should be taught. Descriptive statistics and an item-level content validity index (CVI) were used to analyze data. Fifteen of the objectives achieved a content validity index of 78% or greater. The remaining objectives had content validity indices between 58% and 77%. The preclinical years of medical school were rated as the optimal time for introducing 13 and the clinical years for introducing six of the objectives. Respondents noted the definition of environmental sustainability should be learned prior to medical school and identifying ways to improve the environmental sustainability of health systems in post-graduate training. This study proposes SHE objectives for the continuum of medical education. These objectives ensure the identity of the physician includes the requisite awareness and competence to care for patients who experience the impact of climate and environment on health and advocate for sustainability of the health systems in which they work. CVI: Content validity index; SHE: Sustainable healthcare education.

School Climate of Educational Institutions: Design and Validation of a Diagnostic Scale

ERIC Educational Resources Information Center

Becerra, Sandra

2016-01-01

School climate is recognized as a relevant factor for the improvement of educative processes, favoring the administrative processes and optimum school performance. The present article is the result of a quantitative research model which had the objective of psychometrically designing and validating a scale to diagnose the organizational climate of…

Extra-Tropical Cyclones at Climate Scales: Comparing Models to Observations

NASA Astrophysics Data System (ADS)

Tselioudis, G.; Bauer, M.; Rossow, W.

2009-04-01

Climate is often defined as the accumulation of weather, and weather is not the concern of climate models. Justification for this latter sentiment has long been hidden behind coarse model resolutions and blunt validation tools based on climatological maps. The spatial-temporal resolutions of today's climate models and observations are converging onto meteorological scales, however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough that its accumulation results in a robust climate simulation. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from observations and climate model output. These include the usual cyclone characteristics (centers, tracks), but also adaptive cyclone-centric composites. We have created a novel dataset, the MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid-latitude cyclones, using a search algorithm that delimits the boundaries of each system from the outer-most closed SLP contour. Using this we then extract composites of cloud, radiation, and precipitation properties from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools in process-based climate model evaluation studies will be shown.

A user-targeted synthesis of the VALUE perfect predictor experiment

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Widmann, Martin; Gutierrez, Jose; Kotlarski, Sven; Hertig, Elke; Wibig, Joanna; Rössler, Ole; Huth, Radan

2016-04-01

VALUE is an open European network to validate and compare downscaling methods for climate change research. A key deliverable of VALUE is the development of a systematic validation framework to enable the assessment and comparison of both dynamical and statistical downscaling methods. VALUE's main approach to validation is user-focused: starting from a specific user problem, a validation tree guides the selection of relevant validation indices and performance measures. We consider different aspects: (1) marginal aspects such as mean, variance and extremes; (2) temporal aspects such as spell length characteristics; (3) spatial aspects such as the de-correlation length of precipitation extremes; and multi-variate aspects such as the interplay of temperature and precipitation or scale-interactions. Several experiments have been designed to isolate specific points in the downscaling procedure where problems may occur. Experiment 1 (perfect predictors): what is the isolated downscaling skill? How do statistical and dynamical methods compare? How do methods perform at different spatial scales? Experiment 2 (Global climate model predictors): how is the overall representation of regional climate, including errors inherited from global climate models? Experiment 3 (pseudo reality): do methods fail in representing regional climate change? Here, we present a user-targeted synthesis of the results of the first VALUE experiment. In this experiment, downscaling methods are driven with ERA-Interim reanalysis data to eliminate global climate model errors, over the period 1979-2008. As reference data we use, depending on the question addressed, (1) observations from 86 meteorological stations distributed across Europe; (2) gridded observations at the corresponding 86 locations or (3) gridded spatially extended observations for selected European regions. With more than 40 contributing methods, this study is the most comprehensive downscaling inter-comparison project so far. The results clearly indicate that for several aspects, the downscaling skill varies considerably between different methods. For specific purposes, some methods can therefore clearly be excluded.

Validation of China-wide interpolated daily climate variables from 1960 to 2011

NASA Astrophysics Data System (ADS)

Yuan, Wenping; Xu, Bing; Chen, Zhuoqi; Xia, Jiangzhou; Xu, Wenfang; Chen, Yang; Wu, Xiaoxu; Fu, Yang

2015-02-01

Temporally and spatially continuous meteorological variables are increasingly in demand to support many different types of applications related to climate studies. Using measurements from 600 climate stations, a thin-plate spline method was applied to generate daily gridded climate datasets for mean air temperature, maximum temperature, minimum temperature, relative humidity, sunshine duration, wind speed, atmospheric pressure, and precipitation over China for the period 1961-2011. A comprehensive evaluation of interpolated climate was conducted at 150 independent validation sites. The results showed superior performance for most of the estimated variables. Except for wind speed, determination coefficients ( R 2) varied from 0.65 to 0.90, and interpolations showed high consistency with observations. Most of the estimated climate variables showed relatively consistent accuracy among all seasons according to the root mean square error, R 2, and relative predictive error. The interpolated data correctly predicted the occurrence of daily precipitation at validation sites with an accuracy of 83 %. Moreover, the interpolation data successfully explained the interannual variability trend for the eight meteorological variables at most validation sites. Consistent interannual variability trends were observed at 66-95 % of the sites for the eight meteorological variables. Accuracy in distinguishing extreme weather events differed substantially among the meteorological variables. The interpolated data identified extreme events for the three temperature variables, relative humidity, and sunshine duration with an accuracy ranging from 63 to 77 %. However, for wind speed, air pressure, and precipitation, the interpolation model correctly identified only 41, 48, and 58 % of extreme events, respectively. The validation indicates that the interpolations can be applied with high confidence for the three temperatures variables, as well as relative humidity and sunshine duration based on the performance of these variables in estimating daily variations, interannual variability, and extreme events. Although longitude, latitude, and elevation data are included in the model, additional information, such as topography and cloud cover, should be integrated into the interpolation algorithm to improve performance in estimating wind speed, atmospheric pressure, and precipitation.

Development and Validation of the ACSI: Measuring Students' Science Attitudes, Pro-Environmental Behaviour, Climate Change Attitudes and Knowledge

ERIC Educational Resources Information Center

Dijkstra, E. M.; Goedhart, M. J.

2012-01-01

This article describes the development and validation of the Attitudes towards Climate Change and Science Instrument. This 63-item questionnaire measures students' pro-environmental behaviour, their climate change knowledge and their attitudes towards school science, societal implications of science, scientists, a career in science and the urgency…

Psychometric properties of the Persian version of the “Hospital Ethical Climate Survey”

PubMed Central

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

Sharing the Data along with the Responsibility: Examining an Analytic Scale-Based Model for Assessing School Climate.

ERIC Educational Resources Information Center

Shindler, John; Taylor, Clint; Cadenas, Herminia; Jones, Albert

This study was a pilot effort to examine the efficacy of an analytic trait scale school climate assessment instrument and democratic change system in two urban high schools. Pilot study results indicate that the instrument shows promising soundness in that it exhibited high levels of validity and reliability. In addition, the analytic trait format…

Worksite health and safety climate: scale development and effects of a health promotion intervention.

PubMed

Basen-Engquist, K; Hudmon, K S; Tripp, M; Chamberlain, R

1998-01-01

Environmental influences on health and health behavior have an important place in research on worksite health promotion. We tested the validity and internal consistency of a new measure of organizational health and safety climate that was used in a large randomized trial of a worksite cancer prevention program (the Working Well Trial). The resulting scales then were applied to assess intervention effects. This study uses data from a subset of 40 worksites in the Working Well Trial. Employees at 20 natural gas pipeline worksite and 20 rural electrical cooperatives completed a cross-sectional questionnaire at baseline and 3-year follow-up. A factor analysis of this self-report instrument produced a two-factor solution. The resulting health and safety climate scales had good internal consistency (Cronbach's alpha = 0.74 and 0.82, respectively) and concurrent validity. The health climate scale was correlated more highly with organizational measures that were indicative of a supportive health climate than those indicating supportive safety climate, while the reverse was true of the safety climate scale. Changes in health climate were associated with the number of smoking and smokeless tobacco programs offered at the worksites at the time of the 3-year follow-up (r = 0.46 and 0.42, respectively). The scales were not correlated with most employee health behaviors. The health climate scores increased at intervention worksites, compared with scores at control worksites (F[1,36] = 7.57, P = 0.009). The health and safety climate scales developed for this study provide useful instruments for measuring organizational change related to worksite health promotion activities. The Working Well Intervention resulted in a significant improvement in worksite health climate.

Can species distribution models really predict the expansion of invasive species?

PubMed

Barbet-Massin, Morgane; Rome, Quentin; Villemant, Claire; Courchamp, Franck

2018-01-01

Predictive studies are of paramount importance for biological invasions, one of the biggest threats for biodiversity. To help and better prioritize management strategies, species distribution models (SDMs) are often used to predict the potential invasive range of introduced species. Yet, SDMs have been regularly criticized, due to several strong limitations, such as violating the equilibrium assumption during the invasion process. Unfortunately, validation studies-with independent data-are too scarce to assess the predictive accuracy of SDMs in invasion biology. Yet, biological invasions allow to test SDMs usefulness, by retrospectively assessing whether they would have accurately predicted the latest ranges of invasion. Here, we assess the predictive accuracy of SDMs in predicting the expansion of invasive species. We used temporal occurrence data for the Asian hornet Vespa velutina nigrithorax, a species native to China that is invading Europe with a very fast rate. Specifically, we compared occurrence data from the last stage of invasion (independent validation points) to the climate suitability distribution predicted from models calibrated with data from the early stage of invasion. Despite the invasive species not being at equilibrium yet, the predicted climate suitability of validation points was high. SDMs can thus adequately predict the spread of V. v. nigrithorax, which appears to be-at least partially-climatically driven. In the case of V. v. nigrithorax, SDMs predictive accuracy was slightly but significantly better when models were calibrated with invasive data only, excluding native data. Although more validation studies for other invasion cases are needed to generalize our results, our findings are an important step towards validating the use of SDMs in invasion biology.

Development and validation of a measure of workplace climate for healthy weight maintenance.

PubMed

Sliter, Katherine A

2013-07-01

Due to the obesity epidemic, an increasing amount of research is being conducted to better understand the antecedents and consequences of excess employee weight. One construct often of interest to researchers in this area is organizational climate. Unfortunately, a viable measure of climate, as related to employee weight, does not exist. The purpose of this study was to remedy this by developing and validating a concise, psychometrically sound measure of climate for healthy weight. An item pool was developed based on surveys of full-time employees, and a sorting task was used to eliminate ambiguous items. Items were pilot tested by a sample of 338 full-time employees, and the item pool was reduced through item response theory (IRT) and reliability analyses. Finally, the retained 14 items, comprising 3 subscales, were completed by a sample of 360 full-time employees, representing 26 different organizations from across the United States. Multilevel modeling indicated that sufficient variance was explained by group membership to support aggregation, and confirmatory factor analysis (CFA) supported the hypothesized model of 3 subscale factors and an overall climate factor. Nine hypotheses specific to construct validation were tested. Scores on the new scale correlated significantly with individual-level reports of psychological constructs (e.g., health motivation, general leadership support for health) and physiological phenomena (e.g., body mass index [BMI], physical health problems) to which they should theoretically relate, supporting construct validity. Implications for the use of this scale in both applied and research settings are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.

The Safety Culture Enactment Questionnaire (SCEQ): Theoretical model and empirical validation.

PubMed

de Castro, Borja López; Gracia, Francisco J; Tomás, Inés; Peiró, José M

2017-06-01

This paper presents the Safety Culture Enactment Questionnaire (SCEQ), designed to assess the degree to which safety is an enacted value in the day-to-day running of nuclear power plants (NPPs). The SCEQ is based on a theoretical safety culture model that is manifested in three fundamental components of the functioning and operation of any organization: strategic decisions, human resources practices, and daily activities and behaviors. The extent to which the importance of safety is enacted in each of these three components provides information about the pervasiveness of the safety culture in the NPP. To validate the SCEQ and the model on which it is based, two separate studies were carried out with data collection in 2008 and 2014, respectively. In Study 1, the SCEQ was administered to the employees of two Spanish NPPs (N=533) belonging to the same company. Participants in Study 2 included 598 employees from the same NPPs, who completed the SCEQ and other questionnaires measuring different safety outcomes (safety climate, safety satisfaction, job satisfaction and risky behaviors). Study 1 comprised item formulation and examination of the factorial structure and reliability of the SCEQ. Study 2 tested internal consistency and provided evidence of factorial validity, validity based on relationships with other variables, and discriminant validity between the SCEQ and safety climate. Exploratory Factor Analysis (EFA) carried out in Study 1 revealed a three-factor solution corresponding to the three components of the theoretical model. Reliability analyses showed strong internal consistency for the three scales of the SCEQ, and each of the 21 items on the questionnaire contributed to the homogeneity of its theoretically developed scale. Confirmatory Factor Analysis (CFA) carried out in Study 2 supported the internal structure of the SCEQ; internal consistency of the scales was also supported. Furthermore, the three scales of the SCEQ showed the expected correlation patterns with the measured safety outcomes. Finally, results provided evidence of discriminant validity between the SCEQ and safety climate. We conclude that the SCEQ is a valid, reliable instrument supported by a theoretical framework, and it is useful to measure the enactment of safety culture in NPPs. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Role of Anchor Stations in the Validation of Earth Observation Satellite Data and Products. The Valencia and the Alacant Anchor Stations

NASA Astrophysics Data System (ADS)

Lopez-Baeza, Ernesto; Geraldo Ferreira, A.; Saleh-Contell, Kauzar

Space technology facilitates humanity and science with a global revolutionary view of the Earth through the acquisition of Earth Observation satellite data. Satellites capture information over different spatial and temporal scales and assist in understanding natural climate processes and in detecting and explaining climate change. Accurate Earth Observation data is needed to describe climate processes by improving the parameterisations of different climate elements. Algorithms to produce geophysical parameters from raw satellite observations should go through selection processes or participate in inter-comparison programmes to ensure performance reliability. Geophysical parameter datasets, obtained from satellite observations, should pass a quality control before they are accepted in global databases for impact, diagnostic or sensitivity studies. Calibration and Validation, or simply "Cal/Val", is the activity that endeavours to ensure that remote sensing products are highly consistent and reproducible. This is an evolving scientific activity that is becoming increasingly important as more long-term studies on global change are undertaken, and new satellite missions are launched. Calibration is the process of quantitatively defining the system responses to known, controlled signal inputs. Validation refers to the process of assessing, by independent means, the quality of the data products derived from the system outputs. These definitions are generally accepted and most often used in the remote sensing context to refer specifically and respectively to sensor radiometric calibration and geophysical parameter validation. Anchor Stations are carefully selected locations at which instruments measure quantities that are needed to run, calibrate or validate models and algorithms. These are needed to quanti-tatively evaluate satellite data and convert it into geophysical information. The instruments collect measurements of basic quantities over a long timescale. Measurements are made of meteorological and hydrological background data, and of quantities not readily assessed at operational stations. Anchor Stations also offer infrastructure to undertake validation experi-ments. These are more detailed measurements over shorter intensive observation periods. The Valencia Anchor Station is showing its capabilities and conditions as a reference validation site in the framework of low spatial resolution remote sensing missions such as CERES, GERB and SMOS. The Alacant Anchor Station is a reference site in studies on the interactions between desertification and climate. This paper presents the activities so far carried out at both Anchor Stations, the precise and detailed ground and aircraft experiments carefully designed to develop a specific methodology to validate low spatial resolution satellite data and products, and the knowledge exchange currently being exercised between the University of Valencia, Spain, and FUNCEME, Brazil, in common objectives of mutual interest.

Stochastic Hourly Weather Generator HOWGH: Validation and its Use in Pest Modelling under Present and Future Climates

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Hirschi, M.; Spirig, C.

2014-12-01

To quantify impact of the climate change on a specific pest (or any weather-dependent process) in a specific site, we may use a site-calibrated pest (or other) model and compare its outputs obtained with site-specific weather data representing present vs. perturbed climates. The input weather data may be produced by the stochastic weather generator. Apart from the quality of the pest model, the reliability of the results obtained in such experiment depend on an ability of the generator to represent the statistical structure of the real world weather series, and on the sensitivity of the pest model to possible imperfections of the generator. This contribution deals with the multivariate HOWGH weather generator, which is based on a combination of parametric and non-parametric statistical methods. Here, HOWGH is used to generate synthetic hourly series of three weather variables (solar radiation, temperature and precipitation) required by a dynamic pest model SOPRA to simulate the development of codling moth. The contribution presents results of the direct and indirect validation of HOWGH. In the direct validation, the synthetic series generated by HOWGH (various settings of its underlying model are assumed) are validated in terms of multiple climatic characteristics, focusing on the subdaily wet/dry and hot/cold spells. In the indirect validation, we assess the generator in terms of characteristics derived from the outputs of SOPRA model fed by the observed vs. synthetic series. The weather generator may be used to produce weather series representing present and future climates. In the latter case, the parameters of the generator may be modified by the climate change scenarios based on Global or Regional Climate Models. To demonstrate this feature, the results of codling moth simulations for future climate will be shown. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).

Expertly validated models and phylogenetically-controlled analysis suggests responses to climate change are related to species traits in the order lagomorpha.

PubMed

Leach, Katie; Kelly, Ruth; Cameron, Alison; Montgomery, W Ian; Reid, Neil

2015-01-01

Climate change during the past five decades has impacted significantly on natural ecosystems, and the rate of current climate change is of great concern among conservation biologists. Species Distribution Models (SDMs) have been used widely to project changes in species' bioclimatic envelopes under future climate scenarios. Here, we aimed to advance this technique by assessing future changes in the bioclimatic envelopes of an entire mammalian order, the Lagomorpha, using a novel framework for model validation based jointly on subjective expert evaluation and objective model evaluation statistics. SDMs were built using climatic, topographical, and habitat variables for all 87 lagomorph species under past and current climate scenarios. Expert evaluation and Kappa values were used to validate past and current models and only those deemed 'modellable' within our framework were projected under future climate scenarios (58 species). Phylogenetically-controlled regressions were used to test whether species traits correlated with predicted responses to climate change. Climate change is likely to impact more than two-thirds of lagomorph species, with leporids (rabbits, hares, and jackrabbits) likely to undertake poleward shifts with little overall change in range extent, whilst pikas are likely to show extreme shifts to higher altitudes associated with marked range declines, including the likely extinction of Kozlov's Pika (Ochotona koslowi). Smaller-bodied species were more likely to exhibit range contractions and elevational increases, but showing little poleward movement, and fecund species were more likely to shift latitudinally and elevationally. Our results suggest that species traits may be important indicators of future climate change and we believe multi-species approaches, as demonstrated here, are likely to lead to more effective mitigation measures and conservation management. We strongly advocate studies minimising data gaps in our knowledge of the Order, specifically collecting more specimens for biodiversity archives and targeting data deficient geographic regions.

Expertly Validated Models and Phylogenetically-Controlled Analysis Suggests Responses to Climate Change Are Related to Species Traits in the Order Lagomorpha

PubMed Central

Leach, Katie; Kelly, Ruth; Cameron, Alison; Montgomery, W. Ian; Reid, Neil

2015-01-01

Climate change during the past five decades has impacted significantly on natural ecosystems, and the rate of current climate change is of great concern among conservation biologists. Species Distribution Models (SDMs) have been used widely to project changes in species’ bioclimatic envelopes under future climate scenarios. Here, we aimed to advance this technique by assessing future changes in the bioclimatic envelopes of an entire mammalian order, the Lagomorpha, using a novel framework for model validation based jointly on subjective expert evaluation and objective model evaluation statistics. SDMs were built using climatic, topographical, and habitat variables for all 87 lagomorph species under past and current climate scenarios. Expert evaluation and Kappa values were used to validate past and current models and only those deemed ‘modellable’ within our framework were projected under future climate scenarios (58 species). Phylogenetically-controlled regressions were used to test whether species traits correlated with predicted responses to climate change. Climate change is likely to impact more than two-thirds of lagomorph species, with leporids (rabbits, hares, and jackrabbits) likely to undertake poleward shifts with little overall change in range extent, whilst pikas are likely to show extreme shifts to higher altitudes associated with marked range declines, including the likely extinction of Kozlov’s Pika (Ochotona koslowi). Smaller-bodied species were more likely to exhibit range contractions and elevational increases, but showing little poleward movement, and fecund species were more likely to shift latitudinally and elevationally. Our results suggest that species traits may be important indicators of future climate change and we believe multi-species approaches, as demonstrated here, are likely to lead to more effective mitigation measures and conservation management. We strongly advocate studies minimising data gaps in our knowledge of the Order, specifically collecting more specimens for biodiversity archives and targeting data deficient geographic regions. PMID:25874407

Psychometric evaluation of the Swedish language Person-centred Climate Questionnaire-family version.

PubMed

Lindahl, Jeanette; Elmqvist, Carina; Thulesius, Hans; Edvardsson, David

2015-12-01

In a holistic view of care, the family is important for the patient as well as for the staff and integration of family members in health care is a growing trend. Yet, family participation in the care is sparsely investigated and valid assessment instruments are needed. Data were collected from 200 family members participating in an intervention study at an emergency department (ED) in Sweden. The Person-centred Climate Questionnaire-Family (PCQ-F) is a measure for how family members perceive the psychosocial climate. PCQ-F is a self-report instrument that contains 17 items assessing safety, everydayness and hospitality--three subscale dimensions that mirror the Swedish patient version of the questionnaire, the PCQ-P. The aim of this study was to evaluate the psychometric properties of the Swedish version of the PCQ-F in an ED context. The psychometric properties of the PCQ-F were evaluated using statistical estimates of validity and reliability and showed high content validity and internal consistency. Cronbach's Alpha was >0.7 and item-total correlations were >0.3 and <0.7. In terms of psychometrics, the findings in this study indicate that the PCQ-F can be used with satisfactory validity and reliability to explore to what degree family members perceive ED settings as being person-centred, safe, welcoming and hospitable within an everyday and decorated physical environment. As the PCQ already exists in a valid and reliable patient (PCQ-P) and staff (PCQ-S) version, this new family member version is a significant addition to the literature as it enables further comparative studies of how diverse care settings are perceived by different stakeholders. © 2015 Nordic College of Caring Science.

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

NASA Technical Reports Server (NTRS)

Crane, Robert G.; Hewitson, Bruce

1990-01-01

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

The Factor Replicability of the Litwin and Stringer Organizational Climate Questionnaire: An Inter- and Intra-Organizational Assessment.

ERIC Educational Resources Information Center

Rogers, Evan D.; And Others

1980-01-01

Four recent factor analytic studies of the Litwin and Stringer Organizational Climate Questionnaire (LSOCQ) are compared. Although there is somewhat more intra- than inter-organizational replicability of factors, both comparisons raise considerable doubt about the validity of the Litwin and Stringer instrument. (Author)

Validation of a pre-existing safety climate scale for the Turkish furniture manufacturing industry.

PubMed

Akyuz, Kadri Cemil; Yildirim, Ibrahim; Gungor, Celal

2018-03-22

Understanding the safety climate level is essential to implement a proactive safety program. The objective of this study is to explore the possibility of having a safety climate scale for the Turkish furniture manufacturing industry since there has not been any scale available. The questionnaire recruited 783 subjects. Confirmatory factor analysis (CFA) tested a pre-existing safety scale's fit to the industry. The CFA indicated that the structures of the model present a non-satisfactory fit with the data (χ 2  = 2033.4, df = 314, p ≤ 0.001; root mean square error of approximation = 0.08, normed fit index = 0.65, Tucker-Lewis index = 0.65, comparative fit index = 0.69, parsimony goodness-of-fit index = 0.68). The results suggest that a new scale should be developed and validated to measure the safety climate level in the Turkish furniture manufacturing industry. Due to the hierarchical structure of organizations, future studies should consider a multilevel approach in their exploratory factor analyses while developing a new scale.

Scaling and contextualizing climate-conflict nexus in historical agrarian China

NASA Astrophysics Data System (ADS)

Lee, Harry F.

2017-04-01

This study examines climate-conflict nexus in historical agrarian China in multi-scalar and contextualized approach, illustrating what and how socio-political factors could significantly mediate the climate-violent link in pre-industrial society. Previous empirical large-N studies show that violent conflict in historical agrarian society was triggered by climate-induced food scarcity. The relationship was valid in China, Europe, and various geographic regions in the Northern Hemisphere in pre-industrial era. Nevertheless, the observed relationship has only been verified at a macro level (long-term variability of the nexus is emphasized and data over large area are aggregated), and somewhat generalized in nature (only physical environmental factors are controlled). Three inter-related issues remain unresolved: First, the key explanatory variable of violent conflicts may change substantially at different spatio-temporal scales. It is necessary to check whether the climate-conflict nexus is valid at a micro level (about short-term variability of the nexus and data in finer spatial resolution), and explore how the nexus changes along various spatio-temporal dimensions. Second, as the climate-conflict nexus has only been demonstrated in a broad sense, it is necessary to check whether and how the nexus is mediated by local socio-political context. More non-climatic factors pertinent to the cause and distribution of conflicts (e.g., governance, adaptive mechanisms, etc.) should be considered. Third, the methodology applied in the previous studies assumes spatially-independent observations and linear relationship, which may simplify the climate-conflict link. Moreover, the solitary reliance on quantitative methods may neglect those non-quantifiable socio-political dynamics which mediates the climate-conflict nexus. I plan to address the above issues by using disaggregated spatial analysis and in-depth case studies, with close attention to local and temporal differences and non-linear nature of the climate-conflict link. China will be chosen as study area. Study period will be delimited to AD1-1911. This study represents pioneering research which systematically examines the climate-conflict nexus in pre-industrial society over extended period in multi-scalar and contextualized perspective. By comparing and evaluating the climate-conflict link along various spatio-temporal dimensions and in different socio-political context, it may help to deepen the theoretical understanding of, and also resolve the current debate over, the climate-conflict relationship. Given the large potential changes in climatic regimes projected in coming decades, the findings in this study may have important implications for the social impact of climate change in tropical countries that are in some ways similar to pre-industrial society.

Outcome of the third cloud retrieval evaluation workshop

NASA Astrophysics Data System (ADS)

Roebeling, Rob; Baum, Bryan; Bennartz, Ralf; Hamann, Ulrich; Heidinger, Andy; Thoss, Anke; Walther, Andi

2013-05-01

Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and interannual variations are needed to improve understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role for such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics must be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), held from 15-18 Nov. 2011 in Madison, Wisconsin, USA, is to enhance knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimizing these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods used to prepare daily and monthly cloud parameter climatologies. An important workshop component is discussion on results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on reasons for observed differences. More in depth discussions were held on retrieval principles and validation, and utilization of cloud parameters for climate research. This was done in parallel breakout sessions on cloud vertical placement, cloud physical properties, and cloud climatologies. We present the recommendations of these sessions, propose a way forward to establish international partnerships on cloud research, and summarize actions defined to tailor CREW activities to missions of international programs, such as the Global Energy and Water Cycle Experiment (GEWEX) and Sustained, Co-Ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM). Finally, attention is given to increase the traceability and uniformity of different longterm and homogeneous records of cloud parameters.

Projecting species’ vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?

USGS Publications Warehouse

Steen, Valerie; Sofaer, Helen R.; Skagen, Susan K.; Ray, Andrea J.; Noon, Barry R

2017-01-01

Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross-validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland-dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross-validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water availability may be a more proximal driver than precipitation. However, because cross-validation results were correlated with extrapolation results, the use of cross-validation performance metrics to guide modeling choices where knowledge is limited was supported.

Projecting species' vulnerability to climate change: Which uncertainty sources matter most and extrapolate best?

PubMed

Steen, Valerie; Sofaer, Helen R; Skagen, Susan K; Ray, Andrea J; Noon, Barry R

2017-11-01

Species distribution models (SDMs) are commonly used to assess potential climate change impacts on biodiversity, but several critical methodological decisions are often made arbitrarily. We compare variability arising from these decisions to the uncertainty in future climate change itself. We also test whether certain choices offer improved skill for extrapolating to a changed climate and whether internal cross-validation skill indicates extrapolative skill. We compared projected vulnerability for 29 wetland-dependent bird species breeding in the climatically dynamic Prairie Pothole Region, USA. For each species we built 1,080 SDMs to represent a unique combination of: future climate, class of climate covariates, collinearity level, and thresholding procedure. We examined the variation in projected vulnerability attributed to each uncertainty source. To assess extrapolation skill under a changed climate, we compared model predictions with observations from historic drought years. Uncertainty in projected vulnerability was substantial, and the largest source was that of future climate change. Large uncertainty was also attributed to climate covariate class with hydrological covariates projecting half the range loss of bioclimatic covariates or other summaries of temperature and precipitation. We found that choices based on performance in cross-validation improved skill in extrapolation. Qualitative rankings were also highly uncertain. Given uncertainty in projected vulnerability and resulting uncertainty in rankings used for conservation prioritization, a number of considerations appear critical for using bioclimatic SDMs to inform climate change mitigation strategies. Our results emphasize explicitly selecting climate summaries that most closely represent processes likely to underlie ecological response to climate change. For example, hydrological covariates projected substantially reduced vulnerability, highlighting the importance of considering whether water availability may be a more proximal driver than precipitation. However, because cross-validation results were correlated with extrapolation results, the use of cross-validation performance metrics to guide modeling choices where knowledge is limited was supported.

Measuring School Climate for Gauging Principal Performance: A Review of the Validity and Reliability of Publicly Accessible Measures. A Quality School Leadership Issue Brief

ERIC Educational Resources Information Center

Clifford, Matthew; Menon, Roshni; Gangi, Tracy; Condon, Christopher; Hornung, Katie

2012-01-01

This policy brief provides principal evaluation system designers information about the technical soundness and cost (i.e., time requirements) of publicly available school climate surveys. The authors focus on the technical soundness of school climate surveys because they believe that using validated and reliable surveys as an outcomes measure can…

Transfer of Training.

ERIC Educational Resources Information Center

1996

This document consists of three papers presented at a symposium on transfer of training moderated by Gene Roth at the 1996 conference of the Academy of Human Resource Development (AHRD). "Validation of a Transfer Climate Instrument" (Reid A. Bates et al.) reports a study that attempted to validate Rouiller and Goldstein's (1993) eight-factor…

Impacts of climate change on paddy rice yield in a temperate climate.

PubMed

Kim, Han-Yong; Ko, Jonghan; Kang, Suchel; Tenhunen, John

2013-02-01

The crop simulation model is a suitable tool for evaluating the potential impacts of climate change on crop production and on the environment. This study investigates the effects of climate change on paddy rice production in the temperate climate regions under the East Asian monsoon system using the CERES-Rice 4.0 crop simulation model. This model was first calibrated and validated for crop production under elevated CO2 and various temperature conditions. Data were obtained from experiments performed using a temperature gradient field chamber (TGFC) with a CO2 enrichment system installed at Chonnam National University in Gwangju, Korea in 2009 and 2010. Based on the empirical calibration and validation, the model was applied to deliver a simulated forecast of paddy rice production for the region, as well as for the other Japonica rice growing regions in East Asia, projecting for years 2050 and 2100. In these climate change projection simulations in Gwangju, Korea, the yield increases (+12.6 and + 22.0%) due to CO2 elevation were adjusted according to temperature increases showing variation dependent upon the cultivars, which resulted in significant yield decreases (-22.1% and -35.0%). The projected yields were determined to increase as latitude increases due to reduced temperature effects, showing the highest increase for any of the study locations (+24%) in Harbin, China. It appears that the potential negative impact on crop production may be mediated by appropriate cultivar selection and cultivation changes such as alteration of the planting date. Results reported in this study using the CERES-Rice 4.0 model demonstrate the promising potential for its further application in simulating the impacts of climate change on rice production from a local to a regional scale under the monsoon climate system. © 2012 Blackwell Publishing Ltd.

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.

Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

NASA Astrophysics Data System (ADS)

MacLeod, Dave A.; Jones, Anne; Di Giuseppe, Francesca; Caminade, Cyril; Morse, Andrew P.

2015-04-01

The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006 the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.

Development and validation of climate change system thinking instrument (CCSTI) for measuring system thinking on climate change content

NASA Astrophysics Data System (ADS)

Meilinda; Rustaman, N. Y.; Firman, H.; Tjasyono, B.

2018-05-01

The Climate Change System Thinking Instrument (CCSTI) is developed to measure a system thinking ability in the concept of climate change. CCSTI is developed in four phase’s development including instrument draft development, validation and evaluation including readable material test, expert validation, and field test. The result of field test is analyzed by looking at the readability score in Cronbach’s alpha test. Draft instrument is tested on college students majoring in Biology Education, Physics Education, and Chemistry Education randomly with a total number of 80 college students. Score of Content Validation Index at 0.86, which means that the CCSTI developed are categorized as very appropriate with question indicators and Cronbach’s alpha about 0.605 which mean categorized undesirable to minimal acceptable. From 45 questions of system thinking, there are 37 valid questions spread in four indicators of system thinking, which are system thinking phase I (pre-requirement), system thinking phase II (basic), system thinking phase III (intermediate), and system thinking phase IV (coherent expert).

A National Study of the Validity and Utility of the Comprehensive Assessment of School Environment (CASE) Survey

ERIC Educational Resources Information Center

McGuffey, Amy R.

2016-01-01

A healthy school climate is necessary for improvement. The purpose of this study was to evaluate the construct validity and usability of the Comprehensive Assessment of School Environment (CASE) as it was purportedly realigned to the three dimensions of the Breaking Ranks Framework developed by the National Association of Secondary School…

Pedagogical and Social Climate in School Questionnaire: Factorial Validity and Reliability of the Teacher Version

ERIC Educational Resources Information Center

Dimitrova, Radosveta; Ferrer-Wreder, Laura; Galanti, Maria Rosaria

2016-01-01

This study evaluated the factorial structure of the Pedagogical and Social Climate in School (PESOC) questionnaire among 307 teachers in Bulgaria. The teacher edition of PESOC consists of 11 scales (i.e., Expectations for Students, Unity Among Teachers, Approach to Students, Basic Assumptions About Students' Ability to Learn, School-Home…

Student Perceptions of School Climate: A Validity and Data Use Study of a District-Developed Survey

ERIC Educational Resources Information Center

Martin-Glenn, Mya L.

2013-01-01

Over the past 25 years, researchers have consistently reported that students' perceptions of their school's climate can have a measurable impact on their level of engagement in school, motivation to learn, social development, and, ultimately, their academic achievement. In light of the continued emphasis on education reform and school…

Validation of a δ2Hn-alkane-δ18Ohemicellulose based paleohygrometer: Implications from a climate chamber experiment

NASA Astrophysics Data System (ADS)

Hepp, Johannes; Kathrin Schäfer, Imke; Tuthorn, Mario; Wüthrich, Lorenz; Zech, Jana; Glaser, Bruno; Juchelka, Dieter; Rozanski, Kazimierz; Zech, Roland; Mayr, Christoph; Zech, Michael

2017-04-01

Leaf wax-derived biomarkers, e.g. long chain n-alkanes and fatty acids, and their hydrogen isotopic composition are proved to be of a value in paleoclimatology/-hydrology research. However, the alteration of the isotopic signal as a result of the often unknown amount of leaf water enrichment challenges a direct reconstruction of the isotopic composition of paleoprecipitation. The coupling of ^2H/^1H results of leaf wax-derived biomarkers with 18O/16O results of hemicellulose-derived sugars has the potential to overcome this limitation and additionally allows reconstructing relative air humidity (RH) (Zech et al., 2013). This approach was recently validated by Tuthorn et al. (2015) by applying it to topsoil samples along a climate transect in Argentina. Accordingly, the biomarker-derived RH values correlate significantly with modern actual RH values from the respective study sites, showing the potential of the established 'paleohygrometer' approach. However, a climate chamber validation study to answer open questions regarding this approach, e.g. how robust biosynthetic fractionation factors are, is still missing. Here we present coupled δ2Hn-alkane-δ18Ohemicellulose results obtained for leaf material from a climate chamber experiment, in which Eucalyptus globulus, Vicia faba and Brassica oleracea were grown under controlled conditions (Mayr, 2003). First, the 2H and 18O enrichment of leaf water strongly reflects actual RH values of the climate chambers. Second, the biomarker-based reconstructed RH values correlate well with the actual RH values of the respective climate chamber, validating the proposed 'paleohygrometer' approach. And third, the calculated fractionation factors between the investigated leaf biomarkers (n-C29 and n-C31 for alkanes; arabinose and xylose for hemicellulose) and leaf water are close to the expected once reviewed from the literature (+27\\permil for hemicellulose; -155\\permil for n-alkanes). Nevertheless, minor dependencies of these biomarker fractionation factors from temperature and relative humidity of the climate chamber, as well as from the measured transpiration rate of the plants are evident from the data. As an outlook, the proposed coupled δ2Hn-alkane-δ18Ohemicellulose approach allows (i) more robust δ2H/δ18Oprecipitation reconstructions and (ii) paleohygrometry studies in future paleoclimate research. References Mayr, C., 2003. Möglichkeiten der Klimarekonstruktion im Holozän mit δ13C- und δ2H-Werten von Baum-Jahrringen auf der Basis von Klimakammerversuchen und Rezentstudien. Ludwig-Maximilians-Universität München. Tuthorn, M., Zech, R., Ruppenthal, M., Oelmann, Y., Kahmen, A., del Valle, H.F., Eglinton, T., Rozanski, K., Zech, M., 2015. Coupling δ2H and δ18O biomarker results yields information on relative humidity and isotopic composition of precipitation - a climate transect validation study. Biogeosciences 12, 3913-3924. Zech, M., Tuthorn, M., Detsch, F., Rozanski, K., Zech, R., Zöller, L., Zech, W., Glaser, B., 2013. A 220 ka terrestrial δ18O and deuterium excess biomarker record from an eolian permafrost paleosol sequence, NE-Siberia. Chemical Geology.

Using a rule-based envelope model to predict the expansion of habitat suitability within New Zealand for the tick Haemaphysalis longicornis, with future projections based on two climate change scenarios.

PubMed

Lawrence, K E; Summers, S R; Heath, A C G; McFadden, A M J; Pulford, D J; Tait, A B; Pomroy, W E

2017-08-30

Haemaphysalis longicornis is the only species of tick present in New Zealand which infests livestock and is also the only competent vector for Theileria orientalis. Since 2012, New Zealand has suffered from an epidemic of infectious bovine anaemia associated with T. orientalis, an obligate intracellular protozoan parasite of cattle and buffaloes. The aim of this study was to predict the spatial distribution of habitat suitability of New Zealand for the tick H. longicornis using a simple rule-based climate envelope model, to validate the model against published data and use the validated model to project an expansion in habitat suitability for H. longicornis under two alternative climate change scenarios for the periods 2046-2065 and 2081-2100, relative to the climate of 1981-2010. A rule-based climate envelope model was developed based on the environmental requirements for off-host tick survival. The resulting model was validated against a maximum entropy environmental niche model of environmental suitability for T. orientalis transmission and against a H. longicornis occurrence map. Validation was completed using the I-similarity statistic and by linear regression. The H. longicornis climate envelope model predicted that 75% of cattle farms in the North Island, 3% of cattle farms in the South Island and 54% of cattle farms in New Zealand overall have habitats potentially suitable for the establishment of H. longicornis. The validation methods showed an acceptable level of agreement between the envelope model and published data. Both of the climate change scenarios, for each of the time periods, projected only slight to moderate increases in the average farm habitat suitability scores for all the South Island regions. However, only for the West Coast, Marlborough, Tasman, and Nelson regions did these increases in environmental suitability translate into an increased proportion of cattle farms with low or high H. longicornis habitat suitability. These results will have important implications for the geographical progression of Theileria-associated bovine anaemia (TABA) in New Zealand and will also be of interest to Haemaphysalis longicornis researchers in Australia, Japan, Korea and New Zealand. Copyright © 2017 Elsevier B.V. All rights reserved.

Hydrologic Effects of Global Climate Change on a Large Drained Pine Forest

Treesearch

Devendra M. Amatya; Ge Sun; R. W. Skaggs; G. M Chescheir; J. E. Nettles

2006-01-01

A simulation study using a watershed scale forest hydrology model (DRAINWAT) was conducted to evaluate potential effects of climate change on the hydrology of a 3,000 ha managed pine forest in coastal North Carolina. The model was first validated with a five-year (1996-2000) data set fro111 the study site and then run with 50-years (1951-00) of historic weather data...

Can species distribution models really predict the expansion of invasive species?

PubMed Central

Rome, Quentin; Villemant, Claire; Courchamp, Franck

2018-01-01

Predictive studies are of paramount importance for biological invasions, one of the biggest threats for biodiversity. To help and better prioritize management strategies, species distribution models (SDMs) are often used to predict the potential invasive range of introduced species. Yet, SDMs have been regularly criticized, due to several strong limitations, such as violating the equilibrium assumption during the invasion process. Unfortunately, validation studies–with independent data–are too scarce to assess the predictive accuracy of SDMs in invasion biology. Yet, biological invasions allow to test SDMs usefulness, by retrospectively assessing whether they would have accurately predicted the latest ranges of invasion. Here, we assess the predictive accuracy of SDMs in predicting the expansion of invasive species. We used temporal occurrence data for the Asian hornet Vespa velutina nigrithorax, a species native to China that is invading Europe with a very fast rate. Specifically, we compared occurrence data from the last stage of invasion (independent validation points) to the climate suitability distribution predicted from models calibrated with data from the early stage of invasion. Despite the invasive species not being at equilibrium yet, the predicted climate suitability of validation points was high. SDMs can thus adequately predict the spread of V. v. nigrithorax, which appears to be—at least partially–climatically driven. In the case of V. v. nigrithorax, SDMs predictive accuracy was slightly but significantly better when models were calibrated with invasive data only, excluding native data. Although more validation studies for other invasion cases are needed to generalize our results, our findings are an important step towards validating the use of SDMs in invasion biology. PMID:29509789

Validating Large Scale Networks Using Temporary Local Scale Networks

USDA-ARS?s Scientific Manuscript database

The USDA NRCS Soil Climate Analysis Network and NOAA Climate Reference Networks are nationwide meteorological and land surface data networks with soil moisture measurements in the top layers of soil. There is considerable interest in scaling these point measurements to larger scales for validating ...

Detection of Greenhouse-Gas-Induced Climatic Change

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

Jones, P.D.; Wigley, T.M.L.

1998-05-26

The objective of this report is to assemble and analyze instrumental climate data and to develop and apply climate models as a basis for (1) detecting greenhouse-gas-induced climatic change, and (2) validation of General Circulation Models.

The climate change consensus extends beyond climate scientists

NASA Astrophysics Data System (ADS)

Carlton, J. S.; Perry-Hill, Rebecca; Huber, Matthew; Prokopy, Linda S.

2015-09-01

The existence of anthropogenic climate change remains a public controversy despite the consensus among climate scientists. The controversy may be fed by the existence of scientists from other disciplines publicly casting doubt on the validity of climate science. The extent to which non-climate scientists are skeptical of climate science has not been studied via direct survey. Here we report on a survey of biophysical scientists across disciplines at universities in the Big 10 Conference. Most respondents (93.6%) believe that mean temperatures have risen and most (91.9%) believe in an anthropogenic contribution to rising temperatures. Respondents strongly believe that climate science is credible (mean credibility score 6.67/7). Those who disagree about climate change disagree over basic facts (e.g., the effects of CO2 on climate) and have different cultural and political values. These results suggest that scientists who are climate change skeptics are outliers and that the majority of scientists surveyed believe in anthropogenic climate change and that climate science is credible and mature.

Orbital Noise in the Earth System is a Common Cause of Climate and Greenhouse-Gas Fluctuation

NASA Technical Reports Server (NTRS)

Liu, H. S.; Kolenkiewicz, R.; Wade, C., Jr.; Smith, David E. (Technical Monitor)

2002-01-01

The mismatch between fossil isotopic data and climate models known as the cool-tropic paradox implies that either the data are flawed or we understand very little about the climate models of greenhouse warming. Here we question the validity of the climate models on the scientific background of orbital noise in the Earth system. Our study shows that the insolation pulsation induced by orbital noise is the common cause of climate change and atmospheric concentrations of carbon dioxide and methane. In addition, we find that the intensity of the insolation pulses is dependent on the latitude of the Earth. Thus, orbital noise is the key to understanding the troubling paradox in climate models.

Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Regional Climate: Focus on Northern and Tropical African Climate Variability in the Community Earth System Model (CESM)

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

Wang, Fuyao; Yu, Yan; Notaro, Michael

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled controlmore » run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.« less

Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Regional Climate: Focus on Northern and Tropical African Climate Variability in the Community Earth System Model (CESM)

DOE PAGES

Wang, Fuyao; Yu, Yan; Notaro, Michael; ...

2017-09-27

This study advances the practicality and stability of the traditional multivariate statistical method, generalized equilibrium feedback assessment (GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise GEFA to a fully coupled controlmore » run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics: the percentage of grid cells with consistent response sign, the spatial correlation of atmospheric response patterns, the area-averaged seasonal cycle of response magnitude, and consistency in associated mechanisms between assessments. In CESM, tropical modes, namely El Niño–Southern Oscillation and the tropical Indian Ocean Basin, tropical Indian Ocean dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate. In complementary studies, stepwise GEFA is validated in terms of isolating terrestrial forcings on the atmosphere, and observed oceanic and terrestrial drivers of NTA climate are extracted to establish an observational benchmark for subsequent coupled model evaluation and development of process-based weights for regional climate projections.« less

Validation of catchment models for predicting land-use and climate change impacts. 1. Method

NASA Astrophysics Data System (ADS)

Ewen, J.; Parkin, G.

1996-02-01

Computer simulation models are increasingly being proposed as tools capable of giving water resource managers accurate predictions of the impact of changes in land-use and climate. Previous validation testing of catchment models is reviewed, and it is concluded that the methods used do not clearly test a model's fitness for such a purpose. A new generally applicable method is proposed. This involves the direct testing of fitness for purpose, uses established scientific techniques, and may be implemented within a quality assured programme of work. The new method is applied in Part 2 of this study (Parkin et al., J. Hydrol., 175:595-613, 1996).

Psychometric evaluation of the Arabic language person-centred climate questionnaire-staff version.

PubMed

Aljuaid, Mohammed; Elmontsri, Mustafa; Edvardsson, David; Rawaf, Salman; Majeed, Azeem

2018-05-01

To evaluate the psychometric properties of the Arabic language person-centred climate questionnaire-staff version. There have been increasing calls for a person-centred rather than a disease-centred approach to health care. A limited number of tools measure the extent to which care is delivered in a person-centred manner, and none of these tools have been validated for us in Arab settings. The validated form of the person-centred climate questionnaire-staff version was translated into Arabic and distributed to 152 health care staff in teaching and non-teaching hospitals in Saudi Arabia. Statistical estimates of validity and reliability were used for psychometric evaluation. Items on the Arabic form of the person-centred climate questionnaire-staff version had high reliability (Cronbach's alpha .98). Cronbach's alpha values for the three sub-scales (safety, everydayness and community), were .96, .97 and .95 respectively. Internal consistency was also high and measures of validity were very good. Arabic form of the person-centred climate questionnaire-staff version provides a valid and reliable way to measure the degree of perceived person-centredness. The tool can be used for comparing levels of person-centredness between wards, units, and public and private hospitals. The tool can also be used to measure the extent of person-centredness in health care settings in other Arab countries. © 2017 John Wiley & Sons Ltd.

Verification of GCM-generated regional seasonal precipitation for current climate and of statistical downscaling estimates under changing climate conditions

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

Busuioc, A.; Storch, H. von; Schnur, R.

Empirical downscaling procedures relate large-scale atmospheric features with local features such as station rainfall in order to facilitate local scenarios of climate change. The purpose of the present paper is twofold: first, a downscaling technique is used as a diagnostic tool to verify the performance of climate models on the regional scale; second, a technique is proposed for verifying the validity of empirical downscaling procedures in climate change applications. The case considered is regional seasonal precipitation in Romania. The downscaling model is a regression based on canonical correlation analysis between observed station precipitation and European-scale sea level pressure (SLP). Themore » climate models considered here are the T21 and T42 versions of the Hamburg ECHAM3 atmospheric GCM run in time-slice mode. The climate change scenario refers to the expected time of doubled carbon dioxide concentrations around the year 2050. Generally, applications of statistical downscaling to climate change scenarios have been based on the assumption that the empirical link between the large-scale and regional parameters remains valid under a changed climate. In this study, a rationale is proposed for this assumption by showing the consistency of the 2 x CO{sub 2} GCM scenarios in winter, derived directly from the gridpoint data, with the regional scenarios obtained through empirical downscaling. Since the skill of the GCMs in regional terms is already established, it is concluded that the downscaling technique is adequate for describing climatically changing regional and local conditions, at least for precipitation in Romania during winter.« less

Organizational Climate in Schools in Black Communities in South Africa: A Validation of the OCDQ-RS.

ERIC Educational Resources Information Center

Westhuizen, Philip van der; Mentz, Kobus

Prior to April 1, 1993, the education system in South Africa was fragmented along racial lines. Five departments of education existed, each with its own political head. This paper presents findings of a study that examined the organizational climate of the Department of Education and Training, which regulated education for the 10 major black…

Long-term potential and actual evapotranspiration of two different forests on the Atlantic Coastal Plain

Treesearch

Devendra Amatya; S. Tian; Z. Dai; Ge Sun

2016-01-01

A reliable estimate of potential evapotranspiration (PET) for a forest ecosystem is critical in ecohydrologic modeling related with water supply, vegetation dynamics, and climate change and yet is a challenging task due to its complexity. Based on long-term on-site measured hydro-climatic data and predictions from earlier validated hydrologic modeling studies...

Validating Savings Claims of Cold Climate Zero Energy Ready Homes

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

Williamson, J.; Puttagunta, S.

This study was intended to validate actual performance of three ZERHs in the Northeast to energy models created in REM/Rate v14.5 (one of the certified software programs used to generate a HERS Index) and the National Renewable Energy Laboratory’s Building Energy Optimization (BEopt™) v2.3 E+ (a more sophisticated hourly energy simulation software). This report details the validation methods used to analyze energy consumption at each home.

Study on Climate and Grassland Fire in HulunBuir, Inner Mongolia Autonomous Region, China

PubMed Central

Liu, Meifang; Zhao, Jianjun; Guo, Xiaoyi; Zhang, Zhengxiang; Tan, Gang; Yang, Jihong

2017-01-01

Grassland fire is one of the most important disturbance factors of the natural ecosystem. Climate factors influence the occurrence and development of grassland fire. An analysis of the climate conditions of fire occurrence can form the basis for a study of the temporal and spatial variability of grassland fire. The purpose of this paper is to study the effects of monthly time scale climate factors on the occurrence of grassland fire in HulunBuir, located in the northeast of the Inner Mongolia Autonomous Region in China. Based on the logistic regression method, we used the moderate-resolution imaging spectroradiometer (MODIS) active fire data products named thermal anomalies/fire daily L3 Global 1km (MOD14A1 (Terra) and MYD14A1 (Aqua)) and associated climate data for HulunBuir from 2000 to 2010, and established the model of grassland fire climate index. The results showed that monthly maximum temperature, monthly sunshine hours and monthly average wind speed were all positively correlated with the fire climate index; monthly precipitation, monthly average temperature, monthly average relative humidity, monthly minimum relative humidity and the number of days with monthly precipitation greater than or equal to 5 mm were all negatively correlated with the fire climate index. We used the active fire data from 2011 to 2014 to validate the fire climate index during this time period, and the validation result was good (Pearson’s correlation coefficient was 0.578), which showed that the fire climate index model was suitable for analyzing the occurrence of grassland fire in HulunBuir. Analyses were conducted on the temporal and spatial distribution of the fire climate index from January to December in the years 2011–2014; it could be seen that from March to May and from September to October, the fire climate index was higher, and that the fire climate index of the other months is relatively low. The zones with higher fire climate index are mainly distributed in Xin Barag Youqi, Xin Barag Zuoqi, Zalantun Shi, Oroqen Zizhiqi, and Molidawa Zizhiqi; the zones with medium fire climate index are mainly distributed in Chen Barag Qi, Ewenkizu Zizhiqi, Manzhouli Shi, and Arun Qi; and the zones with lower fire climate index are mainly distributed in Genhe Shi, Ergun city, Yakeshi Shi, and Hailar Shi. The results of this study will contribute to the quantitative assessment and management of early warning and forecasting for mid-to long-term grassland fire risk in HulunBuir. PMID:28304336

Utilizing the social media data to validate 'climate change' indices

NASA Astrophysics Data System (ADS)

Molodtsova, T.; Kirilenko, A.; Stepchenkova, S.

2013-12-01

Reporting the observed and modeled changes in climate to public requires the measures understandable by the general audience. E.g., the NASA GISS Common Sense Climate Index (Hansen et al., 1998) reports the change in climate based on six practically observable parameters such as the air temperature exceeding the norm by one standard deviation. The utility of the constructed indices for reporting climate change depends, however, on an assumption that the selected parameters are felt and connected with the changing climate by a non-expert, which needs to be validated. Dynamic discussion of climate change issues in social media may provide data for this validation. We connected the intensity of public discussion of climate change in social networks with regional weather variations for the territory of the USA. We collected the entire 2012 population of Twitter microblogging activity on climate change topic, accumulating over 1.8 million separate records (tweets) globally. We identified the geographic location of the tweets and associated the daily and weekly intensity of twitting with the following parameters of weather for these locations: temperature anomalies, 'hot' temperature anomalies, 'cold' temperature anomalies, heavy rain/snow events. To account for non-weather related events we included the articles on climate change from the 'prestige press', a collection of major newspapers. We found that the regional changes in parameters of weather significantly affect the number of tweets published on climate change. This effect, however, is short-lived and varies throughout the country. We found that in different locations different weather parameters had the most significant effect on climate change microblogging activity. Overall 'hot' temperature anomalies had significant influence on climate change twitting intensity.

Outcome of the Third Cloud Retrieval Evaluation Workshop

NASA Astrophysics Data System (ADS)

Roebeling, R.; Baum, B.; Bennartz, R.; Hamann, U.; Heidinger, A.; Thoss, A.; Walther, A.

2012-04-01

Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and inter-annual variations are needed to improve the understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics need to be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), which was held from 15-18 November 2011 in Madison, Wisconsin, USA, is to enhance our knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimising these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods that are used to prepare daily and monthly cloud parameter climatologies. An important component of the workshop is the discussion on the results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we will summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on the reasons for the observed differences. More in depth discussions were held on retrieval principles and validation, and the utilization of cloud parameters for climate research. This was done in parallel breakout sessions on cloud vertical placement; cloud physical properties, and cloud climatologies. We will present the recommendations of these sessions, propose a way forward to establish international partnerships on cloud research, and summarize the actions defined to tailor the CREW activities to missions of international programs, such as the Global Energy and Water Cycle Experiment (GEWEX) and Sustained, Co-Ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM). Finally, attention will be given to increase the traceability and uniformity of different long-term and homogeneous records of cloud parameters.

Hospital safety climate surveys: measurement issues.

PubMed

Jackson, Jeanette; Sarac, Cakil; Flin, Rhona

2010-12-01

Organizational safety culture relates to behavioural norms in the workplace and is usually assessed by safety climate surveys. These can be a diagnostic indicator on the state of safety in a hospital. This review examines recent studies using staff surveys of hospital safety climate, focussing on measurement issues. Four questionnaires (hospital survey on patient safety culture, safety attitudes questionnaire, patient safety climate in healthcare organizations, hospital safety climate scale), with acceptable psychometric properties, are now applied across countries and clinical settings. Comparisons for benchmarking must be made with caution in case of questionnaire modifications. Increasing attention is being paid to the unit and hospital level wherein distinct cultures may be located, as well as to associated measurement and study design issues. Predictive validity of safety climate is tested against safety behaviours/outcomes, with some relationships reported, although effects may be specific to professional groups/units. Few studies test the role of intervening variables that could influence the effect of climate on outcomes. Hospital climate studies are becoming a key component of healthcare safety management systems. Large datasets have established more reliable instruments that allow a more focussed investigation of the role of culture in the improvement and maintenance of staff's safety perceptions within units, as well as within hospitals.

Swedish translation and psychometric testing of the safety attitudes questionnaire (operating room version).

PubMed

Göras, Camilla; Wallentin, Fan Yang; Nilsson, Ulrica; Ehrenberg, Anna

2013-03-19

Tens of millions of patients worldwide suffer from avoidable disabling injuries and death every year. Measuring the safety climate in health care is an important step in improving patient safety. The most commonly used instrument to measure safety climate is the Safety Attitudes Questionnaire (SAQ). The aim of the present study was to establish the validity and reliability of the translated version of the SAQ. The SAQ was translated and adapted to the Swedish context. The survey was then carried out with 374 respondents in the operating room (OR) setting. Data was received from three hospitals, a total of 237 responses. Cronbach's alpha and confirmatory factor analysis (CFA) was used to evaluate the reliability and validity of the instrument. The Cronbach's alpha values for each of the factors of the SAQ ranged between 0.59 and 0.83. The CFA and its goodness-of-fit indices (SRMR 0.055, RMSEA 0.043, CFI 0.98) showed good model fit. Intercorrelations between the factors safety climate, teamwork climate, job satisfaction, perceptions of management, and working conditions showed moderate to high correlation with each other. The factor stress recognition had no significant correlation with teamwork climate, perception of management, or job satisfaction. Therefore, the Swedish translation and psychometric testing of the SAQ (OR version) has good construct validity. However, the reliability analysis suggested that some of the items need further refinement to establish sound internal consistency. As suggested by previous research, the SAQ is potentially a useful tool for evaluating safety climate. However, further psychometric testing is required with larger samples to establish the psychometric properties of the instrument for use in Sweden.

Toward Construct Validation of a Transfer Climate Instrument. [and] Improving Positive Transfer: A Test of Relapse Prevention Training on Transfer Outcomes.

ERIC Educational Resources Information Center

Holton, Elwood F., III; And Others

1997-01-01

Includes "Toward Construct Validation of a Transfer Climate Instrument" (Holton et al.); "Improving Positive Transfer: A Test of Relapse Prevention Training on Transfer Outcomes" (Burke); "Invited Reaction: Progress or Relapse?" (Newstrom); "Invited Reaction: Theory, Research, and Practice" (Tang);…

Factor structure of the Essen Climate Evaluation Schema measure of social climate in a UK medium-security setting.

PubMed

Milsom, Sophia A; Freestone, Mark; Duller, Rachel; Bouman, Marisa; Taylor, Celia

2014-04-01

Social climate has an influence on a number of treatment-related factors, including service users' behaviour, staff morale and treatment outcomes. Reliable assessment of social climate is, therefore, beneficial within forensic mental health settings. The Essen Climate Evaluation Schema (EssenCES) has been validated in forensic mental health services in the UK and Germany. Preliminary normative data have been produced for UK high-security national health services and German medium-security and high-security services. We aim to validate the use of the EssenCES scale (English version) and provide preliminary normative data in UK medium-security hospital settings. The EssenCES scale was completed in a medium-security mental health service as part of a service-wide audit. A total of 89 patients and 112 staff completed the EssenCES. The three-factor structure of the EssenCES and its internal construct validity were maintained within the sample. Scores from this medium-security hospital sample were significantly higher than those from earlier high-security hospital data, with three exceptions--'patient cohesion' according to the patients and 'therapeutic hold' according to staff and patients. Our data support the use of the EssenCES scale as a valid measure for assessing social climate within medium-security hospital settings. Significant differences between the means of high-security and medium-security service samples imply that degree of security is a relevant factor affecting the ward climate and that in monitoring quality of secure services, it is likely to be important to apply different scores to reflect standards. Copyright © 2013 John Wiley & Sons, Ltd.

Cross - Scale Intercomparison of Climate Change Impacts Simulated by Regional and Global Hydrological Models in Eleven Large River Basins

NASA Technical Reports Server (NTRS)

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.; Dankers, R.; Daggupati, P.; Donnelly, C.; Florke, M.; Huang, S.; Motovilov, Y.; Buda, S.;

Development and testing of transfer functions for generating quantitative climatic estimates from Australian pollen data

NASA Astrophysics Data System (ADS)

Cook, Ellyn J.; van der Kaars, Sander

2006-10-01

We review attempts to derive quantitative climatic estimates from Australian pollen data, including the climatic envelope, climatic indicator and modern analogue approaches, and outline the need to pursue alternatives for use as input to, or validation of, simulations by models of past, present and future climate patterns. To this end, we have constructed and tested modern pollen-climate transfer functions for mainland southeastern Australia and Tasmania using the existing southeastern Australian pollen database and for northern Australia using a new pollen database we are developing. After testing for statistical significance, 11 parameters were selected for mainland southeastern Australia, seven for Tasmania and six for northern Australia. The functions are based on weighted-averaging partial least squares regression and their predictive ability evaluated against modern observational climate data using leave-one-out cross-validation. Functions for summer, annual and winter rainfall and temperatures are most robust for southeastern Australia, while in Tasmania functions for minimum temperature of the coldest period, mean winter and mean annual temperature are the most reliable. In northern Australia, annual and summer rainfall and annual and summer moisture indexes are the strongest. The validation of all functions means all can be applied to Quaternary pollen records from these three areas with confidence. Copyright

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

Legeais, JeanFrancois; Benveniste, Jérôme

2016-07-01

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

An adaptation strategy of sandland peasants in Yogyakarta toward climate change

NASA Astrophysics Data System (ADS)

Rusdiyana, E.; Suminah

2018-03-01

This study aims to explore and describe the adaptation strategies of sandland peasants toward climate change. Qualitative research method was employed and the data were collected through observation. In addition, the recording of the data, interview and the validity of data were determined by triangulation of sources. The results of the research showed that the adaptation strategies of sandland peasants toward climate change were; (1) the adjustment of crop varieties, (2) the utilization of productive crops as wind breaking, and (3) the irrigation system using “sumur panthek”.

Observed SWE trends and climate analysis for Northwest Pacific North America: validation for future projection of SWE using the CRCM and VIC

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Bronaugh, D.; Rodenhuis, D.

2008-12-01

Observational databases of snow water equivalent (SWE) have been collected from Alaska, western US states and the Canadian provinces of British Columbia, Alberta, Saskatchewan, and territories of NWT, and the Yukon. These databases were initially validated to remove inconsistencies and errors in the station records, dates or the geographic co-ordinates of the station. The cleaned data was then analysed for historical (1950 to 2006) trend using emerging techniques for trend detection based on (first of the month) estimates for January to June. Analysis of SWE showed spatial variability in the count of records across the six month time period, and this study illustrated differences between Canadian and US (or the north and south) collection. Two different data sets (one gridded and one station) were then used to analyse April 1st records, for which there was the greatest spatial spread of station records for analysis with climate information. Initial results show spatial variability (in both magnitude and direction of trend) for trend results, and climate correlations and principal components indicate different drivers of change in SWE across the western US, Canada and north to Alaska. These results will be used to validate future predictions of SWE that are being undertaken using the Canadian Regional Climate Model (CRCM) and the Variable Infiltration Capacity (VIC) hydrologic model for Western Northern America (CRCM) and British Columbia (VIC).

Modeling the Relationship between Safety Climate and Safety Performance in a Developing Construction Industry: A Cross-Cultural Validation Study

PubMed Central

Zahoor, Hafiz; Chan, Albert P. C.; Utama, Wahyudi P.; Gao, Ran; Zafar, Irfan

2017-01-01

This study attempts to validate a safety performance (SP) measurement model in the cross-cultural setting of a developing country. In addition, it highlights the variations in investigating the relationship between safety climate (SC) factors and SP indicators. The data were collected from forty under-construction multi-storey building projects in Pakistan. Based on the results of exploratory factor analysis, a SP measurement model was hypothesized. It was tested and validated by conducting confirmatory factor analysis on calibration and validation sub-samples respectively. The study confirmed the significant positive impact of SC on safety compliance and safety participation, and negative impact on number of self-reported accidents/injuries. However, number of near-misses could not be retained in the final SP model because it attained a lower standardized path coefficient value. Moreover, instead of safety participation, safety compliance established a stronger impact on SP. The study uncovered safety enforcement and promotion as a novel SC factor, whereas safety rules and work practices was identified as the most neglected factor. The study contributed to the body of knowledge by unveiling the deviations in existing dimensions of SC and SP. The refined model is expected to concisely measure the SP in the Pakistani construction industry, however, caution must be exercised while generalizing the study results to other developing countries. PMID:28350366

Modeling the Relationship between Safety Climate and Safety Performance in a Developing Construction Industry: A Cross-Cultural Validation Study.

PubMed

Zahoor, Hafiz; Chan, Albert P C; Utama, Wahyudi P; Gao, Ran; Zafar, Irfan

2017-03-28

This study attempts to validate a safety performance (SP) measurement model in the cross-cultural setting of a developing country. In addition, it highlights the variations in investigating the relationship between safety climate (SC) factors and SP indicators. The data were collected from forty under-construction multi-storey building projects in Pakistan. Based on the results of exploratory factor analysis, a SP measurement model was hypothesized. It was tested and validated by conducting confirmatory factor analysis on calibration and validation sub-samples respectively. The study confirmed the significant positive impact of SC on safety compliance and safety participation , and negative impact on number of self-reported accidents/injuries . However, number of near-misses could not be retained in the final SP model because it attained a lower standardized path coefficient value. Moreover, instead of safety participation , safety compliance established a stronger impact on SP. The study uncovered safety enforcement and promotion as a novel SC factor, whereas safety rules and work practices was identified as the most neglected factor. The study contributed to the body of knowledge by unveiling the deviations in existing dimensions of SC and SP. The refined model is expected to concisely measure the SP in the Pakistani construction industry, however, caution must be exercised while generalizing the study results to other developing countries.

Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

2015-07-01

The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015.

PubMed

Abatzoglou, John T; Dobrowski, Solomon Z; Parks, Sean A; Hegewisch, Katherine C

2018-01-09

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015

NASA Astrophysics Data System (ADS)

Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A.; Hegewisch, Katherine C.

2018-01-01

We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958-2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and solar radiation. TerraClimate additionally produces monthly surface water balance datasets using a water balance model that incorporates reference evapotranspiration, precipitation, temperature, and interpolated plant extractable soil water capacity. These data provide important inputs for ecological and hydrological studies at global scales that require high spatial resolution and time varying climate and climatic water balance data. We validated spatiotemporal aspects of TerraClimate using annual temperature, precipitation, and calculated reference evapotranspiration from station data, as well as annual runoff from streamflow gauges. TerraClimate datasets showed noted improvement in overall mean absolute error and increased spatial realism relative to coarser resolution gridded datasets.

Development and validation of the Family Motivational Climate Questionnaire (FMC-Q).

PubMed

Alonso Tapia, Jesús; Simón Rueda, Cecilia; Asensio Fuentes, César

2013-01-01

The goal of this study was to develop and validate the Family Motivational Climate Questionnaire (FMCQ). Parental involvement (PI) affects children's academic orientations. However, PI questionnaires had not considered parenting behaviours from the perspective of motivational theories. It was therefore decided to develop the FMCQ. 570 Secondary-School students formed the sample. To validate the FMCQ, confirmatory factor analyses, reliability analysis and correlation and regression analyses were conducted. Children's attribution to parents of perceived change in motivational variables affecting achievement, were used as external criteria. Results support most of the hypotheses either related to the FMCQ structure or to its moderating role as predictor of school achievement and of attribution to parents of changes in different motivational variables --interest, effort, perceived ability, success expectancies, resilience, and satisfaction. The results underline the importance of acting on FMC-components in order to improve Children's motivation and achievement.

Comparative Assessment of a New Hydrological Modelling Approach for Prediction of Runoff in Gauged and Ungauged Basins, and Climate Change Impacts Assessment: A Case Study from Benin.

NASA Astrophysics Data System (ADS)

GABA, C. O. U.; Alamou, E.; Afouda, A.; Diekkrüger, B.

2016-12-01

Assessing water resources is still an important challenge especially in the context of climatic changes. Although numerous hydrological models exist, new approaches are still under investigation. In this context, we investigate a new modelling approach based on the Physics Principle of Least Action which was first applied to the Bétérou catchment in Benin and gave very good results. The study presents new hypotheses to go further in the model development with a view of widening its application. The improved version of the model MODHYPMA was applied to sixteen (16) subcatchments in Bénin, West Africa. Its performance was compared to two well-known lumped conceptual models, the GR4J and HBV models. The model was successfully calibrated and validated and showed a good performance in most catchments. The analysis revealed that the three models have similar performance and timing errors. But in contrary to other models, MODHYMA is subject to a less loss of performance from calibration to validation. In order to evaluate the usefulness of our model for the prediction of runoff in ungauged basins, model parameters were estimated from the physical catchments characteristics. We relied on statistical methods applied on calibrated model parameters to deduce relationships between parameters and physical catchments characteristics. These relationships were further tested and validated on gauged basins that were considered ungauged. This regionalization was also performed for GR4J model.We obtained NSE values greater than 0.7 for MODHYPMA while the NSE values for GR4J were inferior to 0.5. In the presented study, the effects of climate change on water resources in the Ouémé catchment at the outlet of Savè (about 23 500 km2) are quantified. The output of a regional climate model was used as input to the hydrological models.Computed within the GLOWA-IMPETUS project, the future climate projections (describing a rainfall reduction of up to 15%) are derived from the regional climate model REMO driven by the global ECHAM model.The results reveal a significant decrease in future water resources (of -66% to -53% for MODHYPMA and of -59% to -46% for GR4J) for the IPCC climate scenarios A1B and B1.

Multi-Site and Multi-Variables Statistical Downscaling Technique in the Monsoon Dominated Region of Pakistan

NASA Astrophysics Data System (ADS)

Khan, Firdos; Pilz, Jürgen

2016-04-01

South Asia is under the severe impacts of changing climate and global warming. The last two decades showed that climate change or global warming is happening and the first decade of 21st century is considered as the warmest decade over Pakistan ever in history where temperature reached 53 0C in 2010. Consequently, the spatio-temporal distribution and intensity of precipitation is badly effected and causes floods, cyclones and hurricanes in the region which further have impacts on agriculture, water, health etc. To cope with the situation, it is important to conduct impact assessment studies and take adaptation and mitigation remedies. For impact assessment studies, we need climate variables at higher resolution. Downscaling techniques are used to produce climate variables at higher resolution; these techniques are broadly divided into two types, statistical downscaling and dynamical downscaling. The target location of this study is the monsoon dominated region of Pakistan. One reason for choosing this area is because the contribution of monsoon rains in this area is more than 80 % of the total rainfall. This study evaluates a statistical downscaling technique which can be then used for downscaling climatic variables. Two statistical techniques i.e. quantile regression and copula modeling are combined in order to produce realistic results for climate variables in the area under-study. To reduce the dimension of input data and deal with multicollinearity problems, empirical orthogonal functions will be used. Advantages of this new method are: (1) it is more robust to outliers as compared to ordinary least squares estimates and other estimation methods based on central tendency and dispersion measures; (2) it preserves the dependence among variables and among sites and (3) it can be used to combine different types of distributions. This is important in our case because we are dealing with climatic variables having different distributions over different meteorological stations. The proposed model will be validated by using the (National Centers for Environmental Prediction / National Center for Atmospheric Research) NCEP/NCAR predictors for the period of 1960-1990 and validated for 1990-2000. To investigate the efficiency of the proposed model, it will be compared with the multivariate multiple regression model and with dynamical downscaling climate models by using different climate indices that describe the frequency, intensity and duration of the variables of interest. KEY WORDS: Climate change, Copula, Monsoon, Quantile regression, Spatio-temporal distribution.

Development and validity of the Emotion and Motivation Self-regulation Questionnaire (EMSR-Q).

PubMed

Alonso-Tapia, Jesús; Panadero Calderón, Ernesto; Díaz Ruiz, Miguel A

2014-07-15

This study has two objectives, first, to develop and validate the "Emotion and Motivation Self-regulation Questionnaire" (EMSR-Q), and second, to analyze (in the context of the questionnaire validation process) the relationships between self-regulation styles (SRS) rooted in goal orientations, and classroom motivational climate (CMC). A total of 664 Secondary Education students from Madrid (Spain) formed the sample of the study. It was divided randomly in two groups to perform confirmatory factor analysis and to cross-validate the results. Both analyses supported a five first-order factor structure, organized around two second-order factors, "Learning self-regulation style" (LSR) and "Avoidance self-regulation style" (ASR): (χ 2 /df = 2.71; GFI = .89; IFI = .84; CFI = .84; RMSEA = .07). Hypotheses concerning the relationships between SRS, goal orientations and expectancies are supported by additional correlation and factor analyses. Moreover, several regression analyses supported for the most part of the remaining hypotheses concerning the role of self-regulation styles as predictors of classroom motivational climate (CMC) perception, of change in self-regulation attributed to teacher work, and of students' satisfaction with this same work. Theoretical and practical implications are discussed.

Estimation of future flow regime for a spatially varied Himalayan watershed using improved multi-site calibration method of SWAT model.

NASA Astrophysics Data System (ADS)

Pradhanang, S. M.; Hasan, M. A.; Booth, P.; Fallatah, O.

2016-12-01

The monsoon and snow driven regime in the Himalayan region has received increasing attention in the recent decade regarding the effects of climate change on hydrologic regimes. Modeling streamflow in such spatially varied catchment requires proper calibration and validation in hydrologic modeling. While calibration and validation are time consuming and computationally intensive, an effective regionalized approach with multi-site information is crucial for flow estimation, especially in daily scale. In this study, we adopted a multi-site approach to calibration and validation of the Soil Water Assessment Tool (SWAT) model for the Karnali river catchment, which is characterized as being the most vulnerable catchment to climate change in the Himalayan region. APHRODITE's (Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation) daily gridded precipitation data, one of the accurate and reliable weather date over this region were utilized in this study. The model evaluation of the entire catchment divided into four sub-catchments, utilizing discharge records from 1963 to 2010. In previous studies, multi-site calibration used only a single set of calibration parameters for all sub-catchment of a large watershed. In this study, we introduced a technique that can incorporate different sets of calibration parameters for each sub-basin, which eventually ameliorate the flow of the whole watershed. Results show that the calibrated model with new method can capture almost identical pattern of flow over the region. The predicted daily streamflow matched the observed values, with a Nash-Sutcliffe coefficient of 0.73 during calibration and 0.71 during validation period. The method perfumed better than existing multi-site calibration methods. To assess the influence of continued climate change on hydrologic processes, we modified the weather inputs for the model using precipitation and temperature changes for two Representative Concentration Pathways (RCPs) scenarios, RCP 4.5 and 8.5. Climate simulation for RCP scenarios were conducted from 1981-2100, where 1981-2005 was considered as baseline and 2006-2100 was considered as the future projection. The result shows that probability of flooding will eventually increase in future years due to increased flow in both scenarios.

Impact of Climate Change on Water Resources in the Guadalquivir River Basin

NASA Astrophysics Data System (ADS)

Yeste Donaire, P.; García-Valdecasas-Ojeda, M.; Góngora García, T. M.; Gámiz-Fortis, S. R.; Castro-Diez, Y.; Esteban-Parra, M. J.

2017-12-01

Climate change has lead to a decrease of precipitation and an increase of temperature in the Mediterranean Basin during the last fifty years. These changes will be more intense over the course of the 21thcentury according to global climate projections. As a consequence, water resources are expected to decrease, particularly in the Guadalquivir River Basin. This study focuses on the hydrological response of the Guadalquivir River Basin to the climate change. For this end, firstly, the implementation of the Variable Infiltration Capacity (VIC) model in the Basin was carried out. The VIC model was calibrated with a dataset of daily precipitation, temperature and streamflow for the period 1990-2000. Precipitation and temperature data were extracted from SPAIN02, a dataset that covers the Peninsular Spain at 0.11º of spatial resolution. Streamflow data were gathered for a representative subset of gauging stations in the basin. These data were provided by the Spanish Center for Public Work Experimentation and Study (CEDEX). Subsequently, the VIC model was validated for the period 2000-2005 in order to verify that the model outputs fit well with the observational data. After the validation of the VIC model for present climate, secondly, the effect of climate change on the Guadalquivir River Basin will be analyzed by developing several simulations of the streamflow for future climate. Precipitation and temperature data will be obtained in this case from future projections coming from high resolution (at 0.088º) simulations carried out with the Weather Research and Forecasting (WRF) model for the Iberian Peninsula. These last simulations will be driven under two different Representative Concentration Pathway (RCP) scenarios, RCP 4.5 and RCP 8.5 for the periods 2021-50 and 2071-2100. The first results of this work show that the VIC model outputs are in good agreement with the observed streamflow for both the calibration and validation periods. In the context of climate change, a generalized decrease in surface and subsurface water resources is expected in the Guadalquivir River Basin. All these results will be of interest for water policy makers and practitioners in the next decades. ACKNOWLEDGEMENTS: This work has been financed by the projects P11-RNM-7941 (Junta de Andalucía) and CGL2013-48539-R (MINECO-Spain, FEDER).

Multilevel Safety Climate and Safety Performance in the Construction Industry: Development and Validation of a Top-Down Mechanism

PubMed Central

Gao, Ran; Chan, Albert P.C.; Utama, Wahyudi P.; Zahoor, Hafiz

2016-01-01

The character of construction projects exposes front-line workers to dangers and accidents. Safety climate has been confirmed to be a predictor of safety performance in the construction industry. This study aims to explore the underlying mechanisms of the relationship between multilevel safety climate and safety performance. An integrated model was developed to study how particular safety climate factors of one level affect those of other levels, and then affect safety performance from the top down. A questionnaire survey was administered on six construction sites in Vietnam. A total of 1030 valid questionnaires were collected from this survey. Approximately half of the data were used to conduct exploratory factor analysis (EFA) and the remaining data were submitted to structural equation modeling (SEM). Top management commitment (TMC) and supervisors’ expectation (SE) were identified as factors to represent organizational safety climate (OSC) and supervisor safety climate (SSC), respectively, and coworkers’ caring and communication (CCC) and coworkers’ role models (CRM) were identified as factors to denote coworker safety climate (CSC). SEM results show that OSC factor is positively related to SSC factor and CSC factors significantly. SSC factor could partially mediate the relationship between OSC factor and CSC factors, as well as the relationship between OSC factor and safety performance. CSC factors partially mediate the relationship between OSC factor and safety performance, and the relationship between SSC factor and safety performance. The findings imply that a positive safety culture should be established both at the organizational level and the group level. Efforts from all top management, supervisors, and coworkers should be provided to improve safety performance in the construction industry. PMID:27834823

Multilevel Safety Climate and Safety Performance in the Construction Industry: Development and Validation of a Top-Down Mechanism.

PubMed

Gao, Ran; Chan, Albert P C; Utama, Wahyudi P; Zahoor, Hafiz

2016-11-08

The character of construction projects exposes front-line workers to dangers and accidents. Safety climate has been confirmed to be a predictor of safety performance in the construction industry. This study aims to explore the underlying mechanisms of the relationship between multilevel safety climate and safety performance. An integrated model was developed to study how particular safety climate factors of one level affect those of other levels, and then affect safety performance from the top down. A questionnaire survey was administered on six construction sites in Vietnam. A total of 1030 valid questionnaires were collected from this survey. Approximately half of the data were used to conduct exploratory factor analysis (EFA) and the remaining data were submitted to structural equation modeling (SEM). Top management commitment (TMC) and supervisors' expectation (SE) were identified as factors to represent organizational safety climate (OSC) and supervisor safety climate (SSC), respectively, and coworkers' caring and communication (CCC) and coworkers' role models (CRM) were identified as factors to denote coworker safety climate (CSC). SEM results show that OSC factor is positively related to SSC factor and CSC factors significantly. SSC factor could partially mediate the relationship between OSC factor and CSC factors, as well as the relationship between OSC factor and safety performance. CSC factors partially mediate the relationship between OSC factor and safety performance, and the relationship between SSC factor and safety performance. The findings imply that a positive safety culture should be established both at the organizational level and the group level. Efforts from all top management, supervisors, and coworkers should be provided to improve safety performance in the construction industry.

Nonannual tree rings in a climate-sensitive Prioria copaifera chronology in the Atrato River, Colombia.

PubMed

Herrera-Ramirez, David; Andreu-Hayles, Laia; Del Valle, Jorge I; Santos, Guaciara M; Gonzalez, Paula L M

2017-08-01

In temperate climates, tree growth dormancy usually ensures the annual nature of tree rings, but in tropical environments, determination of annual periodicity can be more complex. The purposes of the work are as follows: (1) to generate a reliable tree-ring width chronology for Prioria copaifera Griseb. (Leguminoceae), a tropical tree species dwelling in the Atrato River floodplains, Colombia; (2) to assess the climate signal recorded by the tree-ring records; and (3) to validate the annual periodicity of the tree rings using independent methods. We used standard dendrochronological procedures to generate the P. copaifera tree-ring chronology. We used Pearson correlations to evaluate the relationship of the chronology with the meteorological records, climate regional indices, and gridded precipitation/sea surface temperature products. We also evaluated 24 high-precision 14 C measurements spread over a range of preselected tree rings, with assigned calendar years by dendrochronological techniques, before and after the bomb spike in order to validate the annual nature of the tree rings. The tree-ring width chronology was statistically reliable, and it correlated significantly with local records of annual and October-December (OND) streamflow and precipitation across the upper river watershed (positive), and OND temperature (negative). It was also significantly related to the Oceanic Niño Index, Pacific Decadal Oscillation, and the Southern Oscillation Index, as well as sea surface temperatures over the Caribbean and the Pacific region. However, 14 C high-precision measurements over the tree rings demonstrated offsets of up to 40 years that indicate that P. copaifera can produce more than one ring in certain years. Results derived from the strongest climate-growth relationship during the most recent years of the record suggest that the climatic signal reported may be due to the presence of annual rings in some of those trees in recent years. Our study alerts about the risk of applying dendrochronology in species with challenging anatomical features defining tree rings, commonly found in the tropics, without an independent validation of annual periodicity of tree rings. High-precision 14 C measurements in multiple trees are a useful method to validate the identification of annual tree rings.

Construction and Validation of the Lesbian, Gay, Bisexual, and Transgendered Climate Inventory

ERIC Educational Resources Information Center

Liddle, Becky J.; Luzzo, Darrell Anthony; Hauenstein, Anita L.; Schuck, Kelly

2004-01-01

Workplace climate refers to formal and informal organizational characteristics contributing to employee welfare. Workplace climates for lesbian, gay, bisexual, and transgendered (LGBT) employees range from actively supportive to openly hostile. An instrument measuring LGBT workplace climate will enable research on vocational adjustment of LGBT…

The FORBIO Climate data set for climate analyses

NASA Astrophysics Data System (ADS)

Delvaux, C.; Journée, M.; Bertrand, C.

2015-06-01

In the framework of the interdisciplinary FORBIO Climate research project, the Royal Meteorological Institute of Belgium is in charge of providing high resolution gridded past climate data (i.e. temperature and precipitation). This climate data set will be linked to the measurements on seedlings, saplings and mature trees to assess the effects of climate variation on tree performance. This paper explains how the gridded daily temperature (minimum and maximum) data set was generated from a consistent station network between 1980 and 2013. After station selection, data quality control procedures were developed and applied to the station records to ensure that only valid measurements will be involved in the gridding process. Thereafter, the set of unevenly distributed validated temperature data was interpolated on a 4 km × 4 km regular grid over Belgium. The performance of different interpolation methods has been assessed. The method of kriging with external drift using correlation between temperature and altitude gave the most relevant results.

Assessing the impact of climate change upon hydrology and agriculture in the Indrawati Basin, Nepal.

NASA Astrophysics Data System (ADS)

Palazzoli, Irene; Bocchiola, Daniele; Nana, Ester; Maskey, Shreedhar; Uhlenbrook, Stefan

2014-05-01

Agriculture is sensitive to climate change, especially to temperature and precipitation changes. The purpose of this study was to evaluate the climate change impacts upon rain-fed crops production in the Indrawati river basin, Nepal. The Soil and Water Assessment Tool SWAT model was used to model hydrology and cropping systems in the catchment, and to predict the influence of different climate change scenarios therein. Daily weather data collected from about 13 weather stations during 4 decades were used to constrain the SWAT model, and data from two hydrometric stations used to calibrate/validate it. Then management practices (crop calendar) were applied to specific Hydrological Response Units (HRUs) for the main crops of the region, rice, corn and wheat. Manual calibration of crop production was also carried, against values of crop yield in the area from literature. The calibrated and validated model was further applied to assess the impact of three future climate change scenarios (RCPs) upon the crop productivity in the region. Three climate models (GCMs) were adopted, each with three RCPs (2.5, 4.5, 8.5). Hence, impacts of climate change were assessed considering three time windows, namely a baseline period (1995-2004), the middle of century (2045-2054) and the end of century (2085-2094). For each GCM and RCP future hydrology and yield was compared to baseline scenario. The results displayed slightly modified hydrological cycle, and somewhat small variation in crop production, variable with models and RCPs, and for crop type, the largest being for wheat. Keywords: Climate Change, Nepal, hydrological cycle, crop yield.

Marine ARM GPCI Investigation of Clouds Infrared Sea Surface Temperature Autonomous Radiometer (ISAR) Field Campaign Report

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

Reynolds, R. Michael; Long, Charles N.

Sea surface temperature (SST) is one of the most appropriate and important climate parameters: a widespread increase is an indicator of global warming and modifications of the geographical distribution of SST are an extremely sensitive indicator of climate change. There is high demand for accurate, reliable, high-spatial-and-temporal-resolution SST measurements for the parameterization of ocean-atmosphere heat, momentum, and gas (SST is therefore critical to understanding the processes controlling the global carbon dioxide budget) fluxes, for detailed diagnostic and process-orientated studies to better understand the behavior of the climate system, as model boundary conditions, for assimilation into climate models, and for themore » rigorous validation of climate model output. In order to achieve an overall net flux uncertainty < 10 W/m 2 (Bradley and Fairall, 2006), the sea surface (skin) temperature (SSST) must be measured to an error < 0.1 C and a precision of 0.05 C. Anyone experienced in shipboard meteorological measurements will recognize this is a tough specification. These demands require complete confidence in the content, interpretation, accuracy, reliability, and continuity of observational SST data—criteria that can only be fulfilled by the successful implementation of an ongoing data product validation strategy.« less

Middle School Improvement and Reform: Development and Validation of a School-Level Assessment of Climate, Cultural Pluralism, and School Safety.

ERIC Educational Resources Information Center

Brand, Stephen; Felner, Robert; Shim, Minsuk; Seitsinger, Anne; Dumas, Thaddeus

2003-01-01

Examines the structure of perceived school climate and the relationship of climate dimensions to adaptation of students who attend middle-grade-level schools. The climate scales exhibited a stable dimensional structure, high levels of internal consistency, and moderate levels of stability. Ratings of multiple climate dimensions were associated…

Lost in Translation? Psychometric Properties and Construct Validity of the English Essen Climate Evaluation Schema (EssenCES) Social Climate Questionnaire

ERIC Educational Resources Information Center

Tonkin, Matthew; Howells, Kevin; Ferguson, Eamonn; Clark, Amanda; Newberry, Michelle; Schalast, Norbert

2012-01-01

The social climate of correctional (forensic) settings is likely to have a significant impact on the outcome of treatment and the overall functioning of these units. The Essen Climate Evaluation Schema (EssenCES) provides an objective way of measuring social climate that overcomes the content, length, and psychometric limitations of other…

[Reliability and construct validity of an instrument to asses the Self-perception of Family Health Status].

PubMed

Lima Rodríguez, Joaquín Salvador; Lima Serrano, Marta; Jiménez Picón, Nerea; Domínguez Sánchez, Isabel

2012-10-01

Family health determines and it is determined by family´s capacity to function effectively as a biosocial unit in a given culture and society. The main of study has been to test reliability and construct validity of an instrument to asses the Self-perception of Family Health Status. We validated its content by an on-line Dephi panel with experts. We surveyed 258 families in them homes or in primary health centres from Seville, Spain. We administered the instrument that has five Likert scales: Family climate, Family integrity, Family functioning, and Family resistance. We tested reliability by Cronbach Alpha and construct validity by exploratory factor analysis. The five scales obtained values α between 0.73 for the Family Climate and 0.89 for Family Integrity. They showed evidence of one-dimensional interpretation after factor analysis, a) all items got weights r>0.30 in first factor before rotations, b) the first factor explained a significant proportion of variance before rotations, and c) the total variance explained by the main factors extracted was greater than 50%. The scales showed their reliability and validity. They could be employed to assess the self-perception of family health status.

Impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling

NASA Astrophysics Data System (ADS)

Chen, Jie; Li, Chao; Brissette, François P.; Chen, Hua; Wang, Mingna; Essou, Gilles R. C.

2018-05-01

Bias correction is usually implemented prior to using climate model outputs for impact studies. However, bias correction methods that are commonly used treat climate variables independently and often ignore inter-variable dependencies. The effects of ignoring such dependencies on impact studies need to be investigated. This study aims to assess the impacts of correcting the inter-variable correlation of climate model outputs on hydrological modeling. To this end, a joint bias correction (JBC) method which corrects the joint distribution of two variables as a whole is compared with an independent bias correction (IBC) method; this is considered in terms of correcting simulations of precipitation and temperature from 26 climate models for hydrological modeling over 12 watersheds located in various climate regimes. The results show that the simulated precipitation and temperature are considerably biased not only in the individual distributions, but also in their correlations, which in turn result in biased hydrological simulations. In addition to reducing the biases of the individual characteristics of precipitation and temperature, the JBC method can also reduce the bias in precipitation-temperature (P-T) correlations. In terms of hydrological modeling, the JBC method performs significantly better than the IBC method for 11 out of the 12 watersheds over the calibration period. For the validation period, the advantages of the JBC method are greatly reduced as the performance becomes dependent on the watershed, GCM and hydrological metric considered. For arid/tropical and snowfall-rainfall-mixed watersheds, JBC performs better than IBC. For snowfall- or rainfall-dominated watersheds, however, the two methods behave similarly, with IBC performing somewhat better than JBC. Overall, the results emphasize the advantages of correcting the P-T correlation when using climate model-simulated precipitation and temperature to assess the impact of climate change on watershed hydrology. However, a thorough validation and a comparison with other methods are recommended before using the JBC method, since it may perform worse than the IBC method for some cases due to bias nonstationarity of climate model outputs.

Testing the reliability and validity of a measure of safety climate.

PubMed

Anderson, E; McGovern, P M; Kochevar, L; Vesley, D; Gershon, R

2000-01-01

The lack of compliance with universal precautions (UP) is well documented across a wide variety of healthcare professions and has been reported both before and after the enactment of the Occupational Safety and Health Administration's Bloodborne Pathogens Standard. Gershon, Karkashian, and Felknor (1994) found that several factors correlated significantly with healthcare workers' lack of compliance with UP, including a measure of organizational safety climate (e.g., the employees' perception of their organizational culture and practices regarding safety). We conducted a secondary analysis using data from a cross-sectional survey of a convenience sample of 1,746 healthcare workers at risk of occupational exposure to bloodborne pathogens to assess the validity and reliability of Gershon's measure of safety climate. Findings revealed no relationship between safety climate and employees' gender, age, education, tenure in position, profession, hours worked per day, perceived risk, attitude toward risk, and training. An association was demonstrated between safety climate and (1) healthcare worker compliance with UP and (2) the availability of personal protective equipment, providing support for the construct validity of this measure of safety climate. These findings could be used by occupational health professionals to assess employees' perceptions of the safety culture and practices in the workplace and to guide the institution's risk management efforts in association with U.P.

A stakeholder project to model water temperature under future climate scenarios in the Satus and Toppenish watersheds of the Yakima River Basinin Washington, USA

USGS Publications Warehouse

Graves, D.; Maule, A.

2014-01-01

The goal of this study was to support an assessment of the potential effects of climate change on select natural, social, and economic resources in the Yakima River Basin. A workshop with local stakeholders highlighted the usefulness of projecting climate change impacts on anadromous steelhead (Oncorhynchus mykiss), a fish species of importance to local tribes, fisherman, and conservationists. Stream temperature is an important environmental variable for the freshwater stages of steelhead. For this study, we developed water temperature models for the Satus and Toppenish watersheds, two of the key stronghold areas for steelhead in the Yakima River Basin. We constructed the models with the Stream Network Temperature Model (SNTEMP), a mechanistic approach to simulate water temperature in a stream network. The models were calibrated over the April 15, 2008 to September 30, 2008 period and validated over the April 15, 2009 to September 30, 2009 period using historic measurements of stream temperature and discharge provided by the Yakama Nation Fisheries Resource Management Program. Once validated, the models were run to simulate conditions during the spring and summer seasons over a baseline period (1981–2005) and two future climate scenarios with increased air temperature of 1°C and 2°C. The models simulated daily mean and maximum water temperatures at sites throughout the two watersheds under the baseline and future climate scenarios.

Dimensions of Safety Climate among Iranian Nurses.

PubMed

Konjin, Z Naghavi; Shokoohi, Y; Zarei, F; Rahimzadeh, M; Sarsangi, V

2015-10-01

Workplace safety has been a concern of workers and managers for decades. Measuring safety climate is crucial in improving safety performance. It is also a method of benchmarking safety perception. To develop and validate a psychometrics scale for measuring nurses' safety climate. Literature review, subject matter experts and nurse's judgment were used in items developing. Content validity and reliability for new tool were tested by content validity index (CVI) and test-retest analysis, respectively. Exploratory factor analysis (EFA) with varimax rotation was used to improve the interpretation of latent factors. A 40-item scale in 6 factors was developed, which could explain 55% of the observed variance. The 6 factors included employees' involvement in safety and management support, compliance with safety rules, safety training and accessibility to personal protective equipment, hindrance to safe work, safety communication and job pressure, and individual risk perception. The proposed scale can be used in identifying the needed areas to implement interventions in safety climate of nurses.

The evaluation of the climate change effects on maize and fennel cultivation by means of an hydrological physically based model: the case study of an irrigated district of southern Italy

NASA Astrophysics Data System (ADS)

Bonfante, A.; Alfieri, M. S.; Basile, A.; De Lorenzi, F.; Fiorentino, N.; Menenti, M.

2012-04-01

The effect of climate change on irrigated agricultural systems will be different from area to area depending on some factors as: (i) water availability, (ii) crop water demand (iii) soil hydrological behavior and (iv) irrigation management strategy. The adaptation of irrigated crop systems to future climate change can be supported by physically based model which simulate the water and heat fluxes in the soil-vegetation-atmosphere system. The aim of this work is to evaluate the effects of climate change on the heat and water balance of a maize-fennel rotation. This was applied to a on-demand irrigation district of Southern Italy ("Destra Sele", Campania Region, 22.645 ha). Two climate scenarios were considered, current climate (1961-1990) and future climate (2021-2050), the latter constructed by applying statistical downscaling to GCMs scenarios. For each climate scenario the soil moisture regime of the selected study area was calculated by means of a simulation model of the soil-water-atmosphere system (SWAP). Synthetic indicators of the soil water regimes (e.g., crop water stress index - CWSI, available water content) have been calculated and impacts evaluated taking into account the yield response functions to water availability of different cultivars. Different irrigation delivering strategies were also simulated. The hydrological model SWAP was applied to the representative soils of the whole area (20 soil units) for which the soil hydraulic properties were derived by means of pedo-transfer function (HYPRES) tested and validated on the typical soils in the study area. Upper boundary conditions were derived from two climate scenarios, i.e. current and future. Unit gradient in soil water potential was set as lower boundary condition. Crop-specific input data and model parameters were derived from field experiments, in the same area, where the SWAP model was calibrated and validated. The results obtained have shown a significant increase of CWSI in the future climate scenario, and some spatial patterns strongly influenced by the soils characteristics. Adaptability of different maize cultivars has been evaluated. 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) Keywords: Plant Adaptative capacity, SWAP, Climate changes, Maize, Fennel

In-situ databases and comparison of ESA Ocean Colour Climate Change Initiative (OC-CCI) products with precursor data, towards an integrated approach for ocean colour validation and climate studies

NASA Astrophysics Data System (ADS)

Brotas, Vanda; Valente, André; Couto, André B.; Grant, Mike; Chuprin, Andrei; Jackson, Thomas; Groom, Steve; Sathyendranath, Shubha

2014-05-01

Ocean colour (OC) is an Oceanic Essential Climate Variable, which is used by climate modellers and researchers. The European Space Agency (ESA) Climate Change Initiative project, is the ESA response for the need of climate-quality satellite data, with the goal of providing stable, long-term, satellite-based ECV data products. The ESA Ocean Colour CCI focuses on the production of Ocean Colour ECV uses remote sensing reflectances to derive inherent optical properties and chlorophyll a concentration from ESA's MERIS (2002-2012) and NASA's SeaWiFS (1997 - 2010) and MODIS (2002-2012) sensor archives. This work presents an integrated approach by setting up a global database of in situ measurements and by inter-comparing OC-CCI products with pre-cursor datasets. The availability of in situ databases is fundamental for the validation of satellite derived ocean colour products. A global distribution in situ database was assembled, from several pre-existing datasets, with data spanning between 1997 and 2012. It includes in-situ measurements of remote sensing reflectances, concentration of chlorophyll-a, inherent optical properties and diffuse attenuation coefficient. The database is composed from observations of the following datasets: NOMAD, SeaBASS, MERMAID, AERONET-OC, BOUSSOLE and HOTS. The result was a merged dataset tuned for the validation of satellite-derived ocean colour products. This was an attempt to gather, homogenize and merge, a large high-quality bio-optical marine in situ data, as using all datasets in a single validation exercise increases the number of matchups and enhances the representativeness of different marine regimes. An inter-comparison analysis between OC-CCI chlorophyll-a product and satellite pre-cursor datasets was done with single missions and merged single mission products. Single mission datasets considered were SeaWiFS, MODIS-Aqua and MERIS; merged mission datasets were obtained from the GlobColour (GC) as well as the Making Earth Science Data Records for Use in Research Environments (MEaSUREs). OC-CCI product was found to be most similar to SeaWiFS record, and generally, the OC-CCI record was most similar to records derived from single mission than merged mission initiatives. Results suggest that CCI product is a more consistent dataset than other available merged mission initiatives. In conclusion, climate related science, requires long term data records to provide robust results, OC-CCI product proves to be a worthy data record for climate research, as it combines multi-sensor OC observations to provide a >15-year global error-characterized record.

Global Land Product Validation Protocols: An Initiative of the CEOS Working Group on Calibration and Validation to Evaluate Satellite-derived Essential Climate Variables

NASA Astrophysics Data System (ADS)

Guillevic, P. C.; Nickeson, J. E.; Roman, M. O.; camacho De Coca, F.; Wang, Z.; Schaepman-Strub, G.

2016-12-01

The Global Climate Observing System (GCOS) has specified the need to systematically produce and validate Essential Climate Variables (ECVs). The Committee on Earth Observation Satellites (CEOS) Working Group on Calibration and Validation (WGCV) and in particular its subgroup on Land Product Validation (LPV) is playing a key coordination role leveraging the international expertise required to address actions related to the validation of global land ECVs. The primary objective of the LPV subgroup is to set standards for validation methods and reporting in order to provide traceable and reliable uncertainty estimates for scientists and stakeholders. The Subgroup is comprised of 9 focus areas that encompass 10 land surface variables. The activities of each focus area are coordinated by two international co-leads and currently include leaf area index (LAI) and fraction of absorbed photosynthetically active radiation (FAPAR), vegetation phenology, surface albedo, fire disturbance, snow cover, land cover and land use change, soil moisture, land surface temperature (LST) and emissivity. Recent additions to the focus areas include vegetation indices and biomass. The development of best practice validation protocols is a core activity of CEOS LPV with the objective to standardize the evaluation of land surface products. LPV has identified four validation levels corresponding to increasing spatial and temporal representativeness of reference samples used to perform validation. Best practice validation protocols (1) provide the definition of variables, ancillary information and uncertainty metrics, (2) describe available data sources and methods to establish reference validation datasets with SI traceability, and (3) describe evaluation methods and reporting. An overview on validation best practice components will be presented based on the LAI and LST protocol efforts to date.

Multilevel multi-informant structure of the authoritative school climate survey.

PubMed

Konold, Timothy; Cornell, Dewey; Huang, Francis; Meyer, Patrick; Lacey, Anna; Nekvasil, Erin; Heilbrun, Anna; Shukla, Kathan

2014-09-01

The Authoritative School Climate Survey was designed to provide schools with a brief assessment of 2 key characteristics of school climate--disciplinary structure and student support--that are hypothesized to influence 2 important school climate outcomes--student engagement and prevalence of teasing and bullying in school. The factor structure of these 4 constructs was examined with exploratory and confirmatory factor analyses in a statewide sample of 39,364 students (Grades 7 and 8) attending 423 schools. Notably, the analyses used a multilevel structural approach to model the nesting of students in schools for purposes of evaluating factor structure, demonstrating convergent and concurrent validity and gauging the structural invariance of concurrent validity coefficients across gender. These findings provide schools with a core group of school climate measures guided by authoritative discipline theory. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Exploring the impact of transformational leadership on nurse innovation behaviour: a cross-sectional study.

PubMed

Weng, Rhay-Hung; Huang, Ching-Yuan; Chen, Li-Mei; Chang, Li-Yu

2015-05-01

This study explored the influences of transformational leadership on nurse innovation behaviour and the mediating role of organisational climate. Recently, global nursing experts have been aggressively encouraging nurses to pursue innovation in nursing in order to improve nursing outcomes. Nursing innovation, in turn, is affected by nursing leadership. We employed a questionnaire survey to collect data, and selected a sample of nurses from hospitals in Taiwan. A total of 439 valid surveys were obtained. Hierarchical multiple regression model analysis was conducted to test the study hypothesis. The mean values of agreement of nurse innovation behaviour and transformational leadership were 3.40 and 3.78, respectively. Patient safety climate and innovation climate were found to have full mediating effects on the relationship between transformational leadership and innovation behaviour. Organisational climate has a significant impact on innovation behaviour. Transformational leadership has indirect effects on innovation behaviour via the mediation of patient safety climate and innovation climate. Hospitals should enhance transformational leadership by designing leadership training programmes and establishing transformational culture. In addition, nursing managers should foster nursing innovation through improvements in organisational climate. © 2013 John Wiley & Sons Ltd.

Agricultural Adaptations to Climate Changes in West Africa

NASA Astrophysics Data System (ADS)

Guan, K.; Sultan, B.; Lobell, D. B.; Biasutti, M.; Piani, C.; Hammer, G. L.; McLean, G.

2014-12-01

Agricultural production in West Africa is highly vulnerable to climate variability and change and a fast growing demand for food adds yet another challenge. Assessing possible adaptation strategies of crop production in West Africa under climate change is thus critical for ensuring regional food security and improving human welfare. Our previous efforts have identified as the main features of climate change in West Africa a robust increase in temperature and a complex shift in the rainfall pattern (i.e. seasonality delay and total amount change). Unaddressed, these robust climate changes would reduce regional crop production by up to 20%. In the current work, we use two well-validated crop models (APSIM and SARRA-H) to comprehensively assess different crop adaptation options under future climate scenarios. Particularly, we assess adaptations in both the choice of crop types and management strategies. The expected outcome of this study is to provide West Africa with region-specific adaptation recommendations that take into account both climate variability and climate change.

Graphical approach to assess the soil fertility evaluation model validity for rice (case study: southern area of Merapi Mountain, Indonesia)

NASA Astrophysics Data System (ADS)

Julianto, E. A.; Suntoro, W. A.; Dewi, W. S.; Partoyo

2018-03-01

Climate change has been reported to exacerbate land resources degradation including soil fertility decline. The appropriate validity use on soil fertility evaluation could reduce the risk of climate change effect on plant cultivation. This study aims to assess the validity of a Soil Fertility Evaluation Model using a graphical approach. The models evaluated were the Indonesian Soil Research Center (PPT) version model, the FAO Unesco version model, and the Kyuma version model. Each model was then correlated with rice production (dry grain weight/GKP). The goodness of fit of each model can be tested to evaluate the quality and validity of a model, as well as the regression coefficient (R2). This research used the Eviews 9 programme by a graphical approach. The results obtained three curves, namely actual, fitted, and residual curves. If the actual and fitted curves are widely apart or irregular, this means that the quality of the model is not good, or there are many other factors that are still not included in the model (large residual) and conversely. Indeed, if the actual and fitted curves show exactly the same shape, it means that all factors have already been included in the model. Modification of the standard soil fertility evaluation models can improve the quality and validity of a model.

Overview of hypersonic CFD code calibration studies

NASA Technical Reports Server (NTRS)

Miller, Charles G.

1987-01-01

The topics are presented in viewgraph form and include the following: definitions of computational fluid dynamics (CFD) code validation; climate in hypersonics and LaRC when first 'designed' CFD code calibration studied was initiated; methodology from the experimentalist's perspective; hypersonic facilities; measurement techniques; and CFD code calibration studies.

Comparison of elevation and remote sensing derived products as auxiliary data for climate surface interpolation

USGS Publications Warehouse

Alvarez, Otto; Guo, Qinghua; Klinger, Robert C.; Li, Wenkai; Doherty, Paul

2013-01-01

Climate models may be limited in their inferential use if they cannot be locally validated or do not account for spatial uncertainty. Much of the focus has gone into determining which interpolation method is best suited for creating gridded climate surfaces, which often a covariate such as elevation (Digital Elevation Model, DEM) is used to improve the interpolation accuracy. One key area where little research has addressed is in determining which covariate best improves the accuracy in the interpolation. In this study, a comprehensive evaluation was carried out in determining which covariates were most suitable for interpolating climatic variables (e.g. precipitation, mean temperature, minimum temperature, and maximum temperature). We compiled data for each climate variable from 1950 to 1999 from approximately 500 weather stations across the Western United States (32° to 49° latitude and −124.7° to −112.9° longitude). In addition, we examined the uncertainty of the interpolated climate surface. Specifically, Thin Plate Spline (TPS) was used as the interpolation method since it is one of the most popular interpolation techniques to generate climate surfaces. We considered several covariates, including DEM, slope, distance to coast (Euclidean distance), aspect, solar potential, radar, and two Normalized Difference Vegetation Index (NDVI) products derived from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS). A tenfold cross-validation was applied to determine the uncertainty of the interpolation based on each covariate. In general, the leading covariate for precipitation was radar, while DEM was the leading covariate for maximum, mean, and minimum temperatures. A comparison to other products such as PRISM and WorldClim showed strong agreement across large geographic areas but climate surfaces generated in this study (ClimSurf) had greater variability at high elevation regions, such as in the Sierra Nevada Mountains.

Long-Term Climatic Variations in the Almati Oblast in Central Asian Kazakhstan: Correlations between National Centers for Environmental Prediction (NCEP) Reanalysis II Results and Oblast Meteorological Station Data from 1949 to the Present. Volume 5

NASA Technical Reports Server (NTRS)

Welker, Jean E.; Au, Andrew Y.

2003-01-01

As part of a larger analysis of country systems described elsewhere, named a Crop Country Inventory, CCI, large variations in annual crop yield for selected climate sensitive agricultural regions or sub-regions within a country have been studied over extended periods in decades. These climate sensitive regions, principally responsible for large annual variations in an entire country s crop production, generally are characterized by distinctive patterns of atmospheric circulation and synoptic processes that result in large seasonal fluctuations in temperature, precipitation and soil moisture as well as other climate properties. The immediate region of interest is drought prone Kazakhstan in Central Asia, part of the Former Soviet Union, FSU. As a partial validation test in a dry southern region of Kazakhstan, the Almati Oblast was chosen. The Almati Oblast, a sub-region of Kazakhstan located in its southeast corner, is one of 14 oblasts within the Republic of Kazahstan. The climate data set used to characterize this region was taken from the results of the current maturely developed Global Climate Model, GCM. In this paper, the GCM results have been compared to the meteorological station data at the station locations, over various periods. If the empirical correlation of the data sets from both the GCM and station data is sufficiently significant, this would validate the use of the superior GCM profile mapping and integration for the climatic characterization of a sub-region. Precipitation values interpolated from NCEP Reanalysis II data, a global climate database spanning over 5 decades since 1949, have been statistically correlated with monthly-averaged station data from 1949 through 1993, and with daily station data from April through August, 1990 for the Almati Oblast in Kazakhstan. The resultant correlation is significant, which implies that the methodology may be extended to different regions globally for Crop Country Inventory studies.

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

USDA-ARS?s Scientific Manuscript database

Surface soil moisture is critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purpo...

On validation of the rain climatic zone designations for Nigeria

NASA Astrophysics Data System (ADS)

Obiyemi, O. O.; Ibiyemi, T. S.; Ojo, J. S.

2017-07-01

In this paper, validation of rain climatic zone classifications for Nigeria is presented based on global radio-climatic models by the International Telecommunication Union-Radiocommunication (ITU-R) and Crane. Rain rate estimates deduced from several ground-based measurements and those earlier estimated from the precipitation index on the Tropical Rain Measurement Mission (TRMM) were employed for the validation exercise. Although earlier classifications indicated that Nigeria falls into zones P, Q, N, and K for the ITU-R designations, and zones E and H for Crane's climatic zone designations, the results however confirmed that the rain climatic zones across Nigeria can only be classified into four, namely P, Q, M, and N for the ITU-R designations, while the designations by Crane exhibited only three zones, namely E, G, and H. The ITU-R classification was found to be more suitable for planning microwave and millimeter wave links across Nigeria. The research outcomes are vital in boosting the confidence level of system designers in using the ITU-R designations as presented in the map developed for the rain zone designations for estimating the attenuation induced by rain along satellite and terrestrial microwave links over Nigeria.

Safety climate practice in Korean manufacturing industry.

PubMed

Baek, Jong-Bae; Bae, Sejong; Ham, Byung-Ho; Singh, Karan P

2008-11-15

Safety climate survey was sent to 642 plants in 2003 to explore safety climate practices in the Korean manufacturing plants, especially in hazardous chemical treating plants. Out of 642 plants contacted 195 (30.4%) participated in the surveys. Data were collected by e-mail using SQL-server and mail. The main objective of this study was to explore safety climate practices (level of safety climate and the underlying problems). In addition, the variables that may influence the level of safety climate among managers and workers were explored. The questionnaires developed by health and safety executive (HSE) in the UK were modified to incorporate differences in Korean culture. Eleven important factors were summarized. Internal reliability of these factors was validated. Number of employees in the company varied from less than 30 employees (9.2%) to over 1000 employees (37.4%). Both managers and workers showed generally high level of safety climate awareness. The major underlying problems identified were inadequate health and safety procedures/rules, pressure for production, and rule breaking. The length of employment was a significant contributing factor to the level of safety climate. In this study, participants showed generally high level of safety climate, and length of employment affected the differences in the level of safety climate. Managers' commitment to comply safety rules, procedures, and effective safety education and training are recommended.

Multilevel Factor Structure and Concurrent Validity of the Teacher Version of the Authoritative School Climate Survey

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.; Konold, Timothy; Meyer, Joseph P.; Lacey, Anna; Nekvasil, Erin K.; Heilbrun, Anna; Shukla, Kathan D.

2015-01-01

Background: School climate is well recognized as an important influence on student behavior and adjustment to school, but there is a need for theory-guided measures that make use of teacher perspectives. Authoritative school climate theory hypothesizes that a positive school climate is characterized by high levels of disciplinary structure and…

Statistical downscaling of rainfall under transitional climate in Limbang River Basin by using SDSM

NASA Astrophysics Data System (ADS)

Tahir, T.; Hashim, A. M.; Yusof, K. W.

2018-04-01

Climate change is a global phenomenon that has affected hundreds of people around the globe. In transitional climatic patterns, it is essential to compute the severity of rainfall in the regions prone to hydro-meteorological disasters. Therefore, the main aim of this study is to assess the severity of rainfall under three Representative Concentration Pathways (RCPs) from Global Climate Model data of CanESM2 in Limbang River basin. Furthermore, the objective is to check the capability of Statistical Downscaling Model (SDSM) in the tropical region. The historical data of nine weather stations were used for the period of 30 years (1976 - 2005) and Global Climate Model data of CanESM2 under RCPs of RCP2.6, RCP4.5 and RCP8.5 for the period of 2071-2100. The model was calibrated for the period of 1976-1995 and validated for the period of 1996-2005. After successful calibration and validation of SDSM, the future rainfall was simulated separately for all the three scenarios of RCPs. The obtained results have shown the values of R2 and RMSE for the model calibration and validation ranged between 0.58 – 0.86 and between 1.49 and 4.7, respectively for all stations. The obtained future rainfall data from 2071 – 2100 was then compared with the base period rainfall from 1976 - 2005. It was shown that under RCP2.6 scenario there will be an increase of 8.13%, while 14.7% rise in the RCP4.5 scenario during the period of 2071- 2100. An abrupt increase of about 40.6% was observed under the robust scenario of RCP8.5. Therefore, it is concluded that future pattern of rainfall in Limbang River basin under all the scenarios is constantly increasing due to the climate change.

Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, Wiesław; Wrzesien, Mariusz; Niemiec, Rafał; Rudnicki, Witold R.

2016-03-01

Climate models are extremely complex pieces of software. They reflect the best knowledge on the physical components of the climate; nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a simulation crashing. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to the simulation crashing and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the data set used in this research using different methodology. We confirm the main conclusion of the original study concerning the suitability of machine learning for the prediction of crashes. We show that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three others are relevant but redundant and two are not relevant at all. We also show that the variance due to the split of data between training and validation sets has a large influence both on the accuracy of predictions and on the relative importance of variables; hence only a cross-validated approach can deliver a robust prediction of performance and relevance of variables.

Effect of climate change on the irrigation and discharge scheme for winter wheat in Huaibei Plain, China

NASA Astrophysics Data System (ADS)

Zhu, Y.; Ren, L.; Lü, H.

2017-12-01

On the Huaibei Plain of Anhui Province, China, winter wheat (WW) is the most prominent crop. The study area belongs to transitional climate, with shallow water table. The original climate change is complex, in addition, global warming make the climate change more complex. The winter wheat growth period is from October to June, just during the rainless season, the WW growth always depends on part of irrigation water. Under such complex climate change, the rainfall varies during the growing seasons, and water table elevations also vary. Thus, water tables supply variable moisture change between soil water and groundwater, which impact the irrigation and discharge scheme for plant growth and yield. In Huaibei plain, the environmental pollution is very serious because of agricultural use of chemical fertilizer, pesticide, herbicide and etc. In order to protect river water and groundwater from pollution, the irrigation and discharge scheme should be estimated accurately. Therefore, determining the irrigation and discharge scheme for winter wheat under climate change is important for the plant growth management decision-making. Based on field observations and local weather data of 2004-2005 and 2005-2006, the numerical model HYDRUS-1D was validated and calibrated by comparing simulated and measured root-zone soil water contents. The validated model was used to estimate the irrigation and discharge scheme in 2010-2090 under the scenarios described by HadCM3 (1970 to 2000 climate states are taken as baselines) with winter wheat growth in an optimum state indicated by growth height and LAI.

Cross-scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

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

Hattermann, F. F.; Krysanova, V.; Gosling, S. N.

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity of impact models designed for either scale to climate variability and change is comparable. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climatemore » change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a much better reproduction of reference conditions. However, the sensitivity of two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases with distinct differences in others, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability, but whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models validated against observed discharge should be used.« less

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

Rainer, Leo I.; Hoeschele, Marc A.; Apte, Michael G.

This report addresses the results of detailed monitoring completed under Program Element 6 of Lawrence Berkeley National Laboratory's High Performance Commercial Building Systems (HPCBS) PIER program. The purpose of the Energy Simulations and Projected State-Wide Energy Savings project is to develop reasonable energy performance and cost models for high performance relocatable classrooms (RCs) across California climates. A key objective of the energy monitoring was to validate DOE2 simulations for comparison to initial DOE2 performance projections. The validated DOE2 model was then used to develop statewide savings projections by modeling base case and high performance RC operation in the 16 Californiamore » climate zones. The primary objective of this phase of work was to utilize detailed field monitoring data to modify DOE2 inputs and generate performance projections based on a validated simulation model. Additional objectives include the following: (1) Obtain comparative performance data on base case and high performance HVAC systems to determine how they are operated, how they perform, and how the occupants respond to the advanced systems. This was accomplished by installing both HVAC systems side-by-side (i.e., one per module of a standard two module, 24 ft by 40 ft RC) on the study RCs and switching HVAC operating modes on a weekly basis. (2) Develop projected statewide energy and demand impacts based on the validated DOE2 model. (3) Develop cost effectiveness projections for the high performance HVAC system in the 16 California climate zones.« less

Measuring safety climate in elderly homes.

PubMed

Yeung, Koon-Chuen; Chan, Charles C

2012-02-01

Provision of a valid and reliable safety climate dimension brings enormous benefits to the elderly home sector. The aim of the present study was to make use of the safety climate instrument developed by OSHC to measure the safety perceptions of employees in elderly homes such that the factor structure of the safety climate dimensions of elderly homes could be explored. In 2010, surveys by mustering on site method were administered in 27 elderly homes that had participated in the "Hong Kong Safe and Healthy Residential Care Home Accreditation Scheme" organized by the Occupational Safety and Health Council. Six hundred and fifty-one surveys were returned with a response rate of 54.3%. To examine the factor structure of safety climate dimensions in our study, an exploratory factor analysis (EFA) using principal components analysis method was conducted to identify the underlying factors. The results of the modified seven-factor's safety climate structure extracted from 35 items better reflected the safety climate dimensions of elderly homes. The Cronbach alpha range for this study (0.655 to 0.851) indicated good internal consistency among the seven-factor structure. Responses from managerial level, supervisory and professional level, and front-line staff were analyzed to come up with the suggestion on effective ways of improving the safety culture of elderly homes. The overall results showed that managers generally gave positive responses in the factors evaluated, such as "management commitment and concern to safety," "perception of work risks and some contributory influences," "safety communication and awareness," and "safe working attitude and participation." Supervisors / professionals, and frontline level staff on the other hand, have less positive responses. The result of the lowest score in the factors - "perception of safety rules and procedures" underlined the importance of the relevance and practicability of safety rules and procedures. The modified OSHC safety climate tool provided better evidence of structural validity and reliability for use by elderly homes' decision makers as an indicator of employee perception of safety in their institution. The findings and suggestions in the study provide useful information for the management, supervisors/professionals and frontline level staff to cultivate the safety culture in the elderly home sector. Most important, elderly homes can use the modified safety climate scale to identify problem areas in their safety culture and safety management practices and then target these for intervention. Copyright © 2012 Elsevier Ltd. All rights reserved.

Assessment of 1.5°C and 2°C climate change scenarios impact on wheat production in Tunisia

NASA Astrophysics Data System (ADS)

Bergaoui, karim; Belhaj Fraj, Makram; Zaaboul, Rashyd; Allen, Myles; Mitchell, Dann; Schleussner, Carl-Friedrich; Saeed, Fahad; Mc Donnell, Rachael

2017-04-01

Wheat is the main staple crop in North Africa region and contributes the most to food security. It is almost entirely grown under rainfed conditions and its yield is highly impacted by the climate variability, e. g. dry winters, a late autumn or late spring. Irregular rainfall or drought events particularly at key stages of the growing season, lead to both early and terminal wheat stresses and high inter-year variation in yield. The goal of this study was to explore the impacts of future climate on wheat production in Tunisia using an ensemble of regional bias corrected climate models outputs for the 1.5°C and 2°C warming above the pre-industrial levels. By examining the outputs on wheat yield levels the study would help answer the question of whether the ambitious climate change mitigation efforts involved in stabilizing temperatures at 1.5°C would bring the cereal yields needed in North Africa. Tunisia was chosen as the focus country because its wheat systems are found across a wide diversity in biophysical and farming conditions so giving insight on more localized effects. Data availability across a wide range of wheat management systems from subsistence farming systems to highly mechanized agribusinesses also supported work here as model results could be readily validated for the historical period. Two scenarios were obtained using the RCP2.6 as boundary conditions for 1.5 scenario and a weighted combination of RCP2.6 and RCP4.5 for the 2°C scenario using their respective CO2 levels in the future. We calibrated and validated a dynamical crop model, DSSAT, to simulate the national wheat production and to understand the impact of drought on growth and development that causes yield variation. DSSAT simulations were driven by CHIRPS and ERA-Interim reanalysis data as daily climate forcings. The simulations were validated in a set of farmer fields which were representative of the dominant cropping systems in the country. Then, the model was validated with 10 years' state-level production data. Finally, we forced the crop model with HAPPI bias corrected outputs using ISI-MIP approach where the trend and the long-term mean are well represented and we assessed the impact of each scenario on the wheat production at the national level. The results highlighted a difference in wheat yield in some biophysical areas and farming systems. This insight is important as countries develop mitigation and adaptation strategies as the impact costs can be included.

Validating the Heat Stress Indices for Using In Heavy Work Activities in Hot and Dry Climates.

PubMed

Hajizadeh, Roohalah; Golbabaei, Farideh; Farhang Dehghan, Somayeh; Beheshti, Mohammad Hossein; Jafari, Sayed Mohammad; Taheri, Fereshteh

2016-01-01

Necessity of evaluating heat stress in the workplace, require validation of indices and selection optimal index. The present study aimed to assess the precision and validity of some heat stress indices and select the optimum index for using in heavy work activities in hot and dry climates. It carried out on 184 workers from 40 brick kilns workshops in the city of Qom, central Iran (as representative hot and dry climates). After reviewing the working process and evaluation the activity of workers and the type of work, environmental and physiological parameters according to standards recommended by International Organization for Standardization (ISO) including ISO 7243 and ISO 9886 were measured and indices were calculated. Workers engaged in indoor kiln experienced the highest values of natural wet temperature, dry temperature, globe temperature and relative humidity among studied sections (P<0.05). Indoor workplaces had the higher levels of all environmental parameters than outdoors (P=0.0001), except for air velocity. The wet-bulb globe temperature (WBGT) and heat stress index (HSI) indices had the highest correlation with other physiological parameters among the other heat stress indices. Relationship between WBGT index and carotid artery temperature (r=0.49), skin temperature (r=0.319), and oral temperature (r=0.203) was statistically significant (P=0.006). Since WBGT index, as the most applicable index for evaluating heat stress in workplaces is approved by ISO, and due to the positive features of WBGT such as ease of measurement and calculation, and with respect to some limitation in application of HSI; WBGT can be introduced as the most valid empirical index of heat stress in the brick workshops.

Inter-calibration and validation of observations from SAPHIR and ATMS instruments

NASA Astrophysics Data System (ADS)

Moradi, I.; Ferraro, R. R.

2015-12-01

We present the results of evaluating observations from microwave instruments aboard the Suomi National Polar-orbiting Partnership (NPP, ATMS instrument) and Megha-Tropiques (SAPHIR instrument) satellites. The study includes inter-comparison and inter-calibration of observations of similar channels from the two instruments, evaluation of the satellite data using high-quality radiosonde data from Atmospheric Radiation Measurement Program and GPS Radio Occultaion Observations from COSMIC mission, as well as geolocation error correction. The results of this study are valuable for generating climate data records from these instruments as well as for extending current climate data records from similar instruments such as AMSU-B and MHS to the ATMS and SAPHIR instruments. Reference: Moradi et al., Intercalibration and Validation of Observations From ATMS and SAPHIR Microwave Sounders. IEEE Transactions on Geoscience and Remote Sensing. 01/2015; DOI: 10.1109/TGRS.2015.2427165

Redesigning mental healthcare delivery: is there an effect on organizational climate?

PubMed

Joosten, T C M; Bongers, I M B; Janssen, R T J M

2014-02-01

Many studies have investigated the effect of redesign on operational performance; fewer studies have evaluated the effects on employees' perceptions of their working environment (organizational climate). Some authors state that redesign will lead to poorer organizational climate, while others state the opposite. The goal of this study was to empirically investigate this relation. Organizational climate was measured in a field experiment, before and after a redesign intervention. At one of the sites, a redesign project was conducted. At the other site, no redesign efforts took place. Two Dutch child- and adolescent-mental healthcare providers. Professionals that worked at one of the units at the start and/or the end of the intervention period. The main intervention was a redesign project aimed at improving timely delivery of services (modeled after the breakthrough series). Scores on the four models of the organizational climate measure, a validated questionnaire that measures organizational climate. Our analysis showed that climate at the intervention site changed on factors related to productivity and goal achievement (rational goal model). The intervention group scored worse than the comparison group on the part of the questionnaire that focuses on sociotechnical elements of organizational climate. However, observed differences were so small, that their practical relevance seems rather limited. Redesign efforts in healthcare, so it seems, do not influence organizational climate as much as expected.

Validation of catchment models for predicting land-use and climate change impacts. 2. Case study for a Mediterranean catchment

NASA Astrophysics Data System (ADS)

Parkin, G.; O'Donnell, G.; Ewen, J.; Bathurst, J. C.; O'Connell, P. E.; Lavabre, J.

1996-02-01

Validation methods commonly used to test catchment models are not capable of demonstrating a model's fitness for making predictions for catchments where the catchment response is not known (including hypothetical catchments, and future conditions of existing catchments which are subject to land-use or climate change). This paper describes the first use of a new method of validation (Ewen and Parkin, 1996. J. Hydrol., 175: 583-594) designed to address these types of application; the method involves making 'blind' predictions of selected hydrological responses which are considered important for a particular application. SHETRAN (a physically based, distributed catchment modelling system) is tested on a small Mediterranean catchment. The test involves quantification of the uncertainty in four predicted features of the catchment response (continuous hydrograph, peak discharge rates, monthly runoff, and total runoff), and comparison of observations with the predicted ranges for these features. The results of this test are considered encouraging.

Climate change and heat-related mortality in six cities Part 1: model construction and validation

NASA Astrophysics Data System (ADS)

Gosling, Simon N.; McGregor, Glenn R.; Páldy, Anna

2007-08-01

Heat waves are expected to increase in frequency and magnitude with climate change. The first part of a study to produce projections of the effect of future climate change on heat-related mortality is presented. Separate city-specific empirical statistical models that quantify significant relationships between summer daily maximum temperature ( T max) and daily heat-related deaths are constructed from historical data for six cities: Boston, Budapest, Dallas, Lisbon, London, and Sydney. ‘Threshold temperatures’ above which heat-related deaths begin to occur are identified. The results demonstrate significantly lower thresholds in ‘cooler’ cities exhibiting lower mean summer temperatures than in ‘warmer’ cities exhibiting higher mean summer temperatures. Analysis of individual ‘heat waves’ illustrates that a greater proportion of mortality is due to mortality displacement in cities with less sensitive temperature-mortality relationships than in those with more sensitive relationships, and that mortality displacement is no longer a feature more than 12 days after the end of the heat wave. Validation techniques through residual and correlation analyses of modelled and observed values and comparisons with other studies indicate that the observed temperature-mortality relationships are represented well by each of the models. The models can therefore be used with confidence to examine future heat-related deaths under various climate change scenarios for the respective cities (presented in Part 2).

Satellite Remote Sensing of Ozone Change, Air Quality and Climate

NASA Technical Reports Server (NTRS)

Hilsenrath, Ernest; Bhartia, Pawan K. (Technical Monitor)

2001-01-01

To date satellite remote sensing of ozone depletion has been very successful. Data sets have been validated and measured trends are in agreement with model calculations. Technology developed for sensing the stratosphere is now being employed to study air quality and climate with promising results. These new data show that air quality is a transcontinental issue, but that better instrumentation is needed. Recent data show a connection between the stratosphere, troposphere and climate, which will require new technology to quantify these relationships. NASA and NOAA (National Oceanic and Atmospheric Administration) are planning and developing new missions. Recent results from TOMS (Total Ozone Mapping Spectrometer), SeaWiffs, and Terra will be discussed and upcoming missions to study atmospheric chemistry will be discussed.

HESS Opinions "Should we apply bias correction to global and regional climate model data?"

NASA Astrophysics Data System (ADS)

Ehret, U.; Zehe, E.; Wulfmeyer, V.; Warrach-Sagi, K.; Liebert, J.

2012-04-01

Despite considerable progress in recent years, output of both Global and Regional Circulation Models is still afflicted with biases to a degree that precludes its direct use, especially in climate change impact studies. This is well known, and to overcome this problem bias correction (BC), i.e. the correction of model output towards observations in a post processing step for its subsequent application in climate change impact studies has now become a standard procedure. In this paper we argue that bias correction, which has a considerable influence on the results of impact studies, is not a valid procedure in the way it is currently used: it impairs the advantages of Circulation Models which are based on established physical laws by altering spatiotemporal field consistency, relations among variables and by violating conservation principles. Bias correction largely neglects feedback mechanisms and it is unclear whether bias correction methods are time-invariant under climate change conditions. Applying bias correction increases agreement of Climate Model output with observations in hind casts and hence narrows the uncertainty range of simulations and predictions without, however, providing a satisfactory physical justification. This is in most cases not transparent to the end user. We argue that this masks rather than reduces uncertainty, which may lead to avoidable forejudging of end users and decision makers. We present here a brief overview of state-of-the-art bias correction methods, discuss the related assumptions and implications, draw conclusions on the validity of bias correction and propose ways to cope with biased output of Circulation Models in the short term and how to reduce the bias in the long term. The most promising strategy for improved future Global and Regional Circulation Model simulations is the increase in model resolution to the convection-permitting scale in combination with ensemble predictions based on sophisticated approaches for ensemble perturbation. With this article, we advocate communicating the entire uncertainty range associated with climate change predictions openly and hope to stimulate a lively discussion on bias correction among the atmospheric and hydrological community and end users of climate change impact studies.

The Impact of Market Orientation on Patient Safety Climate Among Hospital Nurses.

PubMed

Weng, Rhay-Hung; Chen, Jung-Chien; Pong, Li-Jung; Chen, Li-Mei; Lin, Tzu-Chi

2016-03-01

Improving market orientation and patient safety have become the key concerns of nursing management. For nurses, establishing a patient safety climate is the key to enhancing nursing quality. This study explores how market orientation affects the climate of patient safety among hospital nurses. We proposed adopting a cross-sectional research design and using questionnaires to collect responses from nurses working in two Taiwanese hospitals. Three-hundred and forty-three valid samples were obtained. Multiple regression and path analyses were conducted to test the study. Market orientation was defined as the combination of customer orientation, competitor orientation, and interfunctional coordination. Customer orientation directly affects the climate of patient safety. Although the findings only supported Hypothesis 1, competitor orientation and interfunctional coordination positively affected the patient safety climate through the mediating effects of hospital support for staff. Health care managers could encourage nurses to adopt customer-oriented perspectives to enhance their nursing care. In addition, to enhance competitor orientation, interfunctional coordination, and the patient safety climate, hospital managers could strengthen their support for staff members. © The Author(s) 2014.

Ethical decision-making climate in the ICU: theoretical framework and validation of a self-assessment tool.

PubMed

Van den Bulcke, Bo; Piers, Ruth; Jensen, Hanne Irene; Malmgren, Johan; Metaxa, Victoria; Reyners, Anna K; Darmon, Michael; Rusinova, Katerina; Talmor, Daniel; Meert, Anne-Pascale; Cancelliere, Laura; Zubek, Làszló; Maia, Paolo; Michalsen, Andrej; Decruyenaere, Johan; Kompanje, Erwin J O; Azoulay, Elie; Meganck, Reitske; Van de Sompel, Ariëlla; Vansteelandt, Stijn; Vlerick, Peter; Vanheule, Stijn; Benoit, Dominique D

2018-02-23

Literature depicts differences in ethical decision-making (EDM) between countries and intensive care units (ICU). To better conceptualise EDM climate in the ICU and to validate a tool to assess EDM climates. Using a modified Delphi method, we built a theoretical framework and a self-assessment instrument consisting of 35 statements. This Ethical Decision-Making Climate Questionnaire (EDMCQ) was developed to capture three EDM domains in healthcare: interdisciplinary collaboration and communication; leadership by physicians; and ethical environment. This instrument was subsequently validated among clinicians working in 68 adult ICUs in 13 European countries and the USA. Exploratory and confirmatory factor analysis was used to determine the structure of the EDM climate as perceived by clinicians. Measurement invariance was tested to make sure that variables used in the analysis were comparable constructs across different groups. Of 3610 nurses and 1137 physicians providing ICU bedside care, 2275 (63.1%) and 717 (62.9%) participated respectively. Statistical analyses revealed that a shortened 32-item version of the EDMCQ scale provides a factorial valid measurement of seven facets of the extent to which clinicians perceive an EDM climate: self-reflective and empowering leadership by physicians; practice and culture of open interdisciplinary reflection; culture of not avoiding end-of-life decisions; culture of mutual respect within the interdisciplinary team; active involvement of nurses in end-of-life care and decision-making; active decision-making by physicians; and practice and culture of ethical awareness. Measurement invariance of the EDMCQ across occupational groups was shown, reflecting that nurses and physicians interpret the EDMCQ items in a similar manner. The 32-item version of the EDMCQ might enrich the EDM climate measurement, clinicians' behaviour and the performance of healthcare organisations. This instrument offers opportunities to develop tailored ICU team interventions. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Identification of the prediction model for dengue incidence in Can Tho city, a Mekong Delta area in Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Manh, Cuong Do

2015-01-01

The Mekong Delta is highly vulnerable to climate change and a dengue endemic area in Vietnam. This study aims to examine the association between climate factors and dengue incidence and to identify the best climate prediction model for dengue incidence in Can Tho city, the Mekong Delta area in Vietnam. We used three different regression models comprising: standard multiple regression model (SMR), seasonal autoregressive integrated moving average model (SARIMA), and Poisson distributed lag model (PDLM) to examine the association between climate factors and dengue incidence over the period 2003-2010. We validated the models by forecasting dengue cases for the period of January-December, 2011 using the mean absolute percentage error (MAPE). Receiver operating characteristics curves were used to analyze the sensitivity of the forecast of a dengue outbreak. The results indicate that temperature and relative humidity are significantly associated with changes in dengue incidence consistently across the model methods used, but not cumulative rainfall. The Poisson distributed lag model (PDLM) performs the best prediction of dengue incidence for a 6, 9, and 12-month period and diagnosis of an outbreak however the SARIMA model performs a better prediction of dengue incidence for a 3-month period. The simple or standard multiple regression performed highly imprecise prediction of dengue incidence. We recommend a follow-up study to validate the model on a larger scale in the Mekong Delta region and to analyze the possibility of incorporating a climate-based dengue early warning method into the national dengue surveillance system. Copyright © 2014 Elsevier B.V. All rights reserved.

Investigating the Capacity of Hydrological Models to Project Impacts of Climate Change in the Context of Water Allocation

NASA Astrophysics Data System (ADS)

Velez, Carlos; Maroy, Edith; Rocabado, Ivan; Pereira, Fernando

2017-04-01

To analyse the impacts of climate changes, hydrological models are used to project the hydrology responds under future conditions that normally differ from those for which they were calibrated. The challenge is to assess the validity of the projected effects when there is not data to validate it. A framework for testing the ability of models to project climate change was proposed by Refsgaard et al., (2014). The authors recommend the use of the differential-split sample test (DSST) in order to build confidence in the model projections. The method follow three steps: 1. A small number of sub-periods are selected according to one climate characteristics, 2. The calibration - validation test is applied on these periods, 3. The validation performances are compered to evaluate whether they vary significantly when climatic characteristics differ between calibration and validation. DSST rely on the existing records of climate and hydrological variables; and performances are estimated based on indicators of error between observed and simulated variables. Other authors suggest that, since climate models are not able to reproduce single events but rather statistical properties describing the climate, this should be reflected when testing hydrological models. Thus, performance criteria such as RMSE should be replaced by for instance flow duration curves or other distribution functions. Using this type of performance criteria, Van Steenbergen and Willems, (2012) proposed a method to test the validity of hydrological models in a climate changing context. The method is based on the evaluation of peak flow increases due to different levels of rainfall increases. In contrast to DSST, this method use the projected climate variability and it is especially useful to compare different modelling tools. In the framework of a water allocation project for the region of Flanders (Belgium) we calibrated three hydrological models: NAM, PDM and VHM; for 67 gauged sub-catchments with approx. 40 years of records. This paper investigates the capacity of the three hydrological models to project the impacts of climate change scenarios. It is proposed a general testing framework which combine the use of the existing information through an adapted form of DSST with the approach proposed by Van Steenbergen and Willems, (2012) adapted to assess statistical properties of flows useful in the context of water allocation. To assess the model we use robustness criteria based on a Log Nash-Sutcliffe, BIAS on cummulative volumes and relative changes based on Q50/Q90 estimated from the duration curve. The three conceptual rainfall-runoff models yielded different results per sub-catchments. A relation was found between robustness criteria and changes in mean rainfall and changes in mean potential evapotranspiration. Biases are greatly affected by changes in precipitation, especially when the climate scenarios involve changes in precipitation volume beyond the range used for calibration. Using the combine approach we were able to classify the modelling tools per sub-catchments and create an ensemble of best models to project the impacts of climate variability for the catchments of 10 main rivers in Flanders. Thus, managers could understand better the usability of the modelling tools and the credibility of its outputs for water allocation applications. References Refsgaard, J.C., Madsen, H., Andréassian, V., Arnbjerg-Nielsen, K., Davidson, T.A., Drews, M., Hamilton, D.P., Jeppesen, E., Kjellström, E., Olesen, J.E., Sonnenborg, T.O., Trolle, D., Willems, P., Christensen, J.H., 2014. A framework for testing the ability of models to project climate change and its impacts. Clim. Change. Van Steenbergen, N., Willems, P., 2012. Method for testing the accuracy of rainfall - runoff models in predicting peak flow changes due to rainfall changes , in a climate changing context. J. Hydrol. 415, 425-434.

Development and initial validation of the Classroom Motivational Climate Questionnaire (CMCQ).

PubMed

Alonso Tapia, Jesús; Fernández Heredia, Blanca

2008-11-01

Research on classroom goal-structures (CGS) has shown the usefulness of assessing the classroom motivational climate to evaluate educational interventions and to promote changes in teachers' activity. So, the Classroom Motivational Climate Questionnaire for Secondary and High-School students was developed. To validate it, confirmatory factor analysis and correlation and regression analyses were performed. Results showed that the CMCQ is a highly reliable instrument that covers many of the types of teaching patterns that favour motivation to learn, correlates as expected with other measures of CGS, predicts satisfaction with teacher's work well, and allows detecting teachers who should revise their teaching.

School Climate Measurement and Analysis

ERIC Educational Resources Information Center

Faster, Darlene; Lopez, Daisy

2013-01-01

Today, school climate assessment has become an increasingly important and valued aspect of district, state, and federal policy. Recognizing that effective school climate improvement efforts are grounded in valid and reliable data, the Federal Department of Education launched the Safe and Supportive Schools grant in 2010 to provide 11 states with…

Measuring School Climate: An Overview of Measurement Scales

ERIC Educational Resources Information Center

Kohl, Diane; Recchia, Sophie; Steffgen, Georges

2013-01-01

Background: School climate is a heterogeneous concept with a multitude of standardised and validated instruments available to measure it. Purpose: This overview of measurement scales aims to provide researchers with short summaries of some of the self-report instruments in existence, especially in relation to the link between school climate and…

Validating the Psychological Climate Scale in Voluntary Child Welfare

ERIC Educational Resources Information Center

Zeitlin, Wendy; Claiborne, Nancy; Lawrence, Catherine K.; Auerbach, Charles

2016-01-01

Objective: Organizational climate has emerged as an important factor in understanding and addressing the complexities of providing services in child welfare. This research examines the psychometric properties of each of the dimensions of Parker and colleagues' Psychological Climate Survey in a sample of voluntary child welfare workers. Methods:…

Detection of greenhouse-gas-induced climatic change. Progress report, July 1, 1994--July 31, 1995

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

Jones, P.D.; Wigley, T.M.L.

1995-07-21

The objective of this research is to assembly and analyze instrumental climate data and to develop and apply climate models as a basis for detecting greenhouse-gas-induced climatic change, and validation of General Circulation Models. In addition to changes due to variations in anthropogenic forcing, including greenhouse gas and aerosol concentration changes, the global climate system exhibits a high degree of internally-generated and externally-forced natural variability. To detect the anthropogenic effect, its signal must be isolated from the ``noise`` of this natural climatic variability. A high quality, spatially extensive data base is required to define the noise and its spatial characteristics.more » To facilitate this, available land and marine data bases will be updated and expanded. The data will be analyzed to determine the potential effects on climate of greenhouse gas and aerosol concentration changes and other factors. Analyses will be guided by a variety of models, from simple energy balance climate models to coupled atmosphere ocean General Circulation Models. These analyses are oriented towards obtaining early evidence of anthropogenic climatic change that would lead either to confirmation, rejection or modification of model projections, and towards the statistical validation of General Circulation Model control runs and perturbation experiments.« less

Role of Organizational Climate in Organizational Commitment: The Case of Teaching Hospitals.

PubMed

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.

Precipitation projections under GCMs perspective and Turkish Water Foundation (TWF) statistical downscaling model procedures

NASA Astrophysics Data System (ADS)

Dabanlı, İsmail; Şen, Zekai

2018-04-01

The statistical climate downscaling model by the Turkish Water Foundation (TWF) is further developed and applied to a set of monthly precipitation records. The model is structured by two phases as spatial (regional) and temporal downscaling of global circulation model (GCM) scenarios. The TWF model takes into consideration the regional dependence function (RDF) for spatial structure and Markov whitening process (MWP) for temporal characteristics of the records to set projections. The impact of climate change on monthly precipitations is studied by downscaling Intergovernmental Panel on Climate Change-Special Report on Emission Scenarios (IPCC-SRES) A2 and B2 emission scenarios from Max Plank Institute (EH40PYC) and Hadley Center (HadCM3). The main purposes are to explain the TWF statistical climate downscaling model procedures and to expose the validation tests, which are rewarded in same specifications as "very good" for all stations except one (Suhut) station in the Akarcay basin that is in the west central part of Turkey. Eventhough, the validation score is just a bit lower at the Suhut station, the results are "satisfactory." It is, therefore, possible to say that the TWF model has reasonably acceptable skill for highly accurate estimation regarding standard deviation ratio (SDR), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS) criteria. Based on the validated model, precipitation predictions are generated from 2011 to 2100 by using 30-year reference observation period (1981-2010). Precipitation arithmetic average and standard deviation have less than 5% error for EH40PYC and HadCM3 SRES (A2 and B2) scenarios.

Exploring the possibility of a common structural model measuring associations between safety climate factors and safety behaviour in health care and the petroleum sectors.

PubMed

Olsen, Espen

2010-09-01

The aim of the present study was to explore the possibility of identifying general safety climate concepts in health care and petroleum sectors, as well as develop and test the possibility of a common cross-industrial structural model. Self-completion questionnaire surveys were administered in two organisations and sectors: (1) a large regional hospital in Norway that offers a wide range of hospital services, and (2) a large petroleum company that produces oil and gas worldwide. In total, 1919 and 1806 questionnaires were returned from the hospital and petroleum organisation, with response rates of 55 percent and 52 percent, respectively. Using a split sample procedure principal factor analysis and confirmatory factor analysis revealed six identical cross-industrial measurement concepts in independent samples-five measures of safety climate and one of safety behaviour. The factors' psychometric properties were explored with satisfactory internal consistency and concept validity. Thus, a common cross-industrial structural model was developed and tested using structural equation modelling (SEM). SEM revealed that a cross-industrial structural model could be identified among health care workers and offshore workers in the North Sea. The most significant contributing variables in the model testing stemmed from organisational management support for safety and supervisor/manager expectations and actions promoting safety. These variables indirectly enhanced safety behaviour (stop working in dangerous situations) through transitions and teamwork across units, and teamwork within units as well as learning, feedback, and improvement. Two new safety climate instruments were validated as part of the study: (1) Short Safety Climate Survey (SSCS) and (2) Hospital Survey on Patient Safety Culture-short (HSOPSC-short). Based on development of measurements and structural model assessment, this study supports the possibility of a common safety climate structural model across health care and the offshore petroleum industry. 2010 Elsevier Ltd. All rights reserved.

Spatially distributed potential evapotranspiration modeling and climate projections.

PubMed

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

2018-08-15

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

The patient safety climate in healthcare organizations (PSCHO) survey: Short-form development.

PubMed

Benzer, Justin K; Meterko, Mark; Singer, Sara J

2017-08-01

Measures of safety climate are increasingly used to guide safety improvement initiatives. However, cost and respondent burden may limit the use of safety climate surveys. The purpose of this study was to develop a 15- to 20-item safety climate survey based on the Patient Safety Climate in Healthcare Organizations survey, a well-validated 38-item measure of safety climate. The Patient Safety Climate in Healthcare Organizations was administered to all senior managers, all physicians, and a 10% random sample of all other hospital personnel in 69 private sector hospitals and 30 Veterans Health Administration hospitals. Both samples were randomly divided into a derivation sample to identify a short-form subset and a confirmation sample to assess the psychometric properties of the proposed short form. The short form consists of 15 items represented 3 overarching domains in the long-form scale-organization, work unit, and interpersonal. The proposed short form efficiently captures 3 important sources of variance in safety climate: organizational, work-unit, and interpersonal. The short-form development process was a practical method that can be applied to other safety climate surveys. This safety climate short form may increase response rates in studies that involve busy clinicians or repeated measures. Published 2017. This article is a U.S. Government work and is in the public domain in the USA.

Pinatubo global cooling on target

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

Kerr, R.A.

1993-01-29

When Pinatubo blasted millions of tons of debris into the stratosphere in June 1991, Hansen of NASA's Goddard Institute for Space Studies used his computer climate model to predict that the shade cost by the debris would cool the globe by about half a degree C. Year end temperature reports for 1992 are now showing that the prediction was on target-confirming the tentative belief that volcanos can temporarily cool the climate and validating at least one component of the computer models predicting a greenhouse warming.

A Large Scale Study of the Assessment of the Social Environment of Middle and Secondary Schools: The Validity and Utility of Teachers' Ratings of School Climate, Cultural Pluralism, and Safety Problems for Understanding School Effects and School Improvement

ERIC Educational Resources Information Center

Brand, Stephen; Felner, Robert D.; Seitsinger, Anne; Burns, Amy; Bolton, Natalie

2008-01-01

Due to changes in state and federal policies, as well as logistical and fiscal limitations, researchers must increasingly rely on teachers' reports of school climate dimensions in order to investigate the developmental impact of these dimensions, and to evaluate efforts to enhance the impact of school environments on the development of young…

Evolution of extreme temperature events in short term climate projection for Iberian Peninsula.

NASA Astrophysics Data System (ADS)

Rodriguez, Alfredo; Tarquis, Ana M.; Sanchez, Enrique; Dosio, Alessandro; Ruiz-Ramos, Margarita

2014-05-01

Extreme events of maximum and minimum temperatures are a main hazard for agricultural production in Iberian Peninsula. For this purpose, in this study we analyze projections of their evolution that could be valid for the next decade, represented in this study by the 30-year period 2004-2034 (target period). For this purpose two kinds of data were used in this study: 1) observations from the station network of AEMET (Spanish National Meteorological Agency) for five Spanish locations, and 2) simulated data at a resolution of 50 ×50 km horizontal grid derived from the outputs of twelve Regional Climate Models (RCMs) taken from project ENSEMBLES (van der Linden and Mitchell, 2009), with a bias correction (Dosio and Paruolo, 2011; Dosio et al., 2012) regarding the observational dataset Spain02 (Herrera et al., 2012). To validate the simulated climate, the available period of observations was compared to a baseline period (1964-1994) of simulated climate for all locations. Then, to analyze the changes for the present/very next future, probability of extreme temperature events for 2004-2034 were compared to that of the baseline period. Although only minor changes are expected, small variations in variability may have a significant impact in crop performance. The objective of the work is to evaluate the utility of these short term projections for potential users, as for instance insurance companies. References Dosio A. and Paruolo P., 2011. Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate. Journal of Geophysical Research, VOL. 116,D16106, doi:10.1029/2011JD015934 Dosio A., Paruolo P. and Rojas R., 2012. Bias correction of the ENSEMBLES high resolution climate change projections for use by impact models: Analysis of the climate change signal. Journal of Geophysical Research,Volume 117, D17, doi: 0.1029/2012JD017968 Herrera et. al. (2012) Development and Analysis of a 50 year high-resolution daily gridded precipitation dataset over Spain (Spain02). International Journal of Climatology 32:74-85 DOI: 10.1002/joc.2256. van der Linden, P., and J. F. B. Mitchell (Eds.) (2009), ENSEMBLES: Climate Change and Its Impacts: Summary of Research and Results From the ENSEMBLES Project, Met Off. Hadley Cent, Exeter, U. K.

Climate Change Impact Assessment for Wheat and Rice Productivity, Haryana, India

NASA Astrophysics Data System (ADS)

Rana, M.; Singh, K. K.; Kumari, N.

2017-12-01

Agriculture presents a core of the India Economy and provides food and livelihood activities to much of the Indian population. However, the changing climate is putting challenges to agriculture. The mean temperature in India is increased by 0.1-0.3 degC in Kharif and 0.3-0.7 degC during rabi by 2010, and projected to further increase by 0.4-0.2 degC during Kharif and to 1.1-4.5degC in rabi by 2070. Similarly mean rainfall is projected to increase up to 10% during kharif and rabi by 2070.At same time, there is an increased possibility of climate extremes, such as the timing of onset of monsoon, intensities and frequency of floods and droughts (S.A. Khan et al.,2009).In addition, the rapid population growth at a rate of 1.2% per annum, expected to reach 1.53 billion by the end of 2030; is also a critical issue of this century. Keeping in mind the above facts, this study is carried out in one of major agriculture state in India. The related field data collected from the ongoing experiments in agriculture universities/institutes in the respective state and observed weather data from India Meteorological Dept.(IMD), New Delhi and future climate scenarios data from India Institute of Tropical Meteorology(IITM). Validated CERES Wheat and Rice model embedded in DSSATv4.6 used for simulating the climate change impacts. The yield simulations of crop models were obtained separately for baseline and future data The simulation result indicates significant impact of climate change on both wheat and rice yield. The reason for same attributed to increase in temperature that majorly impact rabi wheat and extreme weather events for Kharif rice. Keywords: Climate Change, CERES Rice-Wheat, Yield, Validation

Future credible precipitation occurrences in Los Alamos, New Mexico

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

Abeele, W.V.

1980-09-01

I have studied many factors thought to have influenced past climatic change. Because they might recur, they are possible suspects for future climatic alterations. Most of these factors are totally unpredictable; therefore, they cast a shadow on the validity of derived climatic predictions. Changes in atmospheric conditions and in continental surfaces, variations in solar radiation, and in the earth's orbit around the sun are among the influential mechanisms investigated. Even when models are set up that include the above parameters, their reliability will depend on unpredictable variables totally alien to the model (like volcanic eruptions). Based on climatic records, however,more » maximum precipitation amounts have been calculated for different probability levels. These seem to correspond well to past precipitation occurrences, derived from tree ring indices. The link between tree ring indices and local climate has been established through regression analysis.« less

[Psychometric evaluation of the Coach Orientation Questionnaire with a Spanish sample of handball coaches].

PubMed

Feu, Sebastián; Ibáñez, Sergio José; Graça, Amândio; Sampaio, Jaime

2007-11-01

The purpose of this study was to develop a questionnaire to investigate volleyball coaches' orientations toward the coaching process. The study was preceded by four developmental stages in order to improve user understanding, validate the content, and refine the psychometric properties of the instrument. Participants for the reliability and validity study were 334 Spanish volleyball team coaches, 86.5% men and 13.2% women. The following 6 factors emerged from the exploratory factor analysis: team-work orientation, technological orientation, innovative orientation, dialogue orientation, directive orientation, and social climate orientation. Statistical results indicated that the instrument produced reliable and valid scores in all the obtained factors (a> .70), showing that this questionnaire is a useful tool to examine coaches' orientations towards coaching.

The Development and Validation of the Ethical Climate Index for Middle and High Schools.

ERIC Educational Resources Information Center

Schulte, Laura E.; Thompson, Franklin; Talbott, Jeanie; Luther, Ann; Garcia, Michelle; Blanchard, Shirley; Conway, Laraine; Mueller, Melanie

2002-01-01

Describes the School Ethical Climate Index (SECI), an instrument to measure the ethical climate of a school. The SECI could be used in school districts to assess areas for school improvement and thereby help reduce school disorder and violence. (Contains 4 tables and 39 references.) (Author/WFA)

A lower bound to the social cost of CO2 emissions

NASA Astrophysics Data System (ADS)

van den Bergh, J. C. J. M.; Botzen, W. J. W.

2014-04-01

Many studies have estimated the social cost of carbon (SCC). We critically evaluate SCC estimates, focusing on omitted cost categories, discounting, uncertainties about damage costs and risk aversion. This allows for the calculation of a lower bound to the SCC. Dominant SCC values turn out to be gross underestimates, notably, but not only, for a low discount rate. The validity of this lower bound is supported by a precautionary approach to reflect risk aversion against extreme climate change. The results justify a more stringent climate policy than is suggested by most influential past studies.

Collaborative Project: Development of an Isotope-Enabled CESM for Testing Abrupt Climate Changes

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

Liu, Zhengyu

One of the most important validations for a state-of-art Earth System Model (ESM) with respect to climate changes is the simulation of the climate evolution and abrupt climate change events in the Earth’s history of the last 21,000 years. However, one great challenge for model validation is that ESMs usually do not directly simulate geochemical variables that can be compared directly with past proxy records. In this proposal, we have met this challenge by developing the simulation capability of major isotopes in a state-of-art ESM, the Community Earth System Model (CESM), enabling us to make direct model-data comparison by comparingmore » the model directly against proxy climate records. Our isotope-enabled ESM incorporates the capability of simulating key isotopes and geotracers, notably δ 18O, δD, δ 14C, and δ 13C, Nd and Pa/Th. The isotope-enabled ESM have been used to perform some simulations for the last 21000 years. The direct comparison of these simulations with proxy records has shed light on the mechanisms of important climate change events.« less

Select Methodology for Validating Advanced Satellite Measurement Systems

NASA Technical Reports Server (NTRS)

Larar, Allen M.; Zhou, Daniel K.; Liu, Xi; Smith, William L.

2008-01-01

Advanced satellite sensors are tasked with improving global measurements of the Earth's atmosphere, clouds, and surface to enable enhancements in weather prediction, climate monitoring capability, and environmental change detection. Measurement system validation is crucial to achieving this goal and maximizing research and operational utility of resultant data. Field campaigns including satellite under-flights with well calibrated FTS sensors aboard high-altitude aircraft are an essential part of the validation task. This presentation focuses on an overview of validation methodology developed for assessment of high spectral resolution infrared systems, and includes results of preliminary studies performed to investigate the performance of the Infrared Atmospheric Sounding Interferometer (IASI) instrument aboard the MetOp-A satellite.

Bias-correction of PERSIANN-CDR Extreme Precipitation Estimates Over the United States

NASA Astrophysics Data System (ADS)

Faridzad, M.; Yang, T.; Hsu, K. L.; Sorooshian, S.

2017-12-01

Ground-based precipitation measurements can be sparse or even nonexistent over remote regions which make it difficult for extreme event analysis. PERSIANN-CDR (CDR), with 30+ years of daily rainfall information, provides an opportunity to study precipitation for regions where ground measurements are limited. In this study, the use of CDR annual extreme precipitation for frequency analysis of extreme events over limited/ungauged basins is explored. The adjustment of CDR is implemented in two steps: (1) Calculated CDR bias correction factor at limited gauge locations based on the linear regression analysis of gauge and CDR annual maxima precipitation; and (2) Extend the bias correction factor to the locations where gauges are not available. The correction factors are estimated at gauge sites over various catchments, elevation zones, and climate regions and the results were generalized to ungauged sites based on regional and climatic similarity. Case studies were conducted on 20 basins with diverse climate and altitudes in the Eastern and Western US. Cross-validation reveals that the bias correction factors estimated on limited calibration data can be extended to regions with similar characteristics. The adjusted CDR estimates also outperform gauge interpolation on validation sites consistently. It is suggested that the CDR with bias adjustment has a potential for study frequency analysis of extreme events, especially for regions with limited gauge observations.

Evaluation of MuSyQ land surface albedo based on LAnd surface Parameters VAlidation System (LAPVAS)

NASA Astrophysics Data System (ADS)

Dou, B.; Wen, J.; Xinwen, L.; Zhiming, F.; Wu, S.; Zhang, Y.

2016-12-01

satellite derived Land surface albedo is an essential climate variable which controls the earth energy budget and it can be used in applications such as climate change, hydrology, and numerical weather prediction. However, the accuracy and uncertainty of surface albedo products should be evaluated with a reliable reference truth data prior to applications. A new comprehensive and systemic project of china, called the Remote Sensing Application Network (CRSAN), has been launched recent years. Two subjects of this project is developing a Multi-source data Synergized Quantitative Remote Sensin g Production System ( MuSyQ ) and a Web-based validation system named LAnd surface remote sensing Product VAlidation System (LAPVAS) , which aims to generate a quantitative remote sensing product for ecosystem and environmental monitoring and validate them with a reference validation data and a standard validation system, respectively. Land surface BRDF/albedo is one of product datasets of MuSyQ which has a pentad period with 1km spatial resolution and is derived by Multi-sensor Combined BRDF Inversion ( MCBI ) Model. In this MuSyQ albedo evaluation, a multi-validation strategy is implemented by LAPVAS, including directly and multi-scale validation with field measured albedo and cross validation with MODIS albedo product with different land cover. The results reveal that MuSyQ albedo data with a 5-day temporal resolution is in higher sensibility and accuracy during land cover change period, e.g. snowing. But results without regard to snow or changed land cover, MuSyQ albedo generally is in similar accuracy with MODIS albedo and meet the climate modeling requirement of an absolute accuracy of 0.05.

Person-centred ward climate as experienced by mentally lucid residents in long-term care facilities.

PubMed

Bergland, Ådel; Hofoss, Dag; Kirkevold, Marit; Vassbø, Tove; Edvardsson, David

2015-02-01

To assess the content validity and reliability of the Person-centred Climate Questionnaire-Patient version in long-term care facilities, to describe residents' perceptions of the extent to which their ward climate was person-centred and to explore whether person-centredness was associated with facility and resident characteristics, such as facility and ward size, having a sensory garden and having a primary caregiver. The importance of the physical environment to persons with dementia has been investigated. However, research is lacking regarding the extent to which mentally lucid residents experience their physical and psycho-social ward climate as person-centred and the factors influencing their experience. Cross-sectional survey design. The Person-centred Climate Questionnaire-Patient version was translated into Norwegian with forward and backward translation. The content validity index for scales was assessed. The Person-centred Climate Questionnaire -Patient version was completed by 145 mentally lucid residents in 17 Norwegian long-term care facilities. Reliability was assessed by Cronbach's α and item-total correlations. Test-retest reliability was assessed by paired samples t-test and Spearman's correlation. To explore differences based on facility and resident characteristics, independent-samples t-test and one-way anova were used. The content validity index for scales was satisfactory. The Person-centred Climate Questionnaire-Patient version was internally consistent and had satisfactory test-retest reliability. The climate was experienced as highly person-centred. No significant differences were found, except that residents in larger facilities experienced the climate as more person-centred in relation to everyday activities (subscale 2) than residents in smaller facilities. The Norwegian version of the Person-centred Climate Questionnaire-Patient version can be regarded as reliable in a long-term care facility context. Perceived degree of person-centredness was not associated with facility or resident characteristics, such as the number of residents, having a sensory garden or knowing that one has a primary caregiver. A person-centred climate can be attained in different kinds of long-term care facilities. © 2014 John Wiley & Sons Ltd.

Pliocene Seasonality along the US Atlantic Coastal Plain Inferred from Growth Increment Analysis of Mercenaria carolinensis

NASA Astrophysics Data System (ADS)

Winkelstern, I. Z.; Surge, D. M.

2010-12-01

Pliocene sea surface temperature (SST) data from the US Atlantic coastal plain is currently insufficient for a detailed understanding of the climatic shifts that occurred during the period. Previous studies, based on oxygen isotope proxy data from marine shells and bryozoan zooid size analysis, have provided constraints on possible annual-scale SST ranges for the region. However, more data are required to fully understand the forcing mechanisms affecting regional Pliocene climate and evaluate modeled temperature projections. Bivalve sclerochronology (growth increment analysis) is an alternative proxy for SST that can provide annually resolved multi-year time series. The method has been validated in previous studies using modern Arctica, Chione, and Mercenaria. We analyzed Pliocene Mercenaria carolinensis shells using sclerochronologic methods and tested the hypothesis that higher SST ranges are reflected in shells selected from the warmest climate interval (3.5-3.3 Ma, upper Yorktown Formation, Virginia) and lower SST ranges are observable in shells selected from the subsequent cooling interval (2.4-1.8 Ma, Chowan River Formation, North Carolina). These results further establish the validity of growth increment analysis using fossil shells and provide the first large dataset (from the region) of reconstructed annual SST from floating time series during these intervals. These data will enhance our knowledge about a warm climate state that has been identified in the 2007 IPCC report as an analogue for expected global warming. Future work will expand this study to include sampling in Florida to gain detailed information about Pliocene SST along a latitudinal gradient.

Determining the importance of model calibration for forecasting absolute/relative changes in streamflow from LULC and climate changes

USGS Publications Warehouse

Niraula, Rewati; Meixner, Thomas; Norman, Laura M.

2015-01-01

Land use/land cover (LULC) and climate changes are important drivers of change in streamflow. Assessing the impact of LULC and climate changes on streamflow is typically done with a calibrated and validated watershed model. However, there is a debate on the degree of calibration required. The objective of this study was to quantify the variation in estimated relative and absolute changes in streamflow associated with LULC and climate changes with different calibration approaches. The Soil and Water Assessment Tool (SWAT) was applied in an uncalibrated (UC), single outlet calibrated (OC), and spatially-calibrated (SC) mode to compare the relative and absolute changes in streamflow at 14 gaging stations within the Santa Cruz River Watershed in southern Arizona, USA. For this purpose, the effect of 3 LULC, 3 precipitation (P), and 3 temperature (T) scenarios were tested individually. For the validation period, Percent Bias (PBIAS) values were >100% with the UC model for all gages, the values were between 0% and 100% with the OC model and within 20% with the SC model. Changes in streamflow predicted with the UC and OC models were compared with those of the SC model. This approach implicitly assumes that the SC model is “ideal”. Results indicated that the magnitude of both absolute and relative changes in streamflow due to LULC predicted with the UC and OC results were different than those of the SC model. The magnitude of absolute changes predicted with the UC and SC models due to climate change (both P and T) were also significantly different, but were not different for OC and SC models. Results clearly indicated that relative changes due to climate change predicted with the UC and OC were not significantly different than that predicted with the SC models. This result suggests that it is important to calibrate the model spatially to analyze the effect of LULC change but not as important for analyzing the relative change in streamflow due to climate change. This study also indicated that model calibration in not necessary to determine the direction of change in streamflow due to LULC and climate change.

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.

Effect of Climate Change on Mediterranean Winter Ranges of Two Migratory Passerines.

PubMed

Tellería, José L; Fernández-López, Javier; Fandos, Guillermo

2016-01-01

We studied the effect of climate change on the distribution of two insectivorous passerines (the meadow pipit Anthus pratensis and the chiffchaff Phylloscopus collybita) in wintering grounds of the Western Mediterranean basin. In this region, precipitation and temperature can affect the distribution of these birds through direct (thermoregulation costs) or indirect effects (primary productivity). Thus, it can be postulated that projected climate changes in the region will affect the extent and suitability of their wintering grounds. We studied pipit and chiffchaff abundance in several hundred localities along a belt crossing Spain and Morocco and assessed the effects of climate and other geographical and habitat predictors on bird distribution. Multivariate analyses reported a positive effect of temperature on the present distribution of the two species, with an additional effect of precipitation on the meadow pipit. These climate variables were used with Maxent to model the occurrence probabilities of species using ring recoveries as presence data. Abundance and occupancy of the two species in the study localities adjusted to the distribution models, with more birds in sectors of high climate suitability. After validation, these models were used to forecast the distribution of climate suitability according to climate projections for 2050-2070 (temperature increase and precipitation reduction). Results show an expansion of climatically suitable sectors into the highlands by the effect of warming on the two species, and a retreat of the meadow pipit from southern sectors related to rain reduction. The predicted patterns show a mean increase in climate suitability for the two species due to the warming of the large highland expanses typical of the western Mediterranean.

Evaluation of the new EMAC-SWIFT chemistry climate model

NASA Astrophysics Data System (ADS)

Scheffler, Janice; Langematz, Ulrike; Wohltmann, Ingo; Rex, Markus

2016-04-01

It is well known that the representation of atmospheric ozone chemistry in weather and climate models is essential for a realistic simulation of the atmospheric state. Including atmospheric ozone chemistry into climate simulations is usually done by prescribing a climatological ozone field, by including a fast linear ozone scheme into the model or by using a climate model with complex interactive chemistry. While prescribed climatological ozone fields are often not aligned with the modelled dynamics, a linear ozone scheme may not be applicable for a wide range of climatological conditions. Although interactive chemistry provides a realistic representation of atmospheric chemistry such model simulations are computationally very expensive and hence not suitable for ensemble simulations or simulations with multiple climate change scenarios. A new approach to represent atmospheric chemistry in climate models which can cope with non-linearities in ozone chemistry and is applicable to a wide range of climatic states is the Semi-empirical Weighted Iterative Fit Technique (SWIFT) that is driven by reanalysis data and has been validated against observational satellite data and runs of a full Chemistry and Transport Model. SWIFT has recently been implemented into the ECHAM/MESSy (EMAC) chemistry climate model that uses a modular approach to climate modelling where individual model components can be switched on and off. Here, we show first results of EMAC-SWIFT simulations and validate these against EMAC simulations using the complex interactive chemistry scheme MECCA, and against observations.

Potential effect of climate change on malaria transmission in Africa.

PubMed

Tanser, Frank C; Sharp, Brian; le Sueur, David

2003-11-29

Climate change is likely to affect transmission of vector-borne diseases such as malaria. We quantitatively estimated current malaria exposure and assessed the potential effect of projected climate scenarios on malaria transmission. We produced a spatiotemporally validated (against 3791 parasite surveys) model of Plasmodium falciparum malaria transmission in Africa. Using different climate scenarios from the Hadley Centre global climate model (HAD CM3) climate experiments, we projected the potential effect of climate change on transmission patterns. Our model showed sensitivity and specificity of 63% and 96%, respectively (within 1 month temporal accuracy), when compared with the parasite surveys. We estimate that on average there are 3.1 billion person-months of exposure (445 million people exposed) in Africa per year. The projected scenarios would estimate a 5-7% potential increase (mainly altitudinal) in malaria distribution with surprisingly little increase in the latitudinal extents of the disease by 2100. Of the overall potential increase (although transmission will decrease in some countries) of 16-28% in person-months of exposure (assuming a constant population), a large proportion will be seen in areas of existing transmission. The effect of projected climate change indicates that a prolonged transmission season is as important as geographical expansion in correct assessment of the effect of changes in transmission patterns. Our model constitutes a valid baseline against which climate scenarios can be assessed and interventions planned.

The Structure and Climate of Size: Small Scale Schooling in an Urban District

ERIC Educational Resources Information Center

LeChasseur, Kimberly

2009-01-01

This study explores mechanisms involved in small scale schooling and student engagement. Specifically, this study questions the validity of arguments for small scale schooling reforms that confound the promised effects of small scale schooling "structures" (such as smaller enrollments, schools-within-schools, and smaller class sizes)…

Measuring the Medical School Educational Environment: Validating an Approach from Saudi Arabia

ERIC Educational Resources Information Center

Alshehri, Sarah A.; Alshehri, Abdulrahman F.; Erwin, T. Dary

2012-01-01

Objective: This study is an empirical analysis of the female students' attitudes toward the medical educational environment and climate in the College of Medicine at King Khalid University. Setting: The Dundee Ready Educational Environment Measure (DREEM) questionnaire was administered on the same day to 100 female students studying in the third…

Stress hormone concentration in Rocky Mountain populations of the American pika (Ochotona princeps)

PubMed Central

Wilkening, Jennifer L.; Ray, Chris; Sweazea, Karen L.

2013-01-01

The American pika (Ochotona princeps) is considered a sentinel species for detecting ecological effects of climate change. Pikas are declining within a large portion of their range, but previous studies have focused only on local pika extinction as a metric of change. We designed a procedure which can provide an earlier warning signal, based on non-invasive sampling and analysis of physiological stress in living pikas. Pikas were sampled at several locations in the Rocky Mountains for the measurement of glucocorticoid metabolites (GCMs) in faeces. Using a time series of faecal pellets from 12 individuals, we detected a significant increase in faecal GCM level in response to capture, thus biologically validating the use of a corticosterone enzyme immunoassay. We also established baseline, peak, and post-peak GCM concentrations for pikas in the Rocky Mountains, which varied according to gender and individual. This is the first study to measure stress hormone metabolites in any species of pika. The methods developed and validated in this study can be used to add non-invasive measurements of physiological stress to pika monitoring programmes and other research designed to assess pika vulnerability to predicted changes in climate. Pika monitoring programmes currently in place use a protocol that relates current site use by pikas with data on local habitat characteristics, such as elevation, to infer potential effects of climate change. Data generated by these monitoring studies can be used to identify the trends in site use by pikas in relationship to habitat covariates. However, this approach does not take into account the role of behavioural thermoregulation and the pika's use of microhabitats to ameliorate variations in climate. Incorporating a stress metric, such as GCM concentration, will provide relatively direct evidence for or against the hypothesis that pikas can be stressed by climate regardless of behavioural adaptations. PMID:27293611

Can quantile mapping improve precipitation extremes from regional climate models?

NASA Astrophysics Data System (ADS)

Tani, Satyanarayana; Gobiet, Andreas

2015-04-01

The ability of quantile mapping to accurately bias correct regard to precipitation extremes is investigated in this study. We developed new methods by extending standard quantile mapping (QMα) to improve the quality of bias corrected extreme precipitation events as simulated by regional climate model (RCM) output. The new QM version (QMβ) was developed by combining parametric and nonparametric bias correction methods. The new nonparametric method is tested with and without a controlling shape parameter (Qmβ1 and Qmβ0, respectively). Bias corrections are applied on hindcast simulations for a small ensemble of RCMs at six different locations over Europe. We examined the quality of the extremes through split sample and cross validation approaches of these three bias correction methods. This split-sample approach mimics the application to future climate scenarios. A cross validation framework with particular focus on new extremes was developed. Error characteristics, q-q plots and Mean Absolute Error (MAEx) skill scores are used for evaluation. We demonstrate the unstable behaviour of correction function at higher quantiles with QMα, whereas the correction functions with for QMβ0 and QMβ1 are smoother, with QMβ1 providing the most reasonable correction values. The result from q-q plots demonstrates that, all bias correction methods are capable of producing new extremes but QMβ1 reproduces new extremes with low biases in all seasons compared to QMα, QMβ0. Our results clearly demonstrate the inherent limitations of empirical bias correction methods employed for extremes, particularly new extremes, and our findings reveals that the new bias correction method (Qmß1) produces more reliable climate scenarios for new extremes. These findings present a methodology that can better capture future extreme precipitation events, which is necessary to improve regional climate change impact studies.

Climate change and spring frost damages for sweet cherries in Germany

NASA Astrophysics Data System (ADS)

Chmielewski, Frank-M.; Götz, Klaus-P.; Weber, Katharina C.; Moryson, Susanne

2018-02-01

Spring frost can be a limiting factor in sweet cherry ( Prunus avium L.) production. Rising temperatures in spring force the development of buds, whereby their vulnerability to freezing temperatures continuously increases. With the beginning of blossom, flowers can resist only light frosts without any significant damage. In this study, we investigated the risk of spring frost damages during cherry blossom for historical and future climate conditions at two different sites in NE (Berlin) and SW Germany (Geisenheim). Two phenological models, developed on the basis of phenological observations at the experimental sweet cherry orchard in Berlin-Dahlem and validated for endodormancy release and for warmer climate conditions (already published), were used to calculate the beginning of cherry blossom in Geisenheim, 1951-2015 (external model validation). Afterwards, on the basis of a statistical regionalisation model WETTREG (RCP 8.5), the frequency of frost during cherry blossom was calculated at both sites for historical (1971-2000) and future climate conditions (2011-2100). From these data, we derived the final flower damage, defined as the percentage of frozen flowers due to single or multiple frost events during blossom. The results showed that rising temperatures in this century can premature the beginning of cherry blossom up to 17 days at both sites, independent of the used phenological model. The frequency and strength of frost was characterised by a high temporal and local variability. For both sites, no significant increase in frost frequency and frost damage during blossom was found. In Geisenheim, frost damages significantly decreased from the middle of the twenty-first century. This study additionally emphasises the importance of reliable phenological models which not only work for current but also for changed climate conditions and at different sites. The date of endodormancy release should always be a known parameter in chilling/forcing models.

Climate change and spring frost damages for sweet cherries in Germany.

PubMed

Chmielewski, Frank-M; Götz, Klaus-P; Weber, Katharina C; Moryson, Susanne

2018-02-01

Spring frost can be a limiting factor in sweet cherry (Prunus avium L.) production. Rising temperatures in spring force the development of buds, whereby their vulnerability to freezing temperatures continuously increases. With the beginning of blossom, flowers can resist only light frosts without any significant damage. In this study, we investigated the risk of spring frost damages during cherry blossom for historical and future climate conditions at two different sites in NE (Berlin) and SW Germany (Geisenheim). Two phenological models, developed on the basis of phenological observations at the experimental sweet cherry orchard in Berlin-Dahlem and validated for endodormancy release and for warmer climate conditions (already published), were used to calculate the beginning of cherry blossom in Geisenheim, 1951-2015 (external model validation). Afterwards, on the basis of a statistical regionalisation model WETTREG (RCP 8.5), the frequency of frost during cherry blossom was calculated at both sites for historical (1971-2000) and future climate conditions (2011-2100). From these data, we derived the final flower damage, defined as the percentage of frozen flowers due to single or multiple frost events during blossom. The results showed that rising temperatures in this century can premature the beginning of cherry blossom up to 17 days at both sites, independent of the used phenological model. The frequency and strength of frost was characterised by a high temporal and local variability. For both sites, no significant increase in frost frequency and frost damage during blossom was found. In Geisenheim, frost damages significantly decreased from the middle of the twenty-first century. This study additionally emphasises the importance of reliable phenological models which not only work for current but also for changed climate conditions and at different sites. The date of endodormancy release should always be a known parameter in chilling/forcing models.

Susceptibility of the Batoka Gorge hydroelectric scheme to climate change

NASA Astrophysics Data System (ADS)

Harrison, Gareth P.; Whittington, H.(Bert) W.

2002-07-01

The continuing and increased use of renewable energy sources, including hydropower, is a key strategy to limit the extent of future climate change. Paradoxically, climate change itself may alter the availability of this natural resource, adversely affecting the financial viability of both existing and potential schemes. Here, a model is described that enables the assessment of the relationship between changes in climate and the viability, technical and financial, of hydro development. The planned Batoka Gorge scheme on the Zambezi River is used as a case study to validate the model and to predict the impact of climate change on river flows, electricity production and scheme financial performance. The model was found to perform well, given the inherent difficulties in the task, although there is concern regarding the ability of the hydrological model to reproduce the historic flow conditions of the upper Zambezi Basin. Simulations with climate change scenarios illustrate the sensitivity of the Batoka Gorge scheme to changes in climate. They suggest significant reductions in river flows, declining power production, reductions in electricity sales revenue and consequently an adverse impact on a range of investment measures.

A critical remark on the applicability of E-OBS European gridded temperature data set for validating control climate simulations

NASA Astrophysics Data System (ADS)

Kyselý, Jan; Plavcová, Eva

2010-12-01

The study compares daily maximum (Tmax) and minimum (Tmin) temperatures in two data sets interpolated from irregularly spaced meteorological stations to a regular grid: the European gridded data set (E-OBS), produced from a relatively sparse network of stations available in the European Climate Assessment and Dataset (ECA&D) project, and a data set gridded onto the same grid from a high-density network of stations in the Czech Republic (GriSt). We show that large differences exist between the two gridded data sets, particularly for Tmin. The errors tend to be larger in tails of the distributions. In winter, temperatures below the 10% quantile of Tmin, which is still far from the very tail of the distribution, are too warm by almost 2°C in E-OBS on average. A large bias is found also for the diurnal temperature range. Comparison with simple average series from stations in two regions reveals that differences between GriSt and the station averages are minor relative to differences between E-OBS and either of the two data sets. The large deviations between the two gridded data sets affect conclusions concerning validation of temperature characteristics in regional climate model (RCM) simulations. The bias of the E-OBS data set and limitations with respect to its applicability for evaluating RCMs stem primarily from (1) insufficient density of information from station observations used for the interpolation, including the fact that the stations available may not be representative for a wider area, and (2) inconsistency between the radii of the areal average values in high-resolution RCMs and E-OBS. Further increases in the amount and quality of station data available within ECA&D and used in the E-OBS data set are essentially needed for more reliable validation of climate models against recent climate on a continental scale.

Assessing Forest Carbon Response to Climate Change and Disturbances Using Long-term Hydro-climatic Observations and Simulations

NASA Astrophysics Data System (ADS)

Trettin, C.; Dai, Z.; Amatya, D. M.

2014-12-01

Long-term climatic and hydrologic observations on the Santee Experimental Forest in the lower coastal plain of South Carolina were used to estimate long-term changes in hydrology and forest carbon dynamics for a pair of first-order watersheds. Over 70 years of climate data indicated that warming in this forest area in the last decades was faster than the global mean; 35+ years of hydrologic records showed that forest ecosystem succession three years following Hurricane Hugo caused a substantial change in the ratio of runoff to precipitation. The change in this relationship between the paired watersheds was attributed to altered evapotranspiration processes caused by greater abundance of pine in the treatment watershed and regeneration of the mixed hardwood-pine forest on the reference watershed. The long-term records and anomalous observations are highly valuable for reliable calibration and validation of hydrological and biogeochemical models capturing the effects of climate variability. We applied the hydrological model MIKESHE that showed that runoff and water table level are sensitive to global warming, and that the sustained warming trends can be expected to decrease stream discharge and lower the mean water table depth. The spatially-explicit biogeochemical model Forest-DNDC, validated using biomass measurements from the watersheds, was used to assess carbon dynamics in response to high resolution hydrologic observation data and simulation results. The simulations showed that the long-term spatiotemporal carbon dynamics, including biomass and fluxes of soil carbon dioxide and methane were highly regulated by disturbance regimes, climatic conditions and water table depth. The utility of linked-modeling framework demonstrated here to assess biogeochemical responses at the watershed scale suggests applications for assessing the consequences of climate change within an urbanizing forested landscape. The approach may also be applicable for validating large-scale models.

The Climate Change Attitude Survey: Measuring Middle School Student Beliefs and Intentions to Enact Positive Environmental Change

ERIC Educational Resources Information Center

Christensen, Rhonda; Knezek, Gerald

2015-01-01

The Climate Change Attitude Survey is composed of 15 Likert-type attitudinal items selected to measure students' beliefs and intentions toward the environment with a focus on climate change. This paper describes the development of the instrument and psychometric performance characteristics including reliability and validity. Data were gathered…

Simple three-pool model accurately describes patterns of long-term litter decomposition in diverse climates

Treesearch

E. Carol Adair; William J. Parton; Steven J. Del Grosso; Shendee L. Silver; Mark E. Harmon; Sonia A. Hall; Ingrid C. Burke; Stephen C. Hart

2008-01-01

As atmospheric CO2 increases, ecosystem carbon sequestration will largely depend on how global changes in climate will alter the balance between net primary production and decomposition. The response of primary production to climatic change has been examined using well-validated mechanistic models, but the same is not true for decomposition, a...

Climate Change and Impacts Research Experiences for Urban Students

NASA Astrophysics Data System (ADS)

Marchese, P.; Carlson, B. E.; Rosenzweig, C.; Austin, S. A.; Peteet, D. M.; Druyan, L.; Fulakeza, M.; Gaffin, S.; Scalzo, F.; Frost, J.; Moshary, F.; Greenbaum, S.; Cheung, T. K.; Howard, A.; Steiner, J. C.; Johnson, L. P.

2011-12-01

Climate change and impacts research for undergraduate urban students is the focus of the Center for Global Climate Research (CGCR). We describe student research and significant results obtained during the Summer 2011. The NSF REU site, is a collaboration between the City University of New York (CUNY) and the NASA Goddard Institute for Space Studies (GISS). The research teams are mentored by NASA scientists and CUNY faculty. Student projects include: Effects of Stratospheric Aerosols on Tropical Cyclone Activity in the North Atlantic Basin; Comparison of Aerosol Optical Depth and Angstrom Exponent Retrieved by AERONET, MISR, and MODIS Measurements; White Roofs to the Rescue: Combating the Urban Heat Island Effect; Tropospheric Ozone Investigations in New York City; Carbon Sequestration with Climate Change in Alaskan Peatlands; Validating Regional Climate Models for Western Sub-Sahara Africa; Bio-Remediation of Toxic Waste Sites: Mineral Characteristics of Cyanide-Treated Mining Waste; Assessment of an Ocean Mixing Parameterization for Climate Studies; Comparative Wind Speed through Doppler Sounding with Pulsed Infrared LIDAR; and Satellite Telemetry and Communications. The CGCR also partners with the New York City Research Initiative (NYCRI) at GISS. The center is supported by NSF ATM-0851932 and the American Recovery and Reinvestment Act of 2009 (ARRA).

Hydrological Dynamics of Central America: Time-of-Emergence of the Global Warming Signal

NASA Astrophysics Data System (ADS)

Imbach, P. A.; Georgiou, S.; Calderer, L.; Coto, A.; Nakaegawa, T.; Chou, S. C.; Lyra, A. A.; Hidalgo, H. G.; Ciais, P.

2016-12-01

Central America is among the world's most vulnerable regions to climate variability and change. Country economies are highly dependent on the agricultural sector and over 40 million people's rural livelihoods directly depend on the use of natural resources. Future climate scenarios show a drier outlook (higher temperatures and lower precipitation) over a region where rural livelihoods are already compromised by water availability and climate variability. Previous efforts to validate modelling of the regional hydrology have been based on high resolution (1 km2) equilibrium models (Imbach et al., 2010) or using dynamic models (Variable Infiltration Capacity) with coarse climate forcing (0.5°) (Hidalgo et al., 2013; Maurer et al., 2009). We present here: (i) validation of the hydrological outputs from high-resolution simulations (10 km2) of a dynamic vegetation model (Orchidee), using 7 different sets of model input forcing data, with monthly runoff observations from 182 catchments across Central America; (ii) the first assessments of the region's hydrological variability using the historical simulations (iii) an estimation of the time of emergence of the climate change signal (under the SRES emission scenarios) on the water balance. We found model performance to be comparable with that from studies in other world regions (Yang et al. 2016) when forced with high resolution precipitation data (monthly values at 5 km2, Funk et al. (2015)) and the Climate Research Unit (CRU 3.2, Harris et al. (2014)) dataset of meteorological parameters. Validation results showed a Pearson correlation coefficient ≈ 0.6, general underestimation of runoff of ≈ 60% and variability close to observed values (ratio of standard deviations of ≈ 0.7). Maps of historical runoff are presented to show areas where high runoff variability follows high mean annual runoff, with opposite trends over the Caribbean. Future scenarios show large areas where future maximum water availability will always fall below minus-one standard deviation of the historical values by mid-century. Additionally, our results highlight the time horizon left to develop adaptation strategies to cope with future reductions in water availability.

Vulnerability of US thermoelectric power generation to climate change when incorporating state-level environmental regulations

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

Liu, Lu; Hejazi, Mohamad; Li, Hongyi

This study explores the interactions between climate and thermoelectric generation in the U.S. by coupling an Earth System Model with a thermoelectric power generation model. We validated model simulations of power production for selected power plants (~44% of existing thermoelectric capacity) against reported values. In addition, we projected future usable capacity for existing power plants under two different climate change scenarios. Results indicate that climate change alone may reduce average thermoelectric generating capacity by 2%-3% by the 2060s. Reductions up to 12% are expected if environmental requirements are enforced without waivers for thermal variation. This study concludes that the impactmore » of climate change on the U.S. thermoelectric power system is less than previous estimates due to an inclusion of a spatially-disaggregated representation of environmental regulations and provisional variances that temporarily relieve power plants from permit requirements. This work highlights the significance of accounting for legal constructs in which the operation of power plants are managed, and underscores the effects of provisional variances in addition to environmental requirements.« less

Global Validation of MODIS Atmospheric Profile-Derived Near-Surface Air Temperature and Dew Point Estimates

NASA Astrophysics Data System (ADS)

Famiglietti, C.; Fisher, J.; Halverson, G. H.

2017-12-01

This study validates a method of remote sensing near-surface meteorology that vertically interpolates MODIS atmospheric profiles to surface pressure level. The extraction of air temperature and dew point observations at a two-meter reference height from 2001 to 2014 yields global moderate- to fine-resolution near-surface temperature distributions that are compared to geographically and temporally corresponding measurements from 114 ground meteorological stations distributed worldwide. This analysis is the first robust, large-scale validation of the MODIS-derived near-surface air temperature and dew point estimates, both of which serve as key inputs in models of energy, water, and carbon exchange between the land surface and the atmosphere. Results show strong linear correlations between remotely sensed and in-situ near-surface air temperature measurements (R2 = 0.89), as well as between dew point observations (R2 = 0.77). Performance is relatively uniform across climate zones. The extension of mean climate-wise percent errors to the entire remote sensing dataset allows for the determination of MODIS air temperature and dew point uncertainties on a global scale.

The International Arctic Buoy Programme (IABP)

NASA Astrophysics Data System (ADS)

Rigor, I. G.; Ortmeyer, M.

2003-12-01

The Arctic has undergone dramatic changes in weather, climate and environment. It should be noted that many of these changes were first observed and studied using data from the International Arctic Buoy Programme (IABP). For example, IABP data were fundamental to Walsh et al. (1996) showing that atmospheric pressure has decreased, Rigor et al. (2000) showing that air temperatures have increased, and to Proshutinsky and Johnson (1997); Steele and Boyd, (1998); Kwok, (2000); and Rigor et al. (2002) showing that the clockwise circulation of sea ice and the ocean has weakened. All these results relied heavily on data from the IABP. In addition to supporting these studies of climate change, the IABP observations are also used to forecast weather and ice conditions, validate satellite retrievals of environmental variables, to force, validate and initialize numerical models. Over 350 papers have been written using data from the IABP. The observations and datasets of the IABP data are one of the cornerstones for environmental forecasting and research in the Arctic.

Genotypic and environmental effects on coffee (Coffea arabica L.) bean fatty acid profile: impact on variety and origin chemometric determination.

PubMed

Villarreal, Diana; Laffargue, Andreina; Posada, Huver; Bertrand, Benoit; Lashermes, Philippe; Dussert, Stephane

2009-12-09

In a previous study, the effectiveness of chlorogenic acids, fatty acids (FA), and elements was compared for the discrimination of Arabica varieties and growing terroirs. Since FA provided the best results, the aim of the present work was to validate their discrimination ability using an extended experimental design, including twice the number of location x variety combinations and 2 years of study. It also aimed at understanding how the environment influences FA composition through correlation analysis using different climatic parameters. Percentages of correct classification of known samples remained very high, independent of the classification criterion. However, cross-validation tests across years indicated that prediction of unknown locations was less efficient than that of unknown genotypes. Environmental temperature during the development of coffee beans had a dramatic influence on their FA composition. Analysis of climate patterns over years enabled us to understand the efficient location discrimination within a single year but only moderate efficiency across years.

Spatial diffusion of influenza outbreak-related climate factors in Chiang Mai Province, Thailand.

PubMed

Nakapan, Supachai; Tripathi, Nitin Kumar; Tipdecho, Taravudh; Souris, Marc

2012-10-24

Influenza is one of the most important leading causes of respiratory illness in the countries located in the tropical areas of South East Asia and Thailand. In this study the climate factors associated with influenza incidence in Chiang Mai Province, Northern Thailand, were investigated. Identification of factors responsible for influenza outbreaks and the mapping of potential risk areas in Chiang Mai are long overdue. This work examines the association between yearly climate patterns between 2001 and 2008 and influenza outbreaks in the Chiang Mai Province. The climatic factors included the amount of rainfall, percent of rainy days, relative humidity, maximum, minimum temperatures and temperature difference. The study develops a statistical analysis to quantitatively assess the relationship between climate and influenza outbreaks and then evaluate its suitability for predicting influenza outbreaks. A multiple linear regression technique was used to fit the statistical model. The Inverse Distance Weighted (IDW) interpolation and Geographic Information System (GIS) techniques were used in mapping the spatial diffusion of influenza risk zones. The results show that there is a significance correlation between influenza outbreaks and climate factors for the majority of the studied area. A statistical analysis was conducted to assess the validity of the model comparing model outputs and actual outbreaks.

Climate Science in a Postmodern World

NASA Astrophysics Data System (ADS)

Verosub, Kenneth L.

2010-08-01

Like many readers of Eos, I have found it hard to understand the persistence of climate doubters and climate skeptics. How can they not accept the science? An important clue can be found in an editorial by Daniel Henninger in the Wall Street Journal that made a connection between climate science and postmodernism [Henninger, 2009]. Postmodernism is a concept that permeates the humanities and the social sciences. In its simplest terms, it postulates that truth is a relative concept. Facts exist, but their interpretation is determined as much by society, culture, politics, and economics as by scientific objectivity. From this perspective, any interpretation is as valid as any other. So, for instance, Herman Melville's Moby Dick can be seen as a novel equally about morality, homosexuality, the repression of the masses, the quest for God, or the killing of whales in the nineteenth century. All interpretations are valid, and all truth is relative.

Assessment of Satellite Radiometry in the Visible Domain

NASA Technical Reports Server (NTRS)

Melin, Frederick; Franz, Bryan A.

2014-01-01

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

Aeolian Dunes: New High-Resolution Archives of Past Wind-Intensity and -Direction

NASA Astrophysics Data System (ADS)

Lindhorst, S.; Betzler, C.

2017-12-01

The understanding of the long-term variability of local wind-fields is most relevant for calibrating climate models and for the prediction of the socio-economic consequences of climate change. Continuous instrumental-based weather observations go back less than two centuries; aeolian dunes, however, contain an archive of past wind-field fluctuations which is basically unread. We present new ways to reconstruct annual to seasonal changes of wind intensity and predominant wind direction from dune-sediment composition and -geometries based on ground-penetrating radar (GPR) data, grain-size analyses and different age-dating approaches. Resulting proxy-based data series on wind are validated against instrumental based weather observations. Our approach can be applied to both recent as well as fossil dunes. Potential applications include the validation of climate models, the reconstruction of past supra-regional wind systems and the monitoring of future shifts in the climate system.

Extensive validation of CM SAF surface radiation products over Europe.

PubMed

Urraca, Ruben; Gracia-Amillo, Ana M; Koubli, Elena; Huld, Thomas; Trentmann, Jörg; Riihelä, Aku; Lindfors, Anders V; Palmer, Diane; Gottschalg, Ralph; Antonanzas-Torres, Fernando

2017-09-15

This work presents a validation of three satellite-based radiation products over an extensive network of 313 pyranometers across Europe, from 2005 to 2015. The products used have been developed by the Satellite Application Facility on Climate Monitoring (CM SAF) and are one geostationary climate dataset (SARAH-JRC), one polar-orbiting climate dataset (CLARA-A2) and one geostationary operational product. Further, the ERA-Interim reanalysis is also included in the comparison. The main objective is to determine the quality level of the daily means of CM SAF datasets, identifying their limitations, as well as analyzing the different factors that can interfere in the adequate validation of the products. The quality of the pyranometer was the most critical source of uncertainty identified. In this respect, the use of records from Second Class pyranometers and silicon-based photodiodes increased the absolute error and the bias, as well as the dispersion of both metrics, preventing an adequate validation of the daily means. The best spatial estimates for the three datasets were obtained in Central Europe with a Mean Absolute Deviation (MAD) within 8-13 W/m 2 , whereas the MAD always increased at high-latitudes, snow-covered surfaces, high mountain ranges and coastal areas. Overall, the SARAH-JRC's accuracy was demonstrated over a dense network of stations making it the most consistent dataset for climate monitoring applications. The operational dataset was comparable to SARAH-JRC in Central Europe, but lacked of the temporal stability of climate datasets, while CLARA-A2 did not achieve the same level of accuracy despite predictions obtained showed high uniformity with a small negative bias. The ERA-Interim reanalysis shows the by-far largest deviations from the surface reference measurements.

Relationships between medical student burnout, empathy, and professionalism climate.

PubMed

Brazeau, Chantal M L R; Schroeder, Robin; Rovi, Sue; Boyd, Linda

2010-10-01

Medical student burnout is prevalent, and there has been much discussion about burnout and professionalism in medical education and the clinical learning environment. Yet, few studies have attempted to explore relationships between those issues using validated instruments. Medical students were surveyed at the beginning of their fourth year using the Maslach Burnout Inventory, the Jefferson Scale of Physician Empathy-Student Version, and the Professionalism Climate Instrument. The data were analyzed using Statistical Package for the Social Sciences, and Spearman correlation analysis was performed. Scores indicative of higher medical student burnout were associated with lower medical student empathy scores and with lower professionalism climate scores observed in medical students, residents, and faculty. Investigators observed relationships between medical student burnout, empathy, and professionalism climate. These findings may have implications for the design of curriculum interventions to promote student well-being and professionalism.

Role of Organizational Climate in Organizational Commitment: The Case of Teaching Hospitals

PubMed Central

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

Improving niche projections of plant species under climate change: Silene acaulis on the British Isles as a case study

NASA Astrophysics Data System (ADS)

Ferrarini, Alessandro; Alsafran, Mohammed H. S. A.; Dai, Junhu; Alatalo, Juha M.

2018-04-01

Empirical works to assist in choosing climatically relevant variables in the attempt to predict climate change impacts on plant species are limited. Further uncertainties arise in choice of an appropriate niche model. In this study we devised and tested a sharp methodological framework, based on stringent variable ranking and filtering and flexible model selection, to minimize uncertainty in both niche modelling and successive projection of plant species distributions. We used our approach to develop an accurate, parsimonious model of Silene acaulis (L.) presence/absence on the British Isles and to project its presence/absence under climate change. The approach suggests the importance of (a) defining a reduced set of climate variables, actually relevant to species presence/absence, from an extensive list of climate predictors, and (b) considering climate extremes instead of, or together with, climate averages in projections of plant species presence/absence under future climate scenarios. Our methodological approach reduced the number of relevant climate predictors by 95.23% (from 84 to only 4), while simultaneously achieving high cross-validated accuracy (97.84%) confirming enhanced model performance. Projections produced under different climate scenarios suggest that S. acaulis will likely face climate-driven fast decline in suitable areas on the British Isles, and that upward and northward shifts to occupy new climatically suitable areas are improbable in the future. Our results also imply that conservation measures for S. acaulis based upon assisted colonization are unlikely to succeed on the British Isles due to the absence of climatically suitable habitat, so different conservation actions (seed banks and/or botanical gardens) are needed.

Impacts Of Global/Regional Climate Changes On Environment And Health: Need For Integrated Research And Education Collaboration (Invited)

NASA Astrophysics Data System (ADS)

Tuluri, F.

2013-12-01

The realization of long term changes in climate in research community has to go beyond the comfort zone through climate literacy in academics. Higher education on climate change is the platform to bring together the otherwise disconnected factors such as effective discovery, decision making, innovation, interdisciplinary collaboration, Climate change is a complex process that may be due to natural internal processes within the climate system, or to variations in natural or anthropogenic (human-driven) external forcing. Global climate change indicates a change in either the mean state of the climate or in its variability, persisting for several decades or longer. This includes changes in average weather conditions on Earth, such as a change in average global temperature, as well as changes in how frequently regions experience heat waves, droughts, floods, storms, and other extreme weather. It is important to examine the effects of climate variations on human health and disorders in order to take preventive measures. Similarly, the influence of climate changes on animal management practices, pests and pest management systems, and high value crops such as citrus and vegetables is also equally important for investigation. New genetic agricultural varieties must be explored, and pilot studies should examine biotechnology transfer. Recent climate model improvements have resulted in an enhanced ability to simulate many aspects of climate variability and extremes. However, they are still characterized by systematic errors and limitations in accurately simulating more precisely regional climate conditions. The present situations warrant developing climate literacy on the synergistic impacts of environmental change, and improve development, testing and validation of integrated stress impacts through computer modeling. In the present study we present a detailed study of the current status on the impacts of global/regional climate changes on environment and health with a view to highlighting the need for integrated research and education collaboration at national and global level.

Development of an Independent Global Land Cover Validation Dataset

NASA Astrophysics Data System (ADS)

Sulla-Menashe, D. J.; Olofsson, P.; Woodcock, C. E.; Holden, C.; Metcalfe, M.; Friedl, M. A.; Stehman, S. V.; Herold, M.; Giri, C.

2012-12-01

Accurate information related to the global distribution and dynamics in global land cover is critical for a large number of global change science questions. A growing number of land cover products have been produced at regional to global scales, but the uncertainty in these products and the relative strengths and weaknesses among available products are poorly characterized. To address this limitation we are compiling a database of high spatial resolution imagery to support international land cover validation studies. Validation sites were selected based on a probability sample, and may therefore be used to estimate statistically defensible accuracy statistics and associated standard errors. Validation site locations were identified using a stratified random design based on 21 strata derived from an intersection of Koppen climate classes and a population density layer. In this way, the two major sources of global variation in land cover (climate and human activity) are explicitly included in the stratification scheme. At each site we are acquiring high spatial resolution (< 1-m) satellite imagery for 5-km x 5-km blocks. The response design uses an object-oriented hierarchical legend that is compatible with the UN FAO Land Cover Classification System. Using this response design, we are classifying each site using a semi-automated algorithm that blends image segmentation with a supervised RandomForest classification algorithm. In the long run, the validation site database is designed to support international efforts to validate land cover products. To illustrate, we use the site database to validate the MODIS Collection 4 Land Cover product, providing a prototype for validating the VIIRS Surface Type Intermediate Product scheduled to start operational production early in 2013. As part of our analysis we evaluate sources of error in coarse resolution products including semantic issues related to the class definitions, mixed pixels, and poor spectral separation between classes.

The perception of the patient safety climate by professionals of the emergency department.

PubMed

Rigobello, Mayara Carvalho Godinho; Carvalho, Rhanna Emanuela Fontenele Lima de; Guerreiro, Juliana Magalhães; Motta, Ana Paula Gobbo; Atila, Elizabeth; Gimenes, Fernanda Raphael Escobar

2017-07-01

The aim of this study was to assess the patient safety climate from the perspective of healthcare professionals working in the emergency department of a hospital in Brazil. Emergency departments are complex and dynamic environments. They are prone to adverse events that compromise the quality of care provided and reveal the importance of patient safety culture and climate. This was a quantitative, descriptive, cross-sectional study. The Safety Attitudes Questionnaire (SAQ) - Short Form 2006 was used for data collection, validated and adapted into Portuguese. The study sample consisted of 125 participants. Most of the participants were female (57.6%) and had worked in emergency department for more than 10years (56.8%). Sixty-two participants (49.6%) were nursing professionals. The participants demonstrated satisfaction with their jobs and dissatisfaction with the actions of management with regard to safety issues. Participants' perceptions about the patient safety climate were found to be negative. Knowledge of professionals' perceptions of patient safety climate in the context of emergency care helps with assessments of the safety culture, contributes to improvement of health care, reduces adverse events, and can focus efforts to improve the quality of care provided to patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

Climate induces seasonality in pneumococcal transmission

PubMed Central

Numminen, Elina; Chewapreecha, Claire; Turner, Claudia; Goldblatt, David; Nosten, Francois; Bentley, Stephen D.; Turner, Paul; Corander, Jukka

2015-01-01

Streptococcus pneumoniae is a significant human pathogen and a leading cause of infant mortality in developing countries. Considerable global variation in the pneumococcal carriage prevalence has been observed and the ecological factors contributing to it are not yet fully understood. We use data from a cohort of infants in Asia to study the effects of climatic conditions on both acquisition and clearance rates of the bacterium, finding significantly higher transmissibility during the cooler and drier months. Conversely, the length of a colonization period is unaffected by the season. Independent carriage data from studies conducted on the African and North American continents suggest similar effects of the climate on the prevalence of this bacterium, which further validates the obtained results. Further studies could be important to replicate the findings and explain the mechanistic role of cooler and dry air in the physiological response to nasopharyngeal acquisition of the pneumococcus. PMID:26067932

Climate induces seasonality in pneumococcal transmission.

PubMed

Numminen, Elina; Chewapreecha, Claire; Turner, Claudia; Goldblatt, David; Nosten, Francois; Bentley, Stephen D; Turner, Paul; Corander, Jukka

2015-06-12

Streptococcus pneumoniae is a significant human pathogen and a leading cause of infant mortality in developing countries. Considerable global variation in the pneumococcal carriage prevalence has been observed and the ecological factors contributing to it are not yet fully understood. We use data from a cohort of infants in Asia to study the effects of climatic conditions on both acquisition and clearance rates of the bacterium, finding significantly higher transmissibility during the cooler and drier months. Conversely, the length of a colonization period is unaffected by the season. Independent carriage data from studies conducted on the African and North American continents suggest similar effects of the climate on the prevalence of this bacterium, which further validates the obtained results. Further studies could be important to replicate the findings and explain the mechanistic role of cooler and dry air in the physiological response to nasopharyngeal acquisition of the pneumococcus.

Assessing the Impact of Climate Change on Extreme Streamflow and Reservoir Operation for Nuuanu Watershed, Oahu, Hawaii

NASA Astrophysics Data System (ADS)

Leta, O. T.; El-Kadi, A. I.; Dulaiova, H.

2016-12-01

Extreme events, such as flooding and drought, are expected to occur at increased frequencies worldwide due to climate change influencing the water cycle. This is particularly critical for tropical islands where the local freshwater resources are very sensitive to climate. This study examined the impact of climate change on extreme streamflow, reservoir water volume and outflow for the Nuuanu watershed, using the Soil and Water Assessment Tool (SWAT) model. Based on the sensitive parameters screened by the Latin Hypercube-One-factor-At-a-Time (LH-OAT) method, SWAT was calibrated and validated to daily streamflow using the SWAT Calibration and Uncertainty Program (SWAT-CUP) at three streamflow gauging stations. Results showed that SWAT adequately reproduced the observed daily streamflow hydrographs at all stations. This was verified with Nash-Sutcliffe Efficiency that resulted in acceptable values of 0.58 to 0.88, whereby more than 90% of observations were bracketed within 95% model prediction uncertainty interval for both calibration and validation periods, signifying the potential applicability of SWAT for future prediction. The climate change impact on extreme flows, reservoir water volume and outflow was assessed under the Representative Concentration Pathways of 4.5 and 8.5 scenarios. We found wide changes in extreme peak and low flows ranging from -44% to 20% and -50% to -2%, respectively, compared to baseline. Consequently, the amount of water stored in Nuuanu reservoir will be decreased up to 27% while the corresponding outflow rates are expected to decrease up to 37% relative to the baseline. In addition, the stored water and extreme flows are highly sensitive to rainfall change when compared to temperature and solar radiation changes. It is concluded that the decrease in extreme low and peak flows can have serious consequences, such as flooding, drought, with detrimental effects on riparian ecological functioning. This study's results are expected to aid in reservoir operation as well as in identifying appropriate climate change adaptation strategies.

Criteria for the prioritization of public health interventions for climate-sensitive vector-borne diseases in Quebec.

PubMed

Hongoh, Valerie; Gosselin, Pierre; Michel, Pascal; Ravel, André; Waaub, Jean-Philippe; Campagna, Céline; Samoura, Karim

2017-01-01

Prioritizing resources for optimal responses to an ever growing list of existing and emerging infectious diseases represents an important challenge to public health. In the context of climate change, there is increasing anticipated variability in the occurrence of infectious diseases, notably climate-sensitive vector-borne diseases. An essential step in prioritizing efforts is to identify what considerations and concerns to take into account to guide decisions and thus set disease priorities. This study was designed to perform a comprehensive review of criteria for vector-borne disease prioritization, assess their applicability in a context of climate change with a diverse cross-section of stakeholders in order to produce a baseline list of considerations to use in this decision-making context. Differences in stakeholder choices were examined with regards to prioritization of these criteria for research, surveillance and disease prevention and control objectives. A preliminary list of criteria was identified following a review of the literature. Discussions with stakeholders were held to consolidate and validate this list of criteria and examine their effects on disease prioritization. After this validation phase, a total of 21 criteria were retained. A pilot vector-borne disease prioritization exercise was conducted using PROMETHEE to examine the effects of the retained criteria on prioritization in different intervention domains. Overall, concerns expressed by stakeholders for prioritization were well aligned with categories of criteria identified in previous prioritization studies. Weighting by category was consistent between stakeholders overall, though some significant differences were found between public health and non-public health stakeholders. From this exercise, a general model for climate-sensitive vector-borne disease prioritization has been developed that can be used as a starting point for further public health prioritization exercises relating to research, surveillance, and prevention and control interventions in a context of climate change. Multi-stakeholder engagement in prioritization can help broaden the range of criteria taken into account, offer opportunities for early identification of potential challenges and may facilitate acceptability of any resulting decisions.

Comparative Synthesis of Current and Future Urban Stormwater Runoff Scenarios in Tampa Bay Basin under a Changing Climate

NASA Astrophysics Data System (ADS)

Khan, M.; Abdul-Aziz, O. I.

2016-12-01

Changes in climatic regimes and basin characteristics such as imperviousness, roughness and land use types would lead to potential changes in stormwater budget. In this study we quantified reference sensitivities of stormwater runoff to the potential climatic and land use/cover changes by developing a large-scale, mechanistic rainfall-runoff model for the Tampa Bay Basin of Florida using the US EPA Storm Water Management Model (SWMM 5.1). Key processes of urban hydrology, its dynamic interactions with groundwater and sea level, hydro-climatic variables and land use/cover characteristics were incorporated within the model. The model was calibrated and validated with historical streamflow data. We then computed the historical (1970-2000) and potential 2050s stormwater budgets for the Tampa Bay Basin. Climatic scenario projected by the global climate models (GCMs) and the regional climate models (RCMs), along with sea level and land use/cover projections, were utilized to anticipate the future stormwater budget. The comparative assessment of current and future stormwater scenario will aid a proactive management of stormwater runoff under a changing climate in the Tampa Bay Basin and similar urban basins around the world.

Assess Climate Change's Impact on Coastal Rivers using a Coupled Climate-Hydrology Model

NASA Astrophysics Data System (ADS)

Xue, Z. G.; Gochis, D.; Yu, W.; Zang, Z.; Sampson, K. M.; Keim, B. D.

2016-12-01

In this study we present a coupled climate-hydrological model reproducing the water cycle of three coastal river basins along the northern Gulf of Mexico for the past three decades (1985-2014). Model simulated climate condition, surface physics, and streamflow were well validated against in situ data and satellite-derived products, giving us the confidence that the newly developed WRF-Hydro model can be a robust tool for evaluating climate change's impact on hydrological regime. Trend analysis of model simulated monthly and annual time series indicates that local climate is getting hotter and dryer, specifically during the growing season. Wavelet analysis reveals that local evapotranspiration is strongly correlated with temperature, while soil moisture, water surplus, and streamflow are coupled with precipitation. In addition, local climate is closely correlated with large-scale climate dynamics such as AMO and ENSO. A possible change-point is detected around year 2004, after which, the monthly precipitation decreased by 14.2%, evapotranspiration increased by 2.9%, and water surplus decreased by 36.5%. The implication of the difference between the water surplus (runoff) calculated using the classic Thornthwaite method and river discharge estimated using streamflow records to the coastal environment is also discussed.

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

PubMed

Harbert, Robert S; Nixon, Kevin C

2015-08-01

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

A 30+ Year AVHRR LAI and FAPAR Climate Data Record: Algorithm Description, Validation, and Case Study

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.

Signal Trees: Communicating Attribution of Climate Change Impacts Through Causal Chain Illustrations

NASA Astrophysics Data System (ADS)

Cutting, H.

2016-12-01

Communicating the attribution of current climate change impacts is a key task for engagment with the general public, news media and policy makers, particularly as climate events unfold in real time. The IPCC WGII in AR5 validated the use of causal chain illustrations to depict attribution of individual climate change impacts. Climate Signals, an online digital platform for mapping and cataloging climate change impacts (launched in May of 2016), explores the use of such illustrations for communicating attribution. The Climate Signals project has developed semi-automated graphing software to produce custom attribution trees for numerous climate change events. This effort offers lessons for engagement of the general public and policy makers in the attribution of climate change impacts.

The development and psychometric evaluation of a safety climate measure for primary care.

PubMed

de Wet, C; Spence, W; Mash, R; Johnson, P; Bowie, P

2010-12-01

Building a safety culture is an important part of improving patient care. Measuring perceptions of safety climate among healthcare teams and organisations is a key element of this process. Existing measurement instruments are largely developed for secondary care settings in North America and many lack adequate psychometric testing. Our aim was to develop and test an instrument to measure perceptions of safety climate among primary care teams in National Health Service for Scotland. Questionnaire development was facilitated through a steering group, literature review, semistructured interviews with primary care team members, a modified Delphi and completion of a content validity index by experts. A cross-sectional postal survey utilising the questionnaire was undertaken in a random sample of west of Scotland general practices to facilitate psychometric evaluation. Statistical methods, including exploratory and confirmatory factor analysis, and Cronbach and Raykov reliability coefficients were conducted. Of the 667 primary care team members based in 49 general practices surveyed, 563 returned completed questionnaires (84.4%). Psychometric evaluation resulted in the development of a 30-item questionnaire with five safety climate factors: leadership, teamwork, communication, workload and safety systems. Retained items have strong factor loadings to only one factor. Reliability coefficients was satisfactory (α = 0.94 and ρ = 0.93). This study is the first stage in the development of an appropriately valid and reliable safety climate measure for primary care. Measuring safety climate perceptions has the potential to help primary care organisations and teams focus attention on safety-related issues and target improvement through educational interventions. Further research is required to explore acceptability and feasibility issues for primary care teams and the potential for organisational benchmarking.

Long Term Cloud Property Datasets From MODIS and AVHRR Using the CERES Cloud Algorithm

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Bedka, Kristopher M.; Doelling, David R.; Sun-Mack, Sunny; Yost, Christopher R.; Trepte, Qing Z.; Bedka, Sarah T.; Palikonda, Rabindra; Scarino, Benjamin R.; Chen, Yan;

Robustness and Uncertainty: Applications for Policy in Climate and Hydrological Modeling

NASA Astrophysics Data System (ADS)

Fields, A. L., III

2015-12-01

Policymakers must often decide how to proceed when presented with conflicting simulation data from hydrological, climatological, and geological models. While laboratory sciences often appeal to the reproducibility of results to argue for the validity of their conclusions, simulations cannot use this strategy for a number of pragmatic and methodological reasons. However, robustness of predictions and causal structures can serve the same function for simulations as reproducibility does for laboratory experiments and field observations in either adjudicating between conflicting results or showing that there is insufficient justification to externally validate the results. Additionally, an interpretation of the argument from robustness is presented that involves appealing to the convergence of many well-built and diverse models rather than the more common version which involves appealing to the probability that one of a set of models is likely to be true. This interpretation strengthens the case for taking robustness as an additional requirement for the validation of simulation results and ultimately supports the idea that computer simulations can provide information about the world that is just as trustworthy as data from more traditional laboratory studies and field observations. Understanding the importance of robust results for the validation of simulation data is especially important for policymakers making decisions on the basis of potentially conflicting models. Applications will span climate, hydrological, and hydroclimatological models.

Localizing drought monitoring products to support agricultural climate service advisories in South Asia

NASA Astrophysics Data System (ADS)

Qamer, F. M.; Matin, M. A.; Yadav, N. K.; Bajracharya, B.; Zaitchik, B. F.; Ellenburg, W. L.; Krupnik, T. J.; Hussain, G.

2017-12-01

The Fifth Assessment Report of the Intergovernmental Panel on Climate Change identifies drought as one of the major climate risks in South Asia. During past two decades, a large amount of climate data have been made available by the scientific community, but the deployment of climate information for local level and agricultural decision making remains less than optimal. The provisioning of locally calibrated, easily accessible, decision-relevant and user-oriented information, in the form of drought advisory service could help to prepare communities to reduce climate vulnerability and increase resilience. A collaborative effort is now underway to strengthen existing and/or establish new drought monitoring and early warning systems in Afghanistan, Bangladesh, Nepal and Pakistan by incorporating standard ground-based observations, earth observation datasets, and numerical forecast models. ICT-based agriculture drought monitoring platforms, hosted at national agricultural and meteorological institutions, are being developed and coupled with communications and information deployment strategies to enable the rapid and efficient deployment of information that farmers can understand, interpret, and act on to adapt to anticipated droughts. Particular emphasis is being placed on the calibration and validation of data products through retrospective analysis of time series data, in addition to the installation of automatic weather station networks. In order to contextualize monitoring products to that they may be relevant for farmers' primary cropping systems, district level farming practices calendars are being compiled and validated through focus groups and surveys to identify the most important times and situations during which farmers can adapt to drought. High-resolution satellite crop distribution maps are under development and validation to add value to these efforts. This programme also aims to enhance capacity of agricultural extension staff to better understand climate information, probabilistic forecasts, related technologies, and adaptation strategies, in addition to equipping them with increased capacity to convey drought risks to farmers and improve climate related decision making.

Reconstruction of spatio-temporal temperature from sparse historical records using robust probabilistic principal component regression

USGS Publications Warehouse

Tipton, John; Hooten, Mevin B.; Goring, Simon

2017-01-01

Scientific records of temperature and precipitation have been kept for several hundred years, but for many areas, only a shorter record exists. To understand climate change, there is a need for rigorous statistical reconstructions of the paleoclimate using proxy data. Paleoclimate proxy data are often sparse, noisy, indirect measurements of the climate process of interest, making each proxy uniquely challenging to model statistically. We reconstruct spatially explicit temperature surfaces from sparse and noisy measurements recorded at historical United States military forts and other observer stations from 1820 to 1894. One common method for reconstructing the paleoclimate from proxy data is principal component regression (PCR). With PCR, one learns a statistical relationship between the paleoclimate proxy data and a set of climate observations that are used as patterns for potential reconstruction scenarios. We explore PCR in a Bayesian hierarchical framework, extending classical PCR in a variety of ways. First, we model the latent principal components probabilistically, accounting for measurement error in the observational data. Next, we extend our method to better accommodate outliers that occur in the proxy data. Finally, we explore alternatives to the truncation of lower-order principal components using different regularization techniques. One fundamental challenge in paleoclimate reconstruction efforts is the lack of out-of-sample data for predictive validation. Cross-validation is of potential value, but is computationally expensive and potentially sensitive to outliers in sparse data scenarios. To overcome the limitations that a lack of out-of-sample records presents, we test our methods using a simulation study, applying proper scoring rules including a computationally efficient approximation to leave-one-out cross-validation using the log score to validate model performance. The result of our analysis is a spatially explicit reconstruction of spatio-temporal temperature from a very sparse historical record.

Douglas-fir plantations in Europe: a retrospective test of assisted migration to address climate change.

PubMed

Isaac-Renton, Miriam G; Roberts, David R; Hamann, Andreas; Spiecker, Heinrich

2014-08-01

We evaluate genetic test plantations of North American Douglas-fir provenances in Europe to quantify how tree populations respond when subjected to climate regime shifts, and we examined whether bioclimate envelope models developed for North America to guide assisted migration under climate change can retrospectively predict the success of these provenance transfers to Europe. The meta-analysis is based on long-term growth data of 2800 provenances transferred to 120 European test sites. The model was generally well suited to predict the best performing provenances along north-south gradients in Western Europe, but failed to predict superior performance of coastal North American populations under continental climate conditions in Eastern Europe. However, model projections appear appropriate when considering additional information regarding adaptation of Douglas-fir provenances to withstand frost and drought, even though the model partially fails in a validation against growth traits alone. We conclude by applying the partially validated model to climate change scenarios for Europe, demonstrating that climate trends observed over the last three decades warrant changes to current use of Douglas-fir provenances in plantation forestry throughout Western and Central Europe. © 2014 John Wiley & Sons Ltd.

Assessing performance and seasonal bias of pollen-based climate reconstructions in a perfect model world

NASA Astrophysics Data System (ADS)

Rehfeld, Kira; Trachsel, Mathias; Telford, Richard J.; Laepple, Thomas

2016-12-01

Reconstructions of summer, winter or annual mean temperatures based on the species composition of bio-indicators such as pollen, foraminifera or chironomids are routinely used in climate model-proxy data comparison studies. Most reconstruction algorithms exploit the joint distribution of modern spatial climate and species distribution for the development of the reconstructions. They rely on the space-for-time substitution and the specific assumption that environmental variables other than those reconstructed are not important or that their relationship with the reconstructed variable(s) should be the same in the past as in the modern spatial calibration dataset. Here we test the implications of this "correlative uniformitarianism" assumption on climate reconstructions in an ideal model world, in which climate and vegetation are known at all times. The alternate reality is a climate simulation of the last 6000 years with dynamic vegetation. Transient changes of plant functional types are considered as surrogate pollen counts and allow us to establish, apply and evaluate transfer functions in the modeled world. We find that in our model experiments the transfer function cross validation r2 is of limited use to identify reconstructible climate variables, as it only relies on the modern spatial climate-vegetation relationship. However, ordination approaches that assess the amount of fossil vegetation variance explained by the reconstructions are promising. We furthermore show that correlations between climate variables in the modern climate-vegetation relationship are systematically extended into the reconstructions. Summer temperatures, the most prominent driving variable for modeled vegetation change in the Northern Hemisphere, are accurately reconstructed. However, the amplitude of the model winter and mean annual temperature cooling between the mid-Holocene and present day is overestimated and similar to the summer trend in magnitude. This effect occurs because temporal changes of a dominant climate variable, such as summer temperatures in the model's Arctic, are imprinted on a less important variable, leading to reconstructions biased towards the dominant variable's trends. Our results, although based on a model vegetation that is inevitably simpler than reality, indicate that reconstructions of multiple climate variables based on modern spatial bio-indicator datasets should be treated with caution. Expert knowledge on the ecophysiological drivers of the proxies, as well as statistical methods that go beyond the cross validation on modern calibration datasets, are crucial to avoid misinterpretation.

Detecting ecosystem performance anomalies for land management in the upper colorado river basin using satellite observations, climate data, and ecosystem models

USGS Publications Warehouse

Gu, Yingxin; Wylie, B.K.

2010-01-01

This study identifies areas with ecosystem performance anomalies (EPA) within the Upper Colorado River Basin (UCRB) during 2005-2007 using satellite observations, climate data, and ecosystem models. The final EPA maps with 250-m spatial resolution were categorized as normal performance, underperformance, and overperformance (observed performance relative to weather-based predictions) at the 90% level of confidence. The EPA maps were validated using "percentage of bare soil" ground observations. The validation results at locations with comparable site potential showed that regions identified as persistently underperforming (overperforming) tended to have a higher (lower) percentage of bare soil, suggesting that our preliminary EPA maps are reliable and agree with ground-based observations. The 3-year (2005-2007) persistent EPA map from this study provides the first quantitative evaluation of ecosystem performance anomalies within the UCRB and will help the Bureau of Land Management (BLM) identify potentially degraded lands. Results from this study can be used as a prototype by BLM and other land managers for making optimal land management decisions. ?? 2010 by the authors.

Detecting Ecosystem Performance Anomalies for Land Management in the Upper Colorado River Basin Using Satellite Observations, Climate Data, and Ecosystem Models

USGS Publications Warehouse

Gu, Yingxin; Wylie, Bruce K.

2010-01-01

This study identifies areas with ecosystem performance anomalies (EPA) within the Upper Colorado River Basin (UCRB) during 2005–2007 using satellite observations, climate data, and ecosystem models. The final EPA maps with 250-m spatial resolution were categorized as normal performance, underperformance, and overperformance (observed performance relative to weather-based predictions) at the 90% level of confidence. The EPA maps were validated using “percentage of bare soil” ground observations. The validation results at locations with comparable site potential showed that regions identified as persistently underperforming (overperforming) tended to have a higher (lower) percentage of bare soil, suggesting that our preliminary EPA maps are reliable and agree with ground-based observations. The 3-year (2005–2007) persistent EPA map from this study provides the first quantitative evaluation of ecosystem performance anomalies within the UCRB and will help the Bureau of Land Management (BLM) identify potentially degraded lands. Results from this study can be used as a prototype by BLM and other land managers for making optimal land management decisions.

Assessing a Top-Down Modeling Approach for Seasonal Scale Snow Sensitivity

NASA Astrophysics Data System (ADS)

Luce, C. H.; Lute, A.

2017-12-01

Mechanistic snow models are commonly applied to assess changes to snowpacks in a warming climate. Such assessments involve a number of assumptions about details of weather at daily to sub-seasonal time scales. Models of season-scale behavior can provide contrast for evaluating behavior at time scales more in concordance with climate warming projections. Such top-down models, however, involve a degree of empiricism, with attendant caveats about the potential of a changing climate to affect calibrated relationships. We estimated the sensitivity of snowpacks from 497 Snowpack Telemetry (SNOTEL) stations in the western U.S. based on differences in climate between stations (spatial analog). We examined the sensitivity of April 1 snow water equivalent (SWE) and mean snow residence time (SRT) to variations in Nov-Mar precipitation and average Nov-Mar temperature using multivariate local-fit regressions. We tested the modeling approach using a leave-one-out cross-validation as well as targeted two-fold non-random cross-validations contrasting, for example, warm vs. cold years, dry vs. wet years, and north vs. south stations. Nash-Sutcliffe Efficiency (NSE) values for the validations were strong for April 1 SWE, ranging from 0.71 to 0.90, and still reasonable, but weaker, for SRT, in the range of 0.64 to 0.81. From these ranges, we exclude validations where the training data do not represent the range of target data. A likely reason for differences in validation between the two metrics is that the SWE model reflects the influence of conservation of mass while using temperature as an indicator of the season-scale energy balance; in contrast, SRT depends more strongly on the energy balance aspects of the problem. Model forms with lower numbers of parameters generally validated better than more complex model forms, with the caveat that pseudoreplication could encourage selection of more complex models when validation contrasts were weak. Overall, the split sample validations confirm transferability of the relationships in space and time contingent upon full representation of validation conditions in the calibration data set. The ability of the top-down space-for-time models to predict in new time periods and locations lends confidence to their application for assessments and for improving finer time scale models.

Effects of climate change on daily minimum and maximum temperatures and cloudiness in the Shikoku region: a statistical downscaling model approach

NASA Astrophysics Data System (ADS)

Tatsumi, Kenichi; Oizumi, Tsutao; Yamashiki, Yosuke

2015-04-01

In this study, we present a detailed analysis of the effect of changes in cloudiness (CLD) between a future period (2071-2099) and the base period (1961-1990) on daily minimum temperature (TMIN) and maximum temperature (TMAX) in the same period for the Shikoku region, Japan. This analysis was performed using climate data obtained with the use of the Statistical DownScaling Model (SDSM). We calibrated the SDSM using the National Center for Environmental Prediction (NCEP) reanalysis dataset for the SDSM input and daily time series of temperature and CLD from 10 surface data points (SDP) in Shikoku. Subsequently, we validated the SDSM outputs, specifically, TMIN, TMAX, and CLD, obtained with the use of the NCEP reanalysis dataset and general circulation model (GCM) data against the SDP. The GCM data used in the validation procedure were those from the Hadley Centre Coupled Model, version 3 (HadCM3) for the Special Report on Emission Scenarios (SRES) A2 and B2 scenarios and from the third generation Coupled Global Climate Model (CGCM3) for the SRES A2 and A1B scenarios. Finally, the validated SDSM was run to study the effect of future changes in CLD on TMIN and TMAX. Our analysis showed that (1) the negative linear fit between changes in TMAX and those in CLD was statistically significant in winter while the relationship between the two changes was not evident in summer, (2) the dependency of future changes in TMAX and TMIN on future changes in CLD were more evident in winter than in other seasons with the present SDSM, (3) the diurnal temperature range (DTR) decreased in the southern part of Shikoku in summer in all the SDSM projections while DTR increased in the northern part of Shikoku in the same season in these projections, (4) the dependencies of changes in DTR on changes in CLD were unclear in summer and winter. Results of the SDSM simulations performed for climate change scenarios such as those from this study contribute to local-scale agricultural and hydrological simulations and development of agricultural and hydrological models.

ISCCP-B1U Geostationary Satellite VIS Channel Vicarious Calibration/Validation in support of creation of long term climate data records

NASA Astrophysics Data System (ADS)

Gopalan, A.; Doelling, D. R.; Bhatt, R.; Haney, C.; Scarino, B. R.

2017-12-01

The International Satellite Cloud Climatology Project (ISCCP) provides a 40-year geostationary (GEO) imager record from satellites worldwide of 3-hourly cloud properties and surface reflectances. ISCCP B1 data archived at the National Climatic Data Center (NCDC) are a collection of measurements from imagers on international GEO meteorological satellites which are sampled to approximately 10-km and at 3-hour intervals. ISCCP coordinated the ingestion of 3-hour geostationary imager pixel level radiances and placed them in a common and consistent unified format (ISCCP-B1U) across GEO imagers and archived the datasets at NCDC for future reprocessing efforts. The GEO imagers in the B1U record lacked onboard calibration to monitor the temporal stability of the visible channel. Consistent calibration of the B1U GEO imager record opens up the potential for their use in global climate studies. The NASA CERES project released the Edition4 products, where the GEO imager calibration has been referenced to the Aqua-MODIS band-1 Collection 6 calibration. This was done by matching coincident GEO and MODIS radiance pairs to transfer the MODIS calibration. This primary method was then validated by the independent vicarious calibration methods using invariant desert and deep convective cloud (DCC) targets. In this study we extend these vicarious methods to the historical ISCCP-B1U format GEO record going back from 2000-1978 while addressing some of the challenges viz. the short historical GEO imager lifetimes, spurious imagery, non-stationary VIS channel space counts, data source processing differences, inadequate spectral response function characterization and possible wavelength dependent degradations. Another challenge, is the occasional abrupt calibration gain discontinuities in time, these are validated by tracking the brightest pixels over time. We discuss the methodology used to address some of the challenges and present results from the two independent vicarious calibration approaches that are then merged according to their respective uncertainties to obtain optimal and self-consistent calibration gain timelines for the various GEO sensors in the historical record in support of global climate change studies

Calculating distributed glacier mass balance for the Swiss Alps from RCM output: Development and testing of downscaling and validation methods

NASA Astrophysics Data System (ADS)

Machguth, H.; Paul, F.; Kotlarski, S.; Hoelzle, M.

2009-04-01

Climate model output has been applied in several studies on glacier mass balance calculation. Hereby, computation of mass balance has mostly been performed at the native resolution of the climate model output or data from individual cells were selected and statistically downscaled. Little attention has been given to the issue of downscaling entire fields of climate model output to a resolution fine enough to compute glacier mass balance in rugged high-mountain terrain. In this study we explore the use of gridded output from a regional climate model (RCM) to drive a distributed mass balance model for the perimeter of the Swiss Alps and the time frame 1979-2003. Our focus lies on the development and testing of downscaling and validation methods. The mass balance model runs at daily steps and 100 m spatial resolution while the RCM REMO provides daily grids (approx. 18 km resolution) of dynamically downscaled re-analysis data. Interpolation techniques and sub-grid parametrizations are combined to bridge the gap in spatial resolution and to obtain daily input fields of air temperature, global radiation and precipitation. The meteorological input fields are compared to measurements at 14 high-elevation weather stations. Computed mass balances are compared to various sets of direct measurements, including stake readings and mass balances for entire glaciers. The validation procedure is performed separately for annual, winter and summer balances. Time series of mass balances for entire glaciers obtained from the model run agree well with observed time series. On the one hand, summer melt measured at stakes on several glaciers is well reproduced by the model, on the other hand, observed accumulation is either over- or underestimated. It is shown that these shifts are systematic and correlated to regional biases in the meteorological input fields. We conclude that the gap in spatial resolution is not a large drawback, while biases in RCM output are a major limitation to model performance. The development and testing of methods to reduce regionally variable biases in entire fields of RCM output should be a focus of pursuing studies.

Climatic Forecasting of Net Infiltration at Yucca Mountain, Using Analogue Meteorological Data

NASA Astrophysics Data System (ADS)

Faybishenko, B.

2005-12-01

Net infiltration is a key hydrologic parameter that, throughout the unsaturated zone, controls the rate of deep percolation, the groundwater recharge, radionuclide transport, and seepage into underground tunnels. Because net infiltration is largely affected by climatic conditions, future changes in climatic conditions will potentially alter net infiltration. The objectives of this presentation are to: (1) Present a conceptual model and a semi-empirical approach for regional climatic forecasting of net infiltration, based on precipitation and temperature data from analogue meteorological stations; and (2) Demonstrate the results of forecasting net infiltration for future climates - interglacial, monsoon and glacial - over the Yucca Mountain region for a period of 500,000 years. Calculations of net infiltration were performed using a modified Budyko's water-balance model, and potential evapotranspiration was evaluated from the temperature-based Thornthwaite formula. (Both Budyko's and Thornthwaite's formulae have been used broadly in hydrological studies.) The results of these calculations were used for ranking net infiltration, along with aridity and precipitation-effectiveness (P-E) indices, for future climatic scenarios. Using this approach, we determined a general trend of increasing net infiltration from the present-day (interglacial) climate to the monsoon, intermediate (glacial transition) climate, a trend that continued into the glacial climate time frame. The ranking of aridity and P-E indices is practically the same as that for net infiltration. Validation of the computed net infiltration rates yielded a good match with other field and modeling study results related to groundwater recharge and net infiltration evaluation.

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

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

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

Effect of Climate Change on Mediterranean Winter Ranges of Two Migratory Passerines

PubMed Central

Tellería, José L.; Fernández-López, Javier; Fandos, Guillermo

2016-01-01

We studied the effect of climate change on the distribution of two insectivorous passerines (the meadow pipit Anthus pratensis and the chiffchaff Phylloscopus collybita) in wintering grounds of the Western Mediterranean basin. In this region, precipitation and temperature can affect the distribution of these birds through direct (thermoregulation costs) or indirect effects (primary productivity). Thus, it can be postulated that projected climate changes in the region will affect the extent and suitability of their wintering grounds. We studied pipit and chiffchaff abundance in several hundred localities along a belt crossing Spain and Morocco and assessed the effects of climate and other geographical and habitat predictors on bird distribution. Multivariate analyses reported a positive effect of temperature on the present distribution of the two species, with an additional effect of precipitation on the meadow pipit. These climate variables were used with Maxent to model the occurrence probabilities of species using ring recoveries as presence data. Abundance and occupancy of the two species in the study localities adjusted to the distribution models, with more birds in sectors of high climate suitability. After validation, these models were used to forecast the distribution of climate suitability according to climate projections for 2050–2070 (temperature increase and precipitation reduction). Results show an expansion of climatically suitable sectors into the highlands by the effect of warming on the two species, and a retreat of the meadow pipit from southern sectors related to rain reduction. The predicted patterns show a mean increase in climate suitability for the two species due to the warming of the large highland expanses typical of the western Mediterranean. PMID:26761791

Developing a Comparative Measure of the Learning Climate in Professional Schools

ERIC Educational Resources Information Center

Bowen, Donald D.; Kilmann, Ralph H.

1975-01-01

The Learning Climate Questionnaire (LCQ) compares the objective properties of schools with measures of overall student satisfaction. The validity of the instrument suggests its use for substantive research investigations into the organizational dynamics of professional schools. (Author/JR)

Spatio-temporal dynamic climate model for Neoleucinodes elegantalis using CLIMEX

NASA Astrophysics Data System (ADS)

da Silva, Ricardo Siqueira; Kumar, Lalit; Shabani, Farzin; da Silva, Ezio Marques; da Silva Galdino, Tarcisio Visintin; Picanço, Marcelo Coutinho

2017-05-01

Seasonal variations are important components in understanding the ecology of insect population of crops. Ecological studies through modeling may be a useful tool for enhancing knowledge of seasonal patterns of insects on field crops as well as seasonal patterns of favorable climatic conditions for species. Recently CLIMEX, a semi-mechanistic niche model, was upgraded and enhanced to consider spatio-temporal dynamics of climate suitability through time. In this study, attempts were made to determine monthly variations of climate suitability for Neoleucinodes elegantalis (Guenée) (Lepidoptera: Crambidae) in five commercial tomato crop localities through the latest version of CLIMEX. We observed that N. elegantalis displays seasonality with increased abundance in tomato crops during summer and autumn, corresponding to the first 6 months of the year in monitored areas in this study. Our model demonstrated a strong accord between the CLIMEX weekly growth index (GIw) and the density of N. elegantalis for this period, thus indicating a greater confidence in our model results. Our model shows a seasonal variability of climatic suitability for N. elegantalis and provides useful information for initiating methods for timely management, such as sampling strategies and control, during periods of high degree of suitability for N. elegantalis. In this study, we ensure that the simulation results are valid through our verification using field data.

A Systematic Review of Primary Care Safety Climate Survey Instruments: Their Origins, Psychometric Properties, Quality, and Usage.

PubMed

Curran, Ciara; Lydon, Sinéad; Kelly, Maureen; Murphy, Andrew; Walsh, Chloe; OʼConnor, Paul

2018-06-01

Safety climate (SC) measurement is a common and feasible method of proactive safety assessment in primary care. However, there is no consensus on which instrument is "best" to use. The aim of the study was to identify the origins, psychometric properties, quality, and SC domains measured by survey instruments used to assess SC in primary care settings. Systematic searches were conducted using Medline, Embase, CINAHL, and PsycInfo in February 2016. English-language, peer-reviewed studies that reported the development and/or use of a SC survey in a primary care setting were included. Two reviewers independently extracted data (survey characteristics, origins, and psychometric properties) from studies and applied the Quality Assessment Tool for Studies with Diverse Designs to assess methodological rigour. Safety climate domains within surveys were deductively analyzed and categorized into common healthcare SC themes. Seventeen SC surveys were identified, of which 16 had been adapted from 2 main U.S. hospital-based surveys. Only 1 survey was developed de novo for a primary care setting. The quantity and quality of psychometric testing varied considerably across the surveys. Management commitment to safety was the most frequently measured SC theme (87.5%). Workload was infrequently measured (25%). Valid and reliable instruments, which are context specific to the healthcare environment for intentional use, are essential to accurately assess SC. Key recommendations include further establishing the construct and criterion-related validity of existing instruments as opposed to developing additional surveys.

Modelling of labour productivity loss due to climate change: HEAT-SHIELD

NASA Astrophysics Data System (ADS)

Kjellstrom, Tord; Daanen, Hein

2016-04-01

Climate change will bring higher heat levels (temperature and humidity combined) to large parts of the world. When these levels reach above thresholds well defined by human physiology, the ability to maintain physical activity levels decrease and labour productivity is reduced. This impact is of particular importance in work situations in areas with long high intensity hot seasons, but also affects cooler areas during heat waves. Our modelling of labour productivity loss includes climate model data of the Inter-Sectoral Impact Model Inter-comparison Project (ISI-MIP), calculations of heat stress indexes during different months, estimations of work capacity loss and its annual impacts in different parts of the world. Different climate models will be compared for the Representative Concentration Pathways (RCPs) and the outcomes of the 2015 Paris Climate Conference (COP21) agreements. The validation includes comparisons of modelling outputs with actual field studies using historical heat data. These modelling approaches are a first stage contribution to the European Commission funded HEAT-SHIELD project.

The Evolution of Indian and Pacific Ocean Denitrification and Nitrogen Dynamcs since the Miocene

NASA Astrophysics Data System (ADS)

Ravelo, A. C.; Carney, C.; Rosenthal, Y.; Holbourn, A.; Kulhanek, D. K.

2017-12-01

The feedbacks between geochemical cycles and physical climate change are poorly understood; however, there has been tremendous progress in developing coupled models to help predict the direction and strength of these feedbacks. As such, there is a need for more data to validate and test these models. To this end, the nitrogen (N) cycle, and its links to the biological pump and to climate, is an active area of paleoceanographic research. Using N isotope records, Robinson et al. (2014) showed that pelagic denitrification in the Indian and Pacific Oceans intensified as climate cooled and subsurface ventilation decreased since the Pliocene. They pointed out that a more ventilated warm Pliocene contrasts with glacial-interglacial patterns wherein more ventilation occurs during cold phases, indicating that different mechanisms may occur at different timescales. Our objective is to better understand the nature of the feedbacks between the oceanic N cycle and climate by focusing on the large dynamic range of conditions that occurred during and since the Miocene. We used new cores drilled during IODP Expedition 363 to generate bulk sediment N isotope records at three western tropical Pacific sites (U1486, U1488, U1490) and one southeastern tropical Indian Ocean site (U1482). We find that the N isotope trends since the Pliocene are in agreement with previous studies showing increasing denitrification as climate cooled. In the Miocene, the Indian Ocean record shows no long-term N isotope trend whereas the Pacific Ocean records show a trend that is roughly coupled to changes in global climate suggesting that pelagic denitrification in the Pacific was strongly influenced by greater ventilation during global warmth. However, there are notable deviations from this coupling during several intervals in the Miocene, and there are site-to-site differences in trends. These deviations and differences can be explained by changes in tropical productivity (e.g., late Miocene biogenic bloom), which drove changes subsurface oxygenation and denitrification, and by changes in regional circulation. Our study provides fundamental data that can be used to validate conceptual and numerical models of the long-term coupling of climate, biological productivity and ocean chemistry.

Limitations of Climatic Data for Inferring Species Boundaries: Insights from Speckled Rattlesnakes

PubMed Central

Flores-Villela, Oscar; Fujita, Matthew K.

2015-01-01

Phenotypes, DNA, and measures of ecological differences are widely used in species delimitation. Although rarely defined in such studies, ecological divergence is almost always approximated using multivariate climatic data associated with sets of specimens (i.e., the “climatic niche”); the justification for this approach is that species-specific climatic envelopes act as surrogates for physiological tolerances. Using identical statistical procedures, we evaluated the usefulness and validity of the climate-as-proxy assumption by comparing performance of genetic (nDNA SNPs and mitochondrial DNA), phenotypic, and climatic data for objective species delimitation in the speckled rattlesnake (Crotalus mitchellii) complex. Ordination and clustering patterns were largely congruent among intrinsic (heritable) traits (nDNA, mtDNA, phenotype), and discordance is explained by biological processes (e.g., ontogeny, hybridization). In contrast, climatic data did not produce biologically meaningful clusters that were congruent with any intrinsic dataset, but rather corresponded to regional differences in atmospheric circulation and climate, indicating an absence of inherent taxonomic signal in these data. Surrogating climate for physiological tolerances adds artificial weight to evidence of species boundaries, as these data are irrelevant for that purpose. Based on the evidence from congruent clustering of intrinsic datasets, we recommend that three subspecies of C. mitchellii be recognized as species: C. angelensis, C. mitchellii, and C. Pyrrhus. PMID:26107178

Limitations of climatic data for inferring species boundaries: insights from speckled rattlesnakes.

PubMed

Meik, Jesse M; Streicher, Jeffrey W; Lawing, A Michelle; Flores-Villela, Oscar; Fujita, Matthew K

2015-01-01

Phenotypes, DNA, and measures of ecological differences are widely used in species delimitation. Although rarely defined in such studies, ecological divergence is almost always approximated using multivariate climatic data associated with sets of specimens (i.e., the "climatic niche"); the justification for this approach is that species-specific climatic envelopes act as surrogates for physiological tolerances. Using identical statistical procedures, we evaluated the usefulness and validity of the climate-as-proxy assumption by comparing performance of genetic (nDNA SNPs and mitochondrial DNA), phenotypic, and climatic data for objective species delimitation in the speckled rattlesnake (Crotalus mitchellii) complex. Ordination and clustering patterns were largely congruent among intrinsic (heritable) traits (nDNA, mtDNA, phenotype), and discordance is explained by biological processes (e.g., ontogeny, hybridization). In contrast, climatic data did not produce biologically meaningful clusters that were congruent with any intrinsic dataset, but rather corresponded to regional differences in atmospheric circulation and climate, indicating an absence of inherent taxonomic signal in these data. Surrogating climate for physiological tolerances adds artificial weight to evidence of species boundaries, as these data are irrelevant for that purpose. Based on the evidence from congruent clustering of intrinsic datasets, we recommend that three subspecies of C. mitchellii be recognized as species: C. angelensis, C. mitchellii, and C. Pyrrhus.

Vegetation zones in changing climate

NASA Astrophysics Data System (ADS)

Belda, Michal; Holtanova, Eva; Halenka, Tomas; Kalvova, Jaroslava

2017-04-01

Climate patterns analysis can be performed for individual climate variables separately or the data can be aggregated using e.g. some kind of climate classification. These classifications usually correspond to vegetation distribution in the sense that each climate type is dominated by one vegetation zone or eco-region. Thus, the Köppen-Trewartha classification provides integrated assessment of temperature and precipitation together with their annual cycle as well. This way climate classifications also can be used as a convenient tool for the assessment and validation of climate models and for the analysis of simulated future climate changes. The Köppen-Trewartha classification is applied on full CMIP5 family of more than 40 GCM simulations and CRU dataset for comparison. This evaluation provides insight on the GCM performance and errors for simulations of the 20th century climate. Common regions are identified, such as Australia or Amazonia, where many state-of-the-art models perform inadequately. Moreover, the analysis of the CMIP5 ensemble for future under RCP 4.5 and RCP 8.5 is performed to assess the climate change for future. There are significant changes for some types in most models e.g. increase of savanna and decrease of tundra for the future climate. For some types significant shifts in latitude can be seen when studying their geographical location in selected continental areas, e.g. toward higher latitudes for boreal climate. Quite significant uncertainty can be seen for some types. For Europe, EuroCORDEX results for both 0.11 and 0.44 degree resolution are validated using Köppen-Trewartha types in comparison to E-OBS based classification. ERA-Interim driven simulations are compared to both present conditions of CMIP5 models as well as their downscaling by EuroCORDEX RCMs. Finally, the climate change signal assessment is provided using the individual climate types. In addition to the changes assessed similarly as for GCMs analysis in terms of the area of individual types, in the continental scale some shifts of boundaries between the selected types can be studied as well providing the information on climate change signal. The shift of the boundary between the boreal zone and continental temperate zone to the north is clearly seen in most simulations as well as eastern move of the boundary of the maritime and continental type of temperate zone. However, there can be quite clear problem with model biases in climate types association. When analysing climate types in Europe and their shifts under climate change using Köppen-Trewartha classification (KTC), for the temperate climate type there are subtypes defined following the continentality patterns, and we can see their generally meridionally located divide across Europe shifted to the east. There is a question whether this is realistic or rather due to the simplistic condition in KTC following the winter minimum temperature, while other continentality indices consider rather the amplitude of temperature during the year. This leads us to connect our analysis of climate change effects using climate classification to the more detailed analysis of continentality patterns development in Europe to provide better insight on the climate regimes and to verify the continentality conditions, their definitions and climate change effects on them. The comparison of several selected continentality indices is shown.

North Atlantic observations sharpen meridional overturning projections

NASA Astrophysics Data System (ADS)

Olson, R.; An, S.-I.; Fan, Y.; Evans, J. P.; Caesar, L.

2018-06-01

Atlantic Meridional Overturning Circulation (AMOC) projections are uncertain due to both model errors, as well as internal climate variability. An AMOC slowdown projected by many climate models is likely to have considerable effects on many aspects of global and North Atlantic climate. Previous studies to make probabilistic AMOC projections have broken new ground. However, they do not drift-correct or cross-validate the projections, and do not fully account for internal variability. Furthermore, they consider a limited subset of models, and ignore the skill of models at representing the temporal North Atlantic dynamics. We improve on previous work by applying Bayesian Model Averaging to weight 13 Coupled Model Intercomparison Project phase 5 models by their skill at modeling the AMOC strength, and its temporal dynamics, as approximated by the northern North-Atlantic temperature-based AMOC Index. We make drift-corrected projections accounting for structural model errors, and for the internal variability. Cross-validation experiments give approximately correct empirical coverage probabilities, which validates our method. Our results present more evidence that AMOC likely already started slowing down. While weighting considerably moderates and sharpens our projections, our results are at low end of previously published estimates. We project mean AMOC changes between periods 1960-1999 and 2060-2099 of -4.0 Sv and -6.8 Sv for RCP4.5 and RCP8.5 emissions scenarios respectively. The corresponding average 90% credible intervals for our weighted experiments are [-7.2, -1.2] and [-10.5, -3.7] Sv respectively for the two scenarios.

Towards person-centredness in aged care - exploring the impact of leadership.

PubMed

Backman, Annica; Sjögren, Karin; Lindkvist, Marie; Lövheim, Hugo; Edvardsson, David

2016-09-01

To explore the association between leadership behaviours among managers in aged care, and person-centredness of care and the psychosocial climate. Theory suggests that leadership is important for improving person-centredness in aged care, however, empirical evidence is lacking. A cross-sectional design was used to collect data from Swedish aged care staff (n = 3661). Valid and reliable questionnaires assessing leadership behaviours, person-centeredness of care and the psychosocial climate were used. Data were analysed using multiple linear regression including interaction terms. Leadership behaviours were significantly related to the person-centredness of care and the psychosocial climate. The level of person-centredness of care moderated the impact of leadership on the psychosocial climate. The leadership behaviour of managers significantly impacts person-centred care practice and contributes to the psychosocial climate for both staff and residents in aged care. This study is the first empirically to confirm that middle managers have a central leadership role in developing and supporting person-centred care practice, thereby creating a positive psychosocial climate and high quality care. © 2016 John Wiley & Sons Ltd.

An investigation of the ways in which public health nutrition policy and practices can address climate change.

PubMed

Sulda, Heidi; Coveney, John; Bentley, Michael

2010-03-01

To develop a framework to guide action in the public health nutrition workforce to develop policies and practices addressing factors contributing to climate change. Action/consultative research. Interviews - South Australia, questionnaire - Australia. Interviews - key informants (n 6) were from various government, academic and non-government positions, invited through email. Questionnaire - participants were members of the public health nutrition workforce (n 186), recruited to the study through emails from public health nutrition contacts for each State in Australia (with the exception of South Australia). Support by participants for climate change as a valid role for dietitians and nutritionists was high (78 %). However, climate change was ranked low against other public health nutrition priorities. Support of participants to conduct programmes to address climate change from professional and work organisations was low. The final framework developed included elements of advocacy/lobbying, policy, professional recognition/support, organisational support, knowledge/skills, partnerships and programmes. This research demonstrates a need for public health nutrition to address climate change, which requires support by organisations, policy, improved knowledge and increased professional development opportunities.

Climate variation and incidence of Ross river virus in Cairns, Australia: a time-series analysis.

PubMed Central

Tong, S; Hu, W

2001-01-01

In this study we assessed the impact of climate variability on the Ross River virus (RRv) transmission and validated an epidemic-forecasting model in Cairns, Australia. Data on the RRv cases recorded between 1985 and 1996 were obtained from the Queensland Department of Health. Climate and population data were supplied by the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. The cross-correlation function (CCF) showed that maximum temperature in the current month and rainfall and relative humidity at a lag of 2 months were positively and significantly associated with the monthly incidence of RRv, whereas relative humidity at a lag of 5 months was inversely associated with the RRv transmission. We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1985 to 1994, and then validated the models using the data collected between 1995 and 1996. The results show that the relative humidity at a lag of 5 months (p < 0.001) and the rainfall at a lag of 2 months (p < 0.05) appeared to play significant roles in the transmission of RRv disease in Cairns. Furthermore, the regressive forecast curves were consistent with the pattern of actual values. PMID:11748035

The Universal Thermal Climate Index UTCI compared to ergonomics standards for assessing the thermal environment.

PubMed

Bröde, Peter; Błazejczyk, Krzysztof; Fiala, Dusan; Havenith, George; Holmér, Ingvar; Jendritzky, Gerd; Kuklane, Kalev; Kampmann, Bernhard

2013-01-01

The growing need for valid assessment procedures of the outdoor thermal environment in the fields of public weather services, public health systems, urban planning, tourism & recreation and climate impact research raised the idea to develop the Universal Thermal Climate Index UTCI based on the most recent scientific progress both in thermo-physiology and in heat exchange theory. Following extensive validation of accessible models of human thermoregulation, the advanced multi-node 'Fiala' model was selected to form the basis of UTCI. This model was coupled with an adaptive clothing model which considers clothing habits by the general urban population and behavioral changes in clothing insulation related to actual environmental temperature. UTCI was developed conceptually as an equivalent temperature. Thus, for any combination of air temperature, wind, radiation, and humidity, UTCI is defined as the air temperature in the reference condition which would elicit the same dynamic response of the physiological model. This review analyses the sensitivity of UTCI to humidity and radiation in the heat and to wind in the cold and compares the results with observational studies and internationally standardized assessment procedures. The capabilities, restrictions and potential future extensions of UTCI are discussed.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Deriving a sea surface climatology of CO2 fugacity in support of air-sea gas flux studies

NASA Astrophysics Data System (ADS)

Goddijn-Murphy, L. M.; Woolf, D. K.; Land, P. E.; Shutler, J. D.; Donlon, C.

2014-07-01

Climatologies, or long-term averages, of essential climate variables are useful for evaluating models and providing a baseline for studying anomalies. The Surface Ocean Carbon Dioxide (CO2) Atlas (SOCAT) has made millions of global underway sea surface measurements of CO2 publicly available, all in a uniform format and presented as fugacity, fCO2. fCO2 is highly sensitive to temperature and the measurements are only valid for the instantaneous sea surface temperature (SST) that is measured concurrent with the in-water CO2 measurement. To create a climatology of fCO2 data suitable for calculating air-sea CO2 fluxes it is therefore desirable to calculate fCO2 valid for climate quality SST. This paper presents a method for creating such a climatology. We recomputed SOCAT's fCO2 values for their respective measurement month and year using climate quality SST data from satellite Earth observation and then extrapolated the resulting fCO2 values to reference year 2010. The data were then spatially interpolated onto a 1° × 1° grid of the global oceans to produce 12 monthly fCO2 distributions for 2010. The partial pressure of CO2 (pCO2) is also provided for those who prefer to use pCO2. The CO2 concentration difference between ocean and atmosphere is the thermodynamic driving force of the air-sea CO2 flux, and hence the presented fCO2 distributions can be used in air-sea gas flux calculations together with climatologies of other climate variables.

Communicating Climate Uncertainties: Challenges and Opportunities Related to Spatial Scales, Extreme Events, and the Warming 'Hiatus'

NASA Astrophysics Data System (ADS)

Casola, J. H.; Huber, D.

2013-12-01

Many media, academic, government, and advocacy organizations have achieved sophistication in developing effective messages based on scientific information, and can quickly translate salient aspects of emerging climate research and evolving observations. However, there are several ways in which valid messages can be misconstrued by decision makers, leading them to inaccurate conclusions about the risks associated with climate impacts. Three cases will be discussed: 1) Issues of spatial scale in interpreting climate observations: Local climate observations may contradict summary statements about the effects of climate change on larger regional or global spatial scales. Effectively addressing these differences often requires communicators to understand local and regional climate drivers, and the distinction between a 'signal' associated with climate change and local climate 'noise.' Hydrological statistics in Missouri and California are shown to illustrate this case. 2) Issues of complexity related to extreme events: Climate change is typically invoked following a wide range of damaging meteorological events (e.g., heat waves, landfalling hurricanes, tornadoes), regardless of the strength of the relationship between anthropogenic climate change and the frequency or severity of that type of event. Examples are drawn from media coverage of several recent events, contrasting useful and potentially confusing word choices and frames. 3) Issues revolving around climate sensitivity: The so-called 'pause' or 'hiatus' in global warming has reverberated strongly through political and business discussions of climate change. Addressing the recent slowdown in warming yields an important opportunity to raise climate literacy in these communities. Attempts to use recent observations as a wedge between climate 'believers' and 'deniers' is likely to be counterproductive. Examples are drawn from Congressional testimony and media stories. All three cases illustrate ways that decision makers can arrive at invalid conclusions from a seemingly valid scientific messages. Honest discussion of uncertainties, and recognition of the spatial and time scales associated with decision making, can work to combat this potential confusion.

Perceptions of motivational climate and teachers' strategies to sustain discipline as predictors of intrinsic motivation in physical education.

PubMed

Gutiérrez, Melchor; Ruiz, Luis-Miguel; López, Esther

2010-11-01

This study examined the relationship among pupils' perceptions of the motivational climate, pupils' perceptions of teachers' strategies to maintain discipline and pupils' intrinsic motivation in physical education. A sample of 2189 Spanish adolescents, ages 13 to 17 years, completed Spanish versions of the EPCM, SSDS, and IMI. Confirmatory factor analyses were carried out to confirm the factorial validity of the scales. Then, the relationship among the variables was explored through Structural Equation Modelling. The most important predictors of pupils' intrinsic motivation were the perceived mastery climate, and perceived teachers' emphasis on intrinsic reasons to maintain discipline. Perceived performance climate and perceived teachers' strategies to maintain discipline based on introjected reasons and indifference, predicted pupils' tension-pressure. Results are discussed in the context of theoretical propositions of self-determination theory and practical issues of enhancing adolescents' motivation in physical education.

Atmospheric Composition Change: Climate-Chemistry Interactions

NASA Technical Reports Server (NTRS)

Isaksen, I.S.A.; Granier, C.; Myhre, G.; Bernsten, T. K.; Dalsoren, S. B.; Gauss, S.; Klimont, Z.; Benestad, R.; Bousquet, P.; Collins, W.;

The traffic climate in China: The mediating effect of traffic safety climate between personality and dangerous driving behavior.

PubMed

Zhang, Qian; Ge, Yan; Qu, Weina; Zhang, Kan; Sun, Xianghong

2018-04-01

Traffic safety climate is defined as road users' attitudes and perceptions of traffic in a specific context at a given point in time. The current study aimed to validate the Chinese version of the Traffic Climate Scale (TCS) and to explore its relation to drivers' personality and dangerous driving behavior. A sample of 413 drivers completed the Big Five Inventory (BFI), the Chinese version of the TCS, the Dula Dangerous Driving Index (DDDI) and a demographic questionnaire. Exploratory factor analysis and confirmatory factor analysis were performed to confirm a three-factor (external affective demands, internal requirements and functionality) solution of the TCS. The reliability and validity of the Chinese version of TCS were verified. More importantly, the results showed that the effect of personality on dangerous driving behavior was mediated by traffic climate. Specifically, the functionality of the TCS mediated the effect of neuroticism on negative cognitive/emotional driving and drunk driving, while openness had an indirect impact on aggressive driving, risky driving and drunk driving based on the internal requirements of the TCS. Additionally, agreeableness had a negative direct impact on four factors of the DDDI, while neuroticism had a positive direct impact on negative cognitive/emotional driving, drunk driving and risky driving. In conclusion, the Chinese version of the TCS will be useful to evaluate drivers' attitudes towards and perceptions of the requirements of traffic environment in which they participate and will also be valuable for comparing traffic cultures and environments in different countries. Copyright © 2018 Elsevier Ltd. All rights reserved.

Development of a multilevel health and safety climate survey tool within a mining setting.

PubMed

Parker, Anthony W; Tones, Megan J; Ritchie, Gabrielle E

2017-09-01

This study aimed to design, implement and evaluate the reliability and validity of a multifactorial and multilevel health and safety climate survey (HSCS) tool with utility in the Australian mining setting. An 84-item questionnaire was developed and pilot tested on a sample of 302 Australian miners across two open cut sites. A 67-item, 10 factor solution was obtained via exploratory factor analysis (EFA) representing prioritization and attitudes to health and safety across multiple domains and organizational levels. Each factor demonstrated a high level of internal reliability, and a series of ANOVAs determined a high level of consistency in responses across the workforce, and generally irrespective of age, experience or job category. Participants tended to hold favorable views of occupational health and safety (OH&S) climate at the management, supervisor, workgroup and individual level. The survey tool demonstrated reliability and validity for use within an open cut Australian mining setting and supports a multilevel, industry specific approach to OH&S climate. Findings suggested a need for mining companies to maintain high OH&S standards to minimize risks to employee health and safety. Future research is required to determine the ability of this measure to predict OH&S outcomes and its utility within other mine settings. As this tool integrates health and safety, it may have benefits for assessment, monitoring and evaluation in the industry, and improving the understanding of how health and safety climate interact at multiple levels to influence OH&S outcomes. Copyright © 2017 National Safety Council and Elsevier Ltd. All rights reserved.

Assessing cover crop management under actual and climate change conditions.

PubMed

Alonso-Ayuso, María; Quemada, Miguel; Vanclooster, Marnik; Ruiz-Ramos, Margarita; Rodriguez, Alfredo; Gabriel, José Luis

2018-04-15

The termination date is recognized as a key management factor to enhance cover crops for multiple benefits and to avoid competition with the following cash crop. However, the optimum date depends on annual meteorological conditions, and climate variability induces uncertainty in a decision that needs to be taken every year. One of the most important cover crop benefits is reducing nitrate leaching, a major concern for irrigated agricultural systems and highly affected by the termination date. This study aimed to determine the effects of cover crops and their termination date on the water and N balances of an irrigated Mediterranean agroecosystem under present and future climate conditions. For that purpose, two field experiments were used for inverse calibration and validation of the WAVE model (Water and Agrochemicals in the soil and Vadose Environment), based on continuous soil water content data, soil nitrogen content and crop measurements. The calibrated and validated model was subsequently used in advanced scenario analysis under present and climate change conditions. Under present conditions, a late termination date increased cover crop biomass and subsequently soil water and N depletion. Hence, preemptive competition risk with the main crop was enhanced, but a reduction of nitrate leaching also occurred. The hypothetical planting date of the following cash crop was also an important tool to reduce preemptive competition. Under climate change conditions, the simulations showed that the termination date will be even more important to reduce preemptive competition and nitrate leaching. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Herbarium specimens, photographs, and field observations show Philadelphia area plants are responding to climate change.

PubMed

Panchen, Zoe A; Primack, Richard B; Anisko, Tomasz; Lyons, Robert E

2012-04-01

The global climate is changing rapidly and is expected to continue changing in coming decades. Studying changes in plant flowering times during a historical period of warming temperatures gives us a way to examine the impacts of climate change and allows us to predict further changes in coming decades. The Greater Philadelphia region has a long and rich history of botanical study and documentation, with abundant herbarium specimens, field observations, and botanical photographs from the mid-1800s onward. These extensive records also provide an opportunity to validate methodologies employed by other climate change researchers at a different biogeographical area and with a different group of species. Data for 2539 flowering records from 1840 to 2010 were assessed to examine changes in flowering response over time and in relation to monthly minimum temperatures of 28 Piedmont species native to the Greater Philadelphia region. Regression analysis of the date of flowering with year or with temperature showed that, on average, the Greater Philadelphia species studied are flowering 16 d earlier over the 170-yr period and 2.7 d earlier per 1°C rise in monthly minimum temperature. Of the species studied, woody plants with short flowering duration are the best indicators of a warming climate. For monthly minimum temperatures, temperatures 1 or 2 mo prior to flowering are most significantly correlated with flowering time. Studies combining herbarium specimens, photographs, and field observations are an effective method for detecting the effects of climate change on flowering times.

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus)

PubMed Central

Shafapour Tehrany, Mahyat; Solhjouy-fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus, the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to the prediction for 2055, for Ae. albopictus expansion. PMID:29576954

A comparative modeling study on non-climatic and climatic risk assessment on Asian Tiger Mosquito (Aedes albopictus).

PubMed

Shabani, Farzin; Shafapour Tehrany, Mahyat; Solhjouy-Fard, Samaneh; Kumar, Lalit

2018-01-01

Aedes albopictus , the Asian Tiger Mosquito, vector of Chikungunya, Dengue Fever and Zika viruses, has proven its hardy adaptability in expansion from its natural Asian, forest edge, tree hole habitat on the back of international trade transportation, re-establishing in temperate urban surrounds, in a range of water receptacles and semi-enclosures of organic matter. Conventional aerial spray mosquito vector controls focus on wetland and stagnant water expanses, proven to miss the protected hollows and crevices favoured by Ae. albopictus. New control or eradication strategies are thus essential, particular in light of potential expansions in the southeastern and eastern USA. Successful regional vector control strategies require risk level analysis. Should strategies prioritize regions with non-climatic or climatic suitability parameters for Ae. albopictus ? Our study used current Ae. albopictus distribution data to develop two independent models: (i) regions with suitable non-climatic factors, and (ii) regions with suitable climate for Ae. albopictus in southeastern USA. Non-climatic model processing used Evidential Belief Function (EBF), together with six geographical conditioning factors (raster data layers), to establish the probability index. Validation of the analysis results was estimated with area under the curve (AUC) using Ae. albopictus presence data. Climatic modeling was based on two General Circulation Models (GCMs), Miroc3.2 and CSIRO-MK30 running the RCP 8.5 scenario in MaxEnt software. EBF non-climatic model results achieved a 0.70 prediction rate and 0.73 success rate, confirming suitability of the study site regions for Ae. albopictus establishment. The climatic model results showed the best-fit model comprised Coldest Quarter Mean Temp, Precipitation of Wettest Quarter and Driest Quarter Precipitation factors with mean AUC value of 0.86. Both GCMs showed that the whole study site is highly suitable and will remain suitable climatically, according to the prediction for 2055, for Ae. albopictus expansion.

A comprehensive evaluation of two MODIS evapotranspiration products over the conterminous United States: using point and gridded FLUXNET and water balance ET

USGS Publications Warehouse

Velpuri, Naga M.; Senay, Gabriel B.; Singh, Ramesh K.; Bohms, Stefanie; Verdin, James P.

2013-01-01

Remote sensing datasets are increasingly being used to provide spatially explicit large scale evapotranspiration (ET) estimates. Extensive evaluation of such large scale estimates is necessary before they can be used in various applications. In this study, two monthly MODIS 1 km ET products, MODIS global ET (MOD16) and Operational Simplified Surface Energy Balance (SSEBop) ET, are validated over the conterminous United States at both point and basin scales. Point scale validation was performed using eddy covariance FLUXNET ET (FLET) data (2001–2007) aggregated by year, land cover, elevation and climate zone. Basin scale validation was performed using annual gridded FLUXNET ET (GFET) and annual basin water balance ET (WBET) data aggregated by various hydrologic unit code (HUC) levels. Point scale validation using monthly data aggregated by years revealed that the MOD16 ET and SSEBop ET products showed overall comparable annual accuracies. For most land cover types, both ET products showed comparable results. However, SSEBop showed higher performance for Grassland and Forest classes; MOD16 showed improved performance in the Woody Savanna class. Accuracy of both the ET products was also found to be comparable over different climate zones. However, SSEBop data showed higher skill score across the climate zones covering the western United States. Validation results at different HUC levels over 2000–2011 using GFET as a reference indicate higher accuracies for MOD16 ET data. MOD16, SSEBop and GFET data were validated against WBET (2000–2009), and results indicate that both MOD16 and SSEBop ET matched the accuracies of the global GFET dataset at different HUC levels. Our results indicate that both MODIS ET products effectively reproduced basin scale ET response (up to 25% uncertainty) compared to CONUS-wide point-based ET response (up to 50–60% uncertainty) illustrating the reliability of MODIS ET products for basin-scale ET estimation. Results from this research would guide the additional parameter refinement required for the MOD16 and SSEBop algorithms in order to further improve their accuracy and performance for agro-hydrologic applications.

Assessing the organizational context for EBP implementation: the development and validity testing of the Implementation Climate Scale (ICS).

PubMed

Ehrhart, Mark G; Aarons, Gregory A; Farahnak, Lauren R

2014-10-23

Although the importance of the organizational environment for implementing evidence-based practices (EBP) has been widely recognized, there are limited options for measuring implementation climate in public sector health settings. The goal of this research was to develop and test a measure of EBP implementation climate that would both capture a broad range of issues important for effective EBP implementation and be of practical use to researchers and managers seeking to understand and improve the implementation of EBPs. Participants were 630 clinicians working in 128 work groups in 32 US-based mental health agencies. Items to measure climate for EBP implementation were developed based on past literature on implementation climate and other strategic climates and in consultation with experts on the implementation of EBPs in mental health settings. The sample was randomly split at the work group level of analysis; half of the sample was used for exploratory factor analysis (EFA), and the other half was used for confirmatory factor analysis (CFA). The entire sample was utilized for additional analyses assessing the reliability, support for level of aggregation, and construct-based evidence of validity. The EFA resulted in a final factor structure of six dimensions for the Implementation Climate Scale (ICS): 1) focus on EBP, 2) educational support for EBP, 3) recognition for EBP, 4) rewards for EBP, 5) selection for EBP, and 6) selection for openness. This structure was supported in the other half of the sample using CFA. Additional analyses supported the reliability and construct-based evidence of validity for the ICS, as well as the aggregation of the measure to the work group level. The ICS is a very brief (18 item) and pragmatic measure of a strategic climate for EBP implementation. It captures six dimensions of the organizational context that indicate to employees the extent to which their organization prioritizes and values the successful implementation of EBPs. The ICS can be used by researchers to better understand the role of the organizational context on implementation outcomes and by organizations to evaluate their current climate as they consider how to improve the likelihood of implementation success.

The ESA DUE GlobVapour Project

NASA Astrophysics Data System (ADS)

Schröder, M.; ESA Due Globvapour Project Team

2010-12-01

The European Space Agency (ESA) Data User Element (DUE) project series aims at bridging the gap between research projects and the sustainable provision of Earth Observation (EO) climate data products at an information level that fully responds to the operational needs of user communities. The ultimate objective of GlobVapour is to provide long-term coherent water vapour data sets exploiting the synergistic capabilities of different EO missions aiming at improved accuracies and enhanced temporal and spatial sampling better than those provided by the single sources. The project seeks to utilize the increasing potential of the synergistic capabilities of past, existing and upcoming satellite missions (ERS-1 and -2, ENVISAT, METOP, MSG as well as relevant non-European missions and in-situ data) in order to meet the increasing needs for coherent long-term water vapour datasets required by the scientific community. GlobVapour develops, validates and applies novel water vapour climate data sets derived from various sensors. More specifically, the primary objectives of the GlobVapour project are: 1)The development of multi-annual global water vapour data sets inclusive of error estimates based on carefully calibrated and inter-calibrated radiances. 2)The validation of the water vapour products against ground based, airborne and other satellite based measurements. 3) The provision of an assessment of the quality of different IASI water vapour profile algorithms developed by the project partners and other groups. 4) The provision of a complete processing system that can further strengthen operational production of the developed products. 5) A demonstration of the use of the products in the field of climate modelling, including applying alternative ways of climate model validation using forward radiation operators. 6) The promotion of the strategy of data set construction and the data sets themselves to the global research and operational community. The ultimate goal of the DUE GlobVapour project is the preparation of recognised data sets and successful concepts that can be used to ensure a sustainable provision of such data from operational entities such as the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility (SAF) network. Key scientific questions which GlobVapour data can contribute to are climate monitoring and attribution, assimilation of different water vapour datasets to form a consistent analysis, model process studies, evaluation of in-situ water vapour measurements, validation of climate models and reanalyses, assessing the relationship between water vapour and dynamics, research and development for operational applications and input to atmospheric reanalyses. This presentation will introduce the GlobVapour project and concept as well as the products which are the global total column water vapour (TCWV) time series from a combination of MERIS and SSM/I as well as TCWV data sets derived from the GOME/SCIAMACHY/GOME-2 and the (A)ATSR instruments. A shorter time series of water vapour profiles will be derived from a combination of IASI and SEVIRI. The retrieval and combination methods as well as first validation results will also be discussed.

Validation of the RegCM4-Subgrid module for the high resolution climate simulation over Korea

NASA Astrophysics Data System (ADS)

Lee, C.; Im, E.; Chang, K.; Choi, Y.

2010-12-01

Given the discernable evidences of climate changes due to human activity, there is a growing demand for the reliable climate change scenario in response to future emission forcing. One of the most significant impacts of climate changes can be that on the hydrological process. Changes in the seasonality and the low and high rainfall extremes can influence the water balance of river basin, with several consequences for societies and ecosystems. In fact, recent studies have reported that East Asia including the Korean peninsula is regarded to be a highly vulnerability region under global warming, especially for water resources. As an attempt to accurately assess the impact of climate change over Korea, we developed the dynamical downscaling system using the RegCM4 with a mosaic-type parameterization of subgrid-scale topography and land use (Sub-BATS). The Sub-BATS system is composed of 20 km coarse-grid cell and 4 km sub-grid cell. Before a full climate change simulation is carried out, we performed the simulation spanning the 19-year periods (1989-2007) with the lateral boundary fields obtained from the ERA-Interim reanalysis. The Korean peninsula is characterized by narrow mountain systems surrounded by ocean, and covered by a relatively dense observational network (approximate 400 stations), which provides an excellent dataset to validate a finescale downscaled results over the region. The evaluation of simulated surface variables (e.g. temperature, precipitation, snow, runoff) shows the usefulness of the RegCM4-Subgrid module as a tool to produce fine scale climate information of surface processes for coupling with hydrological model over the Korean peninsula Acknowledgements This work was supported by the Korea Science and Engineering Foundation (KOSEF) grant funded by the Korea government(MEST) (No. 2009-0085533), and by the "Advanced research on industrial meteorology" and " Development of meteorological resources for green growth." of National Institute of Meteorological Research (NIMR), funded by the Korea Meteorological Administration(KMA).

Linking the Weather Generator with Regional Climate Model: Effect of Higher Resolution

NASA Astrophysics Data System (ADS)

Dubrovsky, Martin; Huth, Radan; Farda, Ales; Skalak, Petr

2014-05-01

This contribution builds on our last year EGU contribution, which followed two aims: (i) validation of the simulations of the present climate made by the ALADIN-Climate Regional Climate Model (RCM) at 25 km resolution, and (ii) presenting a methodology for linking the parametric weather generator (WG) with RCM output (aiming to calibrate a gridded WG capable of producing realistic synthetic multivariate weather series for weather-ungauged locations). Now we have available new higher-resolution (6.25 km) simulations with the same RCM. The main topic of this contribution is an anser to a following question: What is an effect of using a higher spatial resolution on a quality of simulating the surface weather characteristics? In the first part, the high resolution RCM simulation of the present climate will be validated in terms of selected WG parameters, which are derived from the RCM-simulated surface weather series and compared to those derived from weather series observed in 125 Czech meteorological stations. The set of WG parameters will include statistics of the surface temperature and precipitation series. When comparing the WG parameters from the two sources (RCM vs observations), we interpolate the RCM-based parameters into the station locations while accounting for the effect of altitude. In the second part, we will discuss an effect of using the higher resolution: the results of the validation tests will be compared with those obtained with the lower-resolution RCM. Acknowledgements: The present experiment is made within the frame of projects ALARO-Climate (project P209/11/2405 sponsored by the Czech Science Foundation), WG4VALUE (project LD12029 sponsored by the Ministry of Education, Youth and Sports of CR) and VALUE (COST ES 1102 action).

Erosion of lizard diversity by climate change and altered thermal niches.

PubMed

Sinervo, Barry; Méndez-de-la-Cruz, Fausto; Miles, Donald B; Heulin, Benoit; Bastiaans, Elizabeth; Villagrán-Santa Cruz, Maricela; Lara-Resendiz, Rafael; Martínez-Méndez, Norberto; Calderón-Espinosa, Martha Lucía; Meza-Lázaro, Rubi Nelsi; Gadsden, Héctor; Avila, Luciano Javier; Morando, Mariana; De la Riva, Ignacio J; Victoriano Sepulveda, Pedro; Rocha, Carlos Frederico Duarte; Ibargüengoytía, Nora; Aguilar Puntriano, César; Massot, Manuel; Lepetz, Virginie; Oksanen, Tuula A; Chapple, David G; Bauer, Aaron M; Branch, William R; Clobert, Jean; Sites, Jack W

2010-05-14

It is predicted that climate change will cause species extinctions and distributional shifts in coming decades, but data to validate these predictions are relatively scarce. Here, we compare recent and historical surveys for 48 Mexican lizard species at 200 sites. Since 1975, 12% of local populations have gone extinct. We verified physiological models of extinction risk with observed local extinctions and extended projections worldwide. Since 1975, we estimate that 4% of local populations have gone extinct worldwide, but by 2080 local extinctions are projected to reach 39% worldwide, and species extinctions may reach 20%. Global extinction projections were validated with local extinctions observed from 1975 to 2009 for regional biotas on four other continents, suggesting that lizards have already crossed a threshold for extinctions caused by climate change.

A Long-Term and Reproducible Passive Microwave Sea Ice Concentration Data Record for Climate Studies and Monitoring

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.

Simulated Extreme Prepitation Indices over Northeast Brasil in Current Climate and Future Scenarios RCP4.5 and RCP8.5

NASA Astrophysics Data System (ADS)

Wender Santiago Marinho, Marcos; Araújo Costa, Alexandre; Cassain Sales, Domingo; Oliveira Guimarães, Sullyandro; Mariano da Silva, Emerson; das Chagas Vasconcelos Júnior, Francisco

2013-04-01

In this study, we analyzed extreme precipitation indices, for present and future modeled climates over Northeast of Brazil (NEB), from CORDEX simulations over the domain of Tropical Americas. The period for the model validation was from 1989-2007, using data from the European Center (ECWMF) Reanalysis, ERA-INTERIM, as input to drive the regional model (RAMS 6.0). Reanalysis data were assimilated via both lateral boundaries and the entire domain (a much weaker "central nudging"). Six indices of extreme precipitation were calculated over NEB: the average number of days above 10, 20 and 30 mm in one year (R10, R20, R30), the number of consecutive dry days (CDD), the number of consecutive wet days (CWD) and the maximum rainfall in five consecutive days (RX5). Those indices were compared against two independent databases: MERRA (Modern Era Retrospective analysis for Research and Applications) and TRMM (Tropical Rainfall Measuring Mission). After validation, climate simulations were performed for the present climate (1985-2005) and short-term (2015-2035), mid-term (2045-2065) and long-term (2079 to 2099) future climates for two scenarios: RCP 4.5 and RCP 8.5, nesting RAMS into HadGEM2-ES global model (a participant of CMIP5). Along with the indices, we also calculated Probability Distribution Functions (PDFs) to study the behavior of daily precipitation in the present and by the end of the 21st century (2079 to 2099) to assess possible changes under RCPs 4.5 and 8.5. The regional model is capable of representing relatively well the extreme precipitation indices for current climate, but there is some difficulties in performing a proper validation since the observed databases disagree significantly. Future projections show significant changes in most extreme indices. Rnn generally tend to increase, especially under RCP8.5. More significant changes are projected for the long-term period, under RCP8.5, which shows a pronounced R30 enhancement over northern states. CDD tends to decrease over most of NEB in the short but this trend is reverted toward the end of the century in both scenarios with a significant increase in the duration of the dry season over Northwestern and Eastern NEB (exceeding 50 days over certain areas), whereas projected CWD changes are smaller. Rx5 shows a general increasing trend especially in the long term period,under RCP8.5.

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

NASA Astrophysics Data System (ADS)

Huang, M.

2016-12-01

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

Evaluation Of The MODIS-VIIRS Land Surface Reflectance Fundamental Climate Data Record.

NASA Astrophysics Data System (ADS)

Roger, J. C.; Vermote, E.; Skakun, S.; Murphy, E.; Holben, B. N.; Justice, C. O.

2016-12-01

The land surface reflectance is a fundamental climate data record at the basis of the derivation of other climate data records (Albedo, LAI/Fpar, Vegetation indices) and has been recognized as a key parameter in the understanding of the land-surface-climate processes. Here, we present the validation of the Land surface reflectance used for MODIS and VIIRS data. This methodology uses the 6SV Code and data from the AERONET network. The first part was to define a protocol to use the AERONET data. To correctly take into account the aerosol model, we used the aerosol microphysical properties provided by the AERONET network including size-distribution (%Cf, %Cc, rf, rc, σr, σc), complex refractive indices and sphericity. Over the 670 available AERONET sites, we selected 230 sites with sufficient data. To be useful for validation, the aerosol model should be readily available anytime, which is rarely the case. We then used regressions for each microphysical parameter using the aerosol optical thickness at 440nm and the Angström coefficient as parameters. Comparisons with the AERONET dataset give good APU (Accuracy-Precision-Uncertainties) for each parameter. The second part of the study relies on the theoretical land surface retrieval. We generated TOA synthetic data using aerosol models from AERONET and determined APU on the surface reflectance retrieval while applying the MODIS and VIRRS Atmospheric correction software. Over 250 AERONET sites, the global uncertainties are for MODIS band 1 (red) is always lower than 0.0015 (when surface reflectance is > 0.04). This very good result shows the validity of our reference. Then, we used this reference for validating the MODIS and VIIRS surface reflectance products. The overall accuracy clearly reaches specifications. Finally, we will present an error budget of the surface reflectance retrieval. Indeed, to better understand how to improve the methodology, we defined an exhaustive error budget. We included all inputs i.e. sensor, calibration, aerosol properties, atmospheric conditions… This latter work provides a lot of information, such as the aerosol optical thickness obviously drives the uncertainties of the retrieval, the absorption and the volume concentration of the fine aerosol mode have an important impact as well…

Potential Impact of Climate Change on Streamflow of Major Ethiopian Rivers

NASA Astrophysics Data System (ADS)

Gizaw, M. S.; Zhang, S.; Biftu, G. F.; Gan, T. Y.; Tan, X.; Moges, S. A.; Koivusalo, H.

2017-12-01

In this study, HSPF (Hydrologic Simulation Program-FORTRAN) was used to analyze the potential impact of climate change on the streamflow of four major river basins in Ethiopia: Awash, Baro, Genale and Tekeze. The calibrated and validated HSPF model was forced with daily climate data of 10 CMIP5 (Coupled Model Intercomparison Project phase 5) Global Climate Models (GCMs) for the 1971-2000 control period and the RCP4.5 and RCP8.5 climate projections of 2041-2070 (2050s) and 2071-2100 (2080s). The ensemble median of these 10 GCMs projects the temperature in the four study areas to increase by about 2.3 ˚C (3.3 ˚C) in 2050s (2080s) whereas the mean annual precipitation is projected to increase by about 6% (9%) in 2050s (2080s). This results in about 3% (6%) increase in the projected annual streamflow in Awash, Baro and Tekeze rivers whereas the annual streamflow of Genale river is projected to increase by about 18% (33%) in the 2050s (2080s). However, such projected increase in the mean annual streamflow due to increasing precipitation over Ethiopia contradicts the decreasing trends in mean annual precipitation observed in recent decades. Regional climate models of high resolutions could provide more realistic climate projections for Ethiopia's complex topography, thus reducing the uncertainties in future streamflow projections.

Cross-cultural adaptation and validation of the teamwork climate scale.

PubMed

Silva, Mariana Charantola; Peduzzi, Marina; Sangaleti, Carine Teles; Silva, Dirceu da; Agreli, Heloise Fernandes; West, Michael A; Anderson, Neil R

2016-08-22

To adapt and validate the Team Climate Inventory scale, of teamwork climate measurement, for the Portuguese language, in the context of primary health care in Brazil. Methodological study with quantitative approach of cross-cultural adaptation (translation, back-translation, synthesis, expert committee, and pretest) and validation with 497 employees from 72 teams of the Family Health Strategy in the city of Campinas, SP, Southeastern Brazil. We verified reliability by the Cronbach's alpha, construct validity by the confirmatory factor analysis with SmartPLS software, and correlation by the job satisfaction scale. We problematized the overlap of items 9, 11, and 12 of the "participation in the team" factor and the "team goals" factor regarding its definition. The validation showed no overlapping of items and the reliability ranged from 0.92 to 0.93. The confirmatory factor analysis indicated suitability of the proposed model with distribution of the 38 items in the four factors. The correlation between teamwork climate and job satisfaction was significant. The version of the scale in Brazilian Portuguese was validated and can be used in the context of primary health care in the Country, constituting an adequate tool for the assessment and diagnosis of teamwork. Adaptar e validar a escala Team Climate Invetory, de medida do clima de trabalho em equipe, para o idioma português, no contexto da atenção primária à saúde no Brasil. Estudo metodológico com abordagem quantitativa de adaptação transcultural (tradução, retrotradução, síntese, comitê de especialistas e pré-teste) e validação com 497 trabalhadores de 72 equipes da Estratégia Saúde da Família no município de Campinas, São Paulo. Verificou-se confiabilidade pelo alfa de Cronbach, validade de construto pela análise fatorial confirmatória pelo software SmartPLS e correlação com escala de satisfação no trabalho. Foi problematizado a sobreposição dos itens 9, 11 e 12 do fator participação na equipe e o fator objetivos da equipe no tocante à sua definição. A validação mostrou que não houve sobreposição dos itens e a confiabilidade variou entre 0,92 a 0,93. A análise fatorial confirmatória indicou adequação do modelo proposto com distribuição dos 38 itens nos quatro fatores. A correlação entre clima de trabalho em equipe e satisfação no trabalho foi significativa. A versão da escala em português falado no Brasil foi validada e pode ser utilizada no contexto da atenção primária à saúde no País, constituindo ferramenta adequada para a avaliação e diagnóstico do trabalho em equipe.

Leishmaniasis and Climate Change—Case Study: Argentina

PubMed Central

Salomón, Oscar Daniel; Quintana, María Gabriela; Mastrángelo, Andrea Verónica; Fernández, María Soledad

2012-01-01

Vector-borne diseases closely associated with the environment, such as leishmaniases, have been a usual argument about the deleterious impact of climate change on public health. From the biological point of view interaction of different variables has different and even conflicting effects on the survival of vectors and the probability transmission of pathogens. The results on ecoepidemiology of leishmaniasis in Argentina related to climate variables at different scales of space and time are presented. These studies showed that the changes in transmission due to change or increase in frequency and intensity of climatic instability were expressed through changes in the probability of vector-human reservoir effective contacts. These changes of contact in turn are modulated by both direct effects on the biology and ecology of the organisms involved, as by perceptions and changes in the behavior of the human communities at risk. Therefore, from the perspective of public health and state policy, and taking into account the current nonlinear increased velocity of climate change, we concluded that discussing the uncertainties of large-scale models will have lower impact than to develop-validate mitigation strategies to be operative at local level, and compatibles with sustainable development, conservation biodiversity, and respect for cultural diversity. PMID:22685477

Winds: intensity and power density simulated by RegCM4 over South America in present and future climate

NASA Astrophysics Data System (ADS)

Reboita, Michelle Simões; Amaro, Tatiana Rocha; de Souza, Marcelo Rodrigues

2017-09-01

Since wind is an important source of renewable energy, it has attracted attention worldwide. Several studies have been developed in order to know favorable areas where wind farms can be implemented. Therefore, the purpose of this study is to project changes in wind intensity and in wind power density (PD), at 100 m high, over South America and adjacent oceans, by downscaling and ensemble techniques. Regional climate model version 4 (RegCM4) was nested in the output of three global climate models, considering the RCP8.5 scenario. RegCM4 ensemble in the present climate (1979-2005) was validated through comparisons with ERA-Interim reanalysis. The ensemble represents well the spatial pattern of the winds, but there are some differences in relation to the wind intensity registered by ERA-Interim, mainly in center-east Brazil and Patagonia. The comparison between the future climate (2020-2050 and 2070-2098) and the present one shows that there is an increase in wind intensity and PD on the north of SA, center-east Brazil (except in summer) and latitudes higher than 50°S. Such increase is more intense in the period 2070-2098.

Assessment of gridded observations used for climate model validation in the Mediterranean region: the HyMeX and MED-CORDEX framework

NASA Astrophysics Data System (ADS)

Flaounas, Emmanouil; Drobinski, Philippe; Borga, Marco; Calvet, Jean-Christophe; Delrieu, Guy; Morin, Efrat; Tartari, Gianni; Toffolon, Roberta

2012-06-01

This letter assesses the quality of temperature and rainfall daily retrievals of the European Climate Assessment and Dataset (ECA&D) with respect to measurements collected locally in various parts of the Euro-Mediterranean region in the framework of the Hydrological Cycle in the Mediterranean Experiment (HyMeX), endorsed by the Global Energy and Water Cycle Experiment (GEWEX) of the World Climate Research Program (WCRP). The ECA&D, among other gridded datasets, is very often used as a reference for model calibration and evaluation. This is for instance the case in the context of the WCRP Coordinated Regional Downscaling Experiment (CORDEX) and its Mediterranean declination MED-CORDEX. This letter quantifies ECA&D dataset uncertainties associated with temperature and precipitation intra-seasonal variability, seasonal distribution and extremes. Our motivation is to help the interpretation of the results when validating or calibrating downscaling models by the ECA&D dataset in the context of regional climate research in the Euro-Mediterranean region.

Utility of AIRS Retrievals for Climate Studies

NASA Technical Reports Server (NTRS)

Molnar, Guyla I.; Susskind, Joel

2007-01-01

Satellites provide an ideal platform to study the Earth-atmosphere system on practically all spatial and temporal scales. Thus, one may expect that their rapidly growing datasets could provide crucial insights not only for short-term weather processes/predictions but into ongoing and future climate change processes as well. Though Earth-observing satellites have been around for decades, extracting climatically reliable information from their widely varying datasets faces rather formidable challenges. AIRS/AMSU is a state of the art infrared/microwave sounding system that was launched on the EOS Aqua platform on May 4, 2002, and has been providing operational quality measurements since September 2002. In addition to temperature and atmospheric constituent profiles, outgoing longwave radiation and basic cloud parameters are also derived from the AIRS/AMSU observations. However, so far the AIRS products have not been rigorously evaluated and/or validated on a large scale. Here we present preliminary assessments of monthly and 8-day mean AIRS "Version 4.0" retrieved products (available to the public through the DAAC at NASA/GSFC) to assess their utility for climate studies. First we present "consistency checks" by evaluating the time series of means, and "anomalies" (relative to the first 4 full years' worth of AIRS "climate statistics") of several climatically important retrieved parameters. Finally, we also present preliminary results regarding interrelationships of some of these geophysical variables, to assess to what extent they are consistent with the known physics of climate variability/change. In particular, we find at least one observed relationship which contradicts current general circulation climate (GCM) model results: the global water vapor climate feedback which is expected to be strongly positive is deduced to be slightly negative (shades of the "Lindzen effect"?). Though the current AIRS climatology covers only -4.5 years, it will hopefully extend much further into the future.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Development and validation of the Survey of Organizational Research Climate (SORC).

PubMed

Martinson, Brian C; Thrush, Carol R; Lauren Crain, A

2013-09-01

Development and targeting efforts by academic organizations to effectively promote research integrity can be enhanced if they are able to collect reliable data to benchmark baseline conditions, to assess areas needing improvement, and to subsequently assess the impact of specific initiatives. To date, no standardized and validated tool has existed to serve this need. A web- and mail-based survey was administered in the second half of 2009 to 2,837 randomly selected biomedical and social science faculty and postdoctoral fellows at 40 academic health centers in top-tier research universities in the United States. Measures included the Survey of Organizational Research Climate (SORC) as well as measures of perceptions of organizational justice. Exploratory and confirmatory factor analyses yielded seven subscales of organizational research climate, all of which demonstrated acceptable internal consistency (Cronbach's α ranging from 0.81 to 0.87) and adequate test-retest reliability (Pearson r ranging from 0.72 to 0.83). A broad range of correlations between the seven subscales and five measures of organizational justice (unadjusted regression coefficients ranging from 0.13 to 0.95) document both construct and discriminant validity of the instrument. The SORC demonstrates good internal (alpha) and external reliability (test-retest) as well as both construct and discriminant validity.

Development and Validation of the Survey of Organizational Research Climate (SORC)

PubMed Central

Martinson, Brian C.; Thrush, Carol R.; Crain, A. Lauren

2012-01-01

Background Development and targeting efforts by academic organizations to effectively promote research integrity can be enhanced if they are able to collect reliable data to benchmark baseline conditions, to assess areas needing improvement, and to subsequently assess the impact of specific initiatives. To date, no standardized and validated tool has existed to serve this need. Methods A web- and mail-based survey was administered in the second half of 2009 to 2,837 randomly selected biomedical and social science faculty and postdoctoral fellows at 40 academic health centers in top-tier research universities in the United States. Measures included the Survey of Organizational Research Climate (SORC) as well as measures of perceptions of organizational justice. Results Exploratory and confirmatory factor analyses yielded seven subscales of organizational research climate, all of which demonstrated acceptable internal consistency (Cronbach’s α ranging from 0.81 to 0.87) and adequate test-retest reliability (Pearson r ranging from 0.72 to 0.83). A broad range of correlations between the seven subscales and five measures of organizational justice (unadjusted regression coefficients ranging from .13 to .95) document both construct and discriminant validity of the instrument. Conclusions The SORC demonstrates good internal (alpha) and external reliability (test-retest) as well as both construct and discriminant validity. PMID:23096775

Downscaling SMAP Radiometer Soil Moisture over the CONUS using Soil-Climate Information and Ensemble Learning

NASA Astrophysics Data System (ADS)

Abbaszadeh, P.; Moradkhani, H.

2017-12-01

Soil moisture contributes significantly towards the improvement of weather and climate forecast and understanding terrestrial ecosystem processes. It is known as a key hydrologic variable in the agricultural drought monitoring, flood modeling and irrigation management. While satellite retrievals can provide an unprecedented information on soil moisture at global-scale, the products are generally at coarse spatial resolutions (25-50 km2). This often hampers their use in regional or local studies, which normally require a finer resolution of the data set. This work presents a new framework based on an ensemble learning method while using soil-climate information derived from remote-sensing and ground-based observations to downscale the level 3 daily composite version (L3_SM_P) of SMAP radiometer soil moisture over the Continental U.S. (CONUS) at 1 km spatial resolution. In the proposed method, a suite of remotely sensed and in situ data sets in addition to soil texture information and topography data among others were used. The downscaled product was validated against in situ soil moisture measurements collected from a limited number of core validation sites and several hundred sparse soil moisture networks throughout the CONUS. The obtained results indicated a great potential of the proposed methodology to derive the fine resolution soil moisture information applicable for fine resolution hydrologic modeling, data assimilation and other regional studies.

Assessing concentration uncertainty estimates from passive microwave sea ice products

NASA Astrophysics Data System (ADS)

Meier, W.; Brucker, L.; Miller, J. A.

2017-12-01

Sea ice concentration is an essential climate variable and passive microwave derived estimates of concentration are one of the longest satellite-derived climate records. However, until recently uncertainty estimates were not provided. Numerous validation studies provided insight into general error characteristics, but the studies have found that concentration error varied greatly depending on sea ice conditions. Thus, an uncertainty estimate from each observation is desired, particularly for initialization, assimilation, and validation of models. Here we investigate three sea ice products that include an uncertainty for each concentration estimate: the NASA Team 2 algorithm product, the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI-SAF) product, and the NOAA/NSIDC Climate Data Record (CDR) product. Each product estimates uncertainty with a completely different approach. The NASA Team 2 product derives uncertainty internally from the algorithm method itself. The OSI-SAF uses atmospheric reanalysis fields and a radiative transfer model. The CDR uses spatial variability from two algorithms. Each approach has merits and limitations. Here we evaluate the uncertainty estimates by comparing the passive microwave concentration products with fields derived from the NOAA VIIRS sensor. The results show that the relationship between the product uncertainty estimates and the concentration error (relative to VIIRS) is complex. This may be due to the sea ice conditions, the uncertainty methods, as well as the spatial and temporal variability of the passive microwave and VIIRS products.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

Relationships between the Survey of Organizational Research Climate (SORC) and self-reported research practices.

PubMed

Crain, A Lauren; Martinson, Brian C; Thrush, Carol R

2013-09-01

The Survey of Organizational Research Climate (SORC) is a validated tool to facilitate promotion of research integrity and research best practices. This work uses the SORC to assess shared and individual perceptions of the research climate in universities and academic departments and relate these perceptions to desirable and undesirable research practices. An anonymous web- and mail-based survey was administered to randomly selected biomedical and social science faculty and postdoctoral fellows in the United States. Respondents reported their perceptions of the research climates at their universities and primary departments, and the frequency with which they engaged in desirable and undesirable research practices. More positive individual perceptions of the research climate in one's university or department were associated with higher likelihoods of desirable, and lower likelihoods of undesirable, research practices. Shared perceptions of the research climate tended to be similarly predictive of both desirable and undesirable research practices as individuals' deviations from these shared perceptions. Study results supported the central prediction that more positive SORC-measured perceptions of the research climate were associated with more positive reports of research practices. There were differences with respect to whether shared or individual climate perceptions were related to desirable or undesirable practices but the general pattern of results provide empirical evidence that the SORC is predictive of self-reported research behavior.

Assessments of species' vulnerability to climate change: From pseudo to science

USGS Publications Warehouse

Wade, Alisa A.; Hand, Brian K.; Kovach, Ryan; Muhlfeld, Clint C.; Waples, Robin S.; Luikart, Gordon

2017-01-01

Climate change vulnerability assessments (CCVAs) are important tools to plan for and mitigate potential impacts of climate change. However, CCVAs often lack scientific rigor, which can ultimately lead to poor conservation prioritization and associated ecological and economic costs. We discuss the need to improve comparability and consistency of CCVAs and either validate their findings or improve assessment of CCVA uncertainty and sensitivity to methodological assumptions.

The microcomputer scientific software series 9: user's guide to Geo-CLM: geostatistical interpolation of the historical climatic record in the Lake States.

Treesearch

Margaret R. Holdaway

1994-01-01

Describes Geo-CLM, a computer application (for Mac or DOS) whose primary aim is to perform multiple kriging runs to interpolate the historic climatic record at research plots in the Lake States. It is an exploration and analysis tool. Addition capabilities include climatic databases, a flexible test mode, cross validation, lat/long conversion, English/metric units,...

A Field Guide to Extra-Tropical Cyclones: Comparing Models to Observations

NASA Astrophysics Data System (ADS)

Bauer, M.

2008-12-01

Climate it is said is the accumulation of weather. And weather is not the concern of climate models. Justification for this latter sentiment has long hidden behind coarse model resolutions and blunt validation tools based on climatological maps and the like. The spatial-temporal resolutions of today's models and observations are converging onto meteorological scales however, which means that with the correct tools we can test the largely unproven assumption that climate model weather is correct enough, or at least lacks perverting biases, such that its accumulation does in fact result in a robust climate prediction. Towards this effort we introduce a new tool for extracting detailed cyclone statistics from climate model output. These include the usual cyclone distribution statistics (maps, histograms), but also adaptive cyclone- centric composites. We have also created a complementary dataset, The MAP Climatology of Mid-latitude Storminess (MCMS), which provides a detailed 6 hourly assessment of the areas under the influence of mid- latitude cyclones based on Reanalysis products. Using this we then extract complimentary composites from sources such as ISCCP and GPCP to create a large comparative dataset for climate model validation. A demonstration of the potential usefulness of these tools will be shown. dime.giss.nasa.gov/mcms/mcms.html

Assessment of the climate change impacts on fecal coliform contamination in a tidal estuarine system.

PubMed

Liu, Wen-Cheng; Chan, Wen-Ting

2015-12-01

Climate change is one of the key factors affecting the future microbiological water quality in rivers and tidal estuaries. A coupled 3D hydrodynamic and fecal coliform transport model was developed and applied to the Danshuei River estuarine system for predicting the influences of climate change on microbiological water quality. The hydrodynamic and fecal coliform model was validated using observational salinity and fecal coliform distributions. According to the analyses of the statistical error, predictions of the salinity and the fecal coliform concentration from the model simulation quantitatively agreed with the observed data. The validated model was then applied to predict the fecal coliform contamination as a result of climate change, including the change of freshwater discharge and the sea level rise. We found that the reduction of freshwater discharge under climate change scenarios resulted in an increase in the fecal coliform concentration. The sea level rise would decrease fecal coliform distributions because both the water level and the water volume increased. A reduction in freshwater discharge has a negative impact on the fecal coliform concentration, whereas a rising sea level has a positive influence on the fecal coliform contamination. An appropriate strategy for the effective microbiological management in tidal estuaries is required to reveal the persistent trends of climate in the future.

Analysis of climate change impact on rainfall pattern of Sambas district, West Kalimantan

NASA Astrophysics Data System (ADS)

Berliana Sipayung, Sinta; Nurlatifah, Amalia; Siswanto, Bambang; Slamet S, Lilik

2018-05-01

Climate change is one of the most important issues being discussed globally. It caused by global warming and indirectly affecting the world climate cycle. This research discussed the effect of climate change on rainfall pattern of Sambas District and predicted the future rainfall pattern due to climate change. CRU and TRMM were used and has been validated using in situ data. This research was used Climate Modelling and Prediction using CCAM (Conformal Cubic Atmospheric Model) which also validated by in situ data (correlation= 0.81). The results show that temperature trends in Sambas regency increased to 0.082°C/yr from 1991-2014 according to CRU data. High temperature trigger changes in rainfall patterns. Rainfall pattern in Sambas District has an equatorial type where the peak occurs when the sun is right on the equator. Rainfall in Sambas reaches the maximum in March and September when the equinox occurs. The CCAM model is used to project rainfall in Sambas District in the future. The model results show that rainfall in Sambas District is projected to increase to 0.018 mm/month until 2055 so the flow rate increase 0.006 m3/month and the water balance increase 0.009 mm/month.

A comparison of high-resolution pollen-inferred climate data from central Minnesota, USA, to 19th century US military fort climate data and tree-ring inferred climate reconstructions

NASA Astrophysics Data System (ADS)

St Jacques, J.; Cumming, B. F.; Sauchyn, D.; Vanstone, J. R.; Dickenson, J.; Smol, J. P.

2013-12-01

A vital component of paleoclimatology is the validation of paleoclimatological reconstructions. Unfortunately, there is scant instrumental data prior to the 20th century available for this. Hence, typically, we can only do long-term validation using other proxy-inferred climate reconstructions. Minnesota, USA, with its long military fort climate records beginning in 1820 and early dense network of climate stations, offers a rare opportunity for proxy validation. We compare a high-resolution (4-year), millennium-scale, pollen-inferred paleoclimate record derived from varved Lake Mina in central Minnesota to early military fort records and dendroclimatological records. When inferring a paleoclimate record from a pollen record, we rely upon the pollen-climate relationship being constant in time. However, massive human impacts have significantly altered vegetation; and the relationship between modern instrumental climate data and the modern pollen rain becomes altered from what it was in the past. In the Midwest, selective logging, fire suppression, deforestation and agriculture have strongly influenced the modern pollen rain since Euro-American settlement in the mid-1800s. We assess the signal distortion introduced by using the conventional method of modern post-settlement pollen and climate calibration sets to infer climate at Lake Mina from pre-settlement pollen data. Our first February and May temperature reconstructions are based on a pollen dataset contemporaneous with early settlement to which corresponding climate data from the earliest instrumental records has been added to produce a 'pre-settlement' calibration set. The second February and May temperature reconstructions are based on a conventional 'modern' pollen-climate dataset from core-top pollen samples and modern climate normals. The temperature reconstructions are then compared to the earliest instrumental records from Fort Snelling, Minnesota, and it is shown that the reconstructions based on the pre-settlement calibration set give much more credible reconstructions. We then compare the temperature reconstructions based upon the two calibration sets for AD 1116-2002. Significant signal flattening and bias exist when using the conventional modern pollen-climate calibration set rather than the pre-settlement pollen-climate calibration set, resulting in an overestimation of Little Ice Age monthly mean temperatures of 0.5-1.5 oC. Therefore, regional warming from anthropogenic global warming is significantly underestimated when using the conventional method of building pollen-climate calibration sets. We also compare the Lake Mina pollen-inferred effective moisture record to early 19th century climate data and to a four-century tree-ring inferred moisture reconstruction based upon sites in Minnesota and the Dakotas. This comparison shows that regional tree-ring reconstructions are biased towards dry conditions and record wet periods poorly relative to high-resolution pollen reconstructions, giving a false impression of regional aridity. It also suggests that varve chronologies should be based upon cross-dating to ensure a more accurate chronology.

An integrated hydrological modeling approach for detection and attribution of climatic and human impacts on coastal water resources

NASA Astrophysics Data System (ADS)

Feng, Dapeng; Zheng, Yi; Mao, Yixin; Zhang, Aijing; Wu, Bin; Li, Jinguo; Tian, Yong; Wu, Xin

2018-02-01

Water resources in coastal areas can be profoundly influenced by both climate change and human activities. These climatic and human impacts are usually intertwined and difficult to isolate. This study developed an integrated model-based approach for detection and attribution of climatic and human impacts and applied this approach to the Luanhe Plain, a typical coastal area in northern China. An integrated surface water-groundwater model was developed for the study area using GSFLOW (coupled groundwater and surface-water flow). Model calibration and validation were performed for background years between 1975 and 2000. The variation in water resources between the 1980s and 1990s was then quantitatively attributed to climate variability, groundwater pumping and changes in upstream inflow. Climate scenarios for future years (2075-2100) were also developed by downscaling the projections in CMIP5. Potential water resource responses to climate change, as well as their uncertainty, were then investigated through integrated modeling. The study results demonstrated the feasibility and value of the integrated modeling-based analysis for water resource management in areas with complex surface water-groundwater interaction. Specific findings for the Luanhe Plain included the following: (1) During the historical period, upstream inflow had the most significant impact on river outflow to the sea, followed by climate variability, whereas groundwater pumping was the least influential. (2) The increase in groundwater pumping had a dominant influence on the decline in groundwater change, followed by climate variability. (3) Synergetic and counteractive effects among different impacting factors, while identified, were not significant, which implied that the interaction among different factors was not very strong in this case. (4) It is highly probable that future climate change will accelerate groundwater depletion in the study area, implying that strict regulations for groundwater pumping are imperative for adaptation.

Comparison of Ice Cloud Particle Sizes Retrieved from Satellite Data Derived from In Situ Measurements

NASA Technical Reports Server (NTRS)

Han, Qingyuan; Rossow, William B.; Chou, Joyce; Welch, Ronald M.

1997-01-01

Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al.), there is no comparable study for cirrus ice crystals. This study is an effort to supply such a data set.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Satellite Calibration and Verification of Remotely Sensed Cloud and Radiation Properties Using ARM UAV Data

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Charlock, Thomas P.

1998-01-01

The work proposed under this agreement was designed to validate and improve remote sensing of cloud and radiation properties in the atmosphere for climate studies with special emphasis on the use of satellites for monitoring these parameters to further the goals of the Atmospheric Radiation Measurement (ARM) Program.

A Validation Study of the What's My School Mindset? Survey

ERIC Educational Resources Information Center

Hanson, Janet; Bangert, Arthur; Ruff, William

2016-01-01

The What's My School Mindset? (WMSM) survey is purported to operationalize teachers' beliefs of their school's ability to help all children learn and grow. In today's data driven educational climate it is important to select a reliable instrument for collecting teacher perceptions about their school culture. Accurate data is necessary to support…

Current challenges in distinguishing climatic and anthropogenic contributions to alpine grassland variation on the Tibetan Plateau.

PubMed

Li, Lanhui; Zhang, Yili; Liu, Linshan; Wu, Jianshuang; Li, Shicheng; Zhang, Haiyan; Zhang, Binghua; Ding, Mingjun; Wang, Zhaofeng; Paudel, Basanta

2018-06-01

Quantifying the impact of climate change and human activities on grassland dynamics is an essential step for developing sustainable grassland ecosystem management strategies. However, the direction and magnitude of climate change and human activities in driving alpine grassland dynamic over the Tibetan Plateau remain under debates. Here, we systematically reviewed the relevant studies on the methods, main conclusions, and causes for the inconsistency in distinguishing the respective contribution of climatic and anthropogenic forces to alpine grassland dynamic. Both manipulative experiments and traditional statistical analysis show that climate warming increase biomass in alpine meadows and decrease in alpine steppes, while both alpine steppes and meadows benefit from an increase in precipitation or soil moisture. Overgrazing is a major factor for the degradation of alpine grassland in local areas with high level of human activity intensity. However, across the entire Tibetan Plateau and its subregions, four views characterize the remaining controversies: alpine grassland changes are primarily due to (1) climatic force, (2) nonclimatic force, (3) combination of anthropogenic and climatic force, or (4) alternation of anthropogenic and climatic force. Furthermore, these views also show spatial inconsistencies. Differences on the source and quality of remote sensing products, the structure and parameter of models, and overlooking the spatiotemporal heterogeneity of human activity intensity contribute to current disagreements. In this review, we highlight the necessity for taking the spatiotemporal heterogeneity of human activity intensity into account in the models of attribution assessment, and the importance for accurate validation of climatic and anthropogenic contribution to alpine grassland variation at multiple scales for future studies.

Strategies for reforestation under uncertain future climates: guidelines for Alberta, Canada.

PubMed

Gray, Laura K; Hamann, Andreas

2011-01-01

Commercial forestry programs normally use locally collected seed for reforestation under the assumption that tree populations are optimally adapted to local environments. However, in western Canada this assumption is no longer valid because of climate trends that have occurred over the last several decades. The objective of this study is to show how we can arrive at reforestation recommendations with alternative species and genotypes that are viable under a majority of climate change scenarios. In a case study for commercially important tree species of Alberta, we use an ecosystem-based bioclimate envelope modeling approach for western North America to project habitat for locally adapted populations of tree species using multi-model climate projections for the 2020s, 2050s and 2080s. We find that genotypes of species that are adapted to drier climatic conditions will be the preferred planting stock over much of the boreal forest that is commercially managed. Interestingly, no alternative species that are currently not present in Alberta can be recommended with any confidence. Finally, we observe large uncertainties in projections of suitable habitat that make reforestation planning beyond the 2050s difficult for most species. More than 50,000 hectares of forests are commercially planted every year in Alberta. Choosing alternative planting stock, suitable for expected future climates, could therefore offer an effective climate change adaptation strategy at little additional cost. Habitat projections for locally adapted tree populations under observed climate change conform well to projections for the 2020s, which suggests that it is a safe strategy to change current reforestation practices and adapt to new climatic realities through assisted migration prescriptions.

Refutation Texts for Effective Climate Change Education

ERIC Educational Resources Information Center

Nussbaum, E. Michael; Cordova, Jacqueline R.; Rehmat, Abeera P.

2017-01-01

Refutation texts, which are texts that rebut scientific misconceptions and explain the normative concept, can be effective devices for addressing misconceptions and affecting conceptual change. However, few, if any, refutation texts specifically related to climate change have been validated for effectiveness. In this project, we developed and…

Faculty Teaching Climate: Scale Construction and Initial Validation

ERIC Educational Resources Information Center

Knorek, John Kenneth

2012-01-01

The concept "academic culture" has been used as a framework to understand faculty work in higher education. Academic culture research builds on organizational psychology concepts of culture and climate to better understand employee practices and work phenomenon. Ample research has investigated faculty teaching at the disciplinary and…

Student Climate Survey, Spring 1998.

ERIC Educational Resources Information Center

Truckee Meadows Community Coll., Sparks, NV.

Every three years, Truckee Meadows Community College (Nevada) administers a student climate survey that measures the attitudes, perceptions, and opinions of its student population. The instrument used to survey the student body was designed with three basic objectives in mind: (1) validate the institutional mission; (2) obtain input regarding the…

Toward a Global Map of Raindrop Size Distributions. Part 1; Rain-Type Classification and Its Implications for Validating Global Rainfall Products

NASA Technical Reports Server (NTRS)

L'Ecuyer, Tristan S.; Kummerow, Christian; Berg,Wesley

2004-01-01

Variability in the global distribution of precipitation is recognized as a key element in assessing the impact of climate change for life on earth. The response of precipitation to climate forcings is, however, poorly understood because of discrepancies in the magnitude and sign of climatic trends in satellite-based rainfall estimates. Quantifying and ultimately removing these biases is critical for studying the response of the hydrologic cycle to climate change. In addition, estimates of random errors owing to variability in algorithm assumptions on local spatial and temporal scales are critical for establishing how strongly their products should be weighted in data assimilation or model validation applications and for assigning a level of confidence to climate trends diagnosed from the data. This paper explores the potential for refining assumed drop size distributions (DSDs) in global radar rainfall algorithms by establishing a link between satellite observables and information gleaned from regional validation experiments where polarimetric radar, Doppler radar, and disdrometer measurements can be used to infer raindrop size distributions. By virtue of the limited information available in the satellite retrieval framework, the current method deviates from approaches adopted in the ground-based radar community that attempt to relate microphysical processes and resultant DSDs to local meteorological conditions. Instead, the technique exploits the fact that different microphysical pathways for rainfall production are likely to lead to differences in both the DSD of the resulting raindrops and the three-dimensional structure of associated radar reflectivity profiles. Objective rain-type classification based on the complete three-dimensional structure of observed reflectivity profiles is found to partially mitigate random and systematic errors in DSDs implied by differential reflectivity measurements. In particular, it is shown that vertical and horizontal reflectivity structure obtained from spaceborne radar can be used to reproduce significant differences in Z(sub dr) between the easterly and westerly climate regimes observed in the Tropical Rainfall Measuring Mission Large-scale Biosphere-Atmosphere (TRMM-LBA) field experiment as well as the even larger differences between Amazonian rainfall and that observed in eastern Colorado. As such, the technique offers a potential methodology for placing locally observed DSD information into a global framework.

Monthly mean global satellite data sets available in CCM history tape format

NASA Technical Reports Server (NTRS)

Hurrell, James W.; Campbell, G. Garrett

1992-01-01

Satellite data for climate monitoring have become increasingly important over the past decade, especially with increasing concern for inadvertent antropogenic climate change. Although most satellite based data are of short record, satellites can provide the global coverage that traditional meteorological observations network lack. In addition, satellite data are invaluable for the validation of climate models, and they are useful for many diagnostic studies. Herein, several satellite data sets were processed and transposed into 'history tape' format for use with the Community Climate Model (CCM) modular processor. Only a few of the most widely used and best documented data sets were selected at this point, although future work will expand the number of data sets examined as well as update the archived data sets. An attempt was made to include data of longer record and only monthly averaged data were processed. For studies using satellite data over an extended period, it is important to recognize the impact of changes in instrumentation, drift in instrument calibration, errors introduced by retrieval algorithms and other sources of errors such as those resulting from insufficient space and/or time sampling.

Seasonal variation of carcass decomposition and gravesoil chemistry in a cold (Dfa) climate.

PubMed

Meyer, Jessica; Anderson, Brianna; Carter, David O

2013-09-01

It is well known that temperature significantly affects corpse decomposition. Yet relatively few taphonomy studies investigate the effects of seasonality on decomposition. Here, we propose the use of the Köppen-Geiger climate classification system and describe the decomposition of swine (Sus scrofa domesticus) carcasses during the summer and winter near Lincoln, Nebraska, USA. Decomposition was scored, and gravesoil chemistry (total carbon, total nitrogen, ninhydrin-reactive nitrogen, ammonium, nitrate, and soil pH) was assessed. Gross carcass decomposition in summer was three to seven times greater than in winter. Initial significant changes in gravesoil chemistry occurred following approximately 320 accumulated degree days, regardless of season. Furthermore, significant (p < 0.05) correlations were observed between ammonium and pH (positive correlation) and between nitrate and pH (negative correlation). We hope that future decomposition studies employ the Köppen-Geiger climate classification system to understand the seasonality of corpse decomposition, to validate taphonomic methods, and to facilitate cross-climate comparisons of carcass decomposition. © 2013 American Academy of Forensic Sciences.

Validation of non-stationary precipitation series for site-specific impact assessment: comparison of two statistical downscaling techniques

NASA Astrophysics Data System (ADS)

Mullan, Donal; Chen, Jie; Zhang, Xunchang John

2016-02-01

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

UTCI-Fiala multi-node model of human heat transfer and temperature regulation

NASA Astrophysics Data System (ADS)

Fiala, Dusan; Havenith, George; Bröde, Peter; Kampmann, Bernhard; Jendritzky, Gerd

2012-05-01

The UTCI-Fiala mathematical model of human temperature regulation forms the basis of the new Universal Thermal Climate Index (UTC). Following extensive validation tests, adaptations and extensions, such as the inclusion of an adaptive clothing model, the model was used to predict human temperature and regulatory responses for combinations of the prevailing outdoor climate conditions. This paper provides an overview of the underlying algorithms and methods that constitute the multi-node dynamic UTCI-Fiala model of human thermal physiology and comfort. Treated topics include modelling heat and mass transfer within the body, numerical techniques, modelling environmental heat exchanges, thermoregulatory reactions of the central nervous system, and perceptual responses. Other contributions of this special issue describe the validation of the UTCI-Fiala model against measured data and the development of the adaptive clothing model for outdoor climates.

Relationships among Safety Climate, Safety Behavior, and Safety Outcomes for Ethnic Minority Construction Workers.

PubMed

Lyu, Sainan; Hon, Carol K H; Chan, Albert P C; Wong, Francis K W; Javed, Arshad Ali

2018-03-09

In many countries, it is common practice to attract and employ ethnic minority (EM) or migrant workers in the construction industry. This primarily occurs in order to alleviate the labor shortage caused by an aging workforce with a lack of new entrants. Statistics show that EM construction workers are more likely to have occupational fatal and nonfatal injuries than their local counterparts; however, the mechanism underlying accidents and injuries in this vulnerable population has been rarely examined. This study aims to investigate relationships among safety climate, safety behavior, and safety outcomes for EM construction workers. To this end, a theoretical research model was developed based on a comprehensive review of the current literature. In total, 289 valid questionnaires were collected face-to-face from 223 Nepalese construction workers and 56 Pakistani construction workers working on 15 construction sites in Hong Kong. Structural equation modelling was employed to validate the constructs and test the hypothesized model. Results show that there were significant positive relationships between safety climate and safety behaviors, and significant negative relationships between safety behaviors and safety outcomes for EM construction workers. This research contributes to the literature regarding EM workers by providing empirical evidence of the mechanisms by which safety climate affects safety behaviors and outcomes. It also provides insights in order to help the key stakeholders formulate safety strategies for EM workers in many areas where numerous EM workers are employed, such as in the U.S., the UK, Australia, Singapore, Malaysia, and the Middle East.

The impact of climate change on water provision under a low flow regime: a case study of the ecosystems services in the Francoli river basin.

PubMed

Marquès, Montse; Bangash, Rubab Fatima; Kumar, Vikas; Sharp, Richard; Schuhmacher, Marta

2013-12-15

Mediterranean basin is considered one of the most vulnerable regions of the world to climate change and with high probability to face acute water scarcity problem in the coming years. Francolí River basin (NE Spain), located in this vulnerable region is selected as a case study to evaluate the impact of climate change on the delivery of water considering the IPCC scenarios A2 and B1 for the time spans 2011-2040, 2041-2070 and 2071-2100. InVEST model is applied in a low flow river as a new case study, which reported successful results after its model validation. The studied hydrological ecosystem services will be highly impacted by climate change at Francolí River basin. Water yield is expected to be reduced between 11.5 and 44% while total drinking water provisioning will decrease between 13 and 50% having adverse consequences on the water quality of the river. Focusing at regional scale, Prades Mountains and Brugent Tributary provide most of the provision of water and also considered highly vulnerable areas to climate change. However, the most vulnerable part is the northern area which has the lowest provision of water. Francolí River basin is likely to experience desertification at this area drying Anguera and Vallverd tributaries. Copyright © 2013 Elsevier B.V. All rights reserved.

The Use of a Mesoscale Climate Model to Validate the Nocturnal Carbon Flux over a Forested Site

NASA Astrophysics Data System (ADS)

Werth, D.; Parker, M.; Kurzeja, R.; Leclerc, M.; Watson, T.

2007-12-01

The Savannah River National Laboratory is initiating a comprehensive carbon dioxide monitoring and modeling program in collaboration with the University of Georgia and the Brookhaven National Laboratory. One of the primary goals is to study the dynamics of carbon dioxide in the stable nocturnal boundary layer (NBL) over a forested area of the Savannah River Site in southwest South Carolina. In the nocturnal boundary layer (NBL), eddy flux correlation is less effective in determining the release of CO2 due to respiration. Theoretically, however, the flux can be inferred by measuring the build up of CO2 in the stable layer throughout the night. This method of monitoring the flux will be validated and studied in more detail with both observations and the results of a high-resolution regional climate model. The experiment will involve two phases. First, an artificial tracer will be released into the forest boundary layer and observed through an array of sensors and at a flux tower. The event will be simulated with the RAMS climate model run at very high resolution. Ideally, the tracer will remain trapped within the stable layer and accumulate at rates which will allow us to infer the release rate, and this should compare well to the actual release rate. If an unknown mechanism allows the tracer to escape, the model simulation would be used to reveal it. In the second phase, carbon fluxes will be measured overnight through accumulation in the overlying layer. The RAMS model will be coupled with the SiB carbon model to simulate the nocturnal cycle of carbon dynamics, and this will be compared to the data collected during the night. As with the tracer study, the NBL method of flux measurement will be validated against the model. The RAMS-SiB coupled model has been run over the SRS at high-resolution to simulate the NBL, and results from simulations of both phases of the project will be presented.

Physically-based distributed mass balance modeling of a tropical glacier: An application to backward modeling of past climate

NASA Astrophysics Data System (ADS)

Moelg, T.; Cullen, N. J.; Hardy, D. R.; Winkler, M.; Kaser, G.

2009-04-01

The use of spatially distributed (2-D) mass balance models has increased in recent years, but mostly focuses on extratropical glacier surfaces. Here we present the first application of a process-based 2-D model to an African glacier: Kersten Glacier on Kilimanjaro. Multi-year data from an automatic weather station (AWS) at 5873 m a.s.l. (500 hPa) serve to force the model. Validation variables comprise surface temperature, surface height change, snow depth, and incoming radiation - all of which indicate a good model performance. Analyses of the interannual variability in the most significant total mass budget terms (surface accumulation, melt, and sublimation), as well as in the related energy fluxes, exhibit a strong link to atmospheric moisture of a particular year. This is because net shortwave radiation (a result of both cloudiness and surface albedo) is the most variable energy flux on monthly to annual time scales. Internal accumulation (refreezing of melt water), however, shows a time lag and is strongest after a very wet year. Due to the limited validation data at lower elevations, we also perform a detailed sensitivity study by varying 17 model parameters - which yields a total mass loss estimate of 522 +/- 105 kg/m2/year under present climate conditions. Moreover, the verified model allows us to perform backward modeling of the last maximum extent of Kersten Glacier in the 1880s, which is indicated by a well preserved terminal moraine. This step reveals decreases in precipitation (30-45%), water vapor pressure (0.1-0.3 hPa) and cloud cover (2-4 percentage units) as the most likely local climate change between late 19th century and present. Thus, the study also demonstrates how 2-D modeling can help reconstruct past climate for a remote place prior to the availability of measurements. In our case these findings have great relevance for the debate of surface versus mid-tropospheric climate change in the tropics.

Impacts of climate change on large forest wildfire of Washington and Oregon

NASA Astrophysics Data System (ADS)

Yang, Z.; Davis, R. J.; Yost, A.; Cohen, W. B.

2014-12-01

Climate changes in the 21st century were projected to have major impact on wildfire. The state of Washington and Oregon contains a tightly coupled forest ecosystem and fire regime. The objective of this study was to examine the impact of future climate changes for large wildfire in the two states. MAXENT algorithm was used to develop a large forest wildfire suitability model using historical fire for the 1971-2000 time period and validated for 1981-2010 time period . Input variables include climate (e.g. July-August temperature) and topographic variables (e.g. elevation). The model test AUC of 0.77±0.1. Using the predicted versus expected curve and methods described by Hirzel and others (Hirzel et al. 2006), we reclassified the model into four classes; low suitability (0-0.36), moderate suitability 0.36-0.5), high suitability (0.5-0.75), and very high suitability (0.75-1.0). To examine the future climate change impact, climate scenarios (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) from 33 different climate models were used to predict the large wildfire suitability from 1971-2100 using the NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) dataset. Results from ensembles of all the climate scenarios showed that the area with high and very high suitability for large wildfire increased under all 4 climate scenarios from 1971 to 2100. However, under RCP 2.6, the area start to decline from 2080 while the other three scenarios keep increasing. On the extreme case of RCP 8.5, very high suitable area increases from less than 1% during 1971-2000 to 14.9% during 2070-2100. Details about temporal patterns for the study area and changes by ecoregions will be presented.

Quantifying Direct and Indirect Impact of Future Climate on Sub-Arctic Hydrology

NASA Astrophysics Data System (ADS)

Endalamaw, A. M.; Bolton, W. R.; Young-Robertson, J. M.; Morton, D.; Hinzman, L. D.

2016-12-01

Projected future climate will have a significant impact on the hydrology of interior Alaskan sub-arctic watersheds, directly though the changes in precipitation and temperature patterns, and indirectly through the cryospheric and ecological impacts. Although the latter is the dominant factor controlling the hydrological processes in the interior Alaska sub-arctic, it is often overlooked in many climate change impact studies. In this study, we aim to quantify and compare the direct and indirect impact of the projected future climate on the hydrology of the interior Alaskan sub-arctic watersheds. The Variable Infiltration Capacity (VIC) meso-scale hydrological model will be implemented to simulate the hydrological processes, including runoff, evapotranspiration, and soil moisture dynamics in the Chena River Basin (area = 5400km2), located in the interior Alaska sub-arctic region. Permafrost and vegetation distribution will be derived from the Geophysical Institute Permafrost Lab (GIPL) model and the Lund-Potsdam-Jena Dynamic Global Model (LPJ) model, respectively. All models will be calibrated and validated using historical data. The Scenario Network for Alaskan and Arctic Planning (SNAP) 5-model average projected climate data products will be used as forcing data for each of these models. The direct impact of climate change on hydrology is estimated using surface parameterization derived from the present day permafrost and vegetation distribution, and future climate forcing from SNAP projected climate data products. Along with the projected future climate, outputs of GIPL and LPJ will be incorporated into the VIC model to estimate the indirect and overall impact of future climate on the hydrology processes in the interior Alaskan sub-arctic watersheds. Finally, we will present the potential hydrological and ecological changes by the end of the 21st century.

False Balance in Climate Change Reporting Among TV Meteorologists

NASA Astrophysics Data System (ADS)

Timm, K.; Maibach, E.; Boykoff, M.; Broeckelman-Post, M.; Myers, T.; Perkins, D. R., IV

2017-12-01

False balance is the journalistic practice of giving equal weight to both sides of a story, regardless of an established truth and validity on one side. Despite widespread scientific agreement about the anthropogenic causes of climate change, false balance on the subject of climate change remains common in television despite a documented decline in other media. In this exploratory study, 452 American TV meteorologists were surveyed about their climate change beliefs and asked how often and why they present an opposing viewpoint when they present about human contributions to climate change. The results indicate that this practice is fairly common, with nearly 30% of TV meteorologists presenting an opposing viewpoint at least half the time or more frequently when they present about climate change. Weathercasters described including an opposing viewpoint in their stories for many different reasons, including that it is essential to objective and balanced reporting, that it is used to acknowledge different audience viewpoints, and because the science is perceived to be uncertain. The results also suggest that being more certain that climate change is happening, that it is primarily caused by humans, and perceiving the full extent of the scientific consensus about human-caused climate change, are associated with decreased frequency of presenting an opposing viewpoint. This is the first time the issue of false balance has been studied in the context of TV weathercasters, and while more research is needed, these results provide some preliminary evidence to suggest that increasing weathercasters' understanding of the scientific consensus of human caused climate change may help reduce false balance reporting. Furthermore, as meteorologists and weathercasters become more prominent reporters of local climate news, it will be important for them to have techniques to accurately report the science, while maintaining their sense of objectivity.

Describing the Climate of Student Organizations: The Student Organization Environment Scales.

ERIC Educational Resources Information Center

Winston, Roger B., Jr.; Bledsoe, Tyrone; Goldstein, Adam R.; Wisbey, Martha E.; Street, James L.; Brown, Steven R.; Goyen, Kenneth D.; Rounds, Linda E.

1997-01-01

Using M. R. Weisbord's model of organizational diagnosis, researchers developed the Student Organization Environment Scales to measure students' perceptions of the psychosocial environment or climate of college student organizations. Development of the instrument is described and estimates of its reliability and validity are reported. Describes…

Effect of the learning climate of residency programs on faculty's teaching performance as evaluated by residents.

PubMed

Lombarts, Kiki M J M H; Heineman, Maas Jan; Scherpbier, Albert J J A; Arah, Onyebuchi A

2014-01-01

To understand teaching performance of individual faculty, the climate in which residents' learning takes place, the learning climate, may be important. There is emerging evidence that specific climates do predict specific outcomes. Until now, the effect of learning climate on the performance of the individual faculty who actually do the teaching was unknown. THIS STUDY: (i) tested the hypothesis that a positive learning climate was associated with better teaching performance of individual faculty as evaluated by residents, and (ii) explored which dimensions of learning climate were associated with faculty's teaching performance. We conducted two cross-sectional questionnaire surveys amongst residents from 45 residency training programs and multiple specialties in 17 hospitals in the Netherlands. Residents evaluated the teaching performance of individual faculty using the robust System for Evaluating Teaching Qualities (SETQ) and evaluated the learning climate of residency programs using the Dutch Residency Educational Climate Test (D-RECT). The validated D-RECT questionnaire consisted of 11 subscales of learning climate. Main outcome measure was faculty's overall teaching (SETQ) score. We used multivariable adjusted linear mixed models to estimate the separate associations of overall learning climate and each of its subscales with faculty's teaching performance. In total 451 residents completed 3569 SETQ evaluations of 502 faculty. Residents also evaluated the learning climate of 45 residency programs in 17 hospitals in the Netherlands. Overall learning climate was positively associated with faculty's teaching performance (regression coefficient 0.54, 95% confidence interval: 0.37 to 0.71; P<0.001). Three out of 11 learning climate subscales were substantially associated with better teaching performance: 'coaching and assessment', 'work is adapted to residents' competence', and 'formal education'. Individual faculty's teaching performance evaluations are positively affected by better learning climate of residency programs.

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.

Sea Level Rise, Rainfall and Coastal Flooding in Northeastern U.S. Cities Vivien Gornitz, Radley Horton, Philip Orton, Nickitas Georgas, Alan Blumberg, and Cynthia Rosenzweig

NASA Astrophysics Data System (ADS)

Gornitz, V.; Horton, R. M.; Orton, P. M.; Georgas, N.; Blumberg, A. F.; Rosenzweig, C.

2012-12-01

Populations and infrastructure along much of the northeastern coast of the United States will become increasingly vulnerable to the impacts of rising sea level and storm surges over the coming century. This vulnerability is amplified by regional land subsidence and likely also by shifts in ocean circulation. Building upon recent studies for the New York City Panel on Climate Change (NPCC), New York State ClimAid assessment, and the latest U.S. National Climate Assessment, we report new regional sea level rise projections based on the latest CMIP-5 global climate models (GCMs) and RCP emission scenarios, adjusted for revised glacial ice melt contributions, and other factors such as gravitational effects, land water storage, and changes in the Atlantic Meriodional Overturning Circulation (AMOC). Over the coming two years, GCM-derived sea level outputs for future decades will be utilized in risk assessments for coastal flooding in New York City, Boston, and Philadelphia, as part of the Consortium for Climate Risk in the Urban Northeast-RISA project. The Stevens Institute Estuarine and Coastal Ocean Model (sECOM) will be used to produce best estimates (including uncertainty ranges) of sea level rise impacts for a wide range of tropical and extra-tropical cyclones for the 2010s, 2050s, and 2080s. Major improvements over prior studies include (a) the use of a detailed, extensively validated ocean model, and (b) inclusion of rainfall and river flow influences on coastal flooding, which affect flood levels in enclosed tidal waterways (e.g., the Hudson and Delaware Rivers), and which are also likely important in coastal confluence zones of impermeable urbanized watersheds. In addition to the sea level rise results, we present initial model validation results for historical storms.

The meaning and measurement of implementation climate

PubMed Central

2011-01-01

Background Climate has a long history in organizational studies, but few theoretical models integrate the complex effects of climate during innovation implementation. In 1996, a theoretical model was proposed that organizations could develop a positive climate for implementation by making use of various policies and practices that promote organizational members' means, motives, and opportunities for innovation use. The model proposes that implementation climate--or the extent to which organizational members perceive that innovation use is expected, supported, and rewarded--is positively associated with implementation effectiveness. The implementation climate construct holds significant promise for advancing scientific knowledge about the organizational determinants of innovation implementation. However, the construct has not received sufficient scholarly attention, despite numerous citations in the scientific literature. In this article, we clarify the meaning of implementation climate, discuss several measurement issues, and propose guidelines for empirical study. Discussion Implementation climate differs from constructs such as organizational climate, culture, or context in two important respects: first, it has a strategic focus (implementation), and second, it is innovation-specific. Measuring implementation climate is challenging because the construct operates at the organizational level, but requires the collection of multi-dimensional perceptual data from many expected innovation users within an organization. In order to avoid problems with construct validity, assessments of within-group agreement of implementation climate measures must be carefully considered. Implementation climate implies a high degree of within-group agreement in climate perceptions. However, researchers might find it useful to distinguish implementation climate level (the average of implementation climate perceptions) from implementation climate strength (the variability of implementation climate perceptions). It is important to recognize that the implementation climate construct applies most readily to innovations that require collective, coordinated behavior change by many organizational members both for successful implementation and for realization of anticipated benefits. For innovations that do not possess these attributes, individual-level theories of behavior change could be more useful in explaining implementation effectiveness. Summary This construct has considerable value in implementation science, however, further debate and development is necessary to refine and distinguish the construct for empirical use. PMID:21781328

Organizational climate, occupational stress, and employee mental health: mediating effects of organizational efficiency.

PubMed

Arnetz, Bengt B; Lucas, Todd; Arnetz, Judith E

2011-01-01

To determine whether the relationship between organizational climate and employee mental health is consistent (ie, invariant) or differs across four large hospitals, and whether organizational efficiency mediates this relationship. Participants (total N = 5316) completed validated measures of organizational climate variables (social climate, participatory management, goal clarity, and performance feedback), organizational efficiency, occupational stress, and mental health. Path analysis best supported a model in which organizational efficiency partially mediated relationships between organizational climate, occupational stress, and mental health. Focusing on improving both the psychosocial work environment and organizational efficiency might contribute to decreased employee stress, improved mental well-being, and organizational performance.

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

NASA Technical Reports Server (NTRS)

Quann, J. J.

1978-01-01

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

What Do GDGT Thermometers Tell us About Environmental Changes During the Holocene in Central Africa?

NASA Astrophysics Data System (ADS)

Menot, G.; Garcin, Y.; Bard, E. G.; Deschamps, P.

2017-12-01

Africa has been recognized by the IPCC group as one of the most vulnerable continents to climate change. Validation of models currently used for future climate projections relies in part on their ability to reproduce past climate variability. Especially the past abrupt climatic and environmental events that have punctuated the recent history of the African continent are of prime interest to model the transient and non-linear response of the African monsoon and vegetation to both external forcing and internal feedbacks. The role of temperature among other controls of the hydrological cycle has to be assessed. However, reliable temperature benchmark sequences on continents remain scare and not evenly distributed. The recent discovery of tetraethers as paleothermometer has raised a considerable interest as these lipid biomarkers fill a gap between "quantitative but discrete" and "qualitative but continuous" proxies on continents. Their broad application is however to date hampered by the few constrains on their origin as well as on their dynamics and fates related to pedogenic, transport and sedimentary processes. Previous studies on the lake Barombi (Cameroon) demonstrate the potential of newly retrieved lacustrine sequences to document hydrological changes associated with the African humid Period and vegetation changes related to the late Holocene `rainforest crisis' with an appropriate time resolution. Preliminary reconstructed temperature profile reveals a clear shift at the end of the African Humid Period. Prior any interpretation of a climate signal, a more complete characterization of the tetraether distributions is however needed together with a thorough comparison with other sedimentological proxies. Such an approach should allow identifying the processes that have altered the validity of the tetraether record as changes in soil erosion or lacustrine stratification.

Using Ground-Based Measurements and Retrievals to Validate Satellite Data

NASA Technical Reports Server (NTRS)

Dong, Xiquan

2002-01-01

The proposed research is to use the DOE ARM ground-based measurements and retrievals as the ground-truth references for validating satellite cloud results and retrieving algorithms. This validation effort includes four different ways: (1) cloud properties on different satellites, therefore different sensors, TRMM VIRS and TERRA MODIS; (2) cloud properties at different climatic regions, such as DOE ARM SGP, NSA, and TWP sites; (3) different cloud types, low and high level cloud properties; and (4) day and night retrieving algorithms. Validation of satellite-retrieved cloud properties is very difficult and a long-term effort because of significant spatial and temporal differences between the surface and satellite observing platforms. The ground-based measurements and retrievals, only carefully analyzed and validated, can provide a baseline for estimating errors in the satellite products. Even though the validation effort is so difficult, a significant progress has been made during the proposed study period, and the major accomplishments are summarized in the follow.

The Effectiveness of Using Limited Gauge Measurements for Bias Adjustment of Satellite-Based Precipitation Estimation over Saudi Arabia

NASA Astrophysics Data System (ADS)

Alharbi, Raied; Hsu, Kuolin; Sorooshian, Soroosh; Braithwaite, Dan

2018-01-01

Precipitation is a key input variable for hydrological and climate studies. Rain gauges are capable of providing reliable precipitation measurements at point scale. However, the uncertainty of rain measurements increases when the rain gauge network is sparse. Satellite -based precipitation estimations appear to be an alternative source of precipitation measurements, but they are influenced by systematic bias. In this study, a method for removing the bias from the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping, climate classification, and inverse-weighted distance method. Daily PERSIANN-CCS is selected to test the capability of the method for removing the bias over Saudi Arabia during the period of 2010 to 2016. The first six years (2010 - 2015) are calibrated years and 2016 is used for validation. The results show that the yearly correlation coefficient was enhanced by 12%, the yearly mean bias was reduced by 93% during validated year. Root mean square error was reduced by 73% during validated year. The correlation coefficient, the mean bias, and the root mean square error show that the proposed method removes the bias on PERSIANN-CCS effectively that the method can be applied to other regions where the rain gauge network is sparse.

Ancillary health effects of climate mitigation scenarios as drivers of policy uptake: a review of air quality, transportation and diet co-benefits modeling studies

NASA Astrophysics Data System (ADS)

Chang, Kelly M.; Hess, Jeremy J.; Balbus, John M.; Buonocore, Jonathan J.; Cleveland, David A.; Grabow, Maggie L.; Neff, Roni; Saari, Rebecca K.; Tessum, Christopher W.; Wilkinson, Paul; Woodward, Alistair; Ebi, Kristie L.

2017-11-01

Background: Significant mitigation efforts beyond the Nationally Determined Commitments (NDCs) coming out of the 2015 Paris Climate Agreement are required to avoid warming of 2 °C above pre-industrial temperatures. Health co-benefits represent selected near term, positive consequences of climate policies that can offset mitigation costs in the short term before the beneficial impacts of those policies on the magnitude of climate change are evident. The diversity of approaches to modeling mitigation options and their health effects inhibits meta-analyses and syntheses of results useful in policy-making. Methods/Design: We evaluated the range of methods and choices in modeling health co-benefits of climate mitigation to identify opportunities for increased consistency and collaboration that could better inform policy-making. We reviewed studies quantifying the health co-benefits of climate change mitigation related to air quality, transportation, and diet published since the 2009 Lancet Commission ‘Managing the health effects of climate change’ through January 2017. We documented approaches, methods, scenarios, health-related exposures, and health outcomes. Results/Synthesis: Forty-two studies met the inclusion criteria. Air quality, transportation, and diet scenarios ranged from specific policy proposals to hypothetical scenarios, and from global recommendations to stakeholder-informed local guidance. Geographic and temporal scope as well as validity of scenarios determined policy relevance. More recent studies tended to use more sophisticated methods to address complexity in the relevant policy system. Discussion: Most studies indicated significant, nearer term, local ancillary health benefits providing impetus for policy uptake and net cost savings. However, studies were more suited to describing the interaction of climate policy and health and the magnitude of potential outcomes than to providing specific accurate estimates of health co-benefits. Modeling the health co-benefits of climate policy provides policy-relevant information when the scenarios are reasonable, relevant, and thorough, and the model adequately addresses complexity. Greater consistency in selected modeling choices across the health co-benefits of climate mitigation research would facilitate evaluation of mitigation options particularly as they apply to the NDCs and promote policy uptake.

Modeling Soil Organic Carbon Variation Along Climatic and Topographic Trajectories in the Central Andes

NASA Astrophysics Data System (ADS)

Gavilan, C.; Grunwald, S.; Quiroz, R.; Zhu, L.

2015-12-01

The Andes represent the largest and highest mountain range in the tropics. Geological and climatic differentiation favored landscape and soil diversity, resulting in ecosystems adapted to very different climatic patterns. Although several studies support the fact that the Andes are a vast sink of soil organic carbon (SOC) only few have quantified this variable in situ. Estimating the spatial distribution of SOC stocks in data-poor and/or poorly accessible areas, like the Andean region, is challenging due to the lack of recent soil data at high spatial resolution and the wide range of coexistent ecosystems. Thus, the sampling strategy is vital in order to ensure the whole range of environmental covariates (EC) controlling SOC dynamics is represented. This approach allows grasping the variability of the area, which leads to more efficient statistical estimates and improves the modeling process. The objectives of this study were to i) characterize and model the spatial distribution of SOC stocks in the Central Andean region using soil-landscape modeling techniques, and to ii) validate and evaluate the model for predicting SOC content in the area. For that purpose, three representative study areas were identified and a suite of variables including elevation, mean annual temperature, annual precipitation and Normalized Difference Vegetation Index (NDVI), among others, was selected as EC. A stratified random sampling (namely conditioned Latin Hypercube) was implemented and a total of 400 sampling locations were identified. At all sites, four composite topsoil samples (0-30 cm) were collected within a 2 m radius. SOC content was measured using dry combustion and SOC stocks were estimated using bulk density measurements. Regression Kriging was used to map the spatial variation of SOC stocks. The accuracy, fit and bias of SOC models was assessed using a rigorous validation assessment. This study produced the first comprehensive, geospatial SOC stock assessment in this undersampled region that serves as a baseline reference to assess potential impacts of climate and land use change.

Comparison of Malaria Simulations Driven by Meteorological Observations and Reanalysis Products in Senegal.

PubMed

Diouf, Ibrahima; Rodriguez-Fonseca, Belen; Deme, Abdoulaye; Caminade, Cyril; Morse, Andrew P; Cisse, Moustapha; Sy, Ibrahima; Dia, Ibrahima; Ermert, Volker; Ndione, Jacques-André; Gaye, Amadou Thierno

2017-09-25

The analysis of the spatial and temporal variability of climate parameters is crucial to study the impact of climate-sensitive vector-borne diseases such as malaria. The use of malaria models is an alternative way of producing potential malaria historical data for Senegal due to the lack of reliable observations for malaria outbreaks over a long time period. Consequently, here we use the Liverpool Malaria Model (LMM), driven by different climatic datasets, in order to study and validate simulated malaria parameters over Senegal. The findings confirm that the risk of malaria transmission is mainly linked to climate variables such as rainfall and temperature as well as specific landscape characteristics. For the whole of Senegal, a lag of two months is generally observed between the peak of rainfall in August and the maximum number of reported malaria cases in October. The malaria transmission season usually takes place from September to November, corresponding to the second peak of temperature occurring in October. Observed malaria data from the Programme National de Lutte contre le Paludisme (PNLP, National Malaria control Programme in Senegal) and outputs from the meteorological data used in this study were compared. The malaria model outputs present some consistencies with observed malaria dynamics over Senegal, and further allow the exploration of simulations performed with reanalysis data sets over a longer time period. The simulated malaria risk significantly decreased during the 1970s and 1980s over Senegal. This result is consistent with the observed decrease of malaria vectors and malaria cases reported by field entomologists and clinicians in the literature. The main differences between model outputs and observations regard amplitude, but can be related not only to reanalysis deficiencies but also to other environmental and socio-economic factors that are not included in this mechanistic malaria model framework. The present study can be considered as a validation of the reliability of reanalysis to be used as inputs for the calculation of malaria parameters in the Sahel using dynamical malaria models.

Unraveling past impacts of climate change and land management on historic peatland development using proxy-based reconstruction, monitoring data and process modeling.

PubMed

Heinemeyer, Andreas; Swindles, Graeme T

2018-05-08

Peatlands represent globally significant soil carbon stores that have been accumulating for millennia under water-logged conditions. However, deepening water-table depths (WTD) from climate change or human-induced drainage could stimulate decomposition resulting in peatlands turning from carbon sinks to carbon sources. Contemporary WTD ranges of testate amoebae (TA) are commonly used to predict past WTD in peatlands using quantitative transfer function models. Here we present, for the first time, a study comparing TA-based WTD reconstructions to instrumentally monitored WTD and hydrological model predictions using the MILLENNIA peatland model to examine past peatland responses to climate change and land management. Although there was very good agreement between monitored and modeled WTD, TA-reconstructed water table was consistently deeper. Predictions from a larger European TA transfer function data set were wetter, but the overall directional fit to observed WTD was better for a TA transfer function based on data from northern England. We applied a regression-based offset correction to the reconstructed WTD for the validation period (1931-2010). We then predicted WTD using available climate records as MILLENNIA model input and compared the offset-corrected TA reconstruction to MILLENNIA WTD predictions over an extended period (1750-1931) with available climate reconstructions. Although the comparison revealed striking similarities in predicted overall WTD patterns, particularly for a recent drier period (1965-1995), there were clear periods when TA-based WTD predictions underestimated (i.e. drier during 1830-1930) and overestimated (i.e. wetter during 1760-1830) past WTD compared to MILLENNIA model predictions. Importantly, simulated grouse moor management scenarios may explain the drier TA WTD predictions, resulting in considerable model predicted carbon losses and reduced methane emissions, mainly due to drainage. This study demonstrates the value of a site-specific and combined data-model validation step toward using TA-derived moisture conditions to understand past climate-driven peatland development and carbon budgets alongside modeling likely management impacts. © 2018 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Criteria for the prioritization of public health interventions for climate-sensitive vector-borne diseases in Quebec

PubMed Central

Gosselin, Pierre; Michel, Pascal; Ravel, André; Waaub, Jean-Philippe; Campagna, Céline; Samoura, Karim

2017-01-01

Prioritizing resources for optimal responses to an ever growing list of existing and emerging infectious diseases represents an important challenge to public health. In the context of climate change, there is increasing anticipated variability in the occurrence of infectious diseases, notably climate-sensitive vector-borne diseases. An essential step in prioritizing efforts is to identify what considerations and concerns to take into account to guide decisions and thus set disease priorities. This study was designed to perform a comprehensive review of criteria for vector-borne disease prioritization, assess their applicability in a context of climate change with a diverse cross-section of stakeholders in order to produce a baseline list of considerations to use in this decision-making context. Differences in stakeholder choices were examined with regards to prioritization of these criteria for research, surveillance and disease prevention and control objectives. A preliminary list of criteria was identified following a review of the literature. Discussions with stakeholders were held to consolidate and validate this list of criteria and examine their effects on disease prioritization. After this validation phase, a total of 21 criteria were retained. A pilot vector-borne disease prioritization exercise was conducted using PROMETHEE to examine the effects of the retained criteria on prioritization in different intervention domains. Overall, concerns expressed by stakeholders for prioritization were well aligned with categories of criteria identified in previous prioritization studies. Weighting by category was consistent between stakeholders overall, though some significant differences were found between public health and non-public health stakeholders. From this exercise, a general model for climate-sensitive vector-borne disease prioritization has been developed that can be used as a starting point for further public health prioritization exercises relating to research, surveillance, and prevention and control interventions in a context of climate change. Multi-stakeholder engagement in prioritization can help broaden the range of criteria taken into account, offer opportunities for early identification of potential challenges and may facilitate acceptability of any resulting decisions. PMID:29281726

Modelling extreme climatic events in Guadalquivir Estuary ( Spain)

NASA Astrophysics Data System (ADS)

Delgado, Juan; Moreno-Navas, Juan; Pulido, Antoine; García-Lafuente, Juan; Calero Quesada, Maria C.; García, Rodrigo

2017-04-01

Extreme climatic events, such as heat waves and severe storms are predicted to increase in frequency and magnitude as a consequence of global warming but their socio-ecological effects are poorly understood, particularly in estuarine ecosystems. The Guadalquivir Estuary has been anthropologically modified several times, the original salt marshes have been transformed to grow rice and cotton and approximately one-fourth of the total surface of the estuary is now part of two protected areas, one of them is a UNESCO, MAB Biosphere Reserve. The climatic events are most likely to affect Europe in forthcoming decades and a further understanding how these climatic disturbances drive abrupt changes in the Guadalquivir estuary is needed. A barotropic model has been developed to study how severe storm events affects the estuary by conducting paired control and climate-events simulations. The changes in the local wind and atmospheric pressure conditions in the estuary have been studied in detail and several scenarios are obtained by running the model under control and real storm conditions. The model output has been validated with in situ water elevation and good agreement between modelled and real measurements have been obtained. Our preliminary results show that the model demonstrated the capability describe of the tide-surge levels in the estuary, opening the possibility to study the interaction between climatic events and the port operations and food production activities. The barotropic hydrodynamic model provide spatially explicit information on the key variables governing the tide dynamics of estuarine areas under severe climatic scenarios . The numerical model will be a powerful tool in future climate change mitigation and adaptation programs in a complex socio-ecological system.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

High-resolution dynamic downscaling of CMIP5 output over the Tropical Andes

NASA Astrophysics Data System (ADS)

Reichler, Thomas; Andrade, Marcos; Ohara, Noriaki

2015-04-01

Our project is targeted towards making robust predictions of future changes in climate over the tropical part of the South American Andes. This goal is challenging, since tropical lowlands, steep mountains, and snow covered subarctic surfaces meet over relatively short distances, leading to distinct climate regimes within the same domain and pronounced spatial gradients in virtually every climate quantity. We use an innovative approach to solve this problem, including several quadruple nested versions of WRF, a systematic validation strategy to find the version of WRF that best fits our study region, spatial resolutions at the kilometer scale, 20-year-long simulation periods, and bias-corrected output from various CMIP5 simulations that also include the multi-model mean of all CMIP5 models. We show that the simulated changes in climate are consistent with the results from the global climate models and also consistent with two different versions of WRF. We also discuss the expected changes in snow and ice, derived from off-line coupling the regional simulations to a carefully calibrated snow and ice model.

Modeling climatic effects of anthropogenic CO2 emissions: Unknowns and uncertainties

NASA Astrophysics Data System (ADS)

Soon, W.; Baliunas, S.; Idso, S.; Kondratyev, K. Ya.; Posmentier, E. S.

2001-12-01

A likelihood of disastrous global environmental consequences has been surmised as a result of projected increases in anthropogenic greenhouse gas emissions. These estimates are based on computer climate modeling, a branch of science still in its infancy despite recent, substantial strides in knowledge. Because the expected anthropogenic climate forcings are relatively small compared to other background and forcing factors (internal and external), the credibility of the modeled global and regional responses rests on the validity of the models. We focus on this important question of climate model validation. Specifically, we review common deficiencies in general circulation model calculations of atmospheric temperature, surface temperature, precipitation and their spatial and temporal variability. These deficiencies arise from complex problems associated with parameterization of multiply-interacting climate components, forcings and feedbacks, involving especially clouds and oceans. We also review examples of expected climatic impacts from anthropogenic CO2 forcing. Given the host of uncertainties and unknowns in the difficult but important task of climate modeling, the unique attribution of observed current climate change to increased atmospheric CO2 concentration, including the relatively well-observed latest 20 years, is not possible. We further conclude that the incautious use of GCMs to make future climate projections from incomplete or unknown forcing scenarios is antithetical to the intrinsically heuristic value of models. Such uncritical application of climate models has led to the commonly-held but erroneous impression that modeling has proven or substantiated the hypothesis that CO2 added to the air has caused or will cause significant global warming. An assessment of the positive skills of GCMs and their use in suggesting a discernible human influence on global climate can be found in the joint World Meteorological Organisation and United Nations Environmental Programme's Intergovernmental Panel on Climate Change, IPCC, reports (1990, 1995 and 2001). Our review highlights only the enormous scientific difficulties facing the calculation of climatic effects of added atmospheric CO2 in a GCM. The purpose of such a limited review of the deficiencies of climate model physics and the use of GCMs is to illuminate areas for improvement. Our review does not disprove a significant anthropogenic influence on global climate.

A National Program for Analysis of the Climate System

NASA Technical Reports Server (NTRS)

Schubert, Siegfried; Arkin, Phil; Kalnay, Eugenia; Laver, James; Trenberth, Kevin

2002-01-01

Perhaps the single greatest roadblock to fundamental advances in our understanding of climate variability and climate change is the lack of robust and unbiased long-term global observations of the climate system. Such observations are critical for the identification and diagnosis of climate variations, and provide the constraints necessary for developing and validating climate models. The first generation of reanalysis efforts, by using fixed analysis systems, eliminated the artificial climate signals that occurred in analyses generated at the operational numerical weather prediction centers. These datasets are now widely used by the scientific community in a variety of applications including atmosphere-ocean interactions, seasonal prediction, climate monitoring, the hydrological cycle, and a host of regional and other diagnostic studies. These reanalyses, however, had problems that made them sub-optimal or even unusable for some applications. Perhaps the most serious problem for climate applications was that, while the assimilation system remained fixed, changes in the observing systems did produce spurious changes in the perceived climate. The first generation reanalysis products also exposed problems with physical consistency of the products and the accurate representation of physical processes in the climate system. Examples are bias in the estimates of ocean surface fluxes, and inadequate representation of polar hydrology. In this talk, I will describe some initial plans for a national program on reananlysis. The program is envisioned to be part of an on-going activity to maintain, improve, and reprocess our record of climate observations. I will discuss various issues affecting the quality of reanalyses, with a special focus on those relevant to the ocean.

Wave–turbulence interaction-induced vertical mixing and its effects in ocean and climate models

PubMed Central

Qiao, Fangli; Yuan, Yeli; Deng, Jia; Dai, Dejun; Song, Zhenya

2016-01-01

Heated from above, the oceans are stably stratified. Therefore, the performance of general ocean circulation models and climate studies through coupled atmosphere–ocean models depends critically on vertical mixing of energy and momentum in the water column. Many of the traditional general circulation models are based on total kinetic energy (TKE), in which the roles of waves are averaged out. Although theoretical calculations suggest that waves could greatly enhance coexisting turbulence, no field measurements on turbulence have ever validated this mechanism directly. To address this problem, a specially designed field experiment has been conducted. The experimental results indicate that the wave–turbulence interaction-induced enhancement of the background turbulence is indeed the predominant mechanism for turbulence generation and enhancement. Based on this understanding, we propose a new parametrization for vertical mixing as an additive part to the traditional TKE approach. This new result reconfirmed the past theoretical model that had been tested and validated in numerical model experiments and field observations. It firmly establishes the critical role of wave–turbulence interaction effects in both general ocean circulation models and atmosphere–ocean coupled models, which could greatly improve the understanding of the sea surface temperature and water column properties distributions, and hence model-based climate forecasting capability. PMID:26953182

Coupling climate and hydrological models to evaluate the impact of climate change on run of the river hydropower schemes from UK study sites

NASA Astrophysics Data System (ADS)

Pasten-Zapata, Ernesto; Jones, Julie; Moggridge, Helen

2015-04-01

As climate change is expected to generate variations on the Earth's precipitation and temperature, the water cycle will also experience changes. Consequently, water users will have to be prepared for possible changes in future water availability. The main objective of this research is to evaluate the impacts of climate change on river regimes and the implications to the operation and feasibility of run of the river hydropower schemes by analyzing four UK study sites. Run of the river schemes are selected for analysis due to their higher dependence to the available river flow volumes when compared to storage hydropower schemes that can rely on previously accumulated water volumes (linked to poster in session HS5.3). Global Climate Models (GCMs) represent the main tool to assess future climate change. In this research, Regional Climate Models (RCMs), which dynamically downscale GCM outputs providing higher resolutions, are used as starting point to evaluate climate change within the study catchments. RCM daily temperature and precipitation will be downscaled to an appropriate scale for impact studies and bias corrected using different statistical methods: linear scaling, local intensity scaling, power transformation, variance scaling and delta change correction. The downscaled variables will then be coupled to hydrological models that have been previously calibrated and validated against observed daily river flow data. The coupled hydrological and climate models will then be used to simulate historic river flows that are compared to daily observed values in order to evaluate the model accuracy. As this research will employ several different RCMs (from the EURO-CORDEX simulations), downscaling and bias correction methodologies, greenhouse emission scenarios and hydrological models, the uncertainty of each element will be estimated. According to their uncertainty magnitude, a prediction of the best downscaling approach (or approaches) is expected to be obtained. The current progress of the project will be presented along with the steps to be followed in the future.

Consensus achievement of leadership, organisational and individual factors that influence safety climate: Implications for nursing management.

PubMed

Fischer, Shelly A; Jones, Jacqueline; Verran, Joyce A

2018-01-01

To validate a framework of factors that influence the relationship of transformational leadership and safety climate, and to enable testing of safety chain factors by generating hypotheses regarding their mediating and moderating effects. Understanding the patient safety chain and mechanisms by which leaders affect a strong climate of safety is essential to transformational leadership practice, education, and research. A systematic review of leadership and safety literature was used to develop an organising framework of factors proposed to influence the climate of safety. A panel of 25 international experts in leadership and safety engaged a three-round modified Delphi study with Likert-scored surveys. Eighty per cent of participating experts from six countries were retained to the final survey round. Consensus (>66% agreement) was achieved on 40 factors believed to influence safety climate in the acute care setting. Consensus regarding specific factors that play important roles in an organisation's climate of safety can be reached. Generally, the demonstration of leadership commitment to safety is key to cultivating a culture of patient safety. Transformational nurse leaders should consider and employ all three categories of factors in daily leadership activities and decision-making to drive a strong climate of patient safety. © 2017 John Wiley & Sons Ltd.

Potential climate effect of mineral aerosols over West Africa. Part I: model validation and contemporary climate evaluation

NASA Astrophysics Data System (ADS)

Ji, Zhenming; Wang, Guiling; Pal, Jeremy S.; Yu, Miao

2016-02-01

Mineral dusts present in the atmosphere can play an important role in climate over West Africa and surrounding regions. However, current understanding regarding how dust aerosols influence climate of West Africa is very limited. In this study, a regional climate model is used to investigate the potential climatic impacts of dust aerosols. Two sets of simulations driven by reanalysis and Earth System Model boundary conditions are performed with and without the representation of dust processes. The model, regardless of the boundary forcing, captures the spatial and temporal variability of the aerosol optical depth and surface concentration. The shortwave radiative forcing of dust is negative at the surface and positive in the atmosphere, with greater changes in the spring and summer. The presence of mineral dusts causes surface cooling and lower troposphere heating, resulting in a stabilization effect and reduction in precipitation in the northern portion of the monsoon close to the dust emissions region. This results in an enhancement of precipitation to the south. While dusts cause the lower troposphere to stabilize, upper tropospheric cooling makes the region more prone to intense deep convection as is evident by a simulated increase in extreme precipitation. In a companion paper, the impacts of dust emissions on future West African climate are investigated.

The last Deglaciation in the Mediterranean region: a multi-archives synthesis

NASA Astrophysics Data System (ADS)

Bazin, Lucie; Siani, Giuseppe; Landais, Amaelle; Bassinot, Frank; Genty, Dominique; Govin, Aline; Michel, Elisabeth; Nomade, Sebastien; Waelbroeck, Claire

2016-04-01

Multiple proxies record past climatic changes in different climate archives. These proxies are influenced by different component of the climate system and bring complementary information on past climate variability. The major limitation when combining proxies from different archives comes from the coherency of their chronologies. Indeed, each climate archives possess their own dating methods, not necessarily coherent with each other's. Consequently, when we want to assess the latitudinal changes and mechanisms behind a climate event, we often have to rely on assumptions of synchronisation between the different archives, such as synchronous temperature changes during warming events (Austin and Hibbert 2010). Recently, a dating method originally developed to produce coherent chronologies for ice cores (Datice,Lemieux-Dudon et al., 2010) has been adapted in order to integrate different climate archives (ice cores, sediment cores and speleothems (Lemieux-Dudon et al., 2015, Bazin et al., in prep)). In this presentation we present the validation of this multi-archives dating tool with a first application covering the last Deglaciation in the Mediterranean region. For this experiment, we consider the records from Monticchio, the MD90-917, Tenaghi Philippon and Lake Orhid sediment cores as well as continuous speleothems from Sofular, Soreq and La Mine caves. Using the Datice dating tool, and with the identification of common tephra layers between the cores considered, we are able to produce a multi-archives coherent chronology for this region, independently of any climatic assumption. Using this common chronological framework, we show that the usual climatic synchronisation assumptions are not valid over this region for the last glacial-interglacial transition. Finally, we compare our coherent Mediterranean chronology with Greenland ice core records in order to discuss the sequence of events of the last Deglaciation between these two regions.

Ice_Sheets_CCI: Essential Climate Variables for the Greenland Ice Sheet

NASA Astrophysics Data System (ADS)

Forsberg, R.; Sørensen, L. S.; Khan, A.; Aas, C.; Evansberget, D.; Adalsteinsdottir, G.; Mottram, R.; Andersen, S. B.; Ahlstrøm, A.; Dall, J.; Kusk, A.; Merryman, J.; Hvidberg, C.; Khvorostovsky, K.; Nagler, T.; Rott, H.; Scharrer, M.; Shepard, A.; Ticconi, F.; Engdahl, M.

2012-04-01

As part of the ESA Climate Change Initiative (www.esa-cci.org) a long-term project "ice_sheets_cci" started January 1, 2012, in addition to the existing 11 projects already generating Essential Climate Variables (ECV) for the Global Climate Observing System (GCOS). The "ice_sheets_cci" goal is to generate a consistent, long-term and timely set of key climate parameters for the Greenland ice sheet, to maximize the impact of European satellite data on climate research, from missions such as ERS, Envisat and the future Sentinel satellites. The climate parameters to be provided, at first in a research context, and in the longer perspective by a routine production system, would be grids of Greenland ice sheet elevation changes from radar altimetry, ice velocity from repeat-pass SAR data, as well as time series of marine-terminating glacier calving front locations and grounding lines for floating-front glaciers. The ice_sheets_cci project will involve a broad interaction of the relevant cryosphere and climate communities, first through user consultations and specifications, and later in 2012 optional participation in "best" algorithm selection activities, where prototype climate parameter variables for selected regions and time frames will be produced and validated using an objective set of criteria ("Round-Robin intercomparison"). This comparative algorithm selection activity will be completely open, and we invite all interested scientific groups with relevant experience to participate. The results of the "Round Robin" exercise will form the algorithmic basis for the future ECV production system. First prototype results will be generated and validated by early 2014. The poster will show the planned outline of the project and some early prototype results.

The Community Earth System Model-Polar Climate Working Group and the status of CESM2.

NASA Astrophysics Data System (ADS)

Bailey, D. A.; Holland, M. M.; DuVivier, A. K.

2017-12-01

The Polar Climate Working Group (PCWG) is a consortium of scientists who are interested in modeling and understanding the climate in the Arctic and the Antarctic, and how polar climate processes interact with and influence climate at lower latitudes. Our members come from universities and laboratories, and our interests span all elements of polar climate, from the ocean depths to the top of the atmosphere. In addition to conducting scientific modeling experiments, we are charged with contributing to the development and maintenance of the state-of-the-art sea ice model component (CICE) used in the Community Earth System Model (CESM). A recent priority for the PCWG has been to come up with innovative ways to bring the observational and modeling communities together. This will allow for more robust validation of climate model simulations, the development and implementation of more physically-based model parameterizations, improved data assimilation capabilities, and the better use of models to design and implement field experiments. These have been informed by topical workshops and scientific visitors that we have hosted in these areas. These activities will be discussed and information on how the better integration of observations and models has influenced the new version of the CESM, which is due to be released in late 2017, will be provided. Additionally, we will address how enhanced interactions with the observational community will contribute to model developments and validation moving forward.

Performance and Economic Modeling of Horizontally Drilled Ground-Source Heat Pumps in Select California Climates

NASA Astrophysics Data System (ADS)

Wiryadinata, Steven

Service life modeling was performed to gage the viability of unitary 3.5 kWt, ground-source terminal heat pumps (GTHP) employing horizontal directionally drilled geothermal heat exchangers (GHX) over air-source terminal heat pumps (PTHP) in hotels and motels and residential apartment building sectors in California's coastal and inland climates. Results suggest the GTHP can reduce hourly peak demand for the utility by 7%-25% compared to PTHP, depending on the climate and building type. The annual energy savings, which range from -1% to 5%, are highly dependent on the GTHP pump energy use relative to the energy savings attributed to the difference in ground and air temperatures (DeltaT). In mild climates with small ?T, the pump energy use may overcome any advantage to utilizing a GHX. The majority of total levelized cost savings - ranging from 0.18/ft2 to 0.3/ft 2 - are due to reduced maintenance and lifetime capital cost normally associated with geothermal heat pump systems. Without these reductions (not validated for the GTHP system studied), the GTHP technology does not appear to offer significant advantages over PTHP in the climate zones studied here. The GTHP levelized cost was most sensitive to variations in installed cost and in some cases, energy use (influenced by climate zone choice), which together highlights the importance of climate selection for installation, and the need for larger market penetration of ground-source systems in order to bring down installed costs as the technology matures.

Tree rings provide a new class of phenotypes for genetic associations that foster insights into adaptation of conifers to climate change.

PubMed

Housset, Johann M; Nadeau, Simon; Isabel, Nathalie; Depardieu, Claire; Duchesne, Isabelle; Lenz, Patrick; Girardin, Martin P

2018-04-01

Local adaptation in tree species has been documented through a long history of common garden experiments where functional traits (height, bud phenology) are used as proxies for fitness. However, the ability to identify genes or genomic regions related to adaptation to climate requires the evaluation of traits that precisely reflect how and when climate exerts selective constraints. We combine dendroecology with association genetics to establish a link between genotypes, phenotypes and interannual climatic fluctuations. We illustrate this approach by examining individual tree responses embedded in the annual rings of 233 Pinus strobus trees growing in a common garden experiment representing 38 populations from the majority of its range. We found that interannual variability in growth was affected by low temperatures during spring and autumn, and by summer heat and drought. Among-population variation in climatic sensitivity was significantly correlated with the mean annual temperature of the provenance, suggesting local adaptation. Genotype-phenotype associations using these new tree-ring phenotypes validated nine candidate genes identified in a previous genetic-environment association study. Combining dendroecology with association genetics allowed us to assess tree vulnerability to past climate at fine temporal scales and provides avenues for future genomic studies on functional adaptation in forest trees. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

The value of model averaging and dynamical climate model predictions for improving statistical seasonal streamflow forecasts over Australia

NASA Astrophysics Data System (ADS)

Pokhrel, Prafulla; Wang, Q. J.; Robertson, David E.

2013-10-01

Seasonal streamflow forecasts are valuable for planning and allocation of water resources. In Australia, the Bureau of Meteorology employs a statistical method to forecast seasonal streamflows. The method uses predictors that are related to catchment wetness at the start of a forecast period and to climate during the forecast period. For the latter, a predictor is selected among a number of lagged climate indices as candidates to give the "best" model in terms of model performance in cross validation. This study investigates two strategies for further improvement in seasonal streamflow forecasts. The first is to combine, through Bayesian model averaging, multiple candidate models with different lagged climate indices as predictors, to take advantage of different predictive strengths of the multiple models. The second strategy is to introduce additional candidate models, using rainfall and sea surface temperature predictions from a global climate model as predictors. This is to take advantage of the direct simulations of various dynamic processes. The results show that combining forecasts from multiple statistical models generally yields more skillful forecasts than using only the best model and appears to moderate the worst forecast errors. The use of rainfall predictions from the dynamical climate model marginally improves the streamflow forecasts when viewed over all the study catchments and seasons, but the use of sea surface temperature predictions provide little additional benefit.

Misleading prioritizations from modelling range shifts under climate change

USGS Publications Warehouse

Sofaer, Helen R.; Jarnevich, Catherine S.; Flather, Curtis H.

2018-01-01

AimConservation planning requires the prioritization of a subset of taxa and geographical locations to focus monitoring and management efforts. Integration of the threats and opportunities posed by climate change often relies on predictions from species distribution models, particularly for assessments of vulnerability or invasion risk for multiple taxa. We evaluated whether species distribution models could reliably rank changes in species range size under climate and land use change.LocationConterminous U.S.A.Time period1977–2014.Major taxa studiedPasserine birds.MethodsWe estimated ensembles of species distribution models based on historical North American Breeding Bird Survey occurrences for 190 songbirds, and generated predictions to recent years given c. 35 years of observed land use and climate change. We evaluated model predictions using standard metrics of discrimination performance and a more detailed assessment of the ability of models to rank species vulnerability to climate change based on predicted range loss, range gain, and overall change in range size.ResultsSpecies distribution models yielded unreliable and misleading assessments of relative vulnerability to climate and land use change. Models could not accurately predict range expansion or contraction, and therefore failed to anticipate patterns of range change among species. These failures occurred despite excellent overall discrimination ability and transferability to the validation time period, which reflected strong performance at the majority of locations that were either always or never occupied by each species.Main conclusionsModels failed for the questions and at the locations of greatest interest to conservation and management. This highlights potential pitfalls of multi-taxa impact assessments under global change; in our case, models provided misleading rankings of the most impacted species, and spatial information about range changes was not credible. As modelling methods and frameworks continue to be refined, performance assessments and validation efforts should focus on the measures of risk and vulnerability useful for decision-making.

A climate-driven mechanistic population model of Aedes albopictus with diapause.

PubMed

Jia, Pengfei; Lu, Liang; Chen, Xiang; Chen, Jin; Guo, Li; Yu, Xiao; Liu, Qiyong

2016-03-24

The mosquito Aedes albopitus is a competent vector for the transmission of many blood-borne pathogens. An important factor that affects the mosquitoes' development and spreading is climate, such as temperature, precipitation and photoperiod. Existing climate-driven mechanistic models overlook the seasonal pattern of diapause, referred to as the survival strategy of mosquito eggs being dormant and unable to hatch under extreme weather. With respect to diapause, several issues remain unaddressed, including identifying the time when diapause eggs are laid and hatched under different climatic conditions, demarcating the thresholds of diapause and non-diapause periods, and considering the mortality rate of diapause eggs. Here we propose a generic climate-driven mechanistic population model of Ae. albopitus applicable to most Ae. albopictus-colonized areas. The new model is an improvement over the previous work by incorporating the diapause behaviors with many modifications to the stage-specific mechanism of the mosquitoes' life-cycle. monthly Container Index (CI) of Ae. albopitus collected in two Chinese cities, Guangzhou and Shanghai is used for model validation. The simulation results by the proposed model is validated with entomological field data by the Pearson correlation coefficient r (2) in Guangzhou (r (2) = 0.84) and in Shanghai (r (2) = 0.90). In addition, by consolidating the effect of diapause-related adjustments and temperature-related parameters in the model, the improvement is significant over the basic model. The model highlights the importance of considering diapause in simulating Ae. albopitus population. It also corroborates that temperature and photoperiod are significant in affecting the population dynamics of the mosquito. By refining the relationship between Ae. albopitus population and climatic factors, the model serves to establish a mechanistic relation to the growth and decline of the species. Understanding this relationship in a better way will benefit studying the transmission and the spatiotemporal distribution of mosquito-borne epidemics and eventually facilitating the early warning and control of the diseases.

Psychometric Principles in Measurement for Geoscience Education Research: A Climate Change Example

NASA Astrophysics Data System (ADS)

Libarkin, J. C.; Gold, A. U.; Harris, S. E.; McNeal, K.; Bowles, R.

2015-12-01

Understanding learning in geoscience classrooms requires that we use valid and reliable instruments aligned with intended learning outcomes. Nearly one hundred instruments assessing conceptual understanding in undergraduate science and engineering classrooms (often called concept inventories) have been published and are actively being used to investigate learning. The techniques used to develop these instruments vary widely, often with little attention to psychometric principles of measurement. This paper will discuss the importance of using psychometric principles to design, evaluate, and revise research instruments, with particular attention to the validity and reliability steps that must be undertaken to ensure that research instruments are providing meaningful measurement. An example from a climate change inventory developed by the authors will be used to exemplify the importance of validity and reliability, including the value of item response theory for instrument development. A 24-item instrument was developed based on published items, conceptions research, and instructor experience. Rasch analysis of over 1000 responses provided evidence for the removal of 5 items for misfit and one item for potential bias as measured via differential item functioning. The resulting 18-item instrument can be considered a valid and reliable measure based on pre- and post-implementation metrics. Consideration of the relationship between respondent demographics and concept inventory scores provides unique insight into the relationship between gender, religiosity, values and climate change understanding.

Evaluation of Computer Tools for Idea Generation and Team Formation in Project-Based Learning

ERIC Educational Resources Information Center

Ardaiz-Villanueva, Oscar; Nicuesa-Chacon, Xabier; Brene-Artazcoz, Oscar; Sanz de Acedo Lizarraga, Maria Luisa; Sanz de Acedo Baquedano, Maria Teresa

2011-01-01

The main objective of this research was to validate the effectiveness of Wikideas and Creativity Connector tools to stimulate the generation of ideas and originality by university students organized into groups according to their indexes of creativity and affinity. Another goal of the study was to evaluate the classroom climate created by these…

The Complexity of School Racial Climate: Reliability and Validity of a New Measure for Secondary Students

ERIC Educational Resources Information Center

Byrd, Christy M.

2017-01-01

Background: The conceptualization of the role of race and culture in students' experience of school has been limited. This study presents a more comprehensive and multidimensional framework than previously conceptualized and includes the two domains of (1) intergroup interactions (frequency of interaction, quality of interaction, equal status, and…

Non-Heterosexist Organizational Climate and Affirmative Counselor Behaviors: Validation of Instruments.

ERIC Educational Resources Information Center

Bieschke, Kathleen J.; Matthews, Connie R.

The research literature suggests that the mental health professionals serving lesbians, gay men, and bisexual people may not be prepared to adequately address the unique needs of the population. There is a need to study the factors that influence the degree to which therapists attitudes and behaviors are affirmative toward their gay, lesbian, and…

Assessing the Culture and Climate for Quality Improvement in the Work Environment. AIR 1994 Annual Forum Paper.

ERIC Educational Resources Information Center

Cameron, Kim; And Others

This study attempted to develop a reliable and valid instrument for assessing work environment and continuous quality improvement efforts in the non-academic sectors of colleges and universities particularly those institutions who have adopted Total Quality Management programs. A model of a work environment for continuous quality improvement was…

Draw-a-Person-in-the-Rain: Does Geographic Location Matter?

ERIC Educational Resources Information Center

Graves, Adam; Jones, Leslie; Kaplan, Frances F.

2013-01-01

This pilot study examines an aspect of construct validity of the Draw-a-Person-in-the-Rain (DAPR) assessment utilizing a sample ("N" = 58) of third-grade public school children from three geographic regions of the United States (Great Plains, Rocky Mountain, and Pacific Northwest) that differ in climate and frequency of precipitation. A…

Hydrological impacts of climate change on the Tejo and Guadiana Rivers

NASA Astrophysics Data System (ADS)

Kilsby, C. G.; Tellier, S. S.; Fowler, H. J.; Howels, T. R.

2007-05-01

A distributed daily rainfall runoff model is applied to the Tejo and Guadiana river basins in Spain and Portugal to simulate the effects of climate change on runoff production, river flows and water resource availability with results aggregated to the monthly level. The model is calibrated, validated and then used for a series of climate change impact assessments for the period 2070 2100. Future scenarios are derived from the HadRM3H regional climate model (RCM) using two techniques: firstly a bias-corrected RCM output, with monthly mean correction factors calculated from observed rainfall records; and, secondly, a circulation-pattern-based stochastic rainfall model. Major reductions in rainfall and streamflow are projected throughout the year; these results differ from those for previous studies where winter increases are projected. Despite uncertainties in the representation of heavily managed river systems, the projected impacts are serious and pose major threats to the maintenance of bipartite water treaties between Spain and Portugal and the supply of water to urban and rural regions of Portugal.

Military Equal Opportunity Climate Survey: Reliability, Construct Validity, and Preliminary Field Test

DTIC Science & Technology

1990-01-10

reason for the fairly low reliability of the fourth and fifth MEOCS factors), issues of sexism and more subtle forms of racism have come to the fore...psychological climate (for which the individual is the unit for theory ). One approach, described by Glick, would use the intraclass correlation from a...and outcome measures are forced to remain obscure. A major flaw in the measurement of organizational climate is the lack of theory which would serve

Screening and brief intervention for alcohol and other drug use in primary care: associations between organizational climate and practice.

PubMed

Cruvinel, Erica; Richter, Kimber P; Bastos, Ronaldo Rocha; Ronzani, Telmo Mota

2013-02-11

Numerous studies have demonstrated that positive organizational climates contribute to better work performance. Screening and brief intervention (SBI) for alcohol, tobacco, and other drug use has the potential to reach a broad population of hazardous drug users but has not yet been widely adopted in Brazil's health care system. We surveyed 149 primary health care professionals in 30 clinics in Brazil who were trained to conduct SBI among their patients. We prospectively measured how often they delivered SBI to evaluate the association between organizational climate and adoption/performance of SBI. Organizational climate was measured by the 2009 Organizational Climate Scale for Health Organizations, a scale validated in Brazil that assesses leadership, professional development, team spirit, relationship with the community, safety, strategy, and remuneration. Performance of SBI was measured prospectively by weekly assessments during the three months following training. We also assessed self-reported SBI and self-efficacy for performing SBI at three months post-training. We used inferential statistics to depict and test for the significance of associations. Teams with better organizational climates implemented SBI more frequently. Organizational climate factors most closely associated with SBI implementation included professional development and relationship with the community. The dimensions of leadership and remuneration were also significantly associated with SBI. Organizational climate may influence implementation of SBI and ultimately may affect the ability of organizations to identify and address drug use.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J. R.; Maslanik, J. A.

1988-01-01

The principal objectives of this project are: to develop suitable validation data sets to evaluate the effectiveness of the ISCCP operational algorithm for cloud retrieval in polar regions and to validate model simulations of polar cloud cover; to identify limitations of current procedures for varying atmospheric surface conditions, and to explore potential means to remedy them using textural classifiers: and to compare synoptic cloud data from a control run experiment of the Goddard Institute for Space Studies (GISS) climate model 2 with typical observed synoptic cloud patterns. Current investigations underway are listed and the progress made to date is summarized.

A Snapshot of Organizational Climate: Perceptions of Extension Faculty

ERIC Educational Resources Information Center

Tower, Leslie E.; Bowen, Elaine; Alkadry, Mohamad G.

2011-01-01

This article provides a snapshot of the perceptions of workplace climate of Extension faculty at a land-grant, research-high activity university, compared with the perceptions of non-Extension faculty at the same university. An online survey was conducted with a validated instrument. The response rate for university faculty was 44% (968); the…

Validation of non-stationary precipitation series for site-specific impact assessment: Comparison of two statistical downscaling techniques

USDA-ARS?s Scientific Manuscript database

The generation of realistic future precipitation scenarios is crucial for assessing their impacts on a range of environmental and socio-economic impact sectors. A scale mismatch exists, however, between the coarse spatial resolution at which global climate models (GCMs) output future climate scenari...

Strategies for Reforestation under Uncertain Future Climates: Guidelines for Alberta, Canada

PubMed Central

Gray, Laura K.; Hamann, Andreas

2011-01-01

Background Commercial forestry programs normally use locally collected seed for reforestation under the assumption that tree populations are optimally adapted to local environments. However, in western Canada this assumption is no longer valid because of climate trends that have occurred over the last several decades. The objective of this study is to show how we can arrive at reforestation recommendations with alternative species and genotypes that are viable under a majority of climate change scenarios. Methodology/Principal Findings In a case study for commercially important tree species of Alberta, we use an ecosystem-based bioclimate envelope modeling approach for western North America to project habitat for locally adapted populations of tree species using multi-model climate projections for the 2020s, 2050s and 2080s. We find that genotypes of species that are adapted to drier climatic conditions will be the preferred planting stock over much of the boreal forest that is commercially managed. Interestingly, no alternative species that are currently not present in Alberta can be recommended with any confidence. Finally, we observe large uncertainties in projections of suitable habitat that make reforestation planning beyond the 2050s difficult for most species. Conclusion/Significance More than 50,000 hectares of forests are commercially planted every year in Alberta. Choosing alternative planting stock, suitable for expected future climates, could therefore offer an effective climate change adaptation strategy at little additional cost. Habitat projections for locally adapted tree populations under observed climate change conform well to projections for the 2020s, which suggests that it is a safe strategy to change current reforestation practices and adapt to new climatic realities through assisted migration prescriptions. PMID:21853061

The essential interactions between understanding climate variability and climate change

NASA Astrophysics Data System (ADS)

Neelin, J. D.

2017-12-01

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

Impact of model development, calibration and validation decisions on hydrological simulations in West Lake Erie Basin

USDA-ARS?s Scientific Manuscript database

Watershed simulation models are used extensively to investigate hydrologic processes, landuse and climate change impacts, pollutant load assessments and best management practices (BMPs). Developing, calibrating and validating these models require a number of critical decisions that will influence t...

Beyond climate envelopes: effects of weather on regional population trends in butterflies.

PubMed

WallisDeVries, Michiel F; Baxter, Wendy; Van Vliet, Arnold J H

2011-10-01

Although the effects of climate change on biodiversity are increasingly evident by the shifts in species ranges across taxonomical groups, the underlying mechanisms affecting individual species are still poorly understood. The power of climate envelopes to predict future ranges has been seriously questioned in recent studies. Amongst others, an improved understanding of the effects of current weather on population trends is required. We analysed the relation between butterfly abundance and the weather experienced during the life cycle for successive years using data collected within the framework of the Dutch Butterfly Monitoring Scheme for 40 species over a 15-year period and corresponding climate data. Both average and extreme temperature and precipitation events were identified, and multiple regression was applied to explain annual changes in population indices. Significant weather effects were obtained for 39 species, with the most frequent effects associated with temperature. However, positive density-dependence suggested climatic independent trends in at least 12 species. Validation of the short-term predictions revealed a good potential for climate-based predictions of population trends in 20 species. Nevertheless, data from the warm and dry year of 2003 indicate that negative effects of climatic extremes are generally underestimated for habitat specialists in drought-susceptible habitats, whereas generalists remain unaffected. Further climatic warming is expected to influence the trends of 13 species, leading to an improvement for nine species, but a continued decline in the majority of species. Expectations from climate envelope models overestimate the positive effects of climate change in northwestern Europe. Our results underline the challenge to include population trends in predicting range shifts in response to climate change.

Gravity Waves Generated by Convection: A New Idealized Model Tool and Direct Validation with Satellite Observations

NASA Astrophysics Data System (ADS)

Alexander, M. Joan; Stephan, Claudia

2015-04-01

In climate models, gravity waves remain too poorly resolved to be directly modelled. Instead, simplified parameterizations are used to include gravity wave effects on model winds. A few climate models link some of the parameterized waves to convective sources, providing a mechanism for feedback between changes in convection and gravity wave-driven changes in circulation in the tropics and above high-latitude storms. These convective wave parameterizations are based on limited case studies with cloud-resolving models, but they are poorly constrained by observational validation, and tuning parameters have large uncertainties. Our new work distills results from complex, full-physics cloud-resolving model studies to essential variables for gravity wave generation. We use the Weather Research Forecast (WRF) model to study relationships between precipitation, latent heating/cooling and other cloud properties to the spectrum of gravity wave momentum flux above midlatitude storm systems. Results show the gravity wave spectrum is surprisingly insensitive to the representation of microphysics in WRF. This is good news for use of these models for gravity wave parameterization development since microphysical properties are a key uncertainty. We further use the full-physics cloud-resolving model as a tool to directly link observed precipitation variability to gravity wave generation. We show that waves in an idealized model forced with radar-observed precipitation can quantitatively reproduce instantaneous satellite-observed features of the gravity wave field above storms, which is a powerful validation of our understanding of waves generated by convection. The idealized model directly links observations of surface precipitation to observed waves in the stratosphere, and the simplicity of the model permits deep/large-area domains for studies of wave-mean flow interactions. This unique validated model tool permits quantitative studies of gravity wave driving of regional circulation and provides a new method for future development of realistic convective gravity wave parameterizations.

Assessment of the Impacts of Climate Change on Stream Discharge and Water Quality in an Arid, Urbanized Watershed

NASA Astrophysics Data System (ADS)

Ranatunga, T.; Tong, S.; Yang, J.

2011-12-01

Hydrologic and water quality models can provide a general framework to conceptualize and investigate the relationships between climate and water resources. Under a hot and dry climate, highly urbanized watersheds are more vulnerable to changes in climate, such as excess heat and drought. In this study, a comprehensive watershed model, Hydrological Simulation Program FORTRAN (HSPF), is used to assess the impacts of future climate change on the stream discharge and water quality in Las Vegas Wash in Nevada, the only surface water body that drains from the Las Vegas Valley (an area with rapid population growth and urbanization) to Lake Mead. In this presentation, the process of model building, calibration and validation, the generation of climate change scenarios, and the assessment of future climate change effects on stream hydrology and quality are demonstrated. The hydrologic and water quality model is developed based on the data from current national databases and existing major land use categories of the watershed. The model is calibrated for stream discharge, nutrients (nitrogen and phosphorus) and sediment yield. The climate change scenarios are derived from the outputs of the Global Climate Models (GCM) and Regional Climate Models (RCM) simulations, and from the recent assessment reports from the Intergovernmental Panel on Climate Change (IPCC). The Climate Assessment Tool from US EPA's BASINS is used to assess the effects of likely future climate scenarios on the water quantity and quality in Las Vegas Wash. Also the presentation discusses the consequences of these hydrologic changes, including the deficit supplies of clean water during peak seasons of water demand, increased eutrophication potentials, wetland deterioration, and impacts on wild life habitats.

Productivity in the barents sea--response to recent climate variability.

PubMed

Dalpadado, Padmini; Arrigo, Kevin R; Hjøllo, Solfrid S; Rey, Francisco; Ingvaldsen, Randi B; Sperfeld, Erik; van Dijken, Gert L; Stige, Leif C; Olsen, Are; Ottersen, Geir

2014-01-01

The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region.

Productivity in the Barents Sea - Response to Recent Climate Variability

PubMed Central

Dalpadado, Padmini; Arrigo, Kevin R.; Hjøllo, Solfrid S.; Rey, Francisco; Ingvaldsen, Randi B.; Sperfeld, Erik; van Dijken, Gert L.; Stige, Leif C.; Olsen, Are; Ottersen, Geir

2014-01-01

The temporal and spatial dynamics of primary and secondary biomass/production in the Barents Sea since the late 1990s are examined using remote sensing data, observations and a coupled physical-biological model. Field observations of mesozooplankton biomass, and chlorophyll a data from transects (different seasons) and large-scale surveys (autumn) were used for validation of the remote sensing products and modeling results. The validation showed that satellite data are well suited to study temporal and spatial dynamics of chlorophyll a in the Barents Sea and that the model is an essential tool for secondary production estimates. Temperature, open water area, chlorophyll a, and zooplankton biomass show large interannual variations in the Barents Sea. The climatic variability is strongest in the northern and eastern parts. The moderate increase in net primary production evident in this study is likely an ecosystem response to changes in climate during the same period. Increased open water area and duration of open water season, which are related to elevated temperatures, appear to be the key drivers of the changes in annual net primary production that has occurred in the northern and eastern areas of this ecosystem. The temporal and spatial variability in zooplankton biomass appears to be controlled largely by predation pressure. In the southeastern Barents Sea, statistically significant linkages were observed between chlorophyll a and zooplankton biomass, as well as between net primary production and fish biomass, indicating bottom-up trophic interactions in this region. PMID:24788513

MALIBU: A High Spatial Resolution Multi-Angle Imaging Unmanned Airborne System to Validate Satellite-derived BRDF/Albedo Products

NASA Astrophysics Data System (ADS)

Wang, Z.; Roman, M. O.; Pahlevan, N.; Stachura, M.; McCorkel, J.; Bland, G.; Schaaf, C.

2016-12-01

Albedo is a key climate forcing variable that governs the absorption of incoming solar radiation and its ultimate transfer to the atmosphere. Albedo contributes significant uncertainties in the simulation of climate changes; and as such, it is defined by the Global Climate Observing System (GCOS) as a terrestrial essential climate variable (ECV) required by global and regional climate and biogeochemical models. NASA's Goddard Space Flight Center's Multi AngLe Imaging Bidirectional Reflectance Distribution Function small-UAS (MALIBU) is part of a series of pathfinder missions to develop enhanced multi-angular remote sensing techniques using small Unmanned Aircraft Systems (sUAS). The MALIBU instrument package includes two multispectral imagers oriented at two different viewing geometries (i.e., port and starboard sides) capture vegetation optical properties and structural characteristics. This is achieved by analyzing the surface reflectance anisotropy signal (i.e., BRDF shape) obtained from the combination of surface reflectance from different view-illumination angles and spectral channels. Satellite measures of surface albedo from MODIS, VIIRS, and Landsat have been evaluated by comparison with spatially representative albedometer data from sparsely distributed flux towers at fixed heights. However, the mismatch between the footprint of ground measurements and the satellite footprint challenges efforts at validation, especially for heterogeneous landscapes. The BRDF (Bidirectional Reflectance Distribution Function) models of surface anisotropy have only been evaluated with airborne BRDF data over a very few locations. The MALIBU platform that acquires extremely high resolution sub-meter measures of surface anisotropy and surface albedo, can thus serve as an important source of reference data to enable global land product validation efforts, and resolve the errors and uncertainties in the various existing products generated by NASA and its national and international partners.

Benchmarking homogenization algorithms for monthly data

NASA Astrophysics Data System (ADS)

Venema, V. K. C.; Mestre, O.; Aguilar, E.; Auer, I.; Guijarro, J. A.; Domonkos, P.; Vertacnik, G.; Szentimrey, T.; Stepanek, P.; Zahradnicek, P.; Viarre, J.; Müller-Westermeier, G.; Lakatos, M.; Williams, C. N.; Menne, M. J.; Lindau, R.; Rasol, D.; Rustemeier, E.; Kolokythas, K.; Marinova, T.; Andresen, L.; Acquaotta, F.; Fratiannil, S.; Cheval, S.; Klancar, M.; Brunetti, M.; Gruber, C.; Prohom Duran, M.; Likso, T.; Esteban, P.; Brandsma, T.; Willett, K.

2013-09-01

The COST (European Cooperation in Science and Technology) Action ES0601: Advances in homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison and validation study for monthly homogenization algorithms. Time series of monthly temperature and precipitation were evaluated because of their importance for climate studies. The algorithms were validated against a realistic benchmark dataset. Participants provided 25 separate homogenized contributions as part of the blind study as well as 22 additional solutions submitted after the details of the imposed inhomogeneities were revealed. These homogenized datasets were assessed by a number of performance metrics including i) the centered root mean square error relative to the true homogeneous values at various averaging scales, ii) the error in linear trend estimates and iii) traditional contingency skill scores. The metrics were computed both using the individual station series as well as the network average regional series. The performance of the contributions depends significantly on the error metric considered. Although relative homogenization algorithms typically improve the homogeneity of temperature data, only the best ones improve precipitation data. Moreover, state-of-the-art relative homogenization algorithms developed to work with an inhomogeneous reference are shown to perform best. The study showed that currently automatic algorithms can perform as well as manual ones.

Quantifying climate feedbacks in polar regions.

PubMed

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

2018-05-15

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

Variability and Extremes of Precipitation in the Global Climate as Determined by the 25-Year GEWEX/GPCP Data Set

NASA Technical Reports Server (NTRS)

Adler, R. F.; Gu, G.; Curtis, S.; Huffman, G. J.; Bolvin, D. T.; Nelkin, E. J.

2005-01-01

The Global Precipitation Climatology Project (GPCP) 25-year precipitation data set is used to evaluate the variability and extremes on global and regional scales. The variability of precipitation year-to-year is evaluated in relation to the overall lack of a significant global trend and to climate events such as ENSO and volcanic eruptions. The validity of conclusions and limitations of the data set are checked by comparison with independent data sets (e.g., TRMM). The GPCP data set necessarily has a heterogeneous time series of input data sources, so part of the assessment described above is to test the initial results for potential influence by major data boundaries in the record. Regional trends, or inter-decadal changes, are also analyzed to determine validity and correlation with other long-term data sets related to the hydrological cycle (e.g., clouds and ocean surface fluxes). Statistics of extremes (both wet and dry) are analyzed at the monthly time scale for the 25 years. A preliminary result of increasing frequency of extreme monthly values will be a focus to determine validity. Daily values for an eight-year are also examined for variation in extremes and compared to the longer monthly-based study.

Predicting plant invasions under climate change: are species distribution models validated by field trials?

PubMed

Sheppard, Christine S; Burns, Bruce R; Stanley, Margaret C

2014-09-01

Climate change may facilitate alien species invasion into new areas, particularly for species from warm native ranges introduced into areas currently marginal for temperature. Although conclusions from modelling approaches and experimental studies are generally similar, combining the two approaches has rarely occurred. The aim of this study was to validate species distribution models by conducting field trials in sites of differing suitability as predicted by the models, thus increasing confidence in their ability to assess invasion risk. Three recently naturalized alien plants in New Zealand were used as study species (Archontophoenix cunninghamiana, Psidium guajava and Schefflera actinophylla): they originate from warm native ranges, are woody bird-dispersed species and of concern as potential weeds. Seedlings were grown in six sites across the country, differing both in climate and suitability (as predicted by the species distribution models). Seedling growth and survival were recorded over two summers and one or two winter seasons, and temperature and precipitation were monitored hourly at each site. Additionally, alien seedling performances were compared to those of closely related native species (Rhopalostylis sapida, Lophomyrtus bullata and Schefflera digitata). Furthermore, half of the seedlings were sprayed with pesticide, to investigate whether enemy release may influence performance. The results showed large differences in growth and survival of the alien species among the six sites. In the more suitable sites, performance was frequently higher compared to the native species. Leaf damage from invertebrate herbivory was low for both alien and native seedlings, with little evidence that the alien species should have an advantage over the native species because of enemy release. Correlations between performance in the field and predicted suitability of species distribution models were generally high. The projected increase in minimum temperature and reduced frosts with climate change may provide more suitable habitats and enable the spread of these species. © 2014 John Wiley & Sons Ltd.

Break and trend analysis of EUMETSAT Climate Data Records

NASA Astrophysics Data System (ADS)

Doutriaux-Boucher, Marie; Zeder, Joel; Lattanzio, Alessio; Khlystova, Iryna; Graw, Kathrin

2016-04-01

EUMETSAT reprocessed imagery acquired by the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on board Meteosat 8-9. The data covers the period from 2004 to 2012. Climate Data Records (CDRs) of atmospheric parameters such as Atmospheric Motion Vectors (AMV) as well as Clear and All Sky Radiances (CSR and ASR) have been generated. Such CDRs are mainly ingested by ECMWF to produce a reanalysis data. In addition, EUMETSAT produced a long CDR (1982-2004) of land surface albedo exploiting imagery acquired by the Meteosat Visible and Infrared Imager (MVIRI) on board Meteosat 2-7. Such CDR is key information in climate analysis and climate models. Extensive validation has been performed for the surface albedo record and a first validation of the winds and clear sky radiances have been done. All validation results demonstrated that the time series of all parameter appear homogeneous at first sight. Statistical science offers a variety of analyses methods that have been applied to further analyse the homogeneity of the CDRs. Many breakpoint analysis techniques depend on the comparison of two time series which incorporates the issue that both may have breakpoints. This paper will present a quantitative and statistical analysis of eventual breakpoints found in the MVIRI and SEVIRI CDRs that includes attribution of breakpoints to changes of instruments and other events in the data series compared. The value of different methods applied will be discussed with suggestions how to further develop this type of analysis for quality evaluation of CDRs.

Development and validation of a work stressor scale for Australian farming families.

PubMed

McShane, Connar J; Quirk, Frances; Swinbourne, Anne

2016-08-01

The aim of this research was to gain insight into the key stressors for Australian farming families. It is well established that the farming work environment consists of a number of unique stressors which arise from dependency on factors beyond an individual's control (e.g. climate conditions) as well as the overlap between work and family environments. Despite this, limited research has included family factors in the assessment of stress felt by farmers and their families. This research sought to develop a scale of stressors for farming families in an Australian sample. A survey design was used for validity and reliability studies. The validity study involved assessment of factor structure, concurrent validity and discriminant validity. The reliability study used a test-retest reliability design. Participants were recruited from across Australia (38% Queensland; 30% New South Wales) and multiple industries (43% beef; 27% broadacre cropping; 26% horticulture). The validity study involved 278 participants and the reliability study involved 53 participants. Development of a Farming Family Stressor scale. The generated Farming Family Stressor scale presented satisfactory levels of concurrent validity (e.g. r = .73 against the Farm Stress Survey total score), discriminant validity (e.g. r = -.42 to r = .53 against the Satisfaction with Life and Kessler-10 total scores, respectively), internal consistency (Cronbach's alpha >.90) and test-retest reliability (rho > .66). This research lends insight into the complexity of stressors for farming families and has implications for occupational health and mental health programs that seek to reduce stress and improve health outcomes for that group. © 2015 National Rural Health Alliance Inc.

A Bayesian Belief Network framework to predict SOC stock change: the Veneto region (Italy) case study

NASA Astrophysics Data System (ADS)

Dal Ferro, Nicola; Quinn, Claire Helen; Morari, Francesco

2017-04-01

A key challenge for soil scientists is predicting agricultural management scenarios that combine crop productions with high standards of environmental quality. In this context, reversing the soil organic carbon (SOC) decline in croplands is required for maintaining soil fertility and contributing to mitigate GHGs emissions. Bayesian belief networks (BBN) are probabilistic models able to accommodate uncertainty and variability in the predictions of the impacts of management and environmental changes. By linking multiple qualitative and quantitative variables in a cause-and-effect relationships, BBNs can be used as a decision support system at different spatial scales to find best management strategies in the agroecosystems. In this work we built a BBN to model SOC dynamics (0-30 cm layer) in the low-lying plain of Veneto region, north-eastern Italy, and define best practices leading to SOC accumulation and GHGs (CO2-equivalent) emissions reduction. Regional pedo-climatic, land use and management information were combined with experimental and modelled data on soil C dynamics as natural and anthropic key drivers affecting SOC stock change. Moreover, utility nodes were introduced to determine optimal decisions for mitigating GHGs emissions from croplands considering also three different IPCC climate scenarios. The network was finally validated with real field data in terms of SOC stock change. Results showed that the BBN was able to model real SOC stock changes, since validation slightly overestimated SOC reduction (+5%) at the expenses of its accumulation. At regional level, probability distributions showed 50% of SOC loss, while only 17% of accumulation. However, the greatest losses (34%) were associated with low reduction rates (100-500 kg C ha-1 y-1), followed by 33% of stabilized conditions (-100 < SOC < 100 kg ha-1 y-1). Land use management (especially tillage operations and soil cover) played a primary role to affect SOC stock change, while climate conditions were only slightly involved in C regulation within the 0-30 cm layer. The proposed BBN framework was flexible to perform both field-scale validation and regional-scale predictions. Moreover, BBN provided guidelines for improved land management strategies in a perspective of climate change scenarios, although further validation, including a broader set of experimental data, is needed to strengthen the outcomes across Veneto region.

Validation of a Climate-Data Record of the "Clear-Kky" Surface Temperature of the Greenland Ice Sheet

NASA Technical Reports Server (NTRS)

Hall, Dorothy K.; Box, Jason E.; Koenig, Lora S.; DiGirolamo, Nicolo E.; Comiso, Josefino C.; Shuman, Christopher A.

2011-01-01

Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented since 1981. We extended and refined this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. We developed a daily and monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using an ice-surface temperature (1ST) algorithm developed for use with MODIS data. Validation of this CDR is ongoing. MODIS Terra swath data are projected onto a polar stereographic grid at 6.25-km resolution to develop binary, gridded daily and mean-monthly 1ST maps. Each monthly map also has a color-coded image map that is available to download. Also included with the monthly maps is an accompanying map showing number of days in the month that were used to calculate the mean-monthly 1ST. This is important because no 1ST decision is made by the algorithm for cells that are considered cloudy by the internal cloud mask, so a sufficient number of days must be available to produce a mean 1ST for each grid cell. Validation of the CDR consists of several facets: 1) comparisons between ISTs and in-situ measurements; 2) comparisons between ISTs and AWS data; and 3) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+). Previous work shows that Terra MODIS ISTs are about 3 C lower than in-situ temperatures measured at Summit Camp, during the winter of 2008-09 under clear skies. In this work we begin to compare surface temperatures derived from AWS data with ISTs from the MODIS CDR. The Greenland Ice Sheet 1ST CDR will be useful for monitoring surface-temperature trends and can be used as input or for validation of climate models. The CDR can be extended into the future using MODIS Terra, Aqua and NPOESS Preparatory Project Visible Infrared Imager Radiometer Suite (VII RS) data.

Relationships among Safety Climate, Safety Behavior, and Safety Outcomes for Ethnic Minority Construction Workers

PubMed Central

Lyu, Sainan; Chan, Albert P. C.; Wong, Francis K. W.

2018-01-01

In many countries, it is common practice to attract and employ ethnic minority (EM) or migrant workers in the construction industry. This primarily occurs in order to alleviate the labor shortage caused by an aging workforce with a lack of new entrants. Statistics show that EM construction workers are more likely to have occupational fatal and nonfatal injuries than their local counterparts; however, the mechanism underlying accidents and injuries in this vulnerable population has been rarely examined. This study aims to investigate relationships among safety climate, safety behavior, and safety outcomes for EM construction workers. To this end, a theoretical research model was developed based on a comprehensive review of the current literature. In total, 289 valid questionnaires were collected face-to-face from 223 Nepalese construction workers and 56 Pakistani construction workers working on 15 construction sites in Hong Kong. Structural equation modelling was employed to validate the constructs and test the hypothesized model. Results show that there were significant positive relationships between safety climate and safety behaviors, and significant negative relationships between safety behaviors and safety outcomes for EM construction workers. This research contributes to the literature regarding EM workers by providing empirical evidence of the mechanisms by which safety climate affects safety behaviors and outcomes. It also provides insights in order to help the key stakeholders formulate safety strategies for EM workers in many areas where numerous EM workers are employed, such as in the U.S., the UK, Australia, Singapore, Malaysia, and the Middle East. PMID:29522503

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

NASA Technical Reports Server (NTRS)

Hewitson, Bruce

1994-01-01

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

Validation of the Regional Climate Model ALARO with different dynamical downscaling approaches and different horizontal resolutions

NASA Astrophysics Data System (ADS)

Berckmans, Julie; Hamdi, Rafiq; De Troch, Rozemien; Giot, Olivier

2015-04-01

At the Royal Meteorological Institute of Belgium (RMI), climate simulations are performed with the regional climate model (RCM) ALARO, a version of the ALADIN model with improved physical parameterizations. In order to obtain high-resolution information of the regional climate, lateral bounary conditions (LBC) are prescribed from the global climate model (GCM) ARPEGE. Dynamical downscaling is commonly done in a continuous long-term simulation, with the initialisation of the model at the start and driven by the regularly updated LBCs of the GCM. Recently, more interest exists in the dynamical downscaling approach of frequent reinitializations of the climate simulations. For these experiments, the model is initialised daily and driven for 24 hours by the GCM. However, the surface is either initialised daily together with the atmosphere or free to evolve continuously. The surface scheme implemented in ALARO is SURFEX, which can be either run in coupled mode or in stand-alone mode. The regional climate is simulated on different domains, on a 20km horizontal resolution over Western-Europe and a 4km horizontal resolution over Belgium. Besides, SURFEX allows to perform a stand-alone or offline simulation on 1km horizontal resolution over Belgium. This research is in the framework of the project MASC: "Modelling and Assessing Surface Change Impacts on Belgian and Western European Climate", a 4-year project funded by the Belgian Federal Government. The overall aim of the project is to study the feedbacks between climate changes and land surface changes in order to improve regional climate model projections at the decennial scale over Belgium and Western Europe and thus to provide better climate projections and climate change evaluation tools to policy makers, stakeholders and the scientific community.

Assessing the physical service setting: a look at emergency departments.

PubMed

Steinke, Claudia

2015-01-01

To determine the attributes of the physical setting that are important for developing a positive service climate within emergency departments and to validate a measure for assessing physical service design. The design of the physical setting is an important and contributing factor for creating a service climate in organizations. Service climate is defined as employee perceptions of the practices, procedures, and behaviors that get rewarded, supported, and expected with regard to customer service and customer service quality. There has been research conducted which identifies antecedents within organization that promotes a positive service climate which in turn creates service-oriented behaviors by employees toward clients. The antecedent of the physical setting and its impact on perceptions of service climate has been less commonly explored. Using the concept of the physical service setting (which may be defined as aspects of the physical, built environment that facilitate the delivery of quality service), attributes of the physical setting and their relationship with service climate were explored by means of a quantitative paper survey distributed to emergency nurses (n = 180) throughout a province in Canada. The results highlight the validity and reliability of six scales measuring the physical setting and its relation to service. Respondents gave low ratings to the physical setting of their departments, in addition to low ratings of service climate. Respondents feel that the design of the physical setting in the emergency departments where they work is not conducive to providing quality service to clients. Certain attributes of the physical setting were found to be significant in influencing perceptions of service climate, hence service quality, within the emergency department setting. © The Author(s) 2015.

weather@home 2: validation of an improved global-regional climate modelling system

NASA Astrophysics Data System (ADS)

Guillod, Benoit P.; Jones, Richard G.; Bowery, Andy; Haustein, Karsten; Massey, Neil R.; Mitchell, Daniel M.; Otto, Friederike E. L.; Sparrow, Sarah N.; Uhe, Peter; Wallom, David C. H.; Wilson, Simon; Allen, Myles R.

2017-05-01

Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.

Validation and application of a forest gap model to the southern Rocky Mountains

Treesearch

Adrianna C. Foster; Jacquelyn K. Shuman; Herman H. Shugart; Kathleen A. Dwire; Paula J. Fornwalt; Jason Sibold; Jose Negron

2017-01-01

Rocky Mountain forests are highly important for their part in carbon cycling and carbon storage as well as ecosystem services such as water retention and storage and recreational values. These forests are shaped by complex interactions among vegetation, climate, and disturbances. Thus, climate change and shifting disturbances may lead to significant changes in species...

Estimation and Validation of Oceanic Mass Circulation from the GRACE Mission

NASA Technical Reports Server (NTRS)

Boy, J.-P.; Rowlands, D. D.; Sabaka, T. J.; Luthcke, S. B.; Lemoine, F. G.

2011-01-01

Since the launch of the Gravity Recovery And Climate Experiment (GRACE) in March 2002, the Earth's surface mass variations have been monitored with unprecedented accuracy and resolution. Compared to the classical spherical harmonic solutions, global high-resolution mascon solutions allows the retrieval of mass variations with higher spatial and temporal sampling (2 degrees and 10 days). We present here the validation of the GRACE global mascon solutions by comparing mass estimates to a set of about 100 ocean bottom pressure (OSP) records, and show that the forward modelling of continental hydrology prior to the inversion of the K-band range rate data allows better estimates of ocean mass variations. We also validate our GRACE results to OSP variations modelled by different state-of-the-art ocean general circulation models, including ECCO (Estimating the Circulation and Climate of the Ocean) and operational and reanalysis from the MERCATOR project.

Response to Comment on "Water harvesting from air with metal-organic frameworks powered by natural sunlight".

PubMed

Kim, Hyunho; Rao, Sameer R; Kapustin, Eugene A; Narayanan, Shankar; Yang, Sungwoo; Furukawa, Hiroyasu; Umans, Ari S; Yaghi, Omar M; Wang, Evelyn N

2017-11-24

The Comment by Meunier states that the process we described in our report cannot deliver the claimed amount of liquid water in an arid climate. This statement is not valid because the parameters presented in our study were inappropriately combined to draw misguided conclusions. Copyright © 2017, American Association for the Advancement of Science.

Analyzing the water budget and hydrological characteristics and responses to land use in a monsoonal climate river basin in South China

USGS Publications Warehouse

Wu, Yiping; Chen, Ji

2013-01-01

Hydrological models have been increasingly used by hydrologists and water resource managers to understand natural processes and human activities that affect watersheds. In this study, we use the physically based model, Soil and Water Assessment Tool (SWAT), to investigate the hydrological processes in the East River Basin in South China, a coastal area dominated by monsoonal climate. The SWAT model was calibrated using 8-year (1973–1980) record of the daily streamflow at the basin outlet (Boluo station), and then validated using data collected during the subsequent 8 years (1981–1988). Statistical evaluation shows that SWAT can consistently simulate the streamflow of the East River with monthly Nash–Sutcliffe efficiencies of 0.93 for calibration and 0.90 for validation at the Boluo station. We analyzed the model simulations with calibrated parameters, presented the spatiotemporal distribution of the key hydrological components, and quantified their responses to different land uses. Watershed managers can use the results of this study to understand hydrological features and evaluate water resources of the East River in terms of sustainable development and effective management.

A generalized land-use scenario generator: a case study for the Congo basin.

NASA Astrophysics Data System (ADS)

Caporaso, Luca; Tompkins, Adrian Mark; Biondi, Riccardo; Bell, Jean Pierre

2014-05-01

The impact of deforestation on climate is often studied using highly idealized "instant deforestation" experiments due to the lack of generalized deforestation scenario generators coupled to climate model land-surface schemes. A new deforestation scenario generator has been therefore developed to fulfill this role known as the deforestation ScenArio GEnerator, or FOREST-SAGE. The model produces distributed maps of deforestation rates that account for local factors such as proximity to transport networks, distance weighted population density, forest fragmentation and presence of protected areas and logging concessions. The integrated deforestation risk is scaled to give the deforestation rate as specified by macro-region scenarios such as "business as usual" or "increased protection legislation" which are a function of future time. FOREST-SAGE was initialized and validated using the MODerate Resolution Imaging Spectroradiometer Vegetation Continuous Field data. Despite the high cloud coverage of Congo Basin over the year, we were able to validate the results with high confidence from 2001 to 2010 in a large forested area. Furthermore a set of scenarios has been used to provide a range of possible pathways for the evolution of land-use change over the Congo Basin for the period 2010-2030.

Quality assessment of the Ozone_cci Climate Research Data Package (release 2017) - Part 1: Ground-based validation of total ozone column data products

NASA Astrophysics Data System (ADS)

Garane, Katerina; Lerot, Christophe; Coldewey-Egbers, Melanie; Verhoelst, Tijl; Elissavet Koukouli, Maria; Zyrichidou, Irene; Balis, Dimitris S.; Danckaert, Thomas; Goutail, Florence; Granville, Jose; Hubert, Daan; Keppens, Arno; Lambert, Jean-Christopher; Loyola, Diego; Pommereau, Jean-Pierre; Van Roozendael, Michel; Zehner, Claus

2018-03-01

The GOME-type Total Ozone Essential Climate Variable (GTO-ECV) is a level-3 data record, which combines individual sensor products into one single cohesive record covering the 22-year period from 1995 to 2016, generated in the frame of the European Space Agency's Climate Change Initiative Phase II. It is based on level-2 total ozone data produced by the GODFIT (GOME-type Direct FITting) v4 algorithm as applied to the GOME/ERS-2, OMI/Aura, SCIAMACHY/Envisat and GOME-2/Metop-A and Metop-B observations. In this paper we examine whether GTO-ECV meets the specific requirements set by the international climate-chemistry modelling community for decadal stability long-term and short-term accuracy. In the following, we present the validation of the 2017 release of the Climate Research Data Package Total Ozone Column (CRDP TOC) at both level 2 and level 3. The inter-sensor consistency of the individual level-2 data sets has mean differences generally within 0.5 % at moderate latitudes (±50°), whereas the level-3 data sets show mean differences with respect to the OMI reference data record that span between -0.2 ± 0.9 % (for GOME-2B) and 1.0 ± 1.4 % (for SCIAMACHY). Very similar findings are reported for the level-2 validation against independent ground-based TOC observations reported by Brewer, Dobson and SAOZ instruments: the mean bias between GODFIT v4 satellite TOC and the ground instrument is well within 1.0 ± 1.0 % for all sensors, the drift per decade spans between -0.5 % and 1.0 ± 1.0 % depending on the sensor, and the peak-to-peak seasonality of the differences ranges from ˜ 1 % for GOME and OMI to ˜ 2 % for SCIAMACHY. For the level-3 validation, our first goal was to show that the level-3 CRDP produces findings consistent with the level-2 individual sensor comparisons. We show a very good agreement with 0.5 to 2 % peak-to-peak amplitude for the monthly mean difference time series and a negligible drift per decade of the differences in the Northern Hemisphere of -0.11 ± 0.10 % decade-1 for Dobson and +0.22 ± 0.08 % decade-1 for Brewer collocations. The exceptional quality of the level-3 GTO-ECV v3 TOC record temporal stability satisfies well the requirements for the total ozone measurement decadal stability of 1-3 % and the short-term and long-term accuracy requirements of 2 and 3 %, respectively, showing a remarkable inter-sensor consistency, both in the level-2 GODFIT v4 and in the level-3 GTO-ECV v3 datasets, and thus can be used for longer-term analysis of the ozone layer, such as decadal trend studies, chemistry-climate model evaluation and data assimilation applications.

The new WegenerNet climate station network web portal - A gateway to over 10 years of high-resolution precipitation data

NASA Astrophysics Data System (ADS)

Fuchsberger, Jürgen; Kirchengast, Gottfried; Bichler, Christoph; Kabas, Thomas; Lenz, Gunther; Leuprecht, Armin

2017-04-01

The Feldbach region in southeast Austria, characteristic for experiencing a rich variety of weather and climate patterns, has been selected as the focus area for a pioneering weather and climate observation network at very high resolution: The WegenerNet comprises 153 meteorological stations measuring temperature, humidity, precipitation, and other parameters, in a tightly spaced grid within an area of about 20 km × 15 km centered near the city of Feldbach (46.93°N, 15.90°E). With its stations about every 2 km2, each with 5-min time sampling, the network provides regular measurements since January 2007. Detailed information is available in the recent description by Kirchengast et al. (2014) and via www.wegcenter.at/wegenernet. As a smaller "sister network" of the WegenerNet Feldbach region, the WegenerNet Johnsbachtal consists of eleven meteorological stations (complemented by one hydrographic station at the Johnsbach creek), measuring temperature, humidity, precipitation, radiation, wind, and other parameters in an alpine setting at altitudes ranging from below 700 m to over 2100 m. Data are available partly since 2007, partly since more recent dates and have a temporal resolution of 10 minutes. The networks are set to serve as a long-term monitoring and validation facility for weather and climate research and applications. Uses include validation of nonhydrostatic models operated at 1-km-scale resolution and of statistical downscaling techniques (in particular for precipitation), validation of radar and satellite data, study of orography-climate relationships, and many others. Quality-controlled station time series and gridded field data (spacing 200 m × 200 m) are available in near-real time (data latency less than 1-2 h) for visualization and download via a data portal (www.wegenernet.org). This data portal has been undergoing a complete renewal over the last year, and now serves as a modern gateway to the WegenerNet's more than 10 years of high-resolution data. The poster gives a brief introduction to the WegenerNet design and setup and shows a detailed overview of the new data portal. It also focuses on showing examples for high-resolution precipitation measurements, especially heavy-precipitation and convective events. Reference: Kirchengast, G., T. Kabas, A. Leuprecht, C. Bichler, and H. Truhetz (2014): WegenerNet: A pioneering high-resolution network for monitoring weather and climate. Bull. Amer. Meteor. Soc., 95, 227-242, doi:10.1175/BAMS-D-11-00161.1.

Changing Permafrost in the Arctic and its Global Effects in the 21st Century (PAGE21): A very large international and integrated project to measure the impact of permafrost degradation on the climate system

NASA Astrophysics Data System (ADS)

Lantuit, Hugues; Boike, Julia; Dahms, Melanie; Hubberten, Hans-Wolfgang

2013-04-01

The northern permafrost region contains approximately 50% of the estimated global below-ground organic carbon pool and more than twice as much as is contained in the current atmos-pheric carbon pool. The sheer size of this carbon pool, together with the large amplitude of predicted arctic climate change im-plies that there is a high potential for global-scale feedbacks from arctic climate change if these carbon reservoirs are desta-bilized. Nonetheless, significant gaps exist in our current state of knowledge that prevent us from producing accurate assess-ments of the vulnerability of the arctic permafrost to climate change, or of the implications of future climate change for global greenhouse gas (GHG) emissions. Specifically: • Our understanding of the physical and biogeochemical processes at play in permafrost areas is still insuffi-cient in some key aspects • Size estimates for the high latitude continental carbon and nitrogen stocks vary widely between regions and research groups. • The representation of permafrost-related processes in global climate models still tends to be rudimentary, and is one reason for the frequently poor perform-ances of climate models at high latitudes. The key objectives of PAGE21 are: • to improve our understanding of the processes affect-ing the size of the arctic permafrost carbon and nitro-gen pools through detailed field studies and monitor-ing, in order to quantify their size and their vulnerability to climate change, • to produce, assemble and assess high-quality datasets in order to develop and evaluate representations of permafrost and related processes in global models, • to improve these models accordingly, • to use these models to reduce the uncertainties in feed-backs from arctic permafrost to global change, thereby providing the means to assess the feasibility of stabili-zation scenarios, and • to ensure widespread dissemination of our results in order to provide direct input into the ongoing debate on climate-change mitigation. The concept of PAGE21 is to directly address these questions through a close interaction between monitoring activities, proc-ess studies and modeling on the pertinent temporal and spatial scales. Field sites have been selected to cover a wide range of environmental conditions for the validation of large scale mod-els, the development of permafrost monitoring capabilities, the study of permafrost processes, and for overlap with existing monitoring programs. PAGE21 will contribute to upgrading the project sites with the objective of providing a measurement baseline, both for process studies and for modeling programs. PAGE21 is determined to break down the traditional barriers in permafrost sciences between observational and model-supported site studies and large-scale climate modeling. Our concept for the interaction between site-scale studies and large-scale modeling is to establish and maintain a direct link be-tween these two areas for developing and evaluating, on all spatial scales, the land-surface modules of leading European global climate models taking part in the Coupled Model Inter-comparison Project Phase 5 (CMIP5), designed to inform the IPCC process. The timing of this project is such that the main scientific results from PAGE21, and in particular the model-based assessments will build entirely on new outputs and results from the CMIP5 Climate Model Intercomparison Project designed to inform the IPCC Fifth Assessment Report. However, PAGE21 is designed to leave a legacy that will en-dure beyond the lifetime of the projections that it produces. This legacy will comprise • an improved understanding of the key processes and parameters that determine the vulnerability of arctic permafrost to climate change, • the production of a suite of major European coupled climate models including detailed and validated repre-sentations of permafrost-related processes, that will reduce uncertainties in future climate projections pro-duced well beyond the lifetime of PAGE21, and • the training of a new generation of permafrost scien-tists who will bridge the long-standing gap between permafrost field science and global climate modeling, for the long-term benefit of science and society.

A Computing Infrastructure for Supporting Climate Studies

NASA Astrophysics Data System (ADS)

Yang, C.; Bambacus, M.; Freeman, S. M.; Huang, Q.; Li, J.; Sun, M.; Xu, C.; Wojcik, G. S.; Cahalan, R. F.; NASA Climate @ Home Project Team

2011-12-01

Climate change is one of the major challenges facing us on the Earth planet in the 21st century. Scientists build many models to simulate the past and predict the climate change for the next decades or century. Most of the models are at a low resolution with some targeting high resolution in linkage to practical climate change preparedness. To calibrate and validate the models, millions of model runs are needed to find the best simulation and configuration. This paper introduces the NASA effort on Climate@Home project to build a supercomputer based-on advanced computing technologies, such as cloud computing, grid computing, and others. Climate@Home computing infrastructure includes several aspects: 1) a cloud computing platform is utilized to manage the potential spike access to the centralized components, such as grid computing server for dispatching and collecting models runs results; 2) a grid computing engine is developed based on MapReduce to dispatch models, model configuration, and collect simulation results and contributing statistics; 3) a portal serves as the entry point for the project to provide the management, sharing, and data exploration for end users; 4) scientists can access customized tools to configure model runs and visualize model results; 5) the public can access twitter and facebook to get the latest about the project. This paper will introduce the latest progress of the project and demonstrate the operational system during the AGU fall meeting. It will also discuss how this technology can become a trailblazer for other climate studies and relevant sciences. It will share how the challenges in computation and software integration were solved.

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

DOE PAGES

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

2016-09-12

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

Multilevel Factor Structure and Concurrent Validity of the Teacher Version of the Authoritative School Climate Survey.

PubMed

Huang, Francis L; Cornell, Dewey G; Konold, Timothy; Meyer, Joseph P; Lacey, Anna; Nekvasil, Erin K; Heilbrun, Anna; Shukla, Kathan D

2015-12-01

School climate is well recognized as an important influence on student behavior and adjustment to school, but there is a need for theory-guided measures that make use of teacher perspectives. Authoritative school climate theory hypothesizes that a positive school climate is characterized by high levels of disciplinary structure and student support. A teacher version of the Authoritative School Climate Survey (ASCS) was administered to a statewide sample of 9099 7th- and 8th-grade teachers from 366 schools. The study used exploratory and multilevel confirmatory factor analyses (MCFA) that accounted for the nested data structure and allowed for the modeling of the factor structures at 2 levels. Multilevel confirmatory factor analyses conducted on both an exploratory (N = 4422) and a confirmatory sample (N = 4677) showed good support for the factor structures investigated. Factor correlations at 2 levels indicated that schools with greater levels of disciplinary structure and student support had higher student engagement, less teasing and bullying, and lower student aggression toward teachers. The teacher version of the ASCS can be used to assess 2 key domains of school climate and associated measures of student engagement and aggression toward peers and teachers. © 2015, American School Health Association.

Detection and Attribution of Regional Climate Change

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

Bala, G; Mirin, A

2007-01-19

We developed a high resolution global coupled modeling capability to perform breakthrough studies of the regional climate change. The atmospheric component in our simulation uses a 1{sup o} latitude x 1.25{sup o} longitude grid which is the finest resolution ever used for the NCAR coupled climate model CCSM3. Substantial testing and slight retuning was required to get an acceptable control simulation. The major accomplishment is the validation of this new high resolution configuration of CCSM3. There are major improvements in our simulation of the surface wind stress and sea ice thickness distribution in the Arctic. Surface wind stress and oceanmore » circulation in the Antarctic Circumpolar Current are also improved. Our results demonstrate that the FV version of the CCSM coupled model is a state of the art climate model whose simulation capabilities are in the class of those used for IPCC assessments. We have also provided 1000 years of model data to Scripps Institution of Oceanography to estimate the natural variability of stream flow in California. In the future, our global model simulations will provide boundary data to high-resolution mesoscale model that will be used at LLNL. The mesoscale model would dynamically downscale the GCM climate to regional scale on climate time scales.« less

Response of Vegetation Dynamics to Projected Climate Change based on NDVI Simulations using Stepwise Cluster Analysis in the Three-River Headwaters Region of China

NASA Astrophysics Data System (ADS)

Zheng, Y.; Lv, E.; Huang, Y.

2016-12-01

Located in the hinterland of the Qinghai-Tibetan Plateau, the Three-River Headwaters region (THR) features unique eco-environmental conditions and fragile ecosystems, and is very vulnerable to climate change. To investigate the effects of climate change on the ecosystem, the Normalized Difference Vegetation Index (NDVI) was employed as an indicator to reflect the vegetation dynamics in response to climate change. This study proposed a model based on Stepwise-cluster analysis to predict the temporal and spatial distributions of NDVI values for five future years according to Global Circulation Models (GCMs) climate projections under the RCP4.5 scenario. The obtained spatial results showed very good agreements between simulations and remote sensing observations of the NDVI value for both training and validation, and the developed model demonstrated its capability of predicting the monthly changes of NDVI through representing the relationships between it and various climatic factors, including remote sensed precipitation and temperature with no, 1 and 2-month lag period. The monthly average precipitation with one-month lag period was further found to be the most important climatic factor that drives the changes of NDVI in the THR. Compared with the values of NDVI in 2000 - 2013, the predicting results indicate the values of NDVI for the THR in growing season (May to October) will decrease by 15.74% in the next 100 years, suggesting that the THR is going to experience an environmental degradation. The results also show that precipitation is the primary driving factor relative to temperature, especially the one-month-lag precipitation. Findings from this study would help policy makers draw up effective water resource and eco-environmental management strategies for adapting to climate change in the THR.

Climatic extremes improve predictions of spatial patterns of tree species

USGS Publications Warehouse

Zimmermann, N.E.; Yoccoz, N.G.; Edwards, T.C.; Meier, E.S.; Thuiller, W.; Guisan, Antoine; Schmatz, D.R.; Pearman, P.B.

2009-01-01

Understanding niche evolution, dynamics, and the response of species to climate change requires knowledge of the determinants of the environmental niche and species range limits. Mean values of climatic variables are often used in such analyses. In contrast, the increasing frequency of climate extremes suggests the importance of understanding their additional influence on range limits. Here, we assess how measures representing climate extremes (i.e., interannual variability in climate parameters) explain and predict spatial patterns of 11 tree species in Switzerland. We find clear, although comparably small, improvement (+20% in adjusted D2, +8% and +3% in cross-validated True Skill Statistic and area under the receiver operating characteristics curve values) in models that use measures of extremes in addition to means. The primary effect of including information on climate extremes is a correction of local overprediction and underprediction. Our results demonstrate that measures of climate extremes are important for understanding the climatic limits of tree species and assessing species niche characteristics. The inclusion of climate variability likely will improve models of species range limits under future conditions, where changes in mean climate and increased variability are expected.

Developing Present-day Proxy Cases Based on NARVAL Data for Investigating Low Level Cloud Responses to Future Climate Change.

NASA Astrophysics Data System (ADS)

Reilly, Stephanie

2017-04-01

The energy budget of the entire global climate is significantly influenced by the presence of boundary layer clouds. The main aim of the High Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) project is to improve climate model predictions by means of process studies of clouds and precipitation. This study makes use of observed elevated moisture layers as a proxy of future changes in tropospheric humidity. The associated impact on radiative transfer triggers fast responses in boundary layer clouds, providing a framework for investigating this phenomenon. The investigation will be carried out using data gathered during the Next-generation Aircraft Remote-sensing for VALidation (NARVAL) South campaigns. Observational data will be combined with ECMWF reanalysis data to derive the large scale forcings for the Large Eddy Simulations (LES). Simulations will be generated for a range of elevated moisture layers, spanning a multi-dimensional phase space in depth, amplitude, elevation, and cloudiness. The NARVAL locations will function as anchor-points. The results of the large eddy simulations and the observations will be studied and compared in an attempt to determine how simulated boundary layer clouds react to changes in radiative transfer from the free troposphere. Preliminary LES results will be presented and discussed.

Testing the effects of safety climate and disruptive children behavior on school bus drivers performance: A multilevel model.

PubMed

Zohar, Dov; Lee, Jin

2016-10-01

The study was designed to test a multilevel path model whose variables exert opposing effects on school bus drivers' performance. Whereas departmental safety climate was expected to improve driving safety, the opposite was true for in-vehicle disruptive children behavior. The driving safety path in this model consists of increasing risk-taking practices starting with safety shortcuts leading to rule violations and to near-miss events. The study used a sample of 474 school bus drivers in rural areas, driving children to school and school-related activities. Newly developed scales for measuring predictor, mediator and outcome variables were validated with video data taken from inner and outer cameras, which were installed in 29 buses. Results partially supported the model by indicating that group-level safety climate and individual-level children distraction exerted opposite effects on the driving safety path. Furthermore, as hypothesized, children disruption moderated the strength of the safety rule violation-near miss relationship, resulting in greater strength under high disruptiveness. At the same time, the hypothesized interaction between the two predictor variables was not supported. Theoretical and practical implications for studying safety climate in general and distracted driving in particular for professional drivers are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simulation of Drought-induced Tree Mortality Using a New Individual and Hydraulic Trait-based Model (S-TEDy)

NASA Astrophysics Data System (ADS)

Sinha, T.; Gangodagamage, C.; Ale, S.; Frazier, A. G.; Giambelluca, T. W.; Kumagai, T.; Nakai, T.; Sato, H.

2017-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

A Multiscale Simulation Framework to Investigate Hydrobiogeochemical Processes in the Groundwater-Surface Water Interaction Zone

NASA Astrophysics Data System (ADS)

Scheibe, T. D.; Yang, X.; Song, X.; Chen, X.; Hammond, G. E.; Song, H. S.; Hou, Z.; Murray, C. J.; Tartakovsky, A. M.; Tartakovsky, G.; Yang, X.; Zachara, J. M.

2016-12-01

Drought-related tree mortality at a regional scale causes drastic shifts in carbon and water cycling in Southeast Asian tropical rainforests, where severe droughts are projected to occur more frequently, especially under El Niño conditions. To provide a useful tool for projecting the tropical rainforest dynamics under climate change conditions, we developed the Spatially Explicit Individual-Based (SEIB) Dynamic Global Vegetation Model (DGVM) applicable to simulating mechanistic tree mortality induced by the climatic impacts via individual-tree-scale ecophysiology such as hydraulic failure and carbon starvation. In this study, we present the new model, SEIB-originated Terrestrial Ecosystem Dynamics (S-TEDy) model, and the computation results were compared with observations collected at a field site in a Bornean tropical rainforest. Furthermore, after validating the model's performance, numerical experiments addressing a future of the tropical rainforest were conducted using some global climate model (GCM) simulation outputs.

How school can teach civic engagement besides civic education: The role of democratic school climate.

PubMed

Lenzi, Michela; Vieno, Alessio; Sharkey, Jill; Mayworm, Ashley; Scacchi, Luca; Pastore, Massimiliano; Santinello, Massimo

2014-12-01

Civic engagement, defined as involvement in community life, is influenced by reciprocal relationships between individuals and contexts and is a key factor that contributes to positive youth development. The present study evaluates a theoretical model linking perceived democratic school climate with adolescent civic engagement (operationalized as civic responsibility and intentions for future participation), taking into account the mediating role of civic discussions and perceived fairness at school. Participants were 403 adolescents (47.9 % male) ranging in age from 11 to 15 years old (mean age = 13.6). Path analysis results partially validated the proposed theoretical model. Higher levels of democratic school climate were associated with higher levels of adolescent civic responsibility; the association was fully mediated by civic discussions and perceived fairness at school. Adolescents' civic responsibility, then, was positively associated with a stronger intention to participate in the civic domain in the future.

Performance analysis of the lineal model for estimating the maximum power of a HCPV module in different climate conditions

NASA Astrophysics Data System (ADS)

Fernández, Eduardo F.; Almonacid, Florencia; Sarmah, Nabin; Mallick, Tapas; Sanchez, Iñigo; Cuadra, Juan M.; Soria-Moya, Alberto; Pérez-Higueras, Pedro

2014-09-01

A model based on easily obtained atmospheric parameters and on a simple lineal mathematical expression has been developed at the Centre of Advanced Studies in Energy and Environment in southern Spain. The model predicts the maximum power of a HCPV module as a function of direct normal irradiance, air temperature and air mass. Presently, the proposed model has only been validated in southern Spain and its performance in locations with different atmospheric conditions still remains unknown. In order to address this issue, several HCPV modules have been measured in two different locations with different climate conditions than the south of Spain: the Environment and Sustainability Institute in southern UK and the National Renewable Energy Center in northern Spain. Results show that the model has an adequate match between actual and estimated data with a RMSE lower than 3.9% at locations with different climate conditions.

On modeling the paleohydrologic response of closed-basin lakes to fluctuations in climate: Methods, applications, and implications

NASA Astrophysics Data System (ADS)

Liu, Ganming; Schwartz, Franklin W.

2014-04-01

Climate reconstructions using tree rings and lake sediments have contributed significantly to the understanding of Holocene climates. Approaches focused specifically on reconstructing the temporal water-level response of lakes, however, are much less developed. This paper describes a statistical correlation approach based on time series with Palmer Drought Severity Index (PDSI) values derived from instrumental records or tree rings as a basis for reconstructing stage hydrographs for closed-basin lakes. We use a distributed lag correlation model to calculate a variable, ωt that represents the water level of a lake at any time t as a result of integrated climatic forcing from preceding years. The method was validated using both synthetic and measured lake-stage data and the study found that a lake's "memory" of climate fades as time passes, following an exponential-decay function at rates determined by the correlation time lag. Calculated trends in ωt for Moon Lake, Rice Lake, and Lake Mina from A.D. 1401 to 1860 compared well with the established chronologies (salinity, moisture, and Mg/Ca ratios) reconstructed from sediments. This method provides an independent approach for developing high-resolution information on lake behaviors in preinstrumental times and has been able to identify problems of climate signal deterioration in sediment-based climate reconstructions in lakes with a long time lag.

Reliability of regional climate simulations

NASA Astrophysics Data System (ADS)

Ahrens, W.; Block, A.; Böhm, U.; Hauffe, D.; Keuler, K.; Kücken, M.; Nocke, Th.

2003-04-01

Quantification of uncertainty becomes more and more a key issue for assessing the trustability of future climate scenarios. In addition to the mean conditions, climate impact modelers focus in particular on extremes. Before generating such scenarios using e.g. dynamic regional climate models, a careful validation of present-day simulations should be performed to determine the range of errors for the quantities of interest under recent conditions as a raw estimate of their uncertainty in the future. Often, multiple aspects shall be covered together, and the required simulation accuracy depends on the user's demand. In our approach, a massive parallel regional climate model shall be used on the one hand to generate "long-term" high-resolution climate scenarios for several decades, and on the other hand to provide very high-resolution ensemble simulations of future dry spells or heavy rainfall events. To diagnosis the model's performance for present-day simulations, we have recently developed and tested a first version of a validation and visualization chain for this model. It is, however, applicable in a much more general sense and could be used as a common test bed for any regional climate model aiming at this type of simulations. Depending on the user's interest, integrated quality measures can be derived for near-surface parameters using multivariate techniques and multidimensional distance measures in a first step. At this point, advanced visualization techniques have been developed and included to allow for visual data mining and to qualitatively identify dominating aspects and regularities. Univariate techniques that are especially designed to assess climatic aspects in terms of statistical properties can then be used to quantitatively diagnose the error contributions of the individual used parameters. Finally, a comprehensive in-depth diagnosis tool allows to investigate, why the model produces the obtained near-surface results to answer the question if the model performs well from the modeler's point of view. Examples will be presented for results obtained using this approach for assessing the risk of potential total agricultural yield loss under drought conditions in Northeast Brazil and for evaluating simulation results for a 10-year period for Europe. To support multi-run simulations and result evaluation, the model will be embedded into an already existing simulation environment that provides further postprocessing tools for sensitivity studies, behavioral analysis and Monte-Carlo simulations, but also for ensemble scenario analysis in one of the next steps.

Palaeodistribution modelling of European vegetation types at the Last Glacial Maximum using modern analogues from Siberia: Prospects and limitations

NASA Astrophysics Data System (ADS)

Janská, Veronika; Jiménez-Alfaro, Borja; Chytrý, Milan; Divíšek, Jan; Anenkhonov, Oleg; Korolyuk, Andrey; Lashchinskyi, Nikolai; Culek, Martin

2017-03-01

We modelled the European distribution of vegetation types at the Last Glacial Maximum (LGM) using present-day data from Siberia, a region hypothesized to be a modern analogue of European glacial climate. Distribution models were calibrated with current climate using 6274 vegetation-plot records surveyed in Siberia. Out of 22 initially used vegetation types, good or moderately good models in terms of statistical validation and expert-based evaluation were computed for 18 types, which were then projected to European climate at the LGM. The resulting distributions were generally consistent with reconstructions based on pollen records and dynamic vegetation models. Spatial predictions were most reliable for steppe, forest-steppe, taiga, tundra, fens and bogs in eastern and central Europe, which had LGM climate more similar to present-day Siberia. The models for western and southern Europe, regions with a lower degree of climatic analogy, were only reliable for mires and steppe vegetation, respectively. Modelling LGM vegetation types for the wetter and warmer regions of Europe would therefore require gathering calibration data from outside Siberia. Our approach adds value to the reconstruction of vegetation at the LGM, which is limited by scarcity of pollen and macrofossil data, suggesting where specific habitats could have occurred. Despite the uncertainties of climatic extrapolations and the difficulty of validating the projections for vegetation types, the integration of palaeodistribution modelling with other approaches has a great potential for improving our understanding of biodiversity patterns during the LGM.

Pan-European comparison of candidate distributions for climatological drought indices, SPI and SPEI

NASA Astrophysics Data System (ADS)

Stagge, James; Tallaksen, Lena; Gudmundsson, Lukas; Van Loon, Anne; Stahl, Kerstin

2013-04-01

Drought indices are vital to objectively quantify and compare drought severity, duration, and extent across regions with varied climatic and hydrologic regimes. The Standardized Precipitation Index (SPI), a well-reviewed meterological drought index recommended by the WMO, and its more recent water balance variant, the Standardized Precipitation-Evapotranspiration Index (SPEI) both rely on selection of univariate probability distributions to normalize the index, allowing for comparisons across climates. The SPI, considered a universal meteorological drought index, measures anomalies in precipitation, whereas the SPEI measures anomalies in climatic water balance (precipitation minus potential evapotranspiration), a more comprehensive measure of water availability that incorporates temperature. Many reviewers recommend use of the gamma (Pearson Type III) distribution for SPI normalization, while developers of the SPEI recommend use of the three parameter log-logistic distribution, based on point observation validation. Before the SPEI can be implemented at the pan-European scale, it is necessary to further validate the index using a range of candidate distributions to determine sensitivity to distribution selection, identify recommended distributions, and highlight those instances where a given distribution may not be valid. This study rigorously compares a suite of candidate probability distributions using WATCH Forcing Data, a global, historical (1958-2001) climate dataset based on ERA40 reanalysis with 0.5 x 0.5 degree resolution and bias-correction based on CRU-TS2.1 observations. Using maximum likelihood estimation, alternative candidate distributions are fit for the SPI and SPEI across the range of European climate zones. When evaluated at this scale, the gamma distribution for the SPI results in negatively skewed values, exaggerating the index severity of extreme dry conditions, while decreasing the index severity of extreme high precipitation. This bias is particularly notable for shorter aggregation periods (1-6 months) during the summer months in southern Europe (below 45° latitude), and can partially be attributed to distribution fitting difficulties in semi-arid regions where monthly precipitation totals cluster near zero. By contrast, the SPEI has potential for avoiding this fitting difficulty because it is not bounded by zero. However, the recommended log-logistic distribution produces index values with less variation than the standard normal distribution. Among the alternative candidate distributions, the best fit distribution and the distribution parameters vary in space and time, suggesting regional commonalities within hydroclimatic regimes, as discussed further in the presentation.

On the use of harmonized HCHO and NO2 MAXDOAS measurements for the validation of GOME-2 and OMI satellite sensors

NASA Astrophysics Data System (ADS)

Pinardi, Gaia; Hendrick, François; Gielen, Clio; Van Roozendael, Michel; De Smedt, Isabelle; Lambert, Jean-Christopher; Granville, José; Compernolle, Steven; Richter, Andreas; Peters, Enno; Piters, Ankie; Wagner, Thomas; Wang, Yang; Drosoglou, Theano; Bais, Alkis; Wang, Shanshan; Saiz-Lopez, Alfonso

2017-04-01

During the last decade, the MAXDOAS technique has been increasingly recognized as a source of Fiducial Reference Measurements (FRM) suitable for the validation of satellite nadir observations of species relevant for climate and air quality like NO2 and HCHO. As part of the EU FP7 QA4ECV (Quality Assurance for Essential Climate Variables; see http://www.qa4ecv.eu/) project, efforts have been recently made to harmonize a network of a dozen of MAXDOAS spectrometers in view of their use to assess the quality of satellite climate data records generated within the same project. Harmonization tasks have addressed both retrieval steps involved in MAXDOAS retrievals, i.e. the DOAS spectral fit providing the differential slant column densities (DSCDs) and the conversion of the retrieved DSCDs into vertical profiles and/or vertical column densities (VCDs). In this work, we illustrate the successive harmonization steps and present the resulting QA4ECV MAXDOAS database v2. The approach adopted for the conversion of slant to vertical columns is based on a simplified look-up-table approach. The strength and limitation of this approach are discussed using reference data retrieved using an optimal estimation scheme. The QA4ECV MAXDOAS database is then used to validate satellite data sets of NO2 and HCHO columns derived from the Aura/OMI and MetOp/GOME-2 sensors. The methodology of comparison, which is also a subject of the QA4ECV project, is reviewed with respect to co-location criteria, impact of vertical and horizontal smoothing and representativeness of validation sites. We conclude by assessing the current strengths and limitations of the existing MAXDOAS datasets for NO2 and HCHO satellite validation.

'Speaking up' about patient safety concerns and unprofessional behaviour among residents: validation of two scales.

PubMed

Martinez, William; Etchegaray, Jason M; Thomas, Eric J; Hickson, Gerald B; Lehmann, Lisa Soleymani; Schleyer, Anneliese M; Best, Jennifer A; Shelburne, Julia T; May, Natalie B; Bell, Sigall K

2015-11-01

To develop and test the psychometric properties of two new survey scales aiming to measure the extent to which the clinical environment supports speaking up about (a) patient safety concerns and (b) unprofessional behaviour. Residents from six large US academic medical centres completed an anonymous, electronic survey containing questions regarding safety culture and speaking up about safety and professionalism concerns. Confirmatory factor analysis supported two separate, one-factor speaking up climates (SUCs) among residents; one focused on patient safety concerns (SUC-Safe scale) and the other focused on unprofessional behaviour (SUC-Prof scale). Both scales had good internal consistency (Cronbach's α>0.70) and were unique from validated safety and teamwork climate measures (r<0.85 for all correlations), a measure of discriminant validity. The SUC-Safe and SUC-Prof scales were associated with participants' self-reported speaking up behaviour about safety and professionalism concerns (r=0.21, p<0.001 and r=0.22, p<0.001, respectively), a measure of concurrent validity, while teamwork and safety climate scales were not. We created and provided evidence for the reliability and validity of two measures (SUC-Safe and SUC-Prof scales) associated with self-reported speaking up behaviour among residents. These two scales may fill an existing gap in residency and safety culture assessments by measuring the openness of communication about safety and professionalism concerns, two important aspects of safety culture that are under-represented in existing metrics. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Validation of Salinity Data from the Soil Moisture and Ocean Salinity (SMOS) and Aquarius Satellites in the Agulhas Current System

NASA Astrophysics Data System (ADS)

Button, N.

2016-02-01

The Agulhas Current System is an important western boundary current, particularly due to its vital role in the transport of heat and salt from the Indian Ocean to the Atlantic Ocean, such as through Agulhas rings. Accurate measurements of salinity are necessary for assessing the role of the Agulhas Current System and these rings in the global climate system are necessary. With ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius/SAC-D satellites, we now have complete spatial and temporal (since 2009 and 2011, respectively) coverage of salinity data. To use this data to understand the role of the Agulhas Current System in the context of salinity within the global climate system, we must first understand validate the satellite data using in situ and model comparisons. In situ comparisons are important because of the accuracy, but they lack in the spatial and temporal coverage to validate the satellite data. For example, there are approximately 100 floats in the Agulhas Return Current. Therefore, model comparisons, such as the Hybrid Coordinate Ocean Model (HYCOM), are used along with the in situ data for the validation. For the validation, the satellite data, Argo float data, and HYCOM simulations were compared within box regions both inside and outside of the Agulhas Current. These boxed regions include the main Agulhas Current, Agulhas Return Current, Agulhas Retroflection, and Agulhas rings, as well as a low salinity and high salinity region outside of the current system. This analysis reveals the accuracy of the salinity measurements from the Aquarius/SAC-D and SMOS satellites within the Agulhas Current, which then provides accurate salinity data that can then be used to understand the role of the Agulhas Current System in the global climate system.

Quantifying climate feedbacks in polar regions

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

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

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

Quantifying climate feedbacks in polar regions

DOE PAGES

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

2018-05-15

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

Towards process-informed bias correction of climate change simulations

NASA Astrophysics Data System (ADS)

Maraun, Douglas; Shepherd, Theodore G.; Widmann, Martin; Zappa, Giuseppe; Walton, Daniel; Gutiérrez, José M.; Hagemann, Stefan; Richter, Ingo; Soares, Pedro M. M.; Hall, Alex; Mearns, Linda O.

2017-11-01

Biases in climate model simulations introduce biases in subsequent impact simulations. Therefore, bias correction methods are operationally used to post-process regional climate projections. However, many problems have been identified, and some researchers question the very basis of the approach. Here we demonstrate that a typical cross-validation is unable to identify improper use of bias correction. Several examples show the limited ability of bias correction to correct and to downscale variability, and demonstrate that bias correction can cause implausible climate change signals. Bias correction cannot overcome major model errors, and naive application might result in ill-informed adaptation decisions. We conclude with a list of recommendations and suggestions for future research to reduce, post-process, and cope with climate model biases.

Climate Change in Nicaragua: a dynamical downscaling of precipitation and temperature.

NASA Astrophysics Data System (ADS)

Porras, Ignasi; Domingo-Dalmau, Anna; Sole, Josep Maria; Arasa, Raul; Picanyol, Miquel; Ángeles Gonzalez-Serrano, M.°; Masdeu, Marta

2016-04-01

Climate Change affects weather patterns and modifies meteorological extreme events like tropical cyclones, heavy rainfalls, dry events, extreme temperatures, etc. The aim of this study is to show the Climate Change projections over Nicaragua for the period 2010-2040 focused on precipitation and temperature. In order to obtain the climate change signal, the results obtained by modelling a past period (1980-2009) were compared with the ones obtained by modelling a future period (2010-2040). The modelling method was based on a dynamical downscaling, coupling global and regional models. The MPI-ESM-MR global climate model was selected due to the better performance over Nicaragua. Moreover, a detailed sensitivity analysis for different parameterizations and schemes of the Weather Research and Forecast (WRF-ARW) model was made to minimize the model uncertainty. To evaluate and validate the methodology, a comparison between model outputs and satellite measurements data was realized. The results show an expected increment of the temperature and an increment of the number of days per year with temperatures higher than 35°C. Monthly precipitation patterns will change although annual total precipitation will be similar. In addition, number of dry days are expected to increase.

Integrated assessment of water-power grid systems under changing climate

NASA Astrophysics Data System (ADS)

Yan, E.; Zhou, Z.; Betrie, G.

2017-12-01

Energy and water systems are intrinsically interconnected. Due to an increase in climate variability and extreme weather events, interdependency between these two systems has been recently intensified resulting significant impacts on both systems and energy output. To address this challenge, an Integrated Water-Energy Systems Assessment Framework (IWESAF) is being developed to integrate multiple existing or developed models from various sectors. In this presentation, we are focusing on recent improvement in model development of thermoelectric power plant water use simulator, power grid operation and cost optimization model, and model integration that facilitate interaction among water and electricity generation under extreme climate events. A process based thermoelectric power water use simulator includes heat-balance, climate, and cooling system modules that account for power plant characteristics, fuel types, and cooling technology. The model is validated with more than 800 power plants of fossil-fired, nuclear and gas-turbine power plants with different cooling systems. The power grid operation and cost optimization model was implemented for a selected regional in the Midwest. The case study will be demonstrated to evaluate the sensitivity and resilience of thermoelectricity generation and power grid under various climate and hydrologic extremes and potential economic consequences.

Bioclimatic Classification of Northeast Asia for climate change response

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Tree species distribution in temperate forests is more influenced by soil than by climate.

PubMed

Walthert, Lorenz; Meier, Eliane Seraina

2017-11-01

Knowledge of the ecological requirements determining tree species distributions is a precondition for sustainable forest management. At present, the abiotic requirements and the relative importance of the different abiotic factors are still unclear for many temperate tree species. We therefore investigated the relative importance of climatic and edaphic factors for the abundance of 12 temperate tree species along environmental gradients. Our investigations are based on data from 1,075 forest stands across Switzerland including the cold-induced tree line of all studied species and the drought-induced range boundaries of several species. Four climatic and four edaphic predictors represented the important growth factors temperature, water supply, nutrient availability, and soil aeration. The climatic predictors were derived from the meteorological network of MeteoSwiss, and the edaphic predictors were available from soil profiles. Species cover abundances were recorded in field surveys. The explanatory power of the predictors was assessed by variation partitioning analyses with generalized linear models. For six of the 12 species, edaphic predictors were more important than climatic predictors in shaping species distribution. Over all species, abundances depended mainly on nutrient availability, followed by temperature, water supply, and soil aeration. The often co-occurring species responded similar to these growth factors. Drought turned out to be a determinant of the lower range boundary for some species. We conclude that over all 12 studied tree species, soil properties were more important than climate variables in shaping tree species distribution. The inclusion of appropriate soil variables in species distribution models allowed to better explain species' ecological niches. Moreover, our study revealed that the ecological requirements of tree species assessed in local field studies and in experiments are valid at larger scales across Switzerland.

Assessing the impacts of climate change on future water resources: a methodological approach based on equiratio CDF-matching and vine copula

NASA Astrophysics Data System (ADS)

Pham, Minh Tu; Vernieuwe, Hilde; De Baets, Bernard; Verhoest, Niko E. C.

2016-04-01

In this study, the impacts of climate change on future river discharge are evaluated using equiratio CDF-matching and a stochastic copula-based evapotranspiration generator. In recent years, much effort has been dedicated to improve the performances of RCMs outputs, i.e. the downscaled precipitation and temperature, to use in regional studies. However, these outputs usually suffer from bias due to the fact that many important small-scale processes, e.g. the representations of clouds and convection, are not represented explicitly within the models. To solve this problem, several bias correction techniques are developed. In this study, an advanced quantile bias approach called equiratio cumulative distribution function matching (EQCDF) is applied for the outputs from three RCMs for central Belgium, i.e. daily precipitation, temperature and evapotranspiration, for the current (1961-1990) and future climate (2071-2100). The rescaled precipitation and temperature are then used to simulate evapotranspiration via a stochastic copula-based model in which the statistical dependence between evapotranspiration, temperature and precipitation is described by a three-dimensional vine copula. The simulated precipitation and stochastic evapotranspiration are then used to model discharge under present and future climate. To validate, the observations of daily precipitation, temperature and evapotranspiration during 1961 - 1990 in Uccle, Belgium are used. It is found that under current climate, the basic properties of discharge, e.g. mean and frequency distribution, are well modelled; however there is an overestimation of the extreme discharges with return periods higher than 10 years. For the future climate change, compared with historical events, a considerable increase of the discharge magnitude and the number of extreme events is estimated for the studied area in the time period of 2071-2100.

Safety climate in Swiss hospital units: Swiss version of the Safety Climate Survey

PubMed Central

Gehring, Katrin; Mascherek, Anna C.; Bezzola, Paula

2015-01-01

Abstract Rationale, aims and objectives Safety climate measurements are a broadly used element of improvement initiatives. In order to provide a sound and easy‐to‐administer instrument for the use in Swiss hospitals, we translated the Safety Climate Survey into German and French. Methods After translating the Safety Climate Survey into French and German, a cross‐sectional survey study was conducted with health care professionals (HCPs) in operating room (OR) teams and on OR‐related wards in 10 Swiss hospitals. Validity of the instrument was examined by means of Cronbach's alpha and missing rates of the single items. Item‐descriptive statistics group differences and percentage of ‘problematic responses’ (PPR) were calculated. Results 3153 HCPs completed the survey (response rate: 63.4%). 1308 individuals were excluded from the analyses because of a profession other than doctor or nurse or invalid answers (n = 1845; nurses = 1321, doctors = 523). Internal consistency of the translated Safety Climate Survey was good (Cronbach's alpha G erman = 0.86; Cronbach's alpha F rench = 0.84). Missing rates at item level were rather low (0.23–4.3%). We found significant group differences in safety climate values regarding profession, managerial function, work area and time spent in direct patient care. At item level, 14 out of 21 items showed a PPR higher than 10%. Conclusions Results indicate that the French and German translations of the Safety Climate Survey might be a useful measurement instrument for safety climate in Swiss hospital units. Analyses at item level allow for differentiating facets of safety climate into more positive and critical safety climate aspects. PMID:25656302

Validation of the GCOM-W SCA and JAXA soil moisture algorithms

USDA-ARS?s Scientific Manuscript database

Satellite-based remote sensing of soil moisture has matured over the past decade as a result of the Global Climate Observing Mission-Water (GCOM-W) program of JAXA. This program has resulted in improved algorithms that have been supported by rigorous validation. Access to the products and the valida...

Validation of two (parametric vs non-parametric) daily weather generators

NASA Astrophysics Data System (ADS)

Dubrovsky, M.; Skalak, P.

2015-12-01

As the climate models (GCMs and RCMs) fail to satisfactorily reproduce the real-world surface weather regime, various statistical methods are applied to downscale GCM/RCM outputs into site-specific weather series. The stochastic weather generators are among the most favourite downscaling methods capable to produce realistic (observed-like) meteorological inputs for agrological, hydrological and other impact models used in assessing sensitivity of various ecosystems to climate change/variability. To name their advantages, the generators may (i) produce arbitrarily long multi-variate synthetic weather series representing both present and changed climates (in the latter case, the generators are commonly modified by GCM/RCM-based climate change scenarios), (ii) be run in various time steps and for multiple weather variables (the generators reproduce the correlations among variables), (iii) be interpolated (and run also for sites where no weather data are available to calibrate the generator). This contribution will compare two stochastic daily weather generators in terms of their ability to reproduce various features of the daily weather series. M&Rfi is a parametric generator: Markov chain model is used to model precipitation occurrence, precipitation amount is modelled by the Gamma distribution, and the 1st order autoregressive model is used to generate non-precipitation surface weather variables. The non-parametric GoMeZ generator is based on the nearest neighbours resampling technique making no assumption on the distribution of the variables being generated. Various settings of both weather generators will be assumed in the present validation tests. The generators will be validated in terms of (a) extreme temperature and precipitation characteristics (annual and 30-years extremes and maxima of duration of hot/cold/dry/wet spells); (b) selected validation statistics developed within the frame of VALUE project. The tests will be based on observational weather series from several European stations available from the ECA&D database. Acknowledgements: The weather generator is developed and validated within the frame of projects WG4VALUE (sponsored by the Ministry of Education, Youth and Sports of CR), and VALUE (COST ES 1102 action).

Crowdsourcing urban air temperatures through smartphone battery temperatures in São Paulo, Brazil

NASA Astrophysics Data System (ADS)

Droste, Arjan; Pape, Jan-Jaap; Overeem, Aart; Leijnse, Hidde; Steeneveld, Gert-Jan; Van Delden, Aarnout; Uijlenhoet, Remko

2017-04-01

Crowdsourcing as a method to obtain and apply vast datasets is rapidly becoming prominent in meteorology, especially for urban areas where traditional measurements are scarce. Earlier studies showed that smartphone battery temperature readings allow for estimating the daily and city-wide air temperature via a straightforward heat transfer model. This study advances these model estimations by studying spatially and temporally smaller scales. The accuracy of temperature retrievals as a function of the number of battery readings is also studied. An extensive dataset of over 10 million battery temperature readings is available for São Paulo (Brazil), for estimating hourly and daily air temperatures. The air temperature estimates are validated with air temperature measurements from a WMO station, an Urban Fluxnet site, and crowdsourced data from 7 hobby meteorologists' private weather stations. On a daily basis temperature estimates are good, and we show they improve by optimizing model parameters for neighbourhood scales as categorized in Local Climate Zones. Temperature differences between Local Climate Zones can be distinguished from smartphone battery temperatures. When validating the model for hourly temperature estimates, initial results are poor, but are vastly improved by using a diurnally varying parameter function in the heat transfer model rather than one fixed value for the entire day. The obtained results show the potential of large crowdsourced datasets in meteorological studies, and the value of smartphones as a measuring platform when routine observations are lacking.

Measuring Student Improvement in Lower- and Upper-Level University Climate Science Courses

NASA Astrophysics Data System (ADS)

Harris, S. E.; Taylor, S. V.; Schoonmaker, J. E.; Lane, E.; Francois, R. H.; Austin, P.

2011-12-01

What do university students know about climate? What do they learn in a climate course? On the second-to-last day of a course about global climate change, only 48% of our upper-level science students correctly answered a multiple-choice question about the greenhouse effect. The good news: improvement. Only 16% had answered correctly on the first day of class. The bad news: the learning opportunities we've provided appear to have missed more than half the class on a fundamental climate concept. To evaluate the effectiveness of instruction on student learning about climate, we have developed a prototype assessment tool, designed to be deployed as a low-stakes pre-post test. The items included were validated through student interviews to ensure that students interpret the wording and answer choices in the way we intend. This type of validated assessment, administered both at the beginning and end of term, with matched individuals, provides insight regarding the baseline knowledge with which our students enter a course, and the impact of that course on their learning. We administered test items to students in (1) an upper-level climate course for science majors and (2) a lower-level climate course open to all students. Some items were given to both groups, others to only one of the groups. Both courses use evidence-based pedagogy with active student engagement (clickers, small group activities, regular pre-class preparation). Our results with upper-level students show strong gains in student thinking (>70% of students who missed a question on the pre-test answered correctly on the post-test) about stock-and-flow (box model) problems, annual cycles in the Keeling curve, ice-albedo feedbacks, and isotopic fractionation. On different questions, lower-level students showed strong gains regarding albedo and blackbody emission spectra. Both groups show similar baseline knowledge and lower-than-expected gains on greenhouse effect fundamentals, and zero gain regarding the relative importance of different greenhouse gases. A larger percentage of upper-level students (compared to lower-level students) arrive with correct knowledge comparing different greenhouse gases, and explanations of annual cycles in the Keeling curve, but both groups show similar gains with instruction. Instructors can use feedback from these pre-post assessment results to iteratively modify and test the learning opportunities they provide. We aim to continue development and further validation of this tool such that it can be used in many university-level climate courses.

Cloud cover archiving on a global scale - A discussion of principles

NASA Technical Reports Server (NTRS)

Henderson-Sellers, A.; Hughes, N. A.; Wilson, M.

1981-01-01

Monitoring of climatic variability and climate modeling both require a reliable global cloud data set. Examination is made of the temporal and spatial variability of cloudiness in light of recommendations made by GARP in 1975 (and updated by JOC in 1978 and 1980) for cloud data archiving. An examination of the methods of comparing cloud cover frequency curves suggests that the use of the beta distribution not only facilitates objective comparison, but also reduces overall storage requirements. A specific study of the only current global cloud climatology (the U.S. Air Force's 3-dimensional nephanalysis) over the United Kingdom indicates that discussion of methods of validating satellite-based data sets is urgently required.

Developing an approach to effectively use super ensemble experiments for the projection of hydrological extremes under climate change

NASA Astrophysics Data System (ADS)

Watanabe, S.; Kim, H.; Utsumi, N.

2017-12-01

This study aims to develop a new approach which projects hydrology under climate change using super ensemble experiments. The use of multiple ensemble is essential for the estimation of extreme, which is a major issue in the impact assessment of climate change. Hence, the super ensemble experiments are recently conducted by some research programs. While it is necessary to use multiple ensemble, the multiple calculations of hydrological simulation for each output of ensemble simulations needs considerable calculation costs. To effectively use the super ensemble experiments, we adopt a strategy to use runoff projected by climate models directly. The general approach of hydrological projection is to conduct hydrological model simulations which include land-surface and river routing process using atmospheric boundary conditions projected by climate models as inputs. This study, on the other hand, simulates only river routing model using runoff projected by climate models. In general, the climate model output is systematically biased so that a preprocessing which corrects such bias is necessary for impact assessments. Various bias correction methods have been proposed, but, to the best of our knowledge, no method has proposed for variables other than surface meteorology. Here, we newly propose a method for utilizing the projected future runoff directly. The developed method estimates and corrects the bias based on the pseudo-observation which is a result of retrospective offline simulation. We show an application of this approach to the super ensemble experiments conducted under the program of Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI). More than 400 ensemble experiments from multiple climate models are available. The results of the validation using historical simulations by HAPPI indicates that the output of this approach can effectively reproduce retrospective runoff variability. Likewise, the bias of runoff from super ensemble climate projections is corrected, and the impact of climate change on hydrologic extremes is assessed in a cost-efficient way.

On demand processing of climate station sensor data

NASA Astrophysics Data System (ADS)

Wöllauer, Stephan; Forteva, Spaska; Nauss, Thomas

2015-04-01

Large sets of climate stations with several sensors produce big amounts of finegrained time series data. To gain value of this data, further processing and aggregation is needed. We present a flexible system to process the raw data on demand. Several aspects need to be considered to process the raw data in a way that scientists can use the processed data conveniently for their specific research interests. First of all, it is not feasible to pre-process the data in advance because of the great variety of ways it can be processed. Therefore, in this approach only the raw measurement data is archived in a database. When a scientist requires some time series, the system processes the required raw data according to the user-defined request. Based on the type of measurement sensor, some data validation is needed, because the climate station sensors may produce erroneous data. Currently, three validation methods are integrated in the on demand processing system and are optionally selectable. The most basic validation method checks if measurement values are within a predefined range of possible values. For example, it may be assumed that an air temperature sensor measures values within a range of -40 °C to +60 °C. Values outside of this range are considered as a measurement error by this validation method and consequently rejected. An other validation method checks for outliers in the stream of measurement values by defining a maximum change rate between subsequent measurement values. The third validation method compares measurement data to the average values of neighboring stations and rejects measurement values with a high variance. These quality checks are optional, because especially extreme climatic values may be valid but rejected by some quality check method. An other important task is the preparation of measurement data in terms of time. The observed stations measure values in intervals of minutes to hours. Often scientists need a coarser temporal resolution (days, months, years). Therefore, the interval of time aggregation is selectable for the processing. For some use cases it is desirable that the resulting time series are as continuous as possible. To meet these requirements, the processing system includes techniques to fill gaps of missing values by interpolating measurement values with data from adjacent stations using available contemporaneous measurements from the respective stations as training datasets. Alongside processing of sensor values, we created interactive visualization techniques to get a quick overview of a big amount of archived time series data.

Glacier melt buffers river runoff in the Pamir Mountains

NASA Astrophysics Data System (ADS)

Pohl, Eric; Gloaguen, Richard; Andermann, Christoff; Knoche, Malte

2017-03-01

Newly developed approaches based on satellite altimetry and gravity measurements provide promising results on glacier dynamics in the Pamir-Himalaya but cannot resolve short-term natural variability at regional and finer scale. We contribute to the ongoing debate by upscaling a hydrological model that we calibrated for the central Pamir. The model resolves the spatiotemporal variability in runoff over the entire catchment domain with high efficiency. We provide relevant information about individual components of the hydrological cycle and quantify short-term hydrological variability. For validation, we compare the modeled total water storages (TWS) with GRACE (Gravity Recovery and Climate Experiment) data with a very good agreement where GRACE uncertainties are low. The approach exemplifies the potential of GRACE for validating even regional scale hydrological applications in remote and hard to access mountain regions. We use modeled time series of individual hydrological components to characterize the effect of climate variability on the hydrological cycle. We demonstrate that glaciers play a twofold role by providing roughly 35% of the annual runoff of the Panj River basin and by effectively buffering runoff both during very wet and very dry years. The modeled glacier mass balance (GMB) of -0.52 m w.e. yr-1 (2002-2013) for the entire catchment suggests significant reduction of most Pamiri glaciers by the end of this century. The loss of glaciers and their buffer functionality in wet and dry years could not only result in reduced water availability and increase the regional instability, but also increase flood and drought hazards.