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Ecosystem health report cards have become increasingly more important tools for communicating environmental state and assessing progress towards management goals. We provide an overview of the major analytical methods underpinning...
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Ecosystem health report cards have become increasingly more important tools for communicating environmental state and assessing progress towards management goals. We provide an overview of the major analytical methods underpinning the translation of observed data into robust health indices. In particular, we outline the process of indicator selection, illustrate a variety of index metrics and describe index aggregation with consideration for weighting and the propagation of uncertainty.
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Three-dimensional cloud field morphology contributes to scene-averaged cloud reflectivity, but climate models do not currently incorporate methods of identifying situations where this contribution is substantial. This work represe...
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Three-dimensional cloud field morphology contributes to scene-averaged cloud reflectivity, but climate models do not currently incorporate methods of identifying situations where this contribution is substantial. This work represents an effort to identify atmospheric conditions conducive to the formation of cloud field configurations that significantly affect shortwave radiative fluxes. Once identified, these characteristics may form the basis of a parameterization that accounts for radiative impact of complex cloud fields. A k-means clustering algorithm is applied to observed cloud properties taken from the Atmospheric Radiation Measurement Program tropical western Pacific sites to identify specific cloud regimes. Results from a stand-alone stochastic model, which statistically represents shortwave radiative transfer through broken cloud fields, are compared with those of a plane-parallel model. The aggregate scenes in each regime are examined to measure the bias in shortwave flux calculations due to neglected cloud field morphology. The results from the model comparison and cluster analysis suggest that cloud fraction, vertical wind shear, and spacing between cloudy layers are all important indicators of complex cloud field geometry and that these criteria are most often met in cloud regimes characterized by moderate to strong convection. The cluster criteria are applied to output from the Community Climate System Model (version 3.0) and it is found that the presence of persistent high cirrus cloud in model simulations inhibits identification of specific cloud regimes.
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摘要 :
Three-dimensional cloud field morphology contributes to scene-averaged cloud reflectivity, but climate
models do not currently incorporate methods of identifying situations where this contribution is substantial.
This work represe...
展开
Three-dimensional cloud field morphology contributes to scene-averaged cloud reflectivity, but climate
models do not currently incorporate methods of identifying situations where this contribution is substantial.
This work represents an effort to identify atmospheric conditions conducive to the formation of cloud field
configurations that significantly affect shortwave radiative fluxes. Once identified, these characteristics may
form the basis of a parameterization that accounts for radiative impact of complex cloud fields. A k-means
clustering algorithm is applied to observed cloud properties taken from the Atmospheric Radiation Measurement
Program tropical western Pacific sites to identify specific cloud regimes. Results from a stand-alone
stochastic model, which statistically represents shortwave radiative transfer through broken cloud fields, are
compared with those of a plane-parallel model. The aggregate scenes in each regime are examined to measure
the bias in shortwave flux calculations due to neglected cloud field morphology. The results from the model
comparison and cluster analysis suggest that cloud fraction, vertical wind shear, and spacing between cloudy
layers are all important indicators of complex cloud field geometry and that these criteria are most often met
in cloud regimes characterized by moderate to strong convection. The cluster criteria are applied to output
from the Community Climate System Model (version 3.0) and it is found that the presence of persistent high
cirrus cloud in model simulations inhibits identification of specific cloud regimes.
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Context Sustainability indices (SIs) have become increasingly important to sustainability research and practice. However, while the validity of SIs is heavily dependent on how their components are weighted and aggregated, the typo...
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Context Sustainability indices (SIs) have become increasingly important to sustainability research and practice. However, while the validity of SIs is heavily dependent on how their components are weighted and aggregated, the typology and applicability of the existing weighting and aggregation methods remain poorly understood.
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In this paper some tendencies of indicator development and application are presented from a quantitative and a qualitative point-of-view. The results of a mainly statistical analysis of the first twenty volumes of the journal Ecol...
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In this paper some tendencies of indicator development and application are presented from a quantitative and a qualitative point-of-view. The results of a mainly statistical analysis of the first twenty volumes of the journal Ecological Indicators are described and discussed. The focus of this investigation has been set on five questions:. (A) Which types of ecological indicators have been applied and how frequently have they been used? (B) In which management context have the indicators been applied? (C) Which integrative tools have been utilized to present the results in an aggregated form? (D) Has a theory for the application and interpretation of ecological indicators been developed? (E) Which are the resulting challenges in indicator development and application? The answers to the first three questions are given in tables and figures, while the fourth question is answered shortly and with references to the key papers that are covering the theoretical considerations behind the application of ecological indicators. Discussing the focal challenges it is foreseen that two theoretical questions will require enhanced attention the coming years: to apply fewer and more general indices and to translate the multitude of indicators to the concept of sustainability that covers the ecological-sociological-economic and political background of the overall indication activities. Furthermore, the general demands for aggregation and integration and an assessment of normative loadings in indicator systems are listed as focal tasks for future development in the field.
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Management researchers often use consensus-based composition models to examine the antecedents and effects of higher-level constructs. Typically, researchers present three indices, r(wg), ICC(1), and ICC(2), to demonstrate agreeme...
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Management researchers often use consensus-based composition models to examine the antecedents and effects of higher-level constructs. Typically, researchers present three indices, r(wg), ICC(1), and ICC(2), to demonstrate agreement and consistency among lower-level units when justifying aggregation. Nevertheless, researchers debate what values for these indices are sufficient. This study examines the distributional characteristics of ICCs and r(wg) values from three sources: the multilevel literature, a large multinational sample of student teams, and a large sample of randomly generated pseudo teams. Our results support existing cutoff criteria for ICCs but suggest that generally accepted values for r(wg) may, under certain circumstances, reflect pseudo-agreement (i.e., agreement observed among two raters not attributable to the same target). Thus, when there is minimal between-group variance (i.e., low ICCs), it is difficult to determine whether high r(wg) values reflect agreement or pseudo-agreement. Based on these findings, we provide recommendations to help researchers interpret aggregation indices.
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It has been more than a decade since sequential indicator simulation was proposed to model geological features. Due to its simplicity and easiness of implementation, the algorithm attracts the practitioner’s attention and is rapi...
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It has been more than a decade since sequential indicator simulation was proposed to model geological features. Due to its simplicity and easiness of implementation, the algorithm attracts the practitioner’s attention and is rapidly becoming available through commercial software programs for modeling mineral deposits, oil reservoirs, and groundwater resources. However, when the algorithm only uses hard conditioning data, its inadequacy to model the long-range geological features has always been a research debate in geostatistical contexts. To circumvent this difficulty, one or several pieces of soft information can be introduced into the simulation process to assist in reproducing such large-scale settings. An alternative format of Bayesian sequential indicator simulation is developed in this work that integrates a log-linear pooling approach by using the aggregation of probabilities that are reported by two sources of information, hard and soft data. The novelty of this revisited Bayesian technique is that it allows the incorporation of several influences of hard and soft data in the simulation process by assigning the weights to their probabilities. In this procedure, the conditional probability of soft data can be directly estimated from hard conditioning data and then be employed with its corresponding weight of influence to update the weighted conditional portability that is simulated from the same hard conditioning and previously simulated data in a sequential manner. To test the algorithm, a 2D synthetic case study is presented. The findings showed that the resulting maps obtained from the proposed revisited Bayesian sequential indicator simulation approach outperform other techniques in terms of reproduction of long-range geological features while keeping its consistency with other expected local and global statistical measures.
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Resilience is the intrinsic ability of a system to adjust its functioning prior to, during, or following changes and disturbances, so that it can sustain required operations under expected and unexpected conditions. Protection and...
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Resilience is the intrinsic ability of a system to adjust its functioning prior to, during, or following changes and disturbances, so that it can sustain required operations under expected and unexpected conditions. Protection and Civil Defense Organizations (PCDOs), communities and cities deal with disaster management involving routine, non-routine and even unpredictable/unforeseen situations with varying degrees of complexity. It is important that such organizations continually assess their resilience, enable them to learn on their weaknesses and real capacities to cope with emergency situations. This research aimed the development of an Organization Resilience Indicator System (ORIS) based on a fuzzy model to enable PCDOs self-assesses their resilience. Based on a literature review on organizational and community's resilience, a system of resilience indicators was defined. This system was validated by experts using fuzzy set theory to aggregate opinions in the development of a resilience ideal pattern. Then, the resilience of four PCDO organizations was self-evaluated. The results were accordingly to maturity level of the organizations evaluated, indicating that the ORIS is valuable to measure PCDOs resilience.
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In economic models, the aggregate consumption of energy resources is normally ex- pressed either in terms of its total heating value (e.g. Btus or barrels of oil equivalent) or in terms of its economic value (e. g. Divisia indices...
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In economic models, the aggregate consumption of energy resources is normally ex- pressed either in terms of its total heating value (e.g. Btus or barrels of oil equivalent) or in terms of its economic value (e. g. Divisia indices or total expenditures). For most major OECD countries, we find that it matters little whether various energy resources consumed In the industrial sector are aggregated in terms of their heating value r their economic Value-similartrends emerge regardless of which measure is adopted.
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Indicators are widely used in sustainability assessments. They serve both a descriptive function (i.e., assessing a situation or effects of potential changes) and a normative function (i.e., allowing the expression of value judgme...
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Indicators are widely used in sustainability assessments. They serve both a descriptive function (i.e., assessing a situation or effects of potential changes) and a normative function (i.e., allowing the expression of value judgments). These functions are usually considered when identifying and using indicators. However, processes such as formalization, estimation, and customization are needed to produce tangible indicators. These processes and their influence on sustainability assessments are studied less often. We focus on spatial aggregation, a specific type of customization commonly used for landscape-scale and regional assessments. Using a database with 146 indicator profiles for water management, we investigated reasons for spatial aggregation choices, i.e. whether indicators based on spatially-explicit data are aggregated while under development or are provided to users in a disaggregated form. Although the literature assigns a descriptive function to spatial aggregation, our database shows that reasons underlying aggregation choices are more diverse. These reasons include highlighting differences, fitting to the scale of a process, fitting to criteria, recognizing a lack of knowledge, expressing social rationality, contextualizing information, and allowing different interpretations of the same indicator. Some of these reasons reflect the choice to expand or reduce the range of potential uses of an indicator, and therefore the potential for different viewpoints to confront each other. Hence, normative claims combine with descriptive claims when aggregating indicators, and even more so when customizing them. In general, the form of indicators merits more attention in the practice and theory of sustainability assessments.
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