Relevant bibliographies by topics / Climate evaluation

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Climate evaluation'

Author: Grafiati
Published: 4 June 2021
Last updated: 3 February 2022

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Journal articles on the topic "Climate evaluation"

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Jahedi, A., and A. Zarei. "Evaluation of thermal energy consumption in broiler farms and saving strategies." Arquivo Brasileiro de Medicina Veterinária e Zootecnia 72, no. 6 (December 2020): 2355–64. http://dx.doi.org/10.1590/1678-4162-12051.

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ABSTRACT The aim of this study was to evaluate thermal energy consumption in broiler farms and provide solutions to reduce it. This study was performed with a completely randomized design under 4 climatic conditions, including Ardabil (cold climate representative), Khuzestan (warm climate representative), Isfahan (dry climate representative) and Guilan (temperate climate representative) in 4 replicates (4 broiler farms in each climate) and with 5 repetitions (5 periods of breeding per unit) and a capacity of 492,700, Ross 308 broiler in each breeding period. According to the results, in all climates, the proposed solutions to save thermal energy were able to create a significant difference (P<0.05). The experimental results also showed that the difference in thermal energy consumption in cold and dry climates wasmuch higher than in temperate and warm climates (P<0.05). Overall, the results of the present study show that, by optimizing andmodernizing construction equipment in broiler farms, thermal energy losses can be reduced in all climatic conditions.
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Mohammad Reza, Khaleghi. "Application of dendroclimatology in evaluation of climatic changes." Journal of Forest Science 64, No. 3 (March 28, 2018): 139–47. http://dx.doi.org/10.17221/79/2017-jfs.

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The present study tends to describe the survey of climatic changes in the case of the Bojnourd region of North Khorasan, Iran. Climate change due to a fragile ecosystem in semi-arid and arid regions such as Iran is one of the most challenging climatological and hydrological problems. Dendrochronology, which uses tree rings to their exact year of formation to analyse temporal and spatial patterns of processes in the physical and cultural sciences, can be used to evaluate the effects of climate change. In this study, the effects of climate change were simulated using dendrochronology (tree rings) and an artificial neural network (ANN) for the period from 1800 to 2015. The present study was executed using the Quercus castaneifolia C.A. Meyer. Tree-ring width, temperature, and precipitation were the input parameters for the study, and climate change parameters were the outputs. After the training process, the model was verified. The verified network and tree rings were used to simulate climatic parameter changes during the past times. The results showed that the integration of dendroclimatology and an ANN renders a high degree of accuracy and efficiency in the simulation of climate change. The results showed that in the last two centuries, the climate of the study area changed from semiarid to arid, and its annual precipitation decreased significantly.
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Schalast, Norbert, and Jacob Michael Laan. "Measuring Social Climate in German Prisons Using the Essen Climate Evaluation Schema." Prison Journal 97, no. 2 (March 2017): 166–80. http://dx.doi.org/10.1177/0032885517692792.

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Sociotherapeutic prison units have been criticized for their close operational connection with traditional prison systems. This research compared the social climate of German therapeutic prison units with that of traditional prison units, using the Essen Climate Evaluation Schema (EssenCES). The EssenCES was administered in conjunction with the shortened Correctional Institutions Environment Scale. Results indicate significant differences between therapeutic and traditional units’ social climates, with the former demonstrating more supportive, safe, and therapeutic climates. Findings further confirm the psychometric properties of the EssenCES and support its use as a social climate measurement instrument.
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Lee, Huikyo, Alexander Goodman, Lewis McGibbney, Duane E. Waliser, Jinwon Kim, Paul C. Loikith, Peter B. Gibson, and Elias C. Massoud. "Regional Climate Model Evaluation System powered by Apache Open Climate Workbench v1.3.0: an enabling tool for facilitating regional climate studies." Geoscientific Model Development 11, no. 11 (November 5, 2018): 4435–49. http://dx.doi.org/10.5194/gmd-11-4435-2018.

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Abstract. The Regional Climate Model Evaluation System (RCMES) is an enabling tool of the National Aeronautics and Space Administration to support the United States National Climate Assessment. As a comprehensive system for evaluating climate models on regional and continental scales using observational datasets from a variety of sources, RCMES is designed to yield information on the performance of climate models and guide their improvement. Here, we present a user-oriented document describing the latest version of RCMES, its development process, and future plans for improvements. The main objective of RCMES is to facilitate the climate model evaluation process at regional scales. RCMES provides a framework for performing systematic evaluations of climate simulations, such as those from the Coordinated Regional Climate Downscaling Experiment (CORDEX), using in situ observations, as well as satellite and reanalysis data products. The main components of RCMES are (1) a database of observations widely used for climate model evaluation, (2) various data loaders to import climate models and observations on local file systems and Earth System Grid Federation (ESGF) nodes, (3) a versatile processor to subset and regrid the loaded datasets, (4) performance metrics designed to assess and quantify model skill, (5) plotting routines to visualize the performance metrics, (6) a toolkit for statistically downscaling climate model simulations, and (7) two installation packages to maximize convenience of users without Python skills. RCMES website is maintained up to date with a brief explanation of these components. Although there are other open-source software (OSS) toolkits that facilitate analysis and evaluation of climate models, there is a need for climate scientists to participate in the development and customization of OSS to study regional climate change. To establish infrastructure and to ensure software sustainability, development of RCMES is an open, publicly accessible process enabled by leveraging the Apache Software Foundation's OSS library, Apache Open Climate Workbench (OCW). The OCW software that powers RCMES includes a Python OSS library for common climate model evaluation tasks as well as a set of user-friendly interfaces for quickly configuring a model evaluation task. OCW also allows users to build their own climate data analysis tools, such as the statistical downscaling toolkit provided as a part of RCMES.
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Croce, Pietro, Paolo Formichi, and Filippo Landi. "Enhancing the Output of Climate Models: A Weather Generator for Climate Change Impact Studies." Atmosphere 12, no. 8 (August 21, 2021): 1074. http://dx.doi.org/10.3390/atmos12081074.

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Evaluation of effects of climate change on climate variable extremes is a key topic in civil and structural engineering, strongly affecting adaptation strategy for resilience. Appropriate procedures to assess the evolution over time of climatic actions are needed to deal with the inherent uncertainty of climate projections, also in view of providing more sound and robust predictions at the local scale. In this paper, an ad hoc weather generator is presented that is able to provide a quantification of climate model inherent uncertainties. Similar to other weather generators, the proposed algorithm allows the virtualization of the climatic data projection process, overcoming the usual limitations due to the restricted number of available climate model runs, requiring huge computational time. However, differently from other weather generation procedures, this new tool directly samples from the output of Regional Climate Models (RCMs), avoiding the introduction of additional hypotheses about the stochastic properties of the distributions of climate variables. Analyzing the ensemble of so-generated series, future changes of climatic actions can be assessed, and the associated uncertainties duly estimated, as a function of considered greenhouse gases emission scenarios. The efficiency of the proposed weather generator is discussed evaluating performance metrics and referring to a relevant case study: the evaluation of extremes of minimum and maximum temperature, precipitation, and ground snow load in a central Eastern region of Italy, which is part of the Mediterranean climatic zone. Starting from the model ensemble of six RCMs, factors of change uncertainty maps for the investigated region are derived concerning extreme daily temperatures, daily precipitation, and ground snow loads, underlying the potentialities of the proposed approach.
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Tukimat, Nurul Nadrah Aqilah, Ahmad Saifuddin Othman, Saffuan Wan Ahmad, and Khairunisa Muthusamy. "Evaluation of Climate Variability Performances using Statistical Climate Models." Sains Malaysiana 47, no. 1 (January 31, 2018): 77–84. http://dx.doi.org/10.17576/jsm-2018-4701-09.

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Faramarzi, Hassan, Seyed Mohsen Hosseini, Hamid Reza Pourghasemi, and Mahdi Farnaghi. "Forest fire spatial modelling using ordered weighted averaging multi-criteria evaluation." Journal of Forest Science 67, No. 2 (February 4, 2021): 87–100. http://dx.doi.org/10.17221/50/2020-jfs.

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Forest fires are a major environmental issue because they are increasing as a consequence of climate change and global warming. The present study was aimed to model forest fire hazard using the ordered weighted averaging (OWA) multi-criteria evaluation algorithm and to determine the role of human, climatic, and environmental factors in forest fire occurrence within the Golestan National Park (GNP), Iran. The database used for the present study was created according to daily classification of climate changes, environmental basic maps, and human-made influential forest fire factors. In the study area, the forest fires were registered using GPS. Expert opinions were applied through the analytic hierarchy process (AHP) to determine the importance of effective factors. Fuzzy membership functions were used to standardize the thematic layers. The fire risk maps were prepared using different OWA scenarios for man-made, climatic, and environment factors. The findings revealed that roads (weight = 0.288), rainfalls (weight = 0.288), and aspects (weight = 0.255) are the major factors that contribute to the occurrence of forest fire in the study area. The forest fire maps prepared from different scenarios were validated using the relative operating characteristic (ROC) curve. Values of forest fire maps acquired from scenarios of human, environment, climate factors and their combination were 0.87, 0.731, 0.773 and 0.819, respectively.
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Ezekannagha and Crespo. "Suitability Evaluation of Underutilized Crops Under Future Climate Change Using Ecocrop Model: A Case of Bambara Groundnut in Nigeria." Proceedings 36, no. 1 (January 16, 2020): 53. http://dx.doi.org/10.3390/proceedings2019036053.

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The agricultural crop system depends on a few major staple crops such as rice, maize, wheat, sorghum, soybeans, amongst others for food production, leaving certain crops underutilized. Even though these underutilized crops have the potentials of diversifying and sustaining the food and nutrition systems while presenting different resilience to climatic conditions. As the world’s population continues to increase and climate change keeps occurring, these major staple crops are being negatively affected. This study focuses on evaluating the spatial suitability of Bambara groundnut (Vigna subterranea (L.) Verdc.), an indigenous underutilized African legume under past and future climate scenarios in Nigeria, West Africa, where farmers depend mostly on rainfed agriculture. Ten bias-corrected CMIP5 Global climate models simulation downscaled by the Coordinated Regional Climate Downscaling Experiment (CORDEX) regional climate model, RCA4 under the Representative Concentration Pathway (RCP) 8.5 scenario was used to drive the crop suitability model-Ecocrop. The spatial changes in Bambara groundnut suitability were evaluated under 1 past climate period -historical (1980-2010), and 3 future climate period - near future (2010-2040), mid-century (2040-2070), and end century (2070-2099). Our result projects southern Nigeria to remain suitable and an increase in the suitable areas across other parts of the country in future climates. Projected changes were observed in the planting month for Bambara groundnut. The study is relevant and will contribute to the discussions of increasing the number of crops cultivated under climate change as an adaptation strategy towards ensuring a sustainable food system in Nigeria.
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Braverman, Amy, Snigdhansu Chatterjee, Megan Heyman, and Noel Cressie. "Probabilistic evaluation of competing climate models." Advances in Statistical Climatology, Meteorology and Oceanography 3, no. 2 (October 26, 2017): 93–105. http://dx.doi.org/10.5194/ascmo-3-93-2017.

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Abstract. Climate models produce output over decades or longer at high spatial and temporal resolution. Starting values, boundary conditions, greenhouse gas emissions, and so forth make the climate model an uncertain representation of the climate system. A standard paradigm for assessing the quality of climate model simulations is to compare what these models produce for past and present time periods, to observations of the past and present. Many of these comparisons are based on simple summary statistics called metrics. In this article, we propose an alternative: evaluation of competing climate models through probabilities derived from tests of the hypothesis that climate-model-simulated and observed time sequences share common climate-scale signals. The probabilities are based on the behavior of summary statistics of climate model output and observational data over ensembles of pseudo-realizations. These are obtained by partitioning the original time sequences into signal and noise components, and using a parametric bootstrap to create pseudo-realizations of the noise sequences. The statistics we choose come from working in the space of decorrelated and dimension-reduced wavelet coefficients. Here, we compare monthly sequences of CMIP5 model output of average global near-surface temperature anomalies to similar sequences obtained from the well-known HadCRUT4 data set as an illustration.
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Beach, Mary Catherine, Rachel Topazian, Kitty S. Chan, Jeremy Sugarman, and Gail Geller. "Climate of Respect Evaluation in ICUs." Critical Care Medicine 46, no. 6 (June 2018): e502-e507. http://dx.doi.org/10.1097/ccm.0000000000003069.

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Dissertations / Theses on the topic "Climate evaluation"

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Edwards, Morgan Rae. "Climate impact metrics for energy technology evaluation." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/81113.

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Thesis (S.M. in Technology and Policy)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.
Cataloged from PDF version of thesis.
Includes bibliographical references (p. 87-97).
The climate change mitigation potential of energy technologies depends on how their lifecycle greenhouse gas emissions compare to global climate stabilization goals. Current methods for comparing technologies, which assess impacts over an arbitrary, fixed time horizon, do not acknowledge the critical link between technology choices and climate dynamics. In this thesis, I ask how we can use information about the temporal characteristics of greenhouse gases to design new metrics for comparing energy technologies. I propose two new metrics: the Cumulative Climate Impact (CCI) and Instantaneous Climate Impact (ICI). These metrics use limited information about the climate system, such as the year when stabilization occurs, to calculate tradeoffs between greenhouse gases, and hence the technologies that emit these gases. The CCI and ICI represent a middle ground between current metrics and commonly-proposed alternatives, in terms of their level of complexity and information requirements. I apply the CCI and ICI to evaluate the climate change mitigation potential of energy technologies in the transportation sector, with a focus on alternative fuels. I highlight key policy debates about the role of (a) natural gas as a "bridge" to a low carbon energy future and (b) third generation biofuels as a long-term energy solution. New metrics shed light on critical timing-related questions that current metrics gloss over. If natural gas is a bridge fuel, how long is this bridge? If algae biofuels are not commercially viable for the next twenty years, can they still provide a significant climate benefit? I simulate technology decisions using new metrics, and existing metrics like the Global Warming Potential (GWP), identifying the conditions where new metrics improve on existing methods as well as the conditions under which new metrics fail. I show that metrics of intermediate complexity, such as the CCI and ICI, provide a simple, reliable, and policy-relevant approach to technology evaluation and capture key features of the future climate system. I extend these insights to energy technologies in the electricity sector as well as a variety of environmental impact categories.
by Morgan R. Edwards.
S.M.in Technology and Policy
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Jahan, Momtaz. "A Systematic Evaluation of Climate Services and Decision Support Tools for Climate Change Adaptation." Thesis, Virginia Tech, 2021. http://hdl.handle.net/10919/102124.

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Climate services, often refers as decision support tools, are developed to provide information with a view to aid in decision making and policy planning for adaptation due to climate variability and change. This study investigated different publicly available climate services and decision support tools based on previously proposed evaluation framework. This evaluation framework originally consists of four design elements which are divided into nine evaluation metrics for this study. These evaluation metrics are: identification of decision making context, discussion of the role of climate information in decision making, discussion of non-climatic factors, uncertainty of the data presented, accessibility of information, discussion on the development process, sustainability/ ongoing process, discussion of funding sources, and evaluation of the tool through survey, modeling or contingent valuation method. Tools were then given "High", "Medium", and "Low" score for each of the criterion. A total of 19 tools were evaluation for this study. Tools performed relatively well in "characteristics, tailoring, and communication of the climate information" and "governance, process, and structure of the climate service" whereas they got average scores in "problem identification and the decision-making context" and "value of the service provided". Additionally, four case study evaluation of tools showed detail evaluation of how the tools performed against each of the criterion. The results of this study showed the relative strengths and weakness of the evaluated tools which can be used to improve existing climate services to aid in adaptation decision needs for climate change. This will also help in better decision making and policy planning for different sectors impacted by the changing climate.
Master of Science
Climate services, often refers as decision support tools, are developed to provide information with a view to aid in decision making and policy planning for adaptation due to the adverse impacts caused by climate variability and change. This study investigated a total of 19 publicly available climate services and decision support tools based on previously proposed evaluation framework. This evaluation framework originally consists of four design elements which further classified into nine evaluation metrics and each of tools were given "High", "Medium", and "Low" score against these criteria. These metrics are: identification of decision making context, discussion of the role of climate information in decision making, discussion of non-climatic factors, uncertainty of the data presented, accessibility of information, discussion on the development process, sustainability/ ongoing process, discussion of funding sources, and evaluation of the tool through survey, modeling or contingent valuation method. Evaluated tools performed better than average in terms of uncertainty of the data presented, accessibility of information, discussion on the development process, sustainability/ ongoing process, discussion of funding sources, and feedback/ evaluation criteria whereas they performed below average in problem identification and decision making context, discussion of the role of climate information in decision making, and discussion of non-climatic factors. Four case study evaluation were also presented in this study for better understanding of how the evaluation process works for the tools. The results of this study provide an insight about the relative strengths and weakness of the evaluated tools and these can be used to improve existing climate services tools. This will also help in better decision making and policy planning for different sectors that are being impacted by the changing climate.
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McLeod, Charles Ruffin. "Secondary school climate: Using an ecological perspective." Diss., The University of Arizona, 1989. http://hdl.handle.net/10150/184722.

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The purpose of this study is to provide data which will enable administrators, through climate assessment, to make concrete decisions regarding perceptions that can be utilized in targeting areas within the school which need intervention or improvement. The main emphasis of the study is to assess various stakeholders' perceptions regarding school variables (teacher/student relationships, security and maintenance, administration, student academic orientation, student behavioral values, guidance, student/peer relationships, parent and community/school relationships, instructional management, and student activities) and to note perceptual trends, similarities, and differences among stakeholder groups. Much of the existing literature views climate as a separate, yet related, component of effective schools. This study's focus is on better understanding climate from the ecological perspective, viewing climate as a tool in which school climate research can be used in school improvement programs to ensure consistency in conceptualizing and measuring school climate. This study goes beyond many in that it attempts to understand climate from various stakeholders' perceptions, and to discern any patterns or relationships among these. Unlike the previous studies of school climate which consider the perceptions of only one or two groups, this concept of school climate is driven by the shared perceptions of key stakeholder groups in the school operation of itself--Board members, Administration, classified staff, the students, teachers, and parents/community members. Because an inductive research method is most appropriate for a study of this type, a quasi-case study approach was selected as the research procedure. The following data analysis process was used in the study, for each of the ten subcategories of respondent, gender, ethnicity, and group/role, an analysis of variance and test of significance were conducted. These results are presented according to the research questions and subcategory. The contribution that this study makes is in the analysis of climate data. The data presented, looking at group means in the climate subcategories to give a broad, general impression of the school's climate. As the data were broken apart and regrouped, important patterns emerged. This information provides much more specific guidance in targeting school improvement, as well as delineating precisely the subcategories of particular concern to various stakeholder groups. This approach to unpacking the school climate concept takes advantage of the multiple characteristics of this school climate study, and acknowledges the different interests of groups within a school. Given scarce resources and competition for people's time, a finer grained analysis of a school's problems is a rational beginning to focused interventions.
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Tredger, Edward. "On the evaluation of uncertainties in climate models." Thesis, London School of Economics and Political Science (University of London), 2009. http://etheses.lse.ac.uk/3002/.

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The prediction of the Earth's climate system is of immediate importance to many decision-makers. Anthropogenic climate change is a key area of public policy and will likely have widespread impacts across the world over the 21st Century. Understanding potential climate changes, and their magnitudes, is important for effective decision making. The principal tools used to provide such climate predictions are physical models, some of the largest and most complex models ever built. Evaluation of state-of-the-art climate models is vital to understanding our ability to make statements about future climate. This Thesis presents a framework for the analysis of climate models in light of their inherent uncertainties and principles of statistical good practice. The assessment of uncertainties in model predictions to-date is incomplete and warrants more attention that it has previously received. This Thesis aims to motivate a more thorough investigation of climate models as fit for use in decision-support. The behaviour of climate models is explored using data from the largest ever climate modelling experiment, the climateprediction.net project. The availability of a large set of simulations allows novel methods of analysis for the exploration of the uncertainties present in climate simulations. It is shown that climate models are capable of producing very different behaviour and that the associated uncertainties can be large. Whilst no results are found that cast doubt on the hypothesis that greenhouse gases are a significant driver of climate change, the range of behaviour shown in the climateprediction.net data set has implications for our ability to predict future climate and for the interpretation of climate model output. It is argued that uncertainties should be explored and communicated to users of climate predictions in such a way that decision-makers are aware of the relative robustness of climate model output.
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Borlaug, Terje. "Evaluation of production processes for LNG in arctic climate." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for energi- og prosessteknikk, 2011. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-13693.

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Most of nowadays base load LNG plants are localized in the area around equator, with stable warm air and cooling water temperature. For new LNG developments in arctic areas there are several features that differ them from plants operating further south. In this work a ConocoPhillips Optimized Cascade LNG process model has been established in HYSYS® and evaluated. The evaluation focus on the driver configuration and cooling method used in order to optimize process efficiency and capacity of the plant for operation in cold climate. Simulations with air cooling and water cooling have been done. Each cooling method has been evaluated for an aero derivative gas turbine compressor driver, an industrial heavy duty gas turbine compressor driver, and an electric compressor driver configuration. Yearly temperature statistics from Kola has been used. The air cooled simulations have a design temperature of 20°C and the water cooled simulations have a design temperature of 4°C seawater temperature and an air temperature of 5°C. The air cooled cases are not close to design operation the entire year. The aero derivative driver configuration will have problems operating at high air temperatures and a higher design temperature is needed. The heavy duty gas turbine driver configurations have limitation in speed variation and this leads to low process efficiency at low temperatures. The electrical driver configuration will not have problems operating. The results show that air cooling is not the desired cooling method because of lower production variation and lower process efficiency. The water cooled cases are close to design conditions the entire year; hence it has the highest flexibility when it comes to production variation and highest process efficiency. The aero derivative driver configuration varies most throughout the year with lowest production in the summer. The heavy duty gas turbine driver configuration has a lower variation in production. The power delivered to the electrical motors will not be affected by air temperature which lead to high process efficiency and stable production plateau throughout the year.
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Carvalho, Maria João Melo Tavares de. "Performance evaluation of climate models for the Iberian Peninsula." Master's thesis, Universidade de Aveiro, 2012. http://hdl.handle.net/10773/10178.

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Mestrado em Meteorologia e Oceanografia Física
O objetivo deste trabalho é a análise da performance de Modelos Climáticos Regionais (RCMs) e Globais (GCMs) na Península Ibérica. Para tal, foram utilizados dados de precipitação, temperatura máxima e mínima (aos 2 metros) para o passado recente (1962-2000) disponibilizados pelo projeto ENSEMBLES, bem como dados observados da European Climate Assessment & Dataset (ECA&D). A análise foi separada em duas secções: a avaliação de performance dos modelos regionais (utilizando o ensemble das simulações forçadas pelas reanálises ERA40) e a avaliação dos modelos globais (utilizando o ensemble de simulações de modelos regionais forçados por modelos globais). Foram calculadas as climatologias sazonais das variáveis originais, bem como as tendências de índices, de forma a verificar a capacidade dos ensembles de simular as variáveis, os seus extremos e variabilidade temporal. Para alem disso, calcularam-se parâmetros estatísticos, como o Erro Quadrático Médio (RMSE), o viés, o desvio padrão e o Coeficiente de Correlação de Pearson. Com o objetivo de verificar se as distribuições modeladas dos índices são estatisticamente semelhantes, utilizou-se o teste de Kolmogorov- Smirnov. Concluiu-se que o ensemble das simulações forçadas pelas reanálises ERA40 mostram melhor performance, enquanto que a incerteza associada ao ensemble das simulações forçadas por GCMs é superior. Os índices de precipitação que mostram a ocorrência de dias secos têm melhor performance que os que contabilizam os dias molhados. Ambas as temperaturas mostram diferenças entre observações e ensembles inferiores ás da precipitação, bem como melhor representação dos padrões espaciais. No entanto, os dados modelados mostram pior performance em zonas de orografia complexa e ao longo de zonas costeiras, tanto para as variáveis originais como para os índices extremos. A análise dos dados observados mostra que há, em geral, aumento no número de dias em que a temperatura Máxima esteve acima do percentil 90 e uma diminuição no número de dias em que a precipitação foi acima do percentil 90 e a temperatura mínima foi abaixo do percentil 10. Embora não apresentando sempre significância estatística, as tendências destes índices apontam para a existência de alterações climáticas que ocorreram na Península Ibérica durante o século XX.
The goal of this work is to analyse the performance of both Regional Climate Models and simulations where these are driven by Global Climate Models over the Iberian Peninsula. To do so, ENSEMBLES datasets of precipitation, maximum and minimum temperature (at 2 meters) for the recent-past (1961-2000) were used, as well as the European Climate Assessment & Dataset (ECA&D) observed data. The analysis is performed in two parts: RCM performance evaluation (using ERA40- driven simulation ensemble) and GCM performance evaluation (using the ensemble of RCM-GCM simulations). Seasonal climatologies of the original variables, as well as trends of the indices were analysed in order to evaluate the ensembles' ability to simulate the variables, their extremes and their time variability. The skill of the ensembles was measured using statistics such as the root mean square error, BIAS, standard deviation error and Pearson correlation coe_cient. Two sample Kolmogorov-Smirnov tests were performed to verify the similarity of the distributions of the yearly indices. It was found that ERA40-driven ensemble shows results more closely related to the observations than GCM-driven ensemble. Furthermore, the uncertainty associated with the GCM-driven ensemble is generally higher than that of ERA40-driven. Precipitation indices that evaluate the occurrence of dry days perform better than the wet days indices. Temperature shows smaller difference between observations and models and higher spatial pattern reproduction. However, models show lower skill and performance in areas of complex orography and along the coastline, for the original variables, as well as the extreme indices. The analysis of the observed data, showed an overall increase in number of days with maximum temperature over the 90th percentile and a decrease in number of days with precipitation over the 90th percentile and minimum temperature under the 10th percentile. Although not always statistically significant these trends point to changes in the Iberian climate that have already taken place during the 20th century.
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Barrow, Elaine M. "On the construction and evaluation of scenarios of climate change for use in crop-climate models." Thesis, University of East Anglia, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.297485.

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Sanchez, Claudio. "Seamless evaluation of stochastic physics parametrizations." Thesis, University of Exeter, 2014. http://hdl.handle.net/10871/16406.

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A substantial segment of the error in numerical weather prediction and climate projections comes from the intrinsic uncertainties of General Circulation Models of the atmosphere. Stochastic physics schemes are one of the preferred methods to represent the model uncertainty in Ensemble Prediction Systems, where different realizations of the same forecast are created to quantify the probabilities of different outcomes in the atmospheric flow. Stochastic physics schemes have been successfully employed in medium-range and seasonal forecasting systems, as they increase the skill of probabilistic forecasts. Similarly it has been demonstrated than these schemes can improve certain aspects of the model's climate. However, it is still not clear whether they are a truthful representation of the model uncertainties they aim to represent. In this thesis, a collection of stochastic physics schemes are evaluated using a seamless approach. It is found that they can improve the representation of the tropical climate and extra-tropical cyclones, but they degrade the individual representation of these processes deteriorating the deterministic skill of the model. Some important features of the model can be degraded by the stochastic physics schemes, like energy and moisture conservation on climate scales. Some closures to the schemes are proposed and successfully tested to remove or reduce some of the problems found. Alternative approaches in the development of stochastic parametrizations are also investigated. Stochastic physics schemes have some benefits but still require further development to produce a realistic representation of model error. It is also recommended that evaluation methodologies must be expanded to include process-based diagnostics to display the realism of its perturbations.
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Chandrasa, Ganesha Tri. "Evaluation of Regional Climate Model Simulated Rainfall over Indonesia and its Application for Downscaling Future Climate Projections." The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1523464961178694.

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Clark, Logan N. "Southern Hemisphere Pressure Relationships during the 20th Century - Implications for Climate Reconstructions and Model Evaluation." Ohio University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1586778291377432.

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Books on the topic "Climate evaluation"

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Steininger, Karl W., Martin König, Birgit Bednar-Friedl, Lukas Kranzl, Wolfgang Loibl, and Franz Prettenthaler, eds. Economic Evaluation of Climate Change Impacts. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-12457-5.

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Ann-Maree, Hansen, ed. Climate change atlas: Greenhouse simulations from the Model Evaluation Consortium for Climate Assessment. Dordrecht: Kluwer Academic Publishers, 1995.

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Feddema, Johannes J. Evaluation of terrestrial climate variability using a moisture index. Elmer, N.J: C.W. Thornthwaite Associates, Laboratory of Climatology ; Newark, Del., 1994.

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Yu, Rucong, Tianjun Zhou, Tongwen Wu, Wei Xue, and Guangqing Zhou. Development and Evaluation of High Resolution Climate System Models. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0033-1.

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Hay, John E. Vulnerability & adaptation: Evaluation and regional synthesis of national assessments of vulnerability and adaptation to climate change. Apia, Samoa: South Pacific Regional Environment Programme, 2000.

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Organisation for economic co-operation and development. National climate change adaptation: Emerging practices in monitoring and evaluation. Paris: OECD Publishing, 2015.

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Veeraraghavan, Vimala. Organisational climate and performance of schools. New Delhi: Blaze Publishers & Distributors, 1992.

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Smit, Barry. Implications of climatic change for agriculture in Ontario : a summary of Land Evaluation Group reports =: Conséquences du changement climatique sur l'agriculture en Ontario : résumé des rapports du Land Evaluation Group. Ottawa, Ont: Environment Canada = Environnement Canada, 1987.

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A climate of corporate control: How corporations have influenced the U.S. dialogue on climate science and policy. Cambridge, MA: Union of Concerned Scientists, 2012.

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United, States Congress House Committee on Science Space and Technology (2011). Examining the U.N. Intergovernmental Panel on Climate Change process: Hearing before the Committee on Science, Space, and Technology, House of Representatives, One Hundred Thirteenth Congress, second session, May 29, 2014. Washington: U.S. Government Printing Office, 2014.

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Book chapters on the topic "Climate evaluation"

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Posaner, Joshua. "Evaluation." In Energiepolitik und Klimaschutz. Energy Policy and Climate Protection, 233–48. Wiesbaden: Springer Fachmedien Wiesbaden, 2019. http://dx.doi.org/10.1007/978-3-658-27518-1_8.

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Livezey, Robert E. "The Evaluation of Forecasts." In Analysis of Climate Variability, 177–96. Berlin, Heidelberg: Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/978-3-662-03167-4_10.

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Livezey, Robert E. "The Evaluation of Forecasts." In Analysis of Climate Variability, 179–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-662-03744-7_10.

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Formayer, Herbert, Imran Nadeem, and Ivonne Anders. "Climate Change Scenario: From Climate Model Ensemble to Local Indicators." In Economic Evaluation of Climate Change Impacts, 55–74. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12457-5_5.

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Ferguson, Daniel B., Melissa L. Finucane, Victoria W. Keener, and Gigi Owen. "Evaluation to advance science policy: lessons from Pacific RISA and CLIMAS." In Climate in Context, 215–34. Chichester, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118474785.ch10.

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Bachner, Gabriel, Birgit Bednar-Friedl, Stefan Nabernegg, and Karl W. Steininger. "Economic Evaluation Framework and Macroeconomic Modelling." In Economic Evaluation of Climate Change Impacts, 101–20. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12457-5_7.

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Watkiss, Paul. "The Cost of Climate Change in Europe." In Economic Evaluation of Climate Change Impacts, 9–27. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12457-5_2.

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Hassan, Maya, and Hui Xie. "Evaluation and Management Approaches." In Climate Change and Conservation of Coastal Built Heritage, 41–73. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-8672-5_2.

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Dalri-Cecato, Leonardo, André Aguiar Battistelli, and Flávio Rubens Lapolli. "CAPEX and OPEX Evaluation of a Membrane Bioreactor Aiming at Water Reuse." In Climate Change Management, 137–52. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-57235-8_12.

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Steininger, Karl W. "Introduction." In Economic Evaluation of Climate Change Impacts, 1–6. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12457-5_1.

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Conference papers on the topic "Climate evaluation"

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Aloysius, Daisy, Mohd Yusrie Abdullah, Nurfaeziane Nordin, Ailen Ganing, and Jiro Iguchi. "Evaluation of International Technology Transfer for Climate Change Action in Sabah, Malaysia." In International Conference on Climate Change. The International Institute of Knowledge Management - TIIKM, 2019. http://dx.doi.org/10.17501/2513258x.2019.3104.

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Krarti, Moncef. "Evaluation of the Energy Efficiency Effectiveness of Cool Roofs for Residential Applications." In ASME 2014 8th International Conference on Energy Sustainability collocated with the ASME 2014 12th International Conference on Fuel Cell Science, Engineering and Technology. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/es2014-6613.

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Abstract:
This study determines the effects of cool roofs on a home’s energy use, specifically on heating and cooling energy end-uses. Representative cities were chosen for several ASHRAE US climate zones. A series of parametric simulations in EnergyPlus was carried out to assess the performance of cool roofs for selected prototypical residential building models using detailed simulation analysis. The simulation results are then correlated for each climate zone type to give an approximation of the best roof color per climate. The results are given based on total energy used as well as energy cost based on national average electricity and natural gas residential rates. This method allows builders and homeowners the choice between the most cost effective roofing type, and the most energy efficient in the case that they are not the same. Overall, it was found that in hot climates, it is more efficient to have a white roof, while a black roof benefits cooler climates. In mild and mixed climates, the effect of roof color was found rather are different for energy use and energy cost. Therefore the choice is determined by the owner’s requirements. In the cooler and milder climate zones, the analysis shows that the cost excess or savings is fairly small; usually under $10 difference per year. Hotter climates also have a relatively small effect, but more so than the cooler climates, with Phoenix especially showing a savings of $48.60 per year when a white roof is used over a black roof. Energy changes as low as only 4% in the as-built construction style, or as high as nearly 100% change in upgraded envelope cases were found. The study further finds that both the lack of an attic, and high efficiency envelopes increases the magnitude of the percent change in energy requirements.
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"Evaluation of Algal Biomass Production on Vertical Membranes." In ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152136528.

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"Evaluation of climate change impact on drought in Virginia." In ASABE 1st Climate Change Symposium: Adaptation and Mitigation. American Society of Agricultural and Biological Engineers, 2015. http://dx.doi.org/10.13031/cc.20152124181.

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Moultanovsky, Alexander V., and Brett Herrmann. "New Approach to Climate Control System Components Evaluation." In SAE 2001 World Congress. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2001. http://dx.doi.org/10.4271/2001-01-0590.

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Hart, Andrew F., Cameron E. Goodale, Chris A. Mattmann, Paul Zimdars, Dan Crichton, Peter Lean, Jinwon Kim, and Duane Walise. "A cloud-enabled regional climate model evaluation system." In Proceeding of the 2nd international workshop. New York, New York, USA: ACM Press, 2011. http://dx.doi.org/10.1145/1985500.1985508.

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Wolff, W., M. V. Folegatti, and D. L. Flumignan. "LYSIMETRIC EVALUATION OF SEBAL ALGORITHM IN SUBTROPICAL CLIMATE." In IV Inovagri International Meeting. Fortaleza, Ceará, Brasil: INOVAGRI/ESALQ-USP/ABID/UFRB/INCT-EI/INCTSal/INSTITUTO FUTURE, 2017. http://dx.doi.org/10.7127/iv-inovagri-meeting-2017-res1990350.

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Grege-Staltmane, Evija. "Development of Evaluation Methodology for Carbon Dioxide Emissions in Production Processes." In INTERNATIONAL SCIENTIFIC CONFERENCE ''ENVIRONMENTAL AND CLIMATE TECHNOLOGIES 2013. Riga: Riga Technical University, 2013. http://dx.doi.org/10.7250/iscect.2013.006.

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Herath, H. M. R. C., and I. M. S. P. Jayawardena. "EVALUATION OF DOWNSCALED CMIP5 CLIMATE MODELS TO SELECT THE BEST MODELS TO DEVELOP FUTURE CLIMATE SCENARIOS FOR SRI LANKA." In The International Conference on Climate Change. The International Institute of Knowledge Management (TIIKM), 2018. http://dx.doi.org/10.17501/iccc.2017.1204.

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Watson, S. L. "Evaluation of Production Loans for Gas Properties in Today's Economic Climate." In SPE Hydrocarbon Economics and Evaluation Symposium. Society of Petroleum Engineers, 1985. http://dx.doi.org/10.2118/13791-ms.

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Reports on the topic "Climate evaluation"

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Osser, R., and P. Kerrigan. Performance Evaluation of a Hot-Humid Climate Community. Office of Scientific and Technical Information (OSTI), February 2012. http://dx.doi.org/10.2172/1036389.

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Osser, R., and P. Kerrigan. Performance Evaluation of a Hot-Humid Climate Community. Office of Scientific and Technical Information (OSTI), February 2012. http://dx.doi.org/10.2172/1219553.

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Aceves-Saborio, S., and W. J. III Comfort. Load calculation and system evaluation for electric vehicle climate control. Office of Scientific and Technical Information (OSTI), October 1993. http://dx.doi.org/10.2172/10146054.

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Gettelman, Andrew. Advancing Models and Evaluation of Cumulus, Climate and Aerosol Interactions. Office of Scientific and Technical Information (OSTI), October 2015. http://dx.doi.org/10.2172/1224210.

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Goulder, Lawrence, and Roberton Williams. The Choice of Discount Rate for Climate Change Policy Evaluation. Cambridge, MA: National Bureau of Economic Research, August 2012. http://dx.doi.org/10.3386/w18301.

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Dixon, Jason. An Evaluation of Unsaturated Flow Models in an Arid Climate. Office of Scientific and Technical Information (OSTI), December 1999. http://dx.doi.org/10.2172/759261.

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Zhang, Chengzhu, Shaocheng Xie, and Cheng Tao. ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation. Office of Scientific and Technical Information (OSTI), October 2020. http://dx.doi.org/10.2172/1396238.

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Li, Zhijin, Feng Sha, Yangang Liu, Wuyin Lin, Tami Toto, and Andrew Vogelmann. Continuous Evaluation of Fast Processes in Climate Models Using ARM Measurements. Office of Scientific and Technical Information (OSTI), February 2016. http://dx.doi.org/10.2172/1236661.

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Zhang, Minghua. Continuous Evaluation of Fast Processes in Climate Models Using Arm Measurements. Office of Scientific and Technical Information (OSTI), January 2015. http://dx.doi.org/10.2172/1166903.

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MUKUTE, MUTIZWA, JOHN COLVIN, and ARISTIDES BALOI. Africa Climate Change Resilience Alliance: Phase 2 Synthesis Evaluation, final report. Oxfam; Care; Save the Children; World Vision; Overseas Development Institute, June 2017. http://dx.doi.org/10.21201/2017.0087.

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