Journal articles: 'Climate for transfer'

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Platt, Daniel E. "Investment Climate Stunts Tech Transfer." Physics Today 46, no. 7 (July 1993): 11–13. http://dx.doi.org/10.1063/1.2808954.

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Gibbins, Goodwin, and Joanna D. Haigh. "Entropy Production Rates of the Climate." Journal of the Atmospheric Sciences 77, no. 10 (October 1, 2020): 3551–66. http://dx.doi.org/10.1175/jas-d-19-0294.1.

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AbstractThere is ongoing interest in the global entropy production rate as a climate diagnostic and predictor, but progress has been limited by ambiguities in its definition; different conceptual boundaries of the climate system give rise to different internal production rates. Three viable options are described, estimated, and investigated here, two—the material and the total radiative (here “planetary”) entropy production rates—that are well established and a third that has only recently been considered but appears very promising. This new option is labeled the “transfer” entropy production rate and includes all irreversible processes that transfer heat within the climate, radiative, and material, but not those involved in the exchange of radiation with space. Estimates in three model climates put the material rate in the range 27–48 mW m−2 K−1, the transfer rate at 67–76 mW m−2 K−1, and the planetary rate at 1279–1312 mW m−2 K−1. The climate relevance of each rate is probed by calculating their responses to climate changes in a simple radiative–convective model. An increased greenhouse effect causes a significant increase in the material and transfer entropy production rates but has no direct impact on the planetary rate. When the same surface temperature increase is forced by changing the albedo instead, the material and transfer entropy production rates increase less dramatically and the planetary rate also registers an increase. This is pertinent to solar radiation management as it demonstrates the difficulty of reversing greenhouse gas–mediated climate changes by albedo alterations. It is argued that the transfer perspective has particular significance in the climate system and warrants increased prominence.

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Song In Ok and Dongsoo Song. "CBDR and Climate Technology Transfer to cope with Climate Change." Journal of hongik law review 20, no. 2 (June 2019): 419–54. http://dx.doi.org/10.16960/jhlr.20.2.201906.419.

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Duncan, Richard P., Phillip Cassey, and Tim M. Blackburn. "Do climate envelope models transfer? A manipulative test using dung beetle introductions." Proceedings of the Royal Society B: Biological Sciences 276, no. 1661 (February 25, 2009): 1449–57. http://dx.doi.org/10.1098/rspb.2008.1801.

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Climate envelope models (CEMs) are widely used to forecast future shifts in species ranges under climate change, but these models are rarely validated against independent data, and their fundamental assumption that climate limits species distributions is rarely tested. Here, we use the data on the introduction of five South African dung beetle species to Australia to test whether CEMs developed in the native range can predict distribution in the introduced range, where the confounding effects of dispersal limitation, resource limitation and the impact of natural enemies have been removed, leaving climate as the dominant constraint. For two of the five species, models developed in the native range predict distribution in the introduced range about as well as models developed in the introduced range where we know climate limits distribution. For the remaining three species, models developed in the native range perform poorly, implying that non-climatic factors limit the native distribution of these species and need to be accounted for in species distribution models. Quantifying relevant non-climatic factors and their likely interactions with climatic variables for forecasting range shifts under climate change remains a challenging task.

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Sáenz-Romero, Cuauhtémoc, Antoine Kremer, László Nagy, Éva Újvári-Jármay, Alexis Ducousso, Anikó Kóczán-Horváth, Jon Kehlet Hansen, and Csaba Mátyás. "Common garden comparisons confirm inherited differences in sensitivity to climate change between forest tree species." PeerJ 7 (January 15, 2019): e6213. http://dx.doi.org/10.7717/peerj.6213.

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The natural distribution, habitat, growth and evolutionary history of tree species are strongly dependent on ecological and genetic processes in ecosystems subject to fluctuating climatic conditions, but there have been few experimental comparisons of sensitivity between species. We compared the responses of two broadleaved tree species (Fagus sylvatica and Quercus petraea) and two conifer tree species (Pinus sylvestris and Picea abies) to climatic transfers by fitting models containing the same climatic variables. We used published data from European provenance test networks to model the responses of individual populations nested within species. A mixed model approach was applied to develop a response function for tree height over climatic transfer distance, taking into account the climatic conditions at both the seed source and the test location. The two broadleaved species had flat climatic response curves, indicating high levels of plasticity in populations, facilitating adaptation to a broader range of environments, and conferring a high potential for resilience in the face of climatic change. By contrast, the two conifer species had response curves with more pronounced slopes, indicating a lower resilience to climate change. This finding may reflect stronger genetic clines in P. sylvestris and P. abies, which constrain their climate responses to narrower climatic ranges. The response functions had maxima that deviated from the expected maximum productivity in the climate of provenance towards cooler/moister climate conditions, which we interpreted as an adaptation lag. Unilateral, linear regression analyses following transfer to warmer and drier sites confirmed a decline in productivity, predictive of the likely impact of ongoing climate change on forest populations. The responses to mimicked climate change evaluated here are of considerable interest for forestry and ecology, supporting projections of expected performance based on “real-time” field data.

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Landis, Florian, and Thomas Bernauer. "Transfer payments in global climate policy." Nature Climate Change 2, no. 8 (June 3, 2012): 628–33. http://dx.doi.org/10.1038/nclimate1548.

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Macdonald, Gordon J. "Technology Transfer: The Climate Change Challenge." Journal of Environment & Development 1, no. 1 (July 1992): 1–39. http://dx.doi.org/10.1177/107049659200100103.

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Forsyth, Timothy. "Flexible Mechanisms of Climate Technology Transfer." Journal of Environment & Development 8, no. 3 (September 1999): 238–57. http://dx.doi.org/10.1177/107049659900800303.

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9

Wu, Jin. "Moisture-transfer coefficient for climate models." Boundary-Layer Meteorology 77, no. 3-4 (February 1996): 401–7. http://dx.doi.org/10.1007/bf00123535.

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Bennett, Joel B., Wayne E. K. Lehman, and Jamie K. Forst. "Change, Transfer Climate, and Customer Orientation." Group & Organization Management 24, no. 2 (June 1999): 188–216. http://dx.doi.org/10.1177/1059601199242004.

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Govindarajulu, Nalini. "Transfer climate in end‐user computing." Journal of Advances in Management Research 6, no. 1 (April 3, 2009): 87–98. http://dx.doi.org/10.1108/09727980910972181.

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Wen, Melody Ling-Yu, and Danny Yung-Chuan Lin. "How supportive Transfer Climate Affects Individual’s Motivation to Training Transfer." International Journal of Learning and Development 4, no. 1 (February 26, 2014): 83. http://dx.doi.org/10.5296/ijld.v4i1.5074.

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Rouiller, Janice Z., and Irwin L. Goldstein. "The relationship between organizational transfer climate and positive transfer of training." Human Resource Development Quarterly 4, no. 4 (1993): 377–90. http://dx.doi.org/10.1002/hrdq.3920040408.

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Ohlwein, Christian, and Eugene R. Wahl. "Review of probabilistic pollen-climate transfer methods." Quaternary Science Reviews 31 (January 2012): 17–29. http://dx.doi.org/10.1016/j.quascirev.2011.11.002.

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15

Forsyth, Tim. "Technology Transfer and the Climate Change Debate." Environment: Science and Policy for Sustainable Development 40, no. 9 (November 1998): 16–20. http://dx.doi.org/10.1080/00139159809605098.

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Flamos, Alexandros, and Katherine Begg. "Technology transfer insights for new climate regime." Environment, Development and Sustainability 12, no. 1 (December 9, 2008): 19–33. http://dx.doi.org/10.1007/s10668-008-9177-9.

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Kypreos, Socrates, and Hal Turton. "Climate change scenarios and Technology Transfer Protocols." Energy Policy 39, no. 2 (February 2011): 844–53. http://dx.doi.org/10.1016/j.enpol.2010.11.003.

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Helama, S., N. G. Makarenko, L. M. Karimova, O. A. Kruglun, M. Timonen, J. Holopainen, J. Meriläinen, and M. Eronen. "Dendroclimatic transfer functions revisited: Little Ice Age and Medieval Warm Period summer temperatures reconstructed using artificial neural networks and linear algorithms." Annales Geophysicae 27, no. 3 (March 4, 2009): 1097–111. http://dx.doi.org/10.5194/angeo-27-1097-2009.

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Abstract. Tree-rings tell of past climates. To do so, tree-ring chronologies comprising numerous climate-sensitive living-tree and subfossil time-series need to be "transferred" into palaeoclimate estimates using transfer functions. The purpose of this study is to compare different types of transfer functions, especially linear and nonlinear algorithms. Accordingly, multiple linear regression (MLR), linear scaling (LSC) and artificial neural networks (ANN, nonlinear algorithm) were compared. Transfer functions were built using a regional tree-ring chronology and instrumental temperature observations from Lapland (northern Finland and Sweden). In addition, conventional MLR was compared with a hybrid model whereby climate was reconstructed separately for short- and long-period timescales prior to combining the bands of timescales into a single hybrid model. The fidelity of the different reconstructions was validated against instrumental climate data. The reconstructions by MLR and ANN showed reliable reconstruction capabilities over the instrumental period (AD 1802–1998). LCS failed to reach reasonable verification statistics and did not qualify as a reliable reconstruction: this was due mainly to exaggeration of the low-frequency climatic variance. Over this instrumental period, the reconstructed low-frequency amplitudes of climate variability were rather similar by MLR and ANN. Notably greater differences between the models were found over the actual reconstruction period (AD 802–1801). A marked temperature decline, as reconstructed by MLR, from the Medieval Warm Period (AD 931–1180) to the Little Ice Age (AD 1601–1850), was evident in all the models. This decline was approx. 0.5°C as reconstructed by MLR. Different ANN based palaeotemperatures showed simultaneous cooling of 0.2 to 0.5°C, depending on algorithm. The hybrid MLR did not seem to provide further benefit above conventional MLR in our sample. The robustness of the conventional MLR over the calibration, verification and reconstruction periods qualified it as a reasonable transfer function for our forest-limit (i.e., timberline) dataset. ANN appears a potential tool for other environments and/or proxies having more complex and noisier climatic relationships.

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Jaidev, Uma Pricilda. "Transfer climate and transfer of training: the mediating role of transfer intention in hospitality organisations." International Journal of Services and Operations Management 31, no. 1 (2018): 19. http://dx.doi.org/10.1504/ijsom.2018.094181.

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Jaidev, Uma Pricilda. "Transfer climate and transfer of training: the mediating role of transfer intention in hospitality organisations." International Journal of Services and Operations Management 31, no. 1 (2018): 19. http://dx.doi.org/10.1504/ijsom.2018.10015169.

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21

Peters, Stéphanie, Michel Cossette, Reid Bates, Edward Holton, Isabelle Hansez, and Daniel Faulx. "The Influence of Transfer Climate and Job Attitudes on the Transfer Process." Journal of Personnel Psychology 13, no. 4 (January 2014): 157–66. http://dx.doi.org/10.1027/1866-5888/a000109.

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This study investigates the impact job satisfaction, job involvement, organizational commitment, and transfer climate on the training transfer process. Training transfer refers to the application of the new learning and to performance at work. A two-time data collection was implemented among employees of a public health insurance company who attended professional training programs (N = 118). Data analysis revealed that (1) job involvement negatively influenced transfer, (2) peer support positively influenced transfer, (3) openness to change had a negative relationship with transfer, and (4) these three predictors have an indirect effect on performance at work.

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James, Mark Andrew. "Transfer climate and EAP education: Students’ perceptions of challenges to learning transfer." English for Specific Purposes 29, no. 2 (April 2010): 133–47. http://dx.doi.org/10.1016/j.esp.2009.09.002.

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23

Pleško, Nada. "Climatotherapeutic possibilities of Croatia." Tourism and hospitality management 2, no. 2 (December 30, 1996): 325–36. http://dx.doi.org/10.20867/thm.2.2.9.

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Today is obvious course in the world to select the favourable climate for the climatotherapeutic treatment of certain diseases, and such areas are known as climatic health resorts. The four main areas were selected for climatotherapy: -areas along the coast (thalassotherapy), -areas surrounding thermal springs (balneotherapy), -mountainous, not windy, areas (high altitude therapy). -A fourth possibility for climatotherapy is transfer of large groups of people from unfavourable climates to areas with favourable ones. Republic of Croatia is rich with regions of favourable climates for all four kinds of climatotherapy and health tourism, especially if we include still yet a clean air and clean sea. A proof for climatic conditions quality can provide only the long time performed meteorological measurements at places of interest. hi the article are discussed meteorological indices, today most frequently used in Croatia, for a bioclimate estimation, and a content of "CLIMATE AND BIOCLIMATE REVIEW (PROSPECT)". Such prospects could be made for many places with tradition in climatotherapy and they are quoted. "Climate and bioclimate review" gives to doctors, patients or tourists detail information about a climate for each ten days during the year, and about a bioclimate additionally for morning, midday and evening. Prospect enables to choice, in dependence of health state, a most suitable period for coming to Croatia, and also comprises information useful for nautical navigation and for a health resort economic management.

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Chauhan, Dr Pardeep S. "A Study of Barriers to Climate Change Technology Innovation and Its Transfer to Developing Countries." Indian Journal of Applied Research 1, no. 1 (October 1, 2011): 10–12. http://dx.doi.org/10.15373/2249555x/oct2011/4.

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M., Srimannarayana. "An Exploratory Study of Training Transfer Climate in India." International Journal of Business and Management 11, no. 8 (July 20, 2016): 263. http://dx.doi.org/10.5539/ijbm.v11n8p263.

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<p>The purpose of this paper is to explore the extent of training transfer climate prevailing in Indian organizations and find out the differences in the perception of employees based on organizational and respondents’ characteristics. The data collected from 2,778 employees working in 70 different organizations across India using a survey questionnaire formed the basis for analysis. The study found that the overall training transfer climate prevailing in India was moderate, leaving a room for improvement, particularly in the areas, supervisor sanctions and positive personal outcomes when learning is transferred on the job. It further found that the companies in the service sector, privately owned joint ventures, Indian multinational companies and small organizations could do better in creating transfer climate than their counterparts. Further, it was found that the higher the levels of education, the higher the perception of transfer climate. Also, the higher the experience, the higher the perception of transfer climate.</p>

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Boucher, É., J. Guiot, C. Hatté, V. Daux, P. A. Danis, and P. Dussouillez. "An inverse modeling approach for tree-ring-based climate reconstructions under changing atmospheric CO<sub>2</sub> concentrations." Biogeosciences Discussions 10, no. 11 (November 28, 2013): 18479–514. http://dx.doi.org/10.5194/bgd-10-18479-2013.

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Abstract. Over the last decades, dendroclimatologists have relied upon linear transfer functions to reconstruct historical climate. Transfer functions need to be calibrated using recent data from periods where CO2 concentrations reached unprecedented levels (near 400 ppm). Based on these transfer functions, dendroclimatologists must then reconstruct a different past, a past where CO2 concentrations were much below 300 ppm. However, relying upon transfer functions calibrated in this way may introduce an unanticipated bias in the reconstruction of past climate, particularly if CO2 levels have had a noticeable fertilizing effect since the beginning of the industrial era. As an alternative to the transfer function approach, we run the MAIDENiso ecophysiological model in an inverse mode to link together climatic variables, atmospheric CO2 concentrations and tree growth parameters. Our approach endeavors to find the optimal combination of meteorological conditions that best simulate observed tree ring patterns. We test our approach in the Fontainebleau forest (France). By comparing two different CO2 scenarios, we present evidence that increasing CO2 concentrations have had a slight, yet significant, effect on reconstruction results. We demonstrate that higher CO2 concentrations augment the efficiency of water use by trees, therefore favoring the reconstruction of a warmer and drier climate. Under elevated CO2 concentrations, trees close their stomata and need less water to produce the same amount of wood. Inverse process-based modeling represents a powerful alternative to the transfer function technique, especially for the study of divergent tree-ring-to-climate relationships. The approach has several advantages, most notably its ability to distinguish between climatic effects and CO2 imprints on tree growth. Therefore our method produces reconstructions that are less biased by anthropogenic greenhouse gas emissions and that are based on sound ecophysiological knowledge.

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Shue, Henry. "Climate dreaming: negative emissions, risk transfer, and irreversibility." Journal of Human Rights and the Environment 8, no. 2 (September 2017): 203–16. http://dx.doi.org/10.4337/jhre.2017.02.02.

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Henderson, S., and SR Holman. "Global climate change education: technology transfer to schools." Climate Research 3 (1993): 137–40. http://dx.doi.org/10.3354/cr003137.

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Glachant, Matthieu, and Antoine Dechezleprêtre. "What role for climate negotiations on technology transfer?" Climate Policy 17, no. 8 (November 25, 2016): 962–81. http://dx.doi.org/10.1080/14693062.2016.1222257.

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Holton, Elwood F., Reid A. Bates, Dian L. Seyler, and Manuel B. Carvalho. "Toward construct validation of a transfer climate instrument." Human Resource Development Quarterly 8, no. 2 (1997): 95–113. http://dx.doi.org/10.1002/hrdq.3920080203.

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Maharmeh, Thamer Mohammed. "Organizational Climate and Transfer of Training in a Public Corporation in Qatar." International Journal of Research and Studies Publishing 2, no. 20 (June 20, 2021): 131–62. http://dx.doi.org/10.52133/ijrsp.v2.20.4.

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The current research investigates the association between organizational climate and training transfer in case of a Qatari public corporation. It seeks to enhance training transfer through improving the organizational climate. To meet the objectives of the research, survey was developed and distributed to all employees who work for the selected corporation. (152) surveys were returned and analyzed by using SPSS. Results of data analysis revealed that there are positive attitudes towards transfer of training. In other words, employees believe that training influences their performance and behavior. Besides, employees transfer what they learned in training into their workplace. It was also found that employees perceive the overall organizational climate and the dimensions of organizational climate positively. This gives indicator of positive attitudes and perceptions of organizational climate. Regarding the relationship between the dimensions of organizational climate and transfer of training, results of data analysis revealed that there are strong and positive relationships between employee perceptions of eight dimensions of organizational climate and transfer of training into the workplace. It was found that there were positive and strong relationships between employee perceptions of support, responsibility, structure, conflict, identity, warmth, support, and risk on one hand, and their perceptions of training transfer on the other hand. Still, the relationship employee perceptions of rewards and their perceptions of training transfer was weak and not significant.

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Mueller, Valerie, Clark Gray, Sudhanshu Handa, and David Seidenfeld. "Do social protection programs foster short-term and long-term migration adaptation strategies?" Environment and Development Economics 25, no. 2 (August 1, 2019): 135–58. http://dx.doi.org/10.1017/s1355770x19000214.

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AbstractWe examine how migration is influenced by temperature and precipitation variability, and the extent to which the receipt of a cash transfer affects the use of migration as an adaptation strategy. Climate data is merged with georeferenced panel data (2010–2014) on individual migration collected from the Zambian Child Grant Program (CGP) sites. We use the person-year dataset to identify the direct and heterogeneous causal effects of the CGP on mobility. Having access to cash transfers doubles the rate of male, short-distance moves during cool periods, irrespective of wealth. Receipt of cash transfers (among wealthier households) during extreme heat causes an additional retention of males. Cash transfers positively spur long-distance migration under normal climate conditions in the long term. They also facilitate short-distance responses to climate, but not long-distance responses that might be demanded by future climate change.

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Mátyás, Csaba, František Beran, Jaroslav Dostál, Jiří Čáp, Martin Fulín, Monika Vejpustková, Gregor Božič, Pál Balázs, and Josef Frýdl. "Surprising Drought Tolerance of Fir (Abies) Species between Past Climatic Adaptation and Future Projections Reveals New Chances for Adaptive Forest Management." Forests 12, no. 7 (June 22, 2021): 821. http://dx.doi.org/10.3390/f12070821.

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Research Highlights: Data of advanced-age provenance tests were reanalyzed applying a new approach, to directly estimate the growth of populations at their original sites under individually generated future climates. The results revealed the high resilience potential of fir species. Background and Objectives: The growth and survival of silver fir under future climatic scenarios are insufficiently investigated at the xeric limits. The selective signature of past climate determining the current and projected growth was investigated to analyze the prospects of adaptive silviculture and assisted transfer of silver fir populations, and the introduction of non-autochthonous species. Materials and Methods: Hargreaves’ climatic moisture deficit was selected to model height responses of adult populations. Climatic transfer distance was used to assess the relative drought stress of populations at the test site, relating these to the past conditions to which the populations had adapted. ClimateEU and ClimateWNA pathway RCP8.5 data served to determine individually past, current, and future moisture deficit conditions. Besides silver fir, other fir species from South Europe and the American Northwest were also tested. Results: Drought tolerance profiles explained the responses of transferred provenances and predicted their future performance and survival. Silver fir displayed significant within-species differentiation regarding drought stress response. Applying the assumed drought tolerance limit of 100 mm relative moisture deficit, most of the tested silver fir populations seem to survive their projected climate at their origin until the end of the century. Survival is likely also for transferred Balkan fir species and for grand fir populations, but not for the Mediterranean species. Conclusions: The projections are less dramatic than provided by usual inventory assessments, considering also the resilience of populations. The method fills the existing gap between experimentally determined adaptive response and the predictions needed for management decisions. It also underscores the unique potential of provenance tests.

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Lee, Woo Jin, Irma Juskenaite, and Rose Mwebaza. "Public–Private Partnerships for Climate Technology Transfer and Innovation: Lessons from the Climate Technology Centre and Network." Sustainability 13, no. 6 (March 15, 2021): 3185. http://dx.doi.org/10.3390/su13063185.

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The 2030 Agenda for Sustainable Development and the Sustainable Development Goals (SDGs), the Paris Agreement, and a number of important agreements call on the United Nations (UN) to strengthen a relationship with the private sector to develop and transfer climate technology in global action on climate change. The Technology Mechanism (TM) is anchored in the UN Framework Convention on Climate Change as a key enabler for the attainment of the Goals of the Paris Agreement. The growing interest for collaboration with the private sector sets new ambitions for the UN Climate Technology Centre and Network (CTCN). The active engagement of the private sector is critical for successful technology transfer and successful innovation. This paper reviews and analyses the role of the private sector in facilitating technology transfer in CTCN’s Technical Assistance. Furthermore, the shared interest for partnership between the CTCN and the private sector was evaluated by analysing in-depths interviews with major CTCN stakeholders. Based upon this analysis, several recommendations are made on how to enhance public–private partnerships in order to strengthen private sector participation in climate technology transfer activities with a special focus on technology–push and market–pull innovation.

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Das, D., J. Dy, J. Ross, Z. Obradovic, and A. R. Ganguly. "Non-parametric Bayesian mixture of sparse regressions with application towards feature selection for statistical downscaling." Nonlinear Processes in Geophysics Discussions 1, no. 1 (April 11, 2014): 615–48. http://dx.doi.org/10.5194/npgd-1-615-2014.

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Abstract. Climate projections simulated by Global Climate Models (GCM) are often used for assessing the impacts of climate change. However, the relatively coarse resolutions of GCM outputs often precludes their application towards accurately assessing the effects of climate change on finer regional scale phenomena. Downscaling of climate variables from coarser to finer regional scales using statistical methods are often performed for regional climate projections. Statistical downscaling (SD) is based on the understanding that the regional climate is influenced by two factors – the large scale climatic state and the regional or local features. A transfer function approach of SD involves learning a regression model which relates these features (predictors) to a climatic variable of interest (predictand) based on the past observations. However, often a single regression model is not sufficient to describe complex dynamic relationships between the predictors and predictand. We focus on the covariate selection part of the transfer function approach and propose a nonparametric Bayesian mixture of sparse regression models based on Dirichlet Process (DP), for simultaneous clustering and discovery of covariates within the clusters while automatically finding the number of clusters. Sparse linear models are parsimonious and hence relatively more generalizable than non-sparse alternatives, and lends to domain relevant interpretation. Applications to synthetic data demonstrate the value of the new approach and preliminary results related to feature selection for statistical downscaling shows our method can lead to new insights.

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Das, D., J. Dy, J. Ross, Z. Obradovic, and A. R. Ganguly. "Non-parametric Bayesian mixture of sparse regressions with application towards feature selection for statistical downscaling." Nonlinear Processes in Geophysics 21, no. 6 (December 1, 2014): 1145–57. http://dx.doi.org/10.5194/npg-21-1145-2014.

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Abstract. Climate projections simulated by Global Climate Models (GCMs) are often used for assessing the impacts of climate change. However, the relatively coarse resolutions of GCM outputs often preclude their application to accurately assessing the effects of climate change on finer regional-scale phenomena. Downscaling of climate variables from coarser to finer regional scales using statistical methods is often performed for regional climate projections. Statistical downscaling (SD) is based on the understanding that the regional climate is influenced by two factors – the large-scale climatic state and the regional or local features. A transfer function approach of SD involves learning a regression model that relates these features (predictors) to a climatic variable of interest (predictand) based on the past observations. However, often a single regression model is not sufficient to describe complex dynamic relationships between the predictors and predictand. We focus on the covariate selection part of the transfer function approach and propose a nonparametric Bayesian mixture of sparse regression models based on Dirichlet process (DP) for simultaneous clustering and discovery of covariates within the clusters while automatically finding the number of clusters. Sparse linear models are parsimonious and hence more generalizable than non-sparse alternatives, and lend themselves to domain relevant interpretation. Applications to synthetic data demonstrate the value of the new approach and preliminary results related to feature selection for statistical downscaling show that our method can lead to new insights.

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Prince, Melvin, David Burns, Xinyi Lu, and Robert Winsor. "Knowledge and skills transfer between MBA and workplace." Journal of Workplace Learning 27, no. 3 (April 13, 2015): 207–25. http://dx.doi.org/10.1108/jwl-06-2014-0047.

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Purpose – This paper aims to use goal-setting theory to explain the transfer of knowledge and skills between master of business administration (MBA) and the workplace. Design/methodology/approach – Data were obtained by an online survey of MBA students enrolled in at four US graduate business schools. These were a public and private institution in the Northeast region, a private sectarian institution in the Midwest region and a private institution in the Pacific region. All students worked while attending the university. The sampling frame consisted of each school’s MBA enrollees. Questionnaires were distributed to a random cross-section of part-time students at each graduate school of business representative of returned by 144 students. The profiles of responders were consistent with parameters for the entire MBA student population. Findings – The research shows that multiple goals of reciprocal knowledge and skills transfer may be in harmony and mutually reinforcing. In principle, each goal is more likely to be attained with greater economy of effort than might be surmised. Additionally, the same forces may act similarly to facilitate attainment of two well-integrated goals, in this case transfer between MBA studies and work, as well as between work and MBA studies. Research limitations/implications – The present study involved participants from part-time public and private MBA granting institutions in the USA. The study tested and extended goal-setting theory and introduced the innovative concept of reciprocal transfer. Future studies should seek to generalize the findings to a broader population of part-time MBA students, especially from other nations. Despite its strengths, the findings of this study need to be interpreted in the perspective of some limitations. The current study did not measure transfer climates in either the organization or university settings. Transfer climates undoubtedly have an important bearing on transfer outcomes. Practical implications – Review of the present study suggests that a positive MBA environment is needed to influence motivation to learn and perceptions of the MBA program’s utility, thereby promoting transfer of knowledge and skills to MBA studies from the workplace. A supportive work-to-MBA-studies transfer climate will lead to more active learning of course content that has greater relevance for achieving career goals. Potentially generalizable from the organizational transfer climate literature (Rouiller and Goldstein 1990; Rouiller and Goldstein 1993), positive transfer from work to MBA studies will occur when appropriate situational cues and consequences are present in the program. Social implications – A constructive implication suggested by the findings of this study would be the intervention and transfer management by educators to structure and strengthen the university transfer climate of their part-time MBA programs. Traditionally, the concept of transfer climate has been primarily applied to employee workplace training activity and job performance. The university culture of the MBA student might emphasize and reward continuous learning from workplace experiences. Opportunities at the university should be provided for the exercise of newly acquired workplace skills that reinforce MBA learning experiences. Originality/value – This is the first study that shows how learning goals and performance goals are integrated in the context of a new concept, i.e. reciprocal transfer of knowledge and skills between MBA and workplace settings. It also demonstrates, for the first time, the impact of learning and motivation for MBA studies and perceived utility of MBA program on the extent of transfer of learning and skills from the workplace to the university setting.

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Yulia, Yulia, and Reza Arlianda. "Climate Resilience and Policy Transfer in Semarang City, Indonesia." eTropic: electronic journal of studies in the tropics 19, no. 2 (December 21, 2020): 143–71. http://dx.doi.org/10.25120/etropic.19.2.2020.3767.

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Cities around the world are facing tremendous challenges due to climate change. Tropical cities are significantly impacted by temperature increases, higher than average global rising sea levels, and extreme weather events. In the tropical Asia-Pacific region effects from the El Niño-Southern Oscillation are especially severe, which, in turn, cause disasters such as floods and droughts. Climate change requires cooperation from actors across geopolitical borders to respond to the problem collectively, which involves global networks in the exchange of climate mitigation policies and adaptation plans through a process of policy transfer. This paper examines the processes of policy transfer between the tropical coastal city of Semarang in Indonesia and its global networks in the ‘100 Resilient Cities’, and the ‘Water as Leverage’ programs. The paper analyses interviews with actors and stakeholders from these two programs, and examines key factors that determine the success of the climate change policy transfer in Semarang City.

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Cruzado-Vargas, Ana Laura, Arnulfo Blanco-García, Roberto Lindig-Cisneros, Mariela Gómez-Romero, Leonel Lopez-Toledo, Erick de la Barrera, and Cuauhtémoc Sáenz-Romero. "Reciprocal Common Garden Altitudinal Transplants Reveal Potential Negative Impacts of Climate Change on Abies religiosa Populations in the Monarch Butterfly Biosphere Reserve Overwintering Sites." Forests 12, no. 1 (January 9, 2021): 69. http://dx.doi.org/10.3390/f12010069.

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Research Highlights: Reciprocal altitudinal transplants of Abies religiosa seedlings within the Monarch Butterfly Biosphere Reserve (MBBR) allow prediction of the impacts of climatic change, because they grow in sites with a climate that differs from that of their origin. Background and Objectives: Climatic change is generating a mismatch between the sites currently occupied by forest populations and the climate to which they have adapted. This study determined the effect on the survival and growth of A. religiosa seedlings of transfer to sites that were warmer or colder than that of the origin of their seeds. Materials and Methods: Eleven provenances of A. religiosa, collected along an altitudinal gradient (3000 to 3550 m a.s.l.), were assayed in common gardens in three sites of contrasting altitude: 3400, 3000 and 2600 m a.s.l. The results were evaluated by fitting a response curve with a mixed model. Results: The climate transfer distance for the seasonal balance between the temperature conducive to growth (degree days above 5 °C) and the available precipitation (a ratio expressed as dryness index) dominated the shape of the response function curve. The rainy season (June–October) dryness index transfer distance was critical for survival, while that of the cold and dry season (November–February) was critical for aerial biomass, and the annual index was critical for the increase in basal diameter. The effect of climatic transfer distance is much more negative (triggering about 45% mortality) when transfer is toward warmer and dryer sites (at 400 m lower in altitude, +1.9 °C warmer and 16% less precipitation), than when shifting toward colder and wetter sites (400 m higher in altitude, resulting in 95% survival). Conclusions: The projected higher temperatures and lower precipitation due to climatic change will undoubtedly cause severe mortality in young A. religiosa seedlings. A 400 m shift upwards in altitude to compensate for climatic change (assisted migration) appears to be a feasible management action.

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Cruzado-Vargas, Ana, Arnulfo Blanco-García, Roberto Lindig-Cisneros, Mariela Gómez-Romero, Leonel Lopez-Toledo, Erick de la Barrera, and Cuauhtémoc Sáenz-Romero. "Reciprocal Common Garden Altitudinal Transplants Reveal Potential Negative Impacts of Climate Change on Abies religiosa Populations in the Monarch Butterfly Biosphere Reserve Overwintering Sites." Forests 12, no. 1 (January 9, 2021): 69. http://dx.doi.org/10.3390/f12010069.

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Research Highlights: Reciprocal altitudinal transplants of Abies religiosa seedlings within the Monarch Butterfly Biosphere Reserve (MBBR) allow prediction of the impacts of climatic change, because they grow in sites with a climate that differs from that of their origin. Background and Objectives: Climatic change is generating a mismatch between the sites currently occupied by forest populations and the climate to which they have adapted. This study determined the effect on the survival and growth of A. religiosa seedlings of transfer to sites that were warmer or colder than that of the origin of their seeds. Materials and Methods: Eleven provenances of A. religiosa, collected along an altitudinal gradient (3000 to 3550 m a.s.l.), were assayed in common gardens in three sites of contrasting altitude: 3400, 3000 and 2600 m a.s.l. The results were evaluated by fitting a response curve with a mixed model. Results: The climate transfer distance for the seasonal balance between the temperature conducive to growth (degree days above 5 °C) and the available precipitation (a ratio expressed as dryness index) dominated the shape of the response function curve. The rainy season (June–October) dryness index transfer distance was critical for survival, while that of the cold and dry season (November–February) was critical for aerial biomass, and the annual index was critical for the increase in basal diameter. The effect of climatic transfer distance is much more negative (triggering about 45% mortality) when transfer is toward warmer and dryer sites (at 400 m lower in altitude, +1.9 °C warmer and 16% less precipitation), than when shifting toward colder and wetter sites (400 m higher in altitude, resulting in 95% survival). Conclusions: The projected higher temperatures and lower precipitation due to climatic change will undoubtedly cause severe mortality in young A. religiosa seedlings. A 400 m shift upwards in altitude to compensate for climatic change (assisted migration) appears to be a feasible management action.

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Gallagher, Kelly Sims. "China Needs Help with Climate Change." Current History 106, no. 703 (November 1, 2007): 389–94. http://dx.doi.org/10.1525/curh.2007.106.703.389.

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Rehfeldt, Gerald E., Nadja M. Tchebakova, and Leonard K. Barnhardt. "Efficacy of climate transfer functions: introduction of Eurasian populations of Larix into Alberta." Canadian Journal of Forest Research 29, no. 11 (December 1, 1999): 1660–68. http://dx.doi.org/10.1139/x99-143.

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Growth and survival of eight populations of Larix sukaczewii Dylis and one of both Larix sibirica Ledeb. and Larix gmelinii (Rupr.) Rupr. were used to assess the effectiveness of climate transfer functions for predicting the 13-year performance of Eurasian provenances introduced to Alberta. Quadratic regression models showed that transfer distances for five climate variables (mean annual temperature, degree-days <0°C, mean temperature in the coldest month, ratio of the mean annual temperature to mean annual precipitation, and the summer-winter temperature range) were particularly effective in predicting height and survival. Optimal transfer distances did not differ significantly from zero, and as a result, the best growth and survival in Alberta should be obtained by matching the provenance climate to that of the planting site for the five variables. Verification of the climate transfer functions with independent data from Russian provenance tests were strongly supportive. The results demonstrate the effectiveness of climate transfer functions for describing the response of plant populations to the environment and thereby have practical implications in reforestation.

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Keum, Hye-Jin, and Jae-sam Chung. ""Identifying of Relationship among Self efficacy, Metacognition, Learning Achievement, Transfer Climate and Near and Far Transfer in the Context of Corporate Training"." Journal of Educational Technology 23, no. 3 (September 30, 2007): 1–30. http://dx.doi.org/10.17232/kset.23.3.1.

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Son, Seung-Woo. "Intellectual Property and Technology Transfer in Climate Change Regime." Journal of Intellectual Property 5, no. 1 (March 31, 2010): 83–111. http://dx.doi.org/10.34122/jip.2010.03.5.1.83.

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Källander, Björn A. "Climate control in vacuum dryers for convective heat transfer." Wood Science and Technology 36, no. 6 (December 1, 2002): 477–86. http://dx.doi.org/10.1007/s00226-002-0154-4.

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K�llander, Bj�rn A. "Climate control in vacuum dryers for convective heat transfer." Wood Science and Technology 37, no. 1 (June 1, 2003): 3–9. http://dx.doi.org/10.1007/s00226-002-0159-z.

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Wen, Ruilin, Jule Xiao, Yuzhen Ma, Zhaodong Feng, Yuecong Li, and Qinghai Xu. "Pollen–climate transfer functions intended for temperate eastern Asia." Quaternary International 311 (October 2013): 3–11. http://dx.doi.org/10.1016/j.quaint.2013.04.025.

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Zingre, Kishor T., Man Pun Wan, Shanshan Tong, Hua Li, Victor W. C. Chang, Swee Khian Wong, Winston Boo Thian Toh, and Irene Yen Leng Lee. "Modeling of cool roof heat transfer in tropical climate." Renewable Energy 75 (March 2015): 210–23. http://dx.doi.org/10.1016/j.renene.2014.09.045.

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Wittneben, Bettina B. F. "Institutional Change in the Transfer of Climate-Friendly Technology." Business & Society 46, no. 1 (March 2007): 117–24. http://dx.doi.org/10.1177/0007650306295750.

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LIENHARD, JOHN H. "The Intellectual Climate of the Field of Heat Transfer." Heat Transfer Engineering 9, no. 4 (November 1988): 90–92. http://dx.doi.org/10.1080/01457638808939683.

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Journal articles on the topic 'Climate for transfer'

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