Journal articles: 'Regional climate'

1

Brown, Alastair. "Regional climate prediction." Nature Climate Change 5, no. 3 (February 25, 2015): 193. http://dx.doi.org/10.1038/nclimate2561.

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2

Laprise, René. "Regional climate modelling." Journal of Computational Physics 227, no. 7 (March 2008): 3641–66. http://dx.doi.org/10.1016/j.jcp.2006.10.024.

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3

McGregor, J. L. "Regional climate modelling." Meteorology and Atmospheric Physics 63, no. 1-2 (1997): 105–17. http://dx.doi.org/10.1007/bf01025367.

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4

Mieruch, S., S. Noël, H. Bovensmann, J. P. Burrows, and J. A. Freund. "Markov chain analysis of regional climates." Nonlinear Processes in Geophysics 17, no. 6 (November 19, 2010): 651–61. http://dx.doi.org/10.5194/npg-17-651-2010.

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Abstract. We present a novel method for regional climate classification that is based on coarse-grained categorical representations of multivariate climate anomalies and a subsequent Markov chain analysis. From the estimated transition matrix several descriptors, such as persistence, recurrence time and entropy, are derived. These descriptors characterise dynamic properties of regional climate anomalies and are connected with fundamental concepts from nonlinear physics like residence times, relaxation process and predictability. Such characteristics are useful for a comparative analysis of different climate regions and, in the context of global climate change, for a regime shift analysis. We apply the method to the bivariate set of water vapour and temperature anomalies of two regional climates, the Iberian Peninsula and the islands of Hawaii in the central Pacific Ocean. Through the Markov chain analysis and via the derived descriptors we find significant differences between the two climate regions. Since anomalies are departures from seasonal and long term components, these differences relate to differences in the short term stability of both regional climates.

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Rockel, Burkhardt, and Beate Geyer. "The performance of the regional climate model CLM in different climate regions, based on the example of precipitation." Meteorologische Zeitschrift 17, no. 4 (August 25, 2008): 487–98. http://dx.doi.org/10.1127/0941-2948/2008/0297.

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Rockel, Burkhard, Andreas Will, and Andreas Hense. "The Regional Climate Model COSMO-CLM (CCLM)." Meteorologische Zeitschrift 17, no. 4 (August 25, 2008): 347–48. http://dx.doi.org/10.1127/0941-2948/2008/0309.

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Schipper, Janus Willem, Julia Hackenbruch, Hilke Simone Lentink, and Katrin Sedlmeier. "Integrating Adaptation Expertise into Regional Climate Data Analyses through Tailored Climate Parameters." Meteorologische Zeitschrift 28, no. 1 (March 22, 2019): 41–57. http://dx.doi.org/10.1127/metz/2019/0878.

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8

Evans, Graeme. "REGIONAL SURVEY: CLIMATE CHANGE AND REGIONAL STUDIES." Regions Magazine 288, no. 1 (December 2012): 13–14. http://dx.doi.org/10.1080/13673882.2012.10636680.

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9

Kilcik, A. "Regional sun–climate interaction." Journal of Atmospheric and Solar-Terrestrial Physics 67, no. 16 (November 2005): 1573–79. http://dx.doi.org/10.1016/j.jastp.2005.09.003.

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10

McGregor, Helen. "Regional climate goes global." Nature Geoscience 11, no. 1 (January 2018): 18–19. http://dx.doi.org/10.1038/s41561-017-0046-8.

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11

Simeone, Reggie. "Global and regional climate." Weather 61, no. 12 (December 1, 2006): 361. http://dx.doi.org/10.1256/wea.173.06.

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12

DeGaetano, Arthur T., Timothy J. Brown, Steven D. Hilberg, Kelly Redmond, Kevin Robbins, Peter Robinson, Martha Shulski, and Marjorie McGuirk. "Toward Regional Climate Services." Bulletin of the American Meteorological Society 91, no. 12 (December 2010): 1633–44. http://dx.doi.org/10.1175/2010bams2936.1.

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13

Hackenbruch, Julia, Gerd Schädler, and Janus Willem Schipper. "Added value of high-resolution regional climate simulations for regional impact studies." Meteorologische Zeitschrift 25, no. 3 (June 20, 2016): 291–304. http://dx.doi.org/10.1127/metz/2016/0701.

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14

Tatarko, Alexander N., Ekaterina V. Maklasova, and Evert Van de Vliert. "Climato-Economic Context of Regional Crime and Corruption Across the Russian Federation." Environment and Behavior 54, no. 3 (December 17, 2021): 575–96. http://dx.doi.org/10.1177/00139165211060522.

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Cross-national research claims that the crime-and-corruption gap between relatively poor and relatively rich countries is larger in more demanding climates that require more cash and capital to cope with the climate. However, this claim is premature because countries differ in many confounding ways including histories and politics. We, therefore, re-tested the climato-economic context of violent crime and corruption within Russia, a country with considerable regional differences in climate and income. Across the eighty-five administrative units of Russia, the crime-and-corruption gap between relatively poor and relatively rich regions is smaller in more demanding climates. Harsher climates are so strongly associated with higher crime levels that the potential influence of differences in wealth becomes negligible. Furthermore, harsher climates are so strongly associated with higher corruption rates in poorer regions but lower corruption rates in richer regions that the potential influence of the climatic demands as such becomes negligible.

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15

Melikhova, Tamara. "INVESTMENT CLIMATE OF THE REGIONAL CENTERS OF UKRAINE." INTERNATIONAL JOURNAL OF NEW ECONOMICS, PUBLIC ADMINISTRATION AND LAW 1, no. 1 (May 15, 2018): 182–91. http://dx.doi.org/10.31264/2545-093x-2018-1(1)-182-191.

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16

Déqué, Michel. "Regional climate simulation with a mosaic of RCMs." Meteorologische Zeitschrift 19, no. 3 (June 1, 2010): 259–66. http://dx.doi.org/10.1127/0941-2948/2010/0455.

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17

Rockel, Burkhardt, Raymond Arritt, Markku Rummukainen, and Andreas Hense. "The 2nd Lund Regional-scale Climate Modelling Workshop." Meteorologische Zeitschrift 19, no. 4 (August 1, 2010): 323–24. http://dx.doi.org/10.1127/0941-2948/2010/0462.

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18

Giorgi, Filippo, and Andreas F. Prein. "Populated regional climate models (Pop-RCMs): The next frontier in regional climate modeling." PLOS Climate 1, no. 7 (July 13, 2022): e0000042. http://dx.doi.org/10.1371/journal.pclm.0000042.

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19

FUJII, Satoshi. "SURMOUNTING THE WATSUJI'S REGIONAL-SOCIAL CLIMATE THEORY TOWARD PRACTICAL REGIONAL-SOCIAL CLIMATE THEORY:." Doboku Gakkai Ronbunshuu D 62, no. 3 (2006): 334–50. http://dx.doi.org/10.2208/jscejd.62.334.

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20

Belda, Michal, Petr Skalák, Aleš Farda, Tomáš Halenka, Michel Déqué, Gabriella Csima, Judit Bartholy, et al. "CECILIA Regional Climate Simulations for Future Climate: Analysis of Climate Change Signal." Advances in Meteorology 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/354727.

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Regional climate models (RCMs) are important tools used for downscaling climate simulations from global scale models. In project CECILIA, two RCMs were used to provide climate change information for regions of Central and Eastern Europe. Models RegCM and ALADIN-Climate were employed in downscaling global simulations from ECHAM5 and ARPEGE-CLIMAT under IPCC A1B emission scenario in periods 2021–2050 and 2071–2100. Climate change signal present in these simulations is consistent with respective driving data, showing similar large-scale features: warming between 0 and 3°C in the first period and 2 and 5°C in the second period with the least warming in northwestern part of the domain increasing in the southeastern direction and small precipitation changes within range of +1 to −1 mm/day. Regional features are amplified by the RCMs, more so in case of the ALADIN family of models.

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21

Schär, Christoph, Christoph Frei, Daniel Lüthi, and Huw C. Davies. "Surrogate climate-change scenarios for regional climate models." Geophysical Research Letters 23, no. 6 (March 15, 1996): 669–72. http://dx.doi.org/10.1029/96gl00265.

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22

Xie, Shang-Ping. "Advancing climate dynamics toward reliable regional climate projections." Journal of Ocean University of China 12, no. 2 (April 27, 2013): 191–200. http://dx.doi.org/10.1007/s11802-013-2277-7.

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23

Larsén, Xiaoli Guo, Jakob Mann, Jacob Berg, Holger Göttel, and Daniela Jacob. "Wind climate from the regional climate model REMO." Wind Energy 13, no. 4 (May 2010): 279–96. http://dx.doi.org/10.1002/we.337.

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24

von Storch, Hans, and Insa Meincke. "Regional climate offices and regional assessment reports needed." Nature Geoscience 1, no. 2 (February 2008): 78. http://dx.doi.org/10.1038/ngeo111.

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25

DE, U. S. "Climate change impact : Regional scenario." MAUSAM 52, no. 1 (December 29, 2021): 201–12. http://dx.doi.org/10.54302/mausam.v52i1.1688.

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Climate change and global warming are going to be the major issues for the 21st century. Their impacts on agriculture, water availability and other natural resources are of serious concern. The paper briefly summarizes the existing information on global warming, past climatic anomalies and occurrence of extreme events vis-a-vis their impact on south Asia in general and Indian in particular. Use of GCM models in conjunction with crop simulation models for impact assessment in agriculture are briefly touched upon. The impact on hydrosphere in terms of water availability and on the forests in India are also discussed. A major shift in our policy makers paradigm is needed to make development sustainable in the face of climate change, global warming and sea level rise.

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26

Nazarova, Larisa. "Regional Climate Change (Karelia, Russia)." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 2 (August 5, 2015): 356. http://dx.doi.org/10.17770/etr2011vol2.991.

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The overview of climatic conditions in Karelia is based on the data from meteorological observations carried out in 1951-2009 at Roskomgidromet weather stations situated in the study area. Taking the period in question into account, the mean annual air temperature norm has increased by 0.2-0.3°C. The greatest deviation from multiyear averages of mean monthly air temperature is observed in January and March. The investigation of the changes the basic regional climate characteristics is very important in present time because the global climate is changed. The analysis the data about air temperature and precipitation, that were obtained for the different meteorological stations in the investigated region, shows that the regional climate is changed and the main tendencies are directly proportional to the change of the global characteristics.

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27

Fahrenkamp-Uppenbrink, J. "ATMOSPHERIC SCIENCE: Regional Climate Change." Science 301, no. 5636 (August 22, 2003): 1021a—1021. http://dx.doi.org/10.1126/science.301.5636.1021a.

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28

Stephenson, Kimberly, Michael A. Taylor, Tannecia S. Stephenson, Abel Centella, Arnoldo Bezanilla, and John Charlery. "The Regional Climate Science Initiative." Caribbean Quarterly 64, no. 1 (January 2, 2018): 11–25. http://dx.doi.org/10.1080/00086495.2018.1435314.

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29

Harrison, Stephan. "Climate Change and Regional Security." RUSI Journal 153, no. 3 (June 2008): 88–91. http://dx.doi.org/10.1080/03071840802249646.

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30

Eastman, Joseph L., Mike B. Coughenour, and Roger A. Pielke. "Does Grazing Affect Regional Climate?" Journal of Hydrometeorology 2, no. 3 (June 2001): 243–53. http://dx.doi.org/10.1175/1525-7541(2001)002<0243:dgarc>2.0.co;2.

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31

Duan, Yanan. "Climate Change Influences Regional Instability." IOP Conference Series: Earth and Environmental Science 440 (March 19, 2020): 042088. http://dx.doi.org/10.1088/1755-1315/440/4/042088.

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32

Fountain, Kathleen C. "Regional Cooperation on Climate Change." Journal of Government Information 27, no. 3 (May 2000): 418–20. http://dx.doi.org/10.1016/s1352-0237(00)00172-6.

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33

Ogurtsov, M. G., G. E. Kocharov, M. Lindholm, M. Eronen, and Yu A. Nagovitsyn. "Solar Activity and Regional Climate." Radiocarbon 43, no. 2A (2001): 439–47. http://dx.doi.org/10.1017/s0033822200038303.

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We performed a statistical analysis of the data on summer temperature anomalies in northern Fennoscandia (8–1995 AD) and found that a 70–130-yr cycle is present in this series during most of the time period. A comparison of the reconstructed northern Fennoscandia temperature with different indicators of solar activity (Wolf numbers, the length of solar Schwabe cycle, extended bi-decadal radiocarbon series, and data on sunspots observed by naked eye) shows that the more probable cause of the periodicity is the modulation of regional northern Fennoscandia climate by the long-term solar cycle of Gleissberg. The effect of this century-scale solar modulation of the global Northern Hemisphere temperature is weaker.

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34

Curry, J. A., and A. H. Lynch. "Comparing Arctic Regional Climate Model." Eos, Transactions American Geophysical Union 83, no. 9 (2002): 87. http://dx.doi.org/10.1029/2002eo000051.

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35

Kundzewicz, Zbigniew W., and Piotr Matczak. "Climate change regional review: Poland." Wiley Interdisciplinary Reviews: Climate Change 3, no. 4 (May 17, 2012): 297–311. http://dx.doi.org/10.1002/wcc.175.

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36

Sharmina, Maria, Kevin Anderson, and Alice Bows-Larkin. "Climate change regional review: Russia." Wiley Interdisciplinary Reviews: Climate Change 4, no. 5 (June 19, 2013): 373–96. http://dx.doi.org/10.1002/wcc.236.

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37

Suklitsch, Martin, Andreas Gobiet, Armin Leuprecht, and Christoph Frei. "High Resolution Sensitivity Studies with the Regional Climate Model CCLM in the Alpine Region." Meteorologische Zeitschrift 17, no. 4 (August 25, 2008): 467–76. http://dx.doi.org/10.1127/0941-2948/2008/0308.

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38

Ohmura, Atsumu. "Climate on tundra and thoughts on causes of regional climate differences." Annals of Glaciology 31 (2000): 10–14. http://dx.doi.org/10.3189/172756400781819987.

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AbstractThe Axel Heiberg Island Expedition of McGill University, Montreal, Canada, led by the late Fritz Müller was the cradle for a number of scientific investigations, not all of them glaciological. During the four years 1969–72, the tundra climate was investigated in the Expedition Area, encompassing about 100 km2 on the mid-west coast of Axel Heiberg Island, Nunavut, Canada. This series of studies identified the main features of the tundra climate, clarified its causal processes and contributed to an understanding of the differences between tundra climates and those of the neighboring regions with glaciers, ocean surfaces and boreal forests. A fundamental consideration of climate processes on a global scale was conceived during this time. Some significant results are recorded here to commemorate Fritz Müller’s contributions as a polar scientist and a university educator.

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39

Kothe, Steffen, Julian Tödter, and Bodo Ahrens. "Strategies for soil initialization of regional decadal climate predictions." Meteorologische Zeitschrift 25, no. 6 (December 21, 2016): 775–94. http://dx.doi.org/10.1127/metz/2016/0729.

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40

Rutgersson, Anna, Øyvind Sætra, Alvaro Semedo, Björn Carlsson, and Rajesh Kumar. "Impact of surface waves in a Regional Climate Model." Meteorologische Zeitschrift 19, no. 3 (June 1, 2010): 247–57. http://dx.doi.org/10.1127/0941-2948/2010/0456.

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41

O'Brien, Karen L. "Tropical deforestation and climate change." Progress in Physical Geography: Earth and Environment 20, no. 3 (September 1996): 311–35. http://dx.doi.org/10.1177/030913339602000304.

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This article reviews the physical links between tropical rain forests and the atmos phere, and considers the results of studies which address the climatic impacts of deforestation. Tropical deforestation is widely believed to influence local, regional and possibly global cli mates. Although the relationship between deforestation and climate change is complex, there is a growing consensus that deforestation leads to warmer, drier climates. The consensus is based on experimental studies at the microscale and modelling studies at the global scale, sup plemented by a small number of observational studies at the local and regional scale. However, none of the local and regional studies examine both deforestation and climate change in a rigorous manner, or consider the results in the context of synoptic-scale phenomena. Conse quently, there is considerable uncertainty associated with the local and regional impacts of deforestation on the climate.

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42

Ngo-Duc, T., C. Kieu, M. Thatcher, D. Nguyen-Le, and T. Phan-Van. "Climate projections for Vietnam based on regional climate models." Climate Research 60, no. 3 (August 5, 2014): 199–213. http://dx.doi.org/10.3354/cr01234.

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43

Pierce, D. W., T. P. Barnett, B. D. Santer, and P. J. Gleckler. "Selecting global climate models for regional climate change studies." Proceedings of the National Academy of Sciences 106, no. 21 (May 13, 2009): 8441–46. http://dx.doi.org/10.1073/pnas.0900094106.

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44

Schefczyk, Lukas, and Günther Heinemann. "Climate change impact on thunderstorms: Analysis of thunderstorm indices using high-resolution regional climate simulations." Meteorologische Zeitschrift 26, no. 4 (October 26, 2017): 409–19. http://dx.doi.org/10.1127/metz/2017/0749.

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45

Hlinka, J., D. Hartman, N. Jajcay, M. Vejmelka, R. Donner, N. Marwan, J. Kurths, and M. Paluš. "Regional and inter-regional effects in evolving climate networks." Nonlinear Processes in Geophysics 21, no. 2 (April 1, 2014): 451–62. http://dx.doi.org/10.5194/npg-21-451-2014.

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Abstract. Complicated systems composed of many interacting subsystems are frequently studied as complex networks. In the simplest approach, a given real-world system is represented by an undirected graph composed of nodes standing for the subsystems and non-oriented unweighted edges for interactions present among the nodes; the characteristic properties of the graph are subsequently studied and related to the system's behaviour. More detailed graph models may include edge weights, orientations or multiple types of links; potential time-dependency of edges is conveniently captured in so-called evolving networks. Recently, it has been shown that an evolving climate network can be used to disentangle different types of El Niño episodes described in the literature. The time evolution of several graph characteristics has been compared with the intervals of El Niño and La Niña episodes. In this study we identify the sources of the evolving network characteristics by considering a reduced-dimensionality description of the climate system using network nodes given by rotated principal component analysis. The time evolution of structures in local intra-component networks is studied and compared to evolving inter-component connectivity.

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46

Changnon, Stanley A., Peter J. Lamb, and Kenneth G. Hubbard. "Regional Climate Centers: New Institutions for Climate Services and Climate-Impact Research." Bulletin of the American Meteorological Society 71, no. 4 (April 1990): 527–37. http://dx.doi.org/10.1175/1520-0477(1990)071<0527:rccnif>2.0.co;2.

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47

Masson, Valéry, Aude Lemonsu, Julia Hidalgo, and James Voogt. "Urban Climates and Climate Change." Annual Review of Environment and Resources 45, no. 1 (October 17, 2020): 411–44. http://dx.doi.org/10.1146/annurev-environ-012320-083623.

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Cities are particularly vulnerable to extreme weather episodes, which are expected to increase with climate change. Cities also influence their own local climate, for example, through the relative warming known as the urban heat island (UHI) effect. This review discusses urban climate features (even in complex terrain) and processes. We then present state-of-the-art methodologies on the generalization of a common urban neighborhood classification for UHI studies, as well as recent developments in observation systems and crowdsourcing approaches. We discuss new modeling paradigms pertinent to climate impact studies, with a focus on building energetics and urban vegetation. In combination with regional climate modeling, new methods benefit the variety of climate scenarios and models to provide pertinent information at urban scale. Finally, this article presents how recent research in urban climatology contributes to the global agenda on cities and climate change.

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48

Giorgi, Filippo, Christine Shields Brodeur, and Gary T. Bates. "Regional Climate Change Scenarios over the United States Produced with a Nested Regional Climate Model." Journal of Climate 7, no. 3 (March 1994): 375–99. http://dx.doi.org/10.1175/1520-0442(1994)007<0375:rccsot>2.0.co;2.

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49

Jia, Wu, Gao Xue-Jie, Xu Yin-Long, and Pan Jie. "Regional Climate Change and Uncertainty Analysis based on Four Regional Climate Model Simulations over China." Atmospheric and Oceanic Science Letters 8, no. 3 (January 2015): 147–52. http://dx.doi.org/10.1080/16742834.2015.11447252.

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50

Diallo, Ismaïla, Filippo Giorgi, and Frode Stordal. "Influence of Lake Malawi on regional climate from a double-nested regional climate model experiment." Climate Dynamics 50, no. 9-10 (July 29, 2017): 3397–411. http://dx.doi.org/10.1007/s00382-017-3811-x.

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Journal articles on the topic 'Regional climate'

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