Is It Possible to Distinguish Global and Regional Climate Change from Urban Land Cover Induced Signals? A Mid-Latitude City Example
Abstract
:1. Introduction
- (1)
- Assess which effects are locally enforced and due to direct human influence, and which changes are induced by regional and global change.
- (2)
- Provide insights on local effects of urban areas and their magnitude compared to regional climate change signals.
- (3)
- Answer these three questions: Can local meteorological phenomena be assigned to either general climate change effects or urban land cover? Are there impacts of interactions of both? How can these factors be determined and quantified?
2. Air Temperature
2.1. Global and Regional Observations and Projections
2.2. Urban Heat Island
2.3. Development of the UHI in the Past
2.4. Impact of Climate Change on the UHI
2.5. Interaction of Regional and Urban Signals
3. Other Meteorological Parameters
3.1. Surface Temperature
3.2. Wind
3.3. Precipitation
3.4. Solar Radiation
3.5. Human Comfort
3.6. Humidity and Evapotranspiration
4. Conclusions and Outlook
Acknowledgments
Author Contributions
Conflicts of Interest
References
- IPCC. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; Stocker, T.F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S.K., Boschung, J., Nauels, A., Xia, Y., Bex, V., Midgley, P.M., Eds.; Cambridge University Press: Cambridge, UK, 2013; ISBN 978-1-107-66182-0. [Google Scholar]
- Chapman, S.; Watson, J.E.M.; Salazar, A.; Thatcher, M.; McAlpine, C.A. The impact of urbanization and climate change on urban temperatures: A systematic review. Landsc. Ecol. 2017, 32, 1921–1935. [Google Scholar] [CrossRef]
- Schlünzen, K.H.; Grawe, D.; Bohnenstengel, S.; Schlüter, I.; Koppmann, R. Joint modelling of obstacle induced and mesoscale changes-Current limits and challenges. J. Wind Eng. Ind. Aerodyn. 2011, 99, 217–225. [Google Scholar] [CrossRef]
- Von Szombathely, M.; Albrecht, M.; Antanaskovic, D.; Augustin, J.; Augustin, M.; Bechtel, B.; Bürk, T.; Fischereit, J.; Grawe, D.; Hoffmann, P.; et al. A Conceptual Modeling Approach to Health-Related Urban Well-Being. Urban Sci. 2017, 1, 17. [Google Scholar] [CrossRef]
- Morice, C.P.; Kennedy, J.J.; Rayner, N.A.; Jones, P.D. Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set. J. Geophys. Res. 2012, 117. [Google Scholar] [CrossRef]
- Karl, T.R.; Arguez, A.; Huang, B.; Lawrimore, J.H.; McMahon, J.R.; Menne, M.J.; Peterson, T.C.; Vose, R.S.; Zhang, H.-M. Possible artifacts of data biases in the recent global surface warming hiatus. Science 2015, 348, 1469–1472. [Google Scholar] [CrossRef] [PubMed]
- Hansen, J.; Ruedy, R.; Sato, M.; Lo, K. Global surface temperature change. Rev. Geophys. 2010, 48. [Google Scholar] [CrossRef]
- Simmons, A.J.; Berrisford, P.; Dee, D.P.; Hersbach, H.; Hirahara, S.; Thépaut, J.N. A reassessment of temperature variations and trends from global reanalyses and monthly surface climatological datasets. Q. J. R. Meteorol. Soc. 2017, 143, 101–119. [Google Scholar] [CrossRef]
- Schurer, A.P.; Mann, M.E.; Hawkins, E.; Tett, S.F.B.; Hegerl, G.C. Importance of the pre-industrial baseline for likelihood of exceeding Paris goals. Nat. Clim. Chang. 2017, 7, 563–567. [Google Scholar] [CrossRef] [PubMed]
- Haylock, M.R.; Hofstra, N.; Klein Tank, A.M.G.; Klok, E.J.; Jones, P.D.; New, M. A European daily high-resolution gridded dataset of surface temperature and precipitation for 1950–2006. J. Geophys. Res. 2008, 113. [Google Scholar] [CrossRef]
- Van der Schrier, G.; van den Besselaar, E.J.M.; Klein Tank, A.M.G.; Verver, G. Monitoring European average temperature based on the E-OBS gridded data set. J. Geophys. Res. 2013, 118, 5120–5135. [Google Scholar] [CrossRef]
- Jacob, D.; Petersen, J.; Eggert, B.; Alias, A.; Christensen, O.B.; Bouwer, L.M.; Braun, A.; Colette, A.; Déqué, M.; Georgievski, G.; et al. EURO-CORDEX: New high-resolution climate change projections for European impact research. Reg. Environ. Chang. 2014, 14, 563–578. [Google Scholar] [CrossRef]
- Kaspar, F.; Mächel, H. Kapitel 3—Beobachtung von Klima und Klimawandel in Mitteleuropa und Deutschland. In Klimawandel in Deutschland: Entwicklung, Folgen, Risiken und Perspektiven; Brasseur, G., Jacob, D., Schuck-Zöller, S., Eds.; Springer Spektrum: Berlin, Germany, 2016. [Google Scholar]
- Deutschländer, T.; Mächel, H. Kapitel 6—Temperatur inklusive Hitzewellen. In Klimawandel in Deutschland: Entwicklung, Folgen, Risiken und Perspektiven; Brasseur, G., Jacob, D., Schuck-Zöller, S., Eds.; Springer Spektrum: Berlin, Germany, 2016. [Google Scholar]
- Jacob, D.; Kottmeier, C.; Petersen, J.; Rechid, D.; Teichmann, C. Kapitel 4—Regionale Klimamodellierung. In Klimawandel in Deutschland: Entwicklung, Folgen, Risiken und Perspektiven; Brasseur, G.P., Jacob, D., Schuck-Zöller, S., Eds.; Springer Spektrum: Berlin/Heidelberg, Germany, 2016; ISBN 9783662503973. [Google Scholar]
- DWD Climate Data Center (CDC). Historical Daily Station Observations (Temperature, Pressure, Precipitation, Wind, Sunshine Duration, etc.) for Germany, version v004; DWD Climate Data Center: Offenbach, Germany; Available online: ftp://ftp-cdc.dwd.de/pub/CDC/ (accessed on 21 December 2017).
- Meinke, I.; Rechid, D.; Tinz, B.; Maneke, M.; Lefebvre, C.; Isokeit, E. Klima der Region—Zustand, bisherige Entwicklung und mögliche Änderungen bis 2100. In Hamburger Klimabericht—Wissen über Klima, Klimawandel und Auswirkungen in Hamburg und Norddeutschland; von Storch, H., Claussen, M., Eds.; Springer: Berlin/Heidelberg, Germany, 2017; ISBN 978-3-662-55379-4. [Google Scholar]
- Oke, T.R. The energetic basis of the urban heat-island. Q. J. R. Meteorol. Soc. 1982, 108, 1–24. [Google Scholar] [CrossRef]
- Von Storch, H.; Claussen, M. Klimabericht für die Metropolregion Hamburg; Springer: Berlin, Germany, 2011; ISBN 9783642160349. [Google Scholar]
- Schlünzen, K.H.; Hoffmann, P.; Rosenhagen, G.; Riecke, W. Long-term changes and regional differences in temperature and precipitation in the metropolitan area of Hamburg. Int. J. Climatol. 2010, 30, 1121–1136. [Google Scholar] [CrossRef]
- Richter, M.; Deppisch, S.; von Storch, H. Observed Changes in Long-Term Climatic Conditions and Inner-Regional Differences in Urban Regions of the Baltic Sea Coast. Atmos. Clim. Sci. 2013, 3, 165–176. [Google Scholar] [CrossRef]
- Wienert, U.; Kreienkamp, F.; Spekat, A.; Enke, W. A simple method to estimate the urban heat island intensity in data sets used for the simulation of the thermal behaviour of buildings. Meteorol. Z. 2013, 22, 179–185. [Google Scholar] [CrossRef]
- Grawe, D.; Thompson, H.L.; Salmond, J.A.; Cai, X.-M.; Schlünzen, K.H. Modelling the impact of urbanisation on regional climate in the Greater London Area. Int. J. Climatol. 2013, 33, 2388–2401. [Google Scholar] [CrossRef]
- Bechtel, B.; Schmidt, K.J. Floristic mapping data as a proxy for the mean urban heat island. Clim. Res. 2011, 49, 45–58. [Google Scholar] [CrossRef]
- Wiesner, S.; Eschenbach, A.; Ament, F. Urban air temperature anomalies and their relation to soil moisture observed in the city of Hamburg. Meteorol. Z. 2014, 23, 143–157. [Google Scholar] [CrossRef]
- Brümmer, B.; Lange, I.; Konow, H. Atmospheric boundary layer measurements at the 280 m high Hamburg weather mast 1995–2011: Mean annual and diurnal cycles. Meteorol. Z. 2012, 21, 319–335. [Google Scholar] [CrossRef]
- Bechtel, B.; Wiesner, S.; Zaksek, K. Estimation of dense time series of urban air temperatures from multitemporal geostationary satellite data. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 2014, 7, 4129–4137. [Google Scholar] [CrossRef]
- Hoffmann, P.; Krueger, O.; Schlünzen, K.H. A statistical model for the urban heat island and its application to a climate change scenario. Int. J. Climatol. 2012, 32, 1238–1248. [Google Scholar] [CrossRef]
- Trusilova, K.; Riecke, W. Klimauntersuchung für die Metropolregion Hamburg zur Entwicklung verschiedener meteorologischer Parameter bis zum Jahr 2050; Berichte des Deutschen Wetterdienstes Nr. 247.; DWD: Offenbach, Germany, 2015. [Google Scholar]
- Kalnay, E.; Cai, M. Impact of urbanization and land-use change on climate. Nature 2003, 423, 528–531. [Google Scholar] [CrossRef] [PubMed]
- Chrysanthou, A.; van der Schrier, G.; van den Besselaar, E.J.M.; Klein Tank, A.M.G.; Brandsma, T. The effects of urbanization on the rise of the European temperature since 1960. Geophys. Res. Lett. 2014, 41, 7716–7722. [Google Scholar] [CrossRef]
- Jones, P.D.; Lister, D.H.; Li, Q. Urbanization effects in large-scale temperature records, with an emphasis on China. J. Geophys. Res. 2008, 113. [Google Scholar] [CrossRef]
- Li, Y.; Zhu, L.; Zhao, X.; Li, S.; Yan, Y. Urbanization Impact on Temperature Change in China with Emphasis on Land Cover Change and Human Activity. J. Clim. 2013, 26, 8765–8780. [Google Scholar] [CrossRef]
- Parker, D.E. Urban heat island effects on estimates of observed climate change. Wiley Interdiscip. Rev. 2010, 1, 123–133. [Google Scholar] [CrossRef]
- Wang, F.; Ge, Q.; Wang, S.; Li, Q.; Jones, P.D. A New Estimation of Urbanization’s Contribution to the Warming Trend in China. J. Clim. 2015, 28, 8923–8938. [Google Scholar] [CrossRef]
- Harris, I.; Jones, P.D.; Osborn, T.J.; Lister, D.H. Updated high-resolution grids of monthly climatic observations—The CRU TS3.10 Dataset. Int. J. Climatol. 2014, 34, 623–642. [Google Scholar] [CrossRef] [Green Version]
- Schoetter, R.; Hoffmann, P.; Rechid, D.; Schlünzen, K.H. Evaluation and bias correction of regional climate model results using model evaluation measures. J. Appl. Meteorol. Climatol. 2012, 51, 1670–1684. [Google Scholar] [CrossRef]
- Hoffmann, P.; Schoetter, R.; Schlünzen, K.H. Statistical-dynamical downscaling of the urban heat island in Hamburg, Germany. Meteorol. Z. 2016. [Google Scholar] [CrossRef]
- Wilby, R.L. Constructing climate change scenarios of urban heat island intensity and air quality. Environ. Plan. B 2008, 35, 902–919. [Google Scholar] [CrossRef]
- Adachi, S.A.; Kimura, F.; Kusaka, H.; Inoue, T.; Ueda, H. Comparison of the Impact of Global Climate Changes and Urbanization on Summertime Future Climate in the Tokyo Metropolitan Area. J. Appl. Meteorol. Climatol. 2012, 51, 1441–1454. [Google Scholar] [CrossRef]
- Argüeso, D.; Evans, J.P.; Fita, L.; Bormann, K.J. Temperature response to future urbanization and climate change. Clim. Dyn. 2014, 42, 2183–2199. [Google Scholar] [CrossRef]
- Grossman-Clarke, S.; Schubert, S.; Fenner, D. Urban effects on summertime air temperature in Germany under climate change. Int. J. Climatol. 2017, 37, 905–917. [Google Scholar] [CrossRef]
- Hamdi, R.; van de Vyver, H.; Troch, R.D.; Termonia, P. Assessment of three dynamical urban climate downscaling methods: Brussels’s future urban heat island under an A1B emission scenario. Int. J. Climatol. 2014, 34, 978–999. [Google Scholar] [CrossRef]
- Hermans, A. Impacts of Land-Cover Change on the Regional Climate of Northern Germany. Ph.D. Thesis, Universität Hamburg, Hamburg, Germany, 2016. [Google Scholar]
- Boettcher, M.; Hoffmann, P.; Lenhart, H.-J.; Schlünzen, K.H.; Schoetter, R. Influence of large offshore wind farms on North German climate. Meteorol. Z. 2015, 24, 465–480. [Google Scholar] [CrossRef]
- Früh, B.; Becker, P.; Deutschländer, T.; Hessel, J.-D.; Kossmann, M.; Mieskes, I.; Namyslo, J.; Roos, M.; Sievers, U.; Steigerwald, T.; et al. Estimation of climate-change impacts on the urban heat load using an urban climate model and regional climate projections. J. Appl. Meteorol. Climatol. 2011, 50, 167–184. [Google Scholar] [CrossRef]
- Hoffmann, P.; Krueger, O.; Schlünzen, K.H. A statistical model for the urban heat island and its application to a climate change scenario. Int. J. Climatol. 2012, 32, 1238–1248. [Google Scholar] [CrossRef]
- Hoffmann, P.; Schlünzen, K.H. Weather Pattern Classification to Represent the Urban Heat Island in Present and Future Climate. J. Appl. Meteorol. Climatol. 2013, 52, 2699–2714. [Google Scholar] [CrossRef]
- Schlünzen, K.H.; Flagg, D.D.; Fock, B.H.; Gierisch, A.; Lüpkes, C.; Reinhardt, V.; Spensberger, C. Scientific Documentation of the Multiscale Model System M-SYS (METRAS, MITRAS, MECTM, MICTM, MESIM, MEMI); Technical Report 4; Meteorologisches Institut KlimaCampus Universitaet Hamburg: Hamburg, Germany, 2012; p. 140. [Google Scholar]
- Boettcher, M.; Flagg, D.D.; Grawe, D.; Hoffmann, P.; Petrik, R.; Schlünzen, K.H.; Schoetter, R.; Teichert, N. Modelling impacts of urban developments and climate adaptation measures on summer climate of Hamburg. Urban Clim. 2017. submitted. [Google Scholar]
- Arnfield, A.J. Two decades of urban climate research: A review of turbulence, exchanges of energy and water, and the urban heat island. Int. J. Climatol. 2003, 23, 1–26. [Google Scholar] [CrossRef]
- Arnds, D.; Böhner, J.; Bechtel, B. Spatio-temporal variance and meteorological drivers of the urban heat island in a European city. Theor. Appl. Climatol. 2017, 128, 43–61. [Google Scholar] [CrossRef]
- Jacobson, M.Z.; Hoeve, J.E.T. Effects of urban surfaces and white roofs on global and regional climate. J. Clim. 2012, 25, 1028–1044. [Google Scholar] [CrossRef]
- Bechtel, B.S.; Sismanidis, P. Time series analysis of moderate resolution land surface temperatures. In Remote Sensing: Time Series Image Processing; Weng, Q., Ed.; Taylor & Francis: Abingdon, UK, 2017. [Google Scholar]
- Bechtel, B. Robustness of annual cycle parameters to characterize the urban thermal landscapes. IEEE Geosci. Remote Sens. Lett. 2012, 9, 876–880. [Google Scholar] [CrossRef]
- Ching, J.; Mills, G.; Bechtel, B.; See, L.; Feddema, J.; Wang, X.; Ren, C.; Brousse, O.; Martilli, A.; Neophytou, M.; et al. World Urban Database and Access Portal Tools (WUDAPT), an urban weather, climate and environmental modeling infrastructure for the Anthropocene. Bull. Am. Meteorol. Soc. 2017. in review. [Google Scholar]
- Hein, P.; Zhu, K.; Bucher, A.; Kolditz, O.; Pang, Z.; Shao, H. Quantification of exploitable shallow geothermal energy by using Borehole Heat Exchanger coupled Ground Source Heat Pump systems. Energy Convers. Manag. 2016, 127, 80–89. [Google Scholar] [CrossRef]
- Klein, I.; Gessner, U.; Dietz, A.J.; Kuenzer, C. Global WaterPack—A 250 m resolution dataset revealing the daily dynamics of global inland water bodies. Remote Sens. Environ. 2017, 198, 345–362. [Google Scholar] [CrossRef]
- Bobrowski, M.; Bechtel, B.; Oldeland, J.; Weidinger, J.; Schickhoff, U. Upgrading ecological niche models with phenological traits: Refinement of the predicted distribution range of Betula utilis in the Himalayan region. J. Biogeogr. 2018. in review. [Google Scholar]
- Bechtel, B. The climate of the Canary Islands by annual cycle parameters. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 2016, XLI-B8, 243–250. [Google Scholar]
- Bechtel, B.; Zaksek, K.; Hoshyaripour, G. Downscaling land surface temperature in an urban area: A case study for Hamburg, Germany. Remote Sens. 2012, 4, 3184–3200. [Google Scholar] [CrossRef]
- Sismanidis, P.; Keramitsoglou, I.; Bechtel, B.; Kiranoudis, C.T. Improving the Downscaling of diurnal land surface temperatures using the annual cycle parameters as disaggregation kernels. Remote Sens. 2017, 9, 23. [Google Scholar] [CrossRef]
- Sismanidis, P.; Keramitsoglou, I.; Kiranoudis, C.T.; Bechtel, B. Assessing the capability of a downscaled urban land surface temperature time series to reproduce the spatiotemporal features of the original data. Remote Sens. 2016, 8, 274. [Google Scholar] [CrossRef]
- Zhan, W.; Huang, F.; Quan, J.L.; Zhu, X.L.; Gao, L.; Zhou, J.; Ju, W.M. Disaggregation of remotely sensed land surface temperature: A new dynamic methodology. J. Geophys. Res. 2016, 121, 10538–10554. [Google Scholar] [CrossRef]
- Bechtel, B. Die Hitze in der Stadt verstehen—Wie sich die jahreszeitliche Temperaturdynamik von Städten aus dem All beobachten lässt. In Globale Urbanisierung—Perspektive aus dem All; Taubenböck, H., Wurm, M., Esch, T., Dech, S., Eds.; Springer Spektrum: Berlin/Heidelberg, Germany, 2015; pp. 205–216. ISBN 978-3-662-44841-0. [Google Scholar]
- Fu, P.; Weng, Q.H. A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery. Remote Sens. Environ. 2016, 175, 205–214. [Google Scholar] [CrossRef]
- Huang, F.; Zhan, W.F.; Voogt, J.; Hu, L.Q.; Wang, Z.H.; Quan, J.L.; Ju, W.M.; Guo, Z. Temporal upscaling of surface urban heat island by incorporating an annual temperature cycle model: A tale of two cities. Remote Sens. Environ. 2016, 186, 1–12. [Google Scholar] [CrossRef]
- Bechtel, B. Recent advances in thermal remote sensing for urban planning and management. In Proceedings of the 2015 Joint Urban Remote Sensing Event (Jurse), Lausanne, Switzerland, 30 March–1 April 2015. [Google Scholar]
- Kaloustian, N.; Tamminga, M.; Bechtel, B. Local climate zones and annual surface thermal response in a Mediterranean city. In Proceedings of the 2017 Joint Urban Remote Sensing Event (JURSE), Dubai, UAE, 6–8 March 2017; pp. 1–4. [Google Scholar]
- Pinto, J.G.; Reyers, M. Kapitel 8—Winde und Zyklone. In Klimawandel in Deutschland: Entwicklung, Folgen, Risiken und Perspektiven; Brasseur, G.P., Jacob, D., Schuck-Zöller, S., Eds.; Springer Spektrum: Berlin, Germany, 2016; ISBN 9783662503973. [Google Scholar]
- Feser, F.; Barcikowska, M.; Krueger, O.; Schenk, F.; Weisse, R.; Xia, L. Storminess over the North Atlantic and northwestern Europe—A review. Q. J. R. Meteorol. Soc. 2015, 141, 350–382. [Google Scholar] [CrossRef]
- Hov, Ø.; Cubasch, U.; Fischer, E.; Höppe, P.; Iversen, T.; Kvamstø, N.G.; Kundzewicz, Z.W.; Rezacova, D.; Rios, D.; Duarte Santos, F.; et al. Extreme Weather Events in Europe: Preparing for Climate Change Adaptation; Norwegian Meteorological Institute: Oslo, Norway, 2013; ISBN 978-82-7144-100-5. [Google Scholar]
- Ulbrich, U.; Leckebusch, G.C.; Pinto, J.G. Extra-tropical cyclones in the present and future climate: A review. Theor. Appl. Climatol. 2009, 96, 117–131. [Google Scholar] [CrossRef]
- Zappa, G.; Shaffrey, L.C.; Hodges, K.I.; Sansom, P.G.; Stephenson, D.B. A Multimodel assessment of future projections of North Atlantic and European Extratropical Cyclones in the CMIP5 climate models. J. Clim. 2013, 26, 5846–5862. [Google Scholar] [CrossRef]
- Heppelmann, T.; Steiner, A.; Vogt, S. Application of numerical weather prediction in wind power forecasting: Assessment of the diurnal cycle. Meteorol. Z. 2017, 26, 319–331. [Google Scholar] [CrossRef]
- Hertwig, D.; Patnaik, G.; Leitl, B. LES validation of urban flow, part I: Flow statistics and frequency distributions. Environ. Fluid Mech. 2017, 17, 521–550. [Google Scholar] [CrossRef]
- European Environment Agency. Climate Change, Impacts and Vulnerability in Europe 2016. An. Indicator-Based Report; EEA Report No 1/2017; European Environment Agency: Copenhagen, Denmark, 2017. [Google Scholar]
- Casanueva, A.; Rodríguez-Puebla, C.; Frías, M.D.; González-Reviriego, N. Variability of extreme precipitation over Europe and its relationships with teleconnection patterns. Hydrol. Earth Syst. Sci. 2014, 18, 709–725. [Google Scholar] [CrossRef]
- Fleig, A.K.; Tallaksen, L.M.; James, P.; Hisdal, H.; Stahl, K. Attribution of European precipitation and temperature trends to changes in synoptic circulation. Hydrol. Earth Syst. Sci. 2015, 19, 3093–3107. [Google Scholar] [CrossRef]
- Han, J.-Y.; Baik, J.-J.; Lee, H. Urban impacts on precipitation. Asia Pac. J. Atmos. Sci. 2013, 50. [Google Scholar] [CrossRef]
- Shepherd, J.M.; Pierce, H.; Negri, A.J. Rainfall Modification by Major Urban Areas: Observations from Spaceborne Rain Radar on the TRMM Satellite. J. Appl. Meteorol. 2002, 41, 689–701. [Google Scholar] [CrossRef]
- Schoetter, R. Can Local Adaptation Measures Compensate for Regional Climate Change in Hamburg Metropolitan Region. Ph.D. Thesis, Universität Hamburg, Hamburg, Germany, 2013. [Google Scholar] [CrossRef]
- Rosenhagen, G.; Schatzmann, M. Das Klima der Metropolregion auf Grundlage meteorologischer Messungen und Beobachtungen. In Klimabericht für die Metropolregion Hamburg; von Storch, H., Claussen, M., Eds.; Springer: Berlin/Heidelberg, Germany, 2011; pp. 19–60. ISBN 978-3-642-16035-6. [Google Scholar]
- Schönwiese, C.-D.; Janoschitz, R. Klima-Trendatlas Deutschland 1901–2000. In Berichte des Instituts für Atmosphäre und Umwelt der Universität Frankfurt/Main, 2nd ed.; Eigenverlag des Instituts: Frankfurt, Germany, 2008; Volume 4. [Google Scholar]
- Wild, M.; Folini, D.; Henschel, F.; Fischer, N.; Müller, B. Projections of long-term changes in solar radiation based on CMIP5 climate models and their influence on energy yields of photovoltaic systems. Sol. Energy 2015, 116, 12–24. [Google Scholar] [CrossRef]
- Bartók, B.; Wild, M.; Folini, D.; Lüthi, D.; Kotlarski, S.; Schär, C.; Vautard, R.; Jerez, S.; Imecs, Z. Projected changes in surface solar radiation in CMIP5 global climate models and in EURO-CORDEX regional climate models for Europe. Clim. Dyn. 2017, 49, 2665–2683. [Google Scholar] [CrossRef]
- Macpherson, R.K. The assessment of the thermal environment a review. Br. J. Ind. Med. 1962, 19, 151–164. [Google Scholar] [CrossRef] [PubMed]
- De Freitas, C.R.; Grigorieva, E.A. A comprehensive catalogue and classification of human thermal climate indices. Int. J. Biometeorol. 2015, 59, 109–120. [Google Scholar] [CrossRef] [PubMed]
- De Freitas, C.R.; Grigorieva, E.A. A comparison and appraisal of a comprehensive range of human thermal climate indices. Int. J. Biometeorol. 2017, 61, 487–512. [Google Scholar] [CrossRef] [PubMed]
- Fischereit, J.; Schlünzen, K.H. Evaluation of thermal indices for their usability in obstacle resolving meteorology models. Int. J. Biometeorol. 2017. submitted. [Google Scholar]
- Höppe, P. The physiological equivalent temperature—A universal index for the biometeorological assessment of the thermal environment. Int. J. Biometeorol. 1999, 43, 71–75. [Google Scholar] [CrossRef] [PubMed]
- VDI-3787-2. Methods for the Human Biometeorological Evaluation of Climate and Air Quality for Urban and Regional Planning at Regional Level, Part I: Climate; Beuth: Berlin, Germany, 2008. [Google Scholar]
- Matzarakis, A.; Amelung, B. Physiological equivalent temperature as indicator for impacts of climate change on thermal comfort of humans. In Seasonal Forecasts, Climatic Change and Human Health: Health and Climate; Thomson, M.C., Garcia-Herrera, R., Beniston, M., Eds.; Springer: Dordrecht, The Netherlands, 2008; pp. 161–172. ISBN 978-1-4020-6877-5. [Google Scholar]
- Jendritzky, G.; Tinz, B. The thermal environment of the human being on the global scale. Glob. Health Action 2009, 2, 2005. [Google Scholar] [CrossRef] [PubMed]
- Staiger, H. Die Strahlungskomponente im Thermischen Wirkungskomplex für Operationelle Anwendungen in der Human-Biometeorologie. Ph.D. Thesis, Geowissenschaften, Albert-Ludwigs-Universität Freiburg im Breisgau, Freiburg im Breisgau, Germany, 2014. [Google Scholar]
- Rigollier, C.; Bauer, O.; Wald, L. On the clear sky model of the ESRA—European Solar Radiation Atlas—With respect to the Heliosat method. Sol. Energy 2000, 68, 33–48. [Google Scholar] [CrossRef]
- Scharmer, K.; Greif, J. The European Solar Radiation Atlas: Fundamentals and Maps; Les Presses de l′Ecole des Mines: Paris, France, 2000; ISBN 9782911762215. [Google Scholar]
- Remund, R.; Wald, L.; Lefevre, M.; Ranchin, T.; Page, J. Worldwide Linke Turbidity Information. In Proceedings of the ISES Solar World Congress, Gothenburg, Sweden, 16–19 June 2003; p. 13. [Google Scholar]
- Kasten, F. Parametrisierung der Globalstrahlung durch Bedeckungsgrad und Truebungsfaktor. In Proceedings of the Deutsche Meteorologen-Tagung 1983 vom 16. bis 19. Mai 1983, Bad Kissingen, Germany, 16–19 May 1983; pp. 49–50. [Google Scholar]
- Reindl, D.T.; Beckman, W.A.; Duffie, J.A. Diffuse fraction correlations. Sol. Energy 1990, 45, 1–7. [Google Scholar] [CrossRef]
- Konzelmann, T.; van de Wal, R.S.W.; Greuell, W.; Bintanja, R.; Henneken, E.A.C.; Abe-Ouchi, A. Parameterization of global and longwave incoming radiation for the Greenland Ice Sheet. Glob. Planet. Chang. 1994, 9, 143–164. [Google Scholar] [CrossRef]
- Marty, C.; Philipona, R. The Clear-Sky Index to separate clear-sky from cloudy-sky situations in climate research. Geophys. Res. Lett. 2000, 27, 2649–2652. [Google Scholar] [CrossRef]
- Jendritzky, G. Methodik zur Räumlichen Bewertung der Thermischen Komponente im Bioklima des Menschen: Fortgeschriebenes Klima-Michel-Modell; Akademie für Raumforschung und Landesplanung: Hannover, Germany, 1990; ISBN 9783888382079. [Google Scholar]
- Fischereit, J. Impact on Urban Water Surfaces on Thermal Microclimate. Ph.D. Thesis, Universität Hamburg, Hamburg, Germany, 2018. [Google Scholar]
- Thorsson, S.; Lindberg, F.; Björklund, J.; Holmer, B.; Rayner, D. Potential changes in outdoor thermal comfort conditions in Gothenburg, Sweden due to climate change: The influence of urban geometry. Int. J. Climatol. 2011, 31, 324–335. [Google Scholar] [CrossRef]
- Molenaar, R.E.; Heusinkveld, B.G.; Steeneveld, G.J. Projection of rural and urban human thermal comfort in The Netherlands for 2050. Int. J. Climatol. 2016, 36, 1708–1723. [Google Scholar] [CrossRef]
- Maxwell, R.M.; Kollet, S.J. Interdependence of groundwater dynamics and land-energy feedbacks under climate change. Nat. Geosci. 2008, 1, 665–669. [Google Scholar] [CrossRef]
- Taylor, R.G.; Scanlon, B.; Doll, P.; Rodell, M.; van Beek, R.; Wada, Y.; Longuevergne, L.; Leblanc, M.; Famiglietti, J.S.; Edmunds, M.; et al. Ground water and climate change. Nat. Clim. Chang. 2013, 3, 322–329. [Google Scholar] [CrossRef] [Green Version]
- Pfeiffer, E.-M.; Eschenbach, A.; Munch, J.C. Kapitel 20—Boden. In Klimawandel in Deutschland: Entwicklung, Folgen, Risiken und Perspektiven; Brasseur, G., Jacob, D., Schuck-Zöller, S., Eds.; Springer Spektrum: Berlin, Germany, 2016; ISBN 978-3-662-50397-3. [Google Scholar]
- Wiesner, S.; Gröngröft, A.; Ament, F.; Eschenbach, A. Spatial and temporal variability of urban soil water dynamics observed by a soil monitoring network. J. Soils Sediments 2016, 16, 2523–2537. [Google Scholar] [CrossRef]
- Lee, S.-H.; Lee, K.-S.; Jin, W.-C.; Song, H.-K. Effect of an urban park on air temperature differences in a central business district area. Landsc. Ecol. Eng. 2009, 5, 183–191. [Google Scholar] [CrossRef]
- Jansson, C.; Jansson, P.-E.; Gustafsson, D. Near surface climate in an urban vegetated park and its surroundings. Theor. Appl. Climatol. 2007, 89, 185–193. [Google Scholar] [CrossRef]
- Wessolek, G. Bodenüberformung und -versiegelung. In Handbuch der Bodenkunde; Wiley-VCH Verlag GmbH & Co. KGaA: Weinheim, Germany, 2014; ISBN 9783527678495. [Google Scholar]
- Jung, M.; Reichstein, M.; Ciais, P.; Seneviratne, S.I.; Sheffield, J.; Goulden, M.L.; Bonan, G.; Cescatti, A.; Chen, J.Q.; de Jeu, R.; et al. Recent decline in the global land evapotranspiration trend due to limited moisture supply. Nature 2010, 467, 951–954. [Google Scholar] [CrossRef] [PubMed]
- Lee, A.C.K.; Maheswaran, R. The health benefits of urban green spaces: A review of the evidence. J. Public Health 2011, 33, 212–222. [Google Scholar] [CrossRef] [PubMed]
- Peters, E.B.; Hiller, R.V.; McFadden, J.P. Seasonal contributions of vegetation types to suburban evapotranspiration. J. Geophys. Res. 2011, 116, 16. [Google Scholar] [CrossRef]
- Coutts, A.M.; Tapper, N.J.; Beringer, J.; Loughnan, M.; Demuzere, M. Watering our cities: The capacity for Water Sensitive Urban Design to support urban cooling and improve human thermal comfort in the Australian context. Prog. Phys. Geogr. 2013, 37, 2–28. [Google Scholar] [CrossRef]
- Günther, R. The role of soil water content for microclimatic effects of green roofs and urban trees—A case study from Berlin, Germany. J. Heat Isl. Inst. Int. 2014, 9, 19–25. [Google Scholar]
- Jelinkova, V.; Dohnal, M.; Sacha, J. Thermal and water regime studied in a thin soil layer of green roof systems at early stage of pedogenesis. J. Soils Sediments 2016, 16, 2568–2579. [Google Scholar] [CrossRef]
- Nielsen, C.N.; Bühler, O.; Kristoffersen, P. Soil water dynamics and growth of street and park trees. Arboric. Urban For. 2007, 33, 231–245. [Google Scholar]
- Cregg, B.M.; Dix, M.E. Tree moisture stress and insect damage in urban areas in relation to heat island effects. J. Arboric. 2001, 27, 8–17. [Google Scholar]
- Clark, J.K.; Kjelgren, R. Water as a limiting factor in the development of urban trees. J. Arboric. 1990, 16, 203–208. [Google Scholar]
- Rahman, M.A.; Armson, D.; Ennos, A.R. A comparison of the growth and cooling effectiveness of five commonly planted urban tree species. Urban Ecosyst. 2015, 18, 371–389. [Google Scholar] [CrossRef]
- Rahman, M.A.; Moser, A.; Rötzer, T.; Pauleit, S. Microclimatic differences and their influence on transpirational cooling of Tilia cordata in two contrasting street canyons in Munich, Germany. Agric. For. Meteorol. 2017, 232, 443–456. [Google Scholar] [CrossRef]
- Thomsen, S. Impact of Soil Water Availability and Local Climate in Urban Environments on Water Use of Mature Pedunculate oaks (Quercus Robur L.). Ph.D. Thesis, Universität Hamburg, Hamburg, Germany, 2018. [Google Scholar]
Mean Number of Days/Year | Hamburg | Vicinity |
---|---|---|
summer days | 31 | 22 |
hot days | 6 | 3 |
tropical nights | 1 | 0 |
HHairport (1961–2010) | HHdowntown (1961–1999) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
Annual | DJF | MAM | JJA | SON | Annual | DJF | MAM | JJA | SON | |
Tmean | −0.34 * | 0.17 | −0.49 ** | −0.41 ** | −0.13 | 0.33 * | 0.15 | 0.02 | 0.19 | 0.48 ** |
Tmin | 0.03 | 0.29 | 0.15 | −0.18 | −0.07 | 0.11 | −0.07 | 0.13 | 0.18 | 0.03 |
Tmax | 0.02 | 0.15 | 0.02 | −0.16 | 0.11 | 0.44 ** | 0.17 | 0.20 | 0.34 * | 0.55 ** |
City | Hamburg | Hannover | Berlin |
---|---|---|---|
daytime (mean) | 1.7 | 1.9 | 2.4 |
daytime (max) | 3.3 | 3.5 | 4.1 |
nighttime (mean) | 1.2 | 1.2 | 1.4 |
nighttime (max) | 1.8 | 1.7 | 1.9 |
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Wiesner, S.; Bechtel, B.; Fischereit, J.; Gruetzun, V.; Hoffmann, P.; Leitl, B.; Rechid, D.; Schlünzen, K.H.; Thomsen, S. Is It Possible to Distinguish Global and Regional Climate Change from Urban Land Cover Induced Signals? A Mid-Latitude City Example. Urban Sci. 2018, 2, 12. https://doi.org/10.3390/urbansci2010012
Wiesner S, Bechtel B, Fischereit J, Gruetzun V, Hoffmann P, Leitl B, Rechid D, Schlünzen KH, Thomsen S. Is It Possible to Distinguish Global and Regional Climate Change from Urban Land Cover Induced Signals? A Mid-Latitude City Example. Urban Science. 2018; 2(1):12. https://doi.org/10.3390/urbansci2010012
Chicago/Turabian StyleWiesner, Sarah, Benjamin Bechtel, Jana Fischereit, Verena Gruetzun, Peter Hoffmann, Bernd Leitl, Diana Rechid, K. Heinke Schlünzen, and Simon Thomsen. 2018. "Is It Possible to Distinguish Global and Regional Climate Change from Urban Land Cover Induced Signals? A Mid-Latitude City Example" Urban Science 2, no. 1: 12. https://doi.org/10.3390/urbansci2010012