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Modelled spatio-temporal variability of air temperature in an urban climate and its validation: a case study of Brno, Czech Republic
This study compares the results of air temperature model simulations with real temperature measurements in an urban environment. The non-hydrostatic micro-scale model MUKLIMO_3 is used to predict air temperature fields in Brno (Czech Republic). The development of the air temperature fields on three...
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Published in: | Hungarian geographical bulletin 2016, Vol.65 (2), p.169-180 |
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description | This study compares the results of air temperature model simulations with real temperature measurements in an urban environment. The non-hydrostatic micro-scale model MUKLIMO_3 is used to predict air temperature fields in Brno (Czech Republic). The development of the air temperature fields on three different days was modelled which characterising the radiation-driven weather conditions with high temperature that occurred during the summer of 2015. This analysis demonstrates that the model is able to reproduce the spatial distribution of the air temperature during the day. Statistical tests were applied to establish whether significant differences exist between the modelled and measured air temperatures. Verification of the model results against real temperature measurements was performed at five meteorological stations. The mean absolute differences between the simulated and measured daily mean temperatures were 0.7 °C (4 July), 0.6 °C (18 July) and 0.5 °C (28 August), respectively. This demonstrates that the model overestimated the real values, however, not all the differences were statistically significant. Moreover, there were no significant differences in the variability of the temperatures that were compared. This study also shows that the proper definition of Local Climate Zones and their parameters is critical for more precise model performance. |
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The non-hydrostatic micro-scale model MUKLIMO_3 is used to predict air temperature fields in Brno (Czech Republic). The development of the air temperature fields on three different days was modelled which characterising the radiation-driven weather conditions with high temperature that occurred during the summer of 2015. This analysis demonstrates that the model is able to reproduce the spatial distribution of the air temperature during the day. Statistical tests were applied to establish whether significant differences exist between the modelled and measured air temperatures. Verification of the model results against real temperature measurements was performed at five meteorological stations. The mean absolute differences between the simulated and measured daily mean temperatures were 0.7 °C (4 July), 0.6 °C (18 July) and 0.5 °C (28 August), respectively. This demonstrates that the model overestimated the real values, however, not all the differences were statistically significant. 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The non-hydrostatic micro-scale model MUKLIMO_3 is used to predict air temperature fields in Brno (Czech Republic). The development of the air temperature fields on three different days was modelled which characterising the radiation-driven weather conditions with high temperature that occurred during the summer of 2015. This analysis demonstrates that the model is able to reproduce the spatial distribution of the air temperature during the day. Statistical tests were applied to establish whether significant differences exist between the modelled and measured air temperatures. Verification of the model results against real temperature measurements was performed at five meteorological stations. The mean absolute differences between the simulated and measured daily mean temperatures were 0.7 °C (4 July), 0.6 °C (18 July) and 0.5 °C (28 August), respectively. This demonstrates that the model overestimated the real values, however, not all the differences were statistically significant. Moreover, there were no significant differences in the variability of the temperatures that were compared. This study also shows that the proper definition of Local Climate Zones and their parameters is critical for more precise model performance.</description><subject>Air temperature</subject><subject>Climate</subject><subject>High temperature</subject><subject>Radiation</subject><subject>Scale models</subject><subject>Spatial distribution</subject><subject>Statistical analysis</subject><subject>Statistical tests</subject><subject>Temperature</subject><subject>Urban environments</subject><subject>Weather</subject><subject>Weather stations</subject><issn>2064-5031</issn><issn>2064-5147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpFkUtr3DAQx01poSHJF-hJ0Gu81cN6OLd26SOQUCjtWYzkcaJFsVxJDqTnfvB6d5vkMo__zPxmYJrmHaMbJjllH-6W6RaTW2LcKLnhG_2qOeFUda1knX79FFPB3jbnpewopVwZqTt-0vy9SQPGiAMpM9SQ2or3c8oQyQPkAC7EUB9JGgmETPY1zFCXjCRMBCayZLdaH8M9VFyFgYRa1tEYhj1tuiRAPBQkpS7DgfMpT-mCbP-gvyM_cF5cDP6seTNCLHj-3582v758_rn91l5__3q1_XjdekGpboUSTjF0UgihlTPU9EJS2ndaGugRvfbMMNf32rm-k8K4gUnlNUjeGzGCOG2ujtwhwc7Oeb06P9oEwR6ElG8t5Bp8ROuADqOBURnBuk54t09Hx7xB5Sl1K-v9kTXn9HvBUu0uLXlaz7dcMmMYVb1Yu_ixy-dUSsbxeSuj9vA8-_I8q6TlVot_k-SQag</recordid><startdate>2016</startdate><enddate>2016</enddate><creator>Geletič, Jan</creator><creator>Lehnert, Michal</creator><creator>Dobrovolný, Petr</creator><general>Research Centre for Astronomy and Earth Sciences, Hungarian Academy of Sciences, Geographical Institute</general><general>Research Centre for Astronomy and Earth Sciences, Hungarian Academy of Sciences</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X2</scope><scope>8FE</scope><scope>8FH</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>M0K</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>DOA</scope></search><sort><creationdate>2016</creationdate><title>Modelled spatio-temporal variability of air temperature in an urban climate and its validation: a case study of Brno, Czech Republic</title><author>Geletič, Jan ; 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The non-hydrostatic micro-scale model MUKLIMO_3 is used to predict air temperature fields in Brno (Czech Republic). The development of the air temperature fields on three different days was modelled which characterising the radiation-driven weather conditions with high temperature that occurred during the summer of 2015. This analysis demonstrates that the model is able to reproduce the spatial distribution of the air temperature during the day. Statistical tests were applied to establish whether significant differences exist between the modelled and measured air temperatures. Verification of the model results against real temperature measurements was performed at five meteorological stations. The mean absolute differences between the simulated and measured daily mean temperatures were 0.7 °C (4 July), 0.6 °C (18 July) and 0.5 °C (28 August), respectively. This demonstrates that the model overestimated the real values, however, not all the differences were statistically significant. Moreover, there were no significant differences in the variability of the temperatures that were compared. This study also shows that the proper definition of Local Climate Zones and their parameters is critical for more precise model performance.</abstract><cop>Budapest</cop><pub>Research Centre for Astronomy and Earth Sciences, Hungarian Academy of Sciences, Geographical Institute</pub><doi>10.15201/hungeobull.65.2.7</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Air temperature Climate High temperature Radiation Scale models Spatial distribution Statistical analysis Statistical tests Temperature Urban environments Weather Weather stations |
title | Modelled spatio-temporal variability of air temperature in an urban climate and its validation: a case study of Brno, Czech Republic |
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