scholarly journals Air Humidity Characteristics in “Local Climate Zones” of Novi Sad (Serbia) Based on Long-Term Data

2021 ◽  
Vol 10 (12) ◽  
pp. 810
Author(s):  
Jelena Dunjić ◽  
Dragan Milošević ◽  
Milena Kojić ◽  
Stevan Savić ◽  
Zorana Lužanin ◽  
...  
Keyword(s):  
Vapor Pressure ◽  
Air Temperature ◽  
Temporal Dynamics ◽  
Water Vapor Pressure ◽  
Specific Humidity ◽  
Air Humidity ◽  
Climate Zones ◽  
Local Climate ◽  
Local Climate Zones ◽  
Novi Sad

This study aims to investigate spatial and temporal dynamics and relationship between air temperature and five air humidity parameters (relative humidity, water vapor pressure, absolute humidity, specific humidity, and vapor pressure deficit) in Novi Sad, Serbia, based on two-year data (Dec 2015–Dec 2017). The analysis includes different urban areas of Novi Sad, which are delineated in five built (urban) types of local climate zones (LCZ) (LCZ 2, LCZ 5, LCZ 6, LCZ 8, and LCZ 9), and one land cover (natural) local climate zone (LCZ A) located outside the urban area. Temporal analysis included annual, seasonal, and monthly dynamics of air temperature and air humidity parameters, as well as their patterns during the extreme periods (heat and cold wave). The results showed that urban dry island (UDI) occurs in densely urbanized LCZ 2 from February to October, unlike other urban LCZs. The analysis of the air humidity dynamics during the heat wave shows that UDI intensity is most pronounced during the daytime, but also in the evening (approximately until midnight) in LCZ 2. However, lower UDI intensity is observed in the afternoon, in other urban LCZs (LCZ 6, LCZ 8, and LCZ 9) and occasionally in the later afternoon in LCZ 5. Regression analysis confirms the relationship between air temperature and each of the analyzed air humidity parameters.

Comparison of urban climate measurements in Berlin and LES model output for a special observation period

2021 ◽  
Author(s):  
Ines langer ◽  
Alexander Pasternack ◽  
Uwe Ulbrich ◽  
Henning Rust
Keyword(s):  
Mean Square Error ◽  
Urban Climate ◽  
Specific Humidity ◽  
Mean Square ◽  
Climate Zones ◽  
Local Climate ◽  
Large Eddy Simulation Model ◽  
Local Climate Zones ◽  
The City ◽  
Observation Period

<p>Surface (2 m) temperature and specific humidity data are measured at 5-minute intervals in a network comprising 33 stations distributed across the city of Berlin, Germany. These data are utilized in order to validate a LES (large eddy simulation) model designed to assess the local climate at a very high resolution of 10 m to 1 m. This model, was developed at the ​Institute of Meteorology and Climatology (IMUK) of the Leibniz Universität Hannover, Germany, and is developed into an application tool for city planners within the funding programme "[UC²] - Urban Climate under Change", of the German Federal Ministry of Education and Research (BMBF).</p><p>The evaluation distinguishes between the different Local climate zones (LCZ) in the city, which are defined following the concept of Stewart & Oke (2012). For Berlin, the following LCZ have been identified: 2 (compact midrise), 4 (open high-rise), 6 (open low-rise), 8 (large low-rise), A (dense trees), B (scattered trees), D (low Plants), G (water).</p><p>We analyzed one cold winter day during an intensive observation period from 06 UTC on 17<sup>th</sup> January to 06 UTC on 18<sup>th</sup> January, 2017. The minimum and maximum recorded temperatures were -8.1 °C and +2 °C, respectively, the sun shine duration was 6.5 hours. Daily and hourly mean absolute error, mean square error and root mean square error confirm that the deviation between measurements and the PALM-4U model differs between the LCZ for Berlin, with particularly large negative deviations of up to 5 K in forest areas, as they are not yet well represented in the model. Smallest deviations are found for the industrial zone. In all cases, the observed amplitude of the diurnal cycle is underestimated. The role of the driving model for the deviations found is addressed.</p><p>Stewart, I.D., Oke, T.R. (2012) Local climate zones for urban temperature studies. Bull. Amer. Meteor. Soc. 93 1879-1900. DOI: 10.1175/BAMS-D-11-00019.1.</p><p> </p>

scholarly journals Air temperature characteristics of local climate zones in the Augsburg urban area (Bavaria, southern Germany) under varying synoptic conditions

Urban Climate ◽  
2018 ◽  
Vol 25 ◽  
pp. 152-166 ◽  
Author(s):  
Christoph Beck ◽  
Annette Straub ◽  
Susanne Breitner ◽  
Josef Cyrys ◽  
Andreas Philipp ◽  
...  
Keyword(s):  
Urban Area ◽  
Air Temperature ◽  
Climate Zones ◽  
Southern Germany ◽  
Local Climate ◽  
Temperature Characteristics ◽  
Local Climate Zones ◽  
Synoptic Conditions

scholarly journals Classifying urban meteorological stations sites by 'local climate zones': Preliminary results for the city of Novi Sad (Serbia)

2013 ◽  
Vol 17 (3) ◽  
pp. 60-68 ◽  
Author(s):  
Stevan Savic ◽  
Dragan Milosevic ◽  
Lazar Lazic ◽  
Vladimir Markovic ◽  
Daniela Arsenovic ◽  
...  
Keyword(s):  
Climate Zones ◽  
Local Climate ◽  
Preliminary Results ◽  
Local Climate Zones ◽  
Novi Sad ◽  
The City

Air humidity characteristics of local climate zones: A three-year observational study in Nanjing

2020 ◽  
Vol 171 ◽  
pp. 106661 ◽  
Author(s):  
Xiaoshan Yang ◽  
Lilliana L.H. Peng ◽  
Yuan Chen ◽  
Lingye Yao ◽  
Qingqing Wang
Keyword(s):  
Observational Study ◽  
Air Humidity ◽  
Climate Zones ◽  
Local Climate ◽  
Local Climate Zones

scholarly journals Impact of Land Cover Composition and Structure on Air Temperature Based on the Local Climate Zone Scheme in Hangzhou, China

Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 936
Author(s):  
Hai Yan ◽  
Shimin Yang ◽  
Xiaohui Guo ◽  
Fan Wu ◽  
Renwu Wu ◽  
...  
Keyword(s):  
Land Cover ◽  
Air Temperature ◽  
Temperature Difference ◽  
Thermal Environment ◽  
Urban Climate ◽  
Rapid Urbanization ◽  
Climate Zones ◽  
Local Climate ◽  
Composition And Structure ◽  
Local Climate Zones

At present, conflicts between urban development and the climate environment are becoming increasingly apparent under rapid urbanization in China. Revealing the dynamic mechanism and controlling factors of the urban outdoor thermal environment is the necessary theoretical preparation for regulating and improving the urban climate environment. Taking Hangzhou as an example and based on the local climate zones classification system, we investigated the effects of land cover composition and structure on temperature variability at the local scale. The measurement campaign was conducted within four local climate zones (LCZ 2, 4, 5, and LCZ 9) during 7 days in the summer of 2018. The results showed that the temperature difference within the respective LCZ was always below 1.1 °C and the mean temperature difference between LCZs caused by different surface physical properties was as high as 1.6 °C at night. Among four LCZs, LCZ 2 was always the hottest, and LCZ 9 was the coolest at night. In particular, the percentage of pervious surface was the most important land cover feature in explaining the air temperature difference. For both daytime and nighttime, increasing the percentage of pervious surface as well as decreasing the percentage of impervious surface and the percentage of building surface could lower the local temperature, with the strongest influence radius range from 120 m to 150 m. Besides, the temperature increased with the SVF increased at day and opposite at night.

scholarly journals Outdoor human thermal comfort in local climate zones of Novi Sad (Serbia) during heat wave period

2016 ◽  
Vol 65 (2) ◽  
pp. 129-137 ◽  
Author(s):  
Dragan D. Milošević ◽  
Stevan m. Savić ◽  
Vladimir Marković ◽  
Daniela Arsenović ◽  
Ivan Šećerov
Keyword(s):  
Thermal Comfort ◽  
Heat Wave ◽  
Wave Period ◽  
Climate Zones ◽  
Local Climate ◽  
Human Thermal Comfort ◽  
Local Climate Zones ◽  
Novi Sad

scholarly journals Analysis of land surface temperatures in the "Local Climate Zones" of Novi Sad (Serbia)

2020 ◽  
Vol 100 (1) ◽  
pp. 41-50
Author(s):  
Stevan Savic ◽  
Jan Geletic ◽  
Dragan Milosevic ◽  
Michal Lehnert
Keyword(s):  
Land Surface ◽  
Landsat 8 ◽  
Similar Time ◽  
Climate Zones ◽  
Local Climate ◽  
Surface Temperatures ◽  
Local Climate Zones ◽  
Scattered Trees ◽  
Land Surface Temperatures ◽  
Novi Sad

In this study, the Local Climate Zones (LCZs) in Novi Sad, the second largest city in Serbia, are analysed as to surface temperature differences. The LCZs were delineated on the basis of the GIS-based method created by Geletic & Lehnert (2016). Land Surface Temperatures (LSTs) were derived from the satellites Terra, sensor ASTER, and LANDSAT-8. The thermal images were provided at a similar time (at about 9.30 AM) between 2002 and 2008 (ASTER) and between 2013 and 2017 (LANDSAT-8). Statistical analyses, including the analysis of variance (ANOVA) and Tukey-HSD test, were employed to reveal LST differences between the LCZs. The results indicate that in 84% of cases there were significant differences in LST between pairs of LCZs. Temperature differences between LCZs were the most pronounced in the summer season. In general, 8 (large low-rise), 10 (heavy industry), 2 (compact midrise) and 3 (compact low-rise) LCZs had the highest surface temperatures in Novi Sad. Contrary to this, LCZs A (dense trees), B (scattered trees) G (water bodies) were the coolest zones.

Thermal properties based on air temperature observations in different local climate zones in Bogotá, Colombia

2020 ◽  
Vol 82 ◽  
pp. 15-31
Author(s):  
EA Ramírez-Aguilar ◽  
LCL Souza
Keyword(s):  
Thermal Properties ◽  
Air Temperature ◽  
Thermal Sensation ◽  
Urban Morphology ◽  
Early Application ◽  
Climate Zones ◽  
Local Climate ◽  
Local Climate Zones ◽  
Temperature Observations ◽  
The City

This paper demonstrates an early application of local climate zones (LCZs) in the city of Bogotá, Colombia. The main goal was to assess the thermal properties within the areas of influence (sectors) of 10 meteorological stations in the city, classified into the LCZ scheme. Air temperature observations at 07:00, 13:00 and 19:00 h (T7:00, T13:00 and T19:00) and daily measurements were obtained from the stations, and the maximum (Tmax), minimum (Tmin) and mean (Tmean) values were calculated. Their distribution and variation were analyzed, thermal sensation categories were calculated, and the thermal differences (ΔTLCZX-LCZD) between open-compact LCZ types and LCZD (typical rural type with low plants) were obtained in order to identify patterns between the stations and their assigned LCZs. Furthermore, we compared urban morphology (form) parameters to the ranges proposed in the literature to classify LCZs. The results clearly showed variations and patterns between the stations and their assigned LCZs when using Tmin, T7:00 and T19:00 air temperature data and the indices and categories calculated from these. Values of ΔTLCZX-LCZD > 5°C were found in the densely urbanised LCZ at night, and some negative values at noon suggested the presence of an urban cool island. The results show the usefulness of LCZs in understanding differences and temperature variations between divergent urban sectors. However, when different LCZ types are grouped, the thermal differences between them can be better appreciated and explained. The main conclusion is that the urban surface of Bogotá does not generate high temperatures, but decreases the occurrences of low values in Tmin, Tmean, T19:00 and T7:00.

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