The effect of background wind on summertime daily maximum air temperature in Kowloon, Hong Kong

2021 ◽  
pp. 108693
Author(s):  
Cheng Zhang ◽  
Qun Wang ◽  
Pak Wai Chan ◽  
Chao Ren ◽  
Yuguo Li
Keyword(s):  
Hong Kong ◽  
Air Temperature ◽  
Daily Maximum ◽  
Background Wind ◽  
Maximum Air Temperature

Micro-climatological influences on temperature condition in an old people’s home in Helsinki, Finland, caused by extended heat-waves 

2021 ◽  
Author(s):  
Achim Drebs ◽  
Tim Sinsel ◽  
Kirsti Jylhä
Keyword(s):  
Air Temperature ◽  
Heat Waves ◽  
Daily Maximum ◽  
Old People ◽  
Concrete Walls ◽  
Meteorological Forcing ◽  
Clear Sky ◽  
Wave Event ◽  
Construction Type ◽  
Maximum Air Temperature

<p>In our research we describe the micro-climatological influences of two heat-waves around and the air temperature development in a certain old people’s home in Helsinki, Finland. The stand-alone six-storey concrete building was erected in the late 1970’s and represents the prevailing construction type of this area. The building is located on a slightly southwards declining slope.</p><p>The first simulation used real meteorological forcing-data from the heat-wave event in summer 2018, which lasted from July, 13<sup>th</sup> until August, 5<sup>th</sup>. In this period the daily maximum air temperature reached almost every day 25 °C and more, sometimes even more than 30 °C. All air temperature, wind, humidity, and solar radiation (cloudiness) measurements were conducted at a near-by synoptical weather station.</p><p>The second simulation used fourteen-day constructed meteorological forcing-data, based on a clear-sky, slowly increasing air temperature, higher than normal humidity, and low wind conditions assumption starting on July, 13<sup>th</sup> (day 194 of the year).</p><p>We used the holistic ENVI-met simulation soft-ware to simulate the physical environment around the old people’s home and especially the energy fluxes inside the concrete walls to explain the needs for cooling demands.</p><p>The research is part of the HEATCLIM-project financed by the Academy of Finland Science Program CLIHE (2020-2023).</p>

scholarly journals Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil

2015 ◽  
Vol 35 (4) ◽  
pp. 769-777 ◽  
Author(s):  
Izabele B. Kruel ◽  
Monica C. Meschiatti ◽  
Gabriel C. Blain ◽  
Ana M. H. de Ávila
Keyword(s):  
Air Temperature ◽  
Rio Grande ◽  
Location Parameter ◽  
Temperature Series ◽  
Likelihood Method ◽  
Daily Maximum ◽  
Rio Grande Do Sul ◽  
The Mean ◽  
Maximum Air Temperature ◽  
Over Time

ABSTRACT Changes in the frequency of occurrence of extreme weather events have been pointed out as a likely impact of global warming. In this context, this study aimed to detect climate change in series of extreme minimum and maximum air temperature of Pelotas, State of Rio Grande do Sul, (1896 - 2011) and its influence on the probability of occurrence of these variables. We used the general extreme value distribution (GEV) in its stationary and non-stationary forms. In the latter case, GEV parameters are variable over time. On the basis of goodness-of-fit tests and of the maximum likelihood method, the GEV model in which the location parameter increases over time presents the best fit of the daily minimum air temperature series. Such result describes a significant increase in the mean values of this variable, which indicates a potential reduction in the frequency of frosts. The daily maximum air temperature series is also described by a non-stationary model, whose location parameter decreases over time, and the scale parameter related to sample variance rises between the beginning and end of the series. This result indicates a drop in the mean of daily maximum air temperature values and increased dispersion of the sample data.

scholarly journals Daily Minimum and Maximum Air Temperature in Poland in the Years 1951–2005

2009 ◽  
Vol 2 (1) ◽  
pp. 35-56 ◽  
Author(s):  
Marek Kejna ◽  
Andrzej Araźny ◽  
Rafał Maszewski ◽  
Rajmund Przybylak ◽  
Joanna Uscka-Kowalkowska ◽  
...  
Keyword(s):  
Air Temperature ◽  
North Atlantic ◽  
Daily Maximum ◽  
Grid Data ◽  
The North ◽  
Nao Index ◽  
Air Temperatures ◽  
The North Atlantic ◽  
The North Atlantic Oscillation ◽  
Maximum Air Temperature

Abstract In this study grid data of daily maximum and minimum air temperatures taken from the NCEP/NCAR reanalysis for the territory of Poland for the years 1951-2005 have been used as a basis for an analysis of the spatial distribution of daily maximum and minimum air temperature, the frequency of characteristic days and the variability of these parameters in the period analysed. The results obtained were then compared to the variability in atmospheric circulation in Europe, described by the North Atlantic Oscillation (NAO) index.

Using multi-timescale methods and satellite-derived land surface temperature for the interpolation of daily maximum air temperature in Oregon

2015 ◽  
Vol 35 (13) ◽  
pp. 3862-3878 ◽  
Author(s):  
Benoit Parmentier ◽  
Brian J. McGill ◽  
Adam M. Wilson ◽  
James Regetz ◽  
Walter Jetz ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Daily Maximum ◽  
Maximum Air Temperature

scholarly journals The occurrence of heat waves in Europe and their circulation conditions

Geografie ◽  
2019 ◽  
Vol 124 (1) ◽  
pp. 1-17 ◽  
Author(s):  
Arkadiusz M. Tomczyk ◽  
Ewa Bednorz ◽  
Marek Półrolniczak
Keyword(s):  
Sea Level ◽  
Heat Wave ◽  
Air Temperature ◽  
Atmospheric Pressure ◽  
Geopotential Height ◽  
Heat Waves ◽  
Daily Maximum ◽  
Isobaric Surface ◽  
Hot Days ◽  
Maximum Air Temperature

The objective of the paper was to characterize the occurrence of heat waves in Europe between 1976 and 2015 and to determine circulation conditions causing their occurrence. The heat waves were recognized as a sequence of at least 5 consecutive hot days. The hot day was defined as a day on which daily maximum air temperature was higher than 95th percentile of all the values in the analyzed period. The conducted research showed an increase in the number of heat waves and their duration in the analyzed period. The longest heat wave occurred in 2010, in Moscow, which lasted 45 days. The most intense changes were observed in the eastern and south-eastern regions. The occurrence of heat waves was mainly connected with positive anomalies of atmospheric pressure at sea level, geopotential height of 500 hPa, and temperature on isobaric surface 850 hPa.

scholarly journals An Assessment of Methods and Remote-Sensing Derived Covariates for Regional Predictions of 1 km Daily Maximum Air Temperature

2014 ◽  
Vol 6 (9) ◽  
pp. 8639-8670 ◽  
Author(s):  
Benoit Parmentier ◽  
Brian McGill ◽  
Adam Wilson ◽  
James Regetz ◽  
Walter Jetz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Air Temperature ◽  
Daily Maximum ◽  
Maximum Air Temperature

scholarly journals Statistical Forecast of Daily Maximum Air Temperature in Arid Areas at Summertime

2020 ◽  
Vol 52 (3) ◽  
pp. 353-365
Author(s):  
Monim Al-Jiboori ◽  
Mahmoud Jawad Abu Al-Shaeer ◽  
Ahemd S. Hassan
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Absolute Error ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum ◽  
Forecast Errors ◽  
Arid Areas ◽  
Storm Events ◽  
Maximum Air Temperature

Based on historical observations of summers for the period from 2004 to 2018 with a focus on daily maximum and minimum air temperatures and wind speed recorded at 0600 GMT, a non-linear regression hypothesis is developed for forecasting daily maximum air temperature (Tmax) in arid areas such as Baghdad International airport station, which has a hot climate with no cloud cover or rain. Observations with dust storm events were excluded, thus this hypothesis could be used to predict daily Tmax on any day during summers characterized by fair weather. Using mean annual daily temperature range, daily minimum temperature, and the trend of maximum temperature with wind speed, Tmax was forecasted and then compared to those recorded by meteorological instruments. To improve the accuracy of the hypothesis, daily forecast errors, bias, and mean absolute error were analyzed to detect their characteristics through calculating relative frequencies of occurrence. At the end of this analysis, a value of (-0.45ºC) was added to the hypothesis as a bias term.

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