Development of Daily Maximum Air Temperature Estimation Algorithm for the Korean Peninsula Using Modis Data

Author(s):  
Mi Hee Lee ◽  
Jung hum Yu ◽  
Hyewon Yun ◽  
Eunji Cheon
2017 ◽  
Vol 34 (5) ◽  
pp. 650-662 ◽  
Author(s):  
Fangfang Huang ◽  
Weiqiang Ma ◽  
Binbin Wang ◽  
Zeyong Hu ◽  
Yaoming Ma ◽  
...  

2021 ◽  
Author(s):  
Achim Drebs ◽  
Tim Sinsel ◽  
Kirsti Jylhä

<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>


Author(s):  
Shengpan Lin ◽  
Nathan J. Moore ◽  
Joseph P. Messina ◽  
Mark H. DeVisser ◽  
Jiaping Wu

2015 ◽  
Vol 35 (4) ◽  
pp. 769-777 ◽  
Author(s):  
Izabele B. Kruel ◽  
Monica C. Meschiatti ◽  
Gabriel C. Blain ◽  
Ana M. H. de Ávila

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.


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