scholarly journals Observational Evidence of Neighborhood Scale Reductions in Air Temperature Associated with Increases in Roof Albedo

Climate ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 98 ◽  
Author(s):  
Arash Mohegh ◽  
Ronnen Levinson ◽  
Haider Taha ◽  
Haley Gilbert ◽  
Jiachen Zhang ◽  
...  
Keyword(s):  
Los Angeles ◽  
Air Temperature ◽  
Robust Regression ◽  
Spatial Density ◽  
Daily Average ◽  
Air Temperatures ◽  
San Fernando ◽  
Weather Stations ◽  
Meteorological Observations ◽  
Neighborhood Scale

The effects of neighborhood-scale land use and land cover (LULC) properties on observed air temperatures are investigated in two regions within Los Angeles County: Central Los Angeles and the San Fernando Valley (SFV). LULC properties of particular interest in this study are albedo and tree fraction. High spatial density meteorological observations are obtained from 76 personal weather-stations. Observed air temperatures were then related to the spatial mean of each LULC parameter within a 500 m radius “neighborhood” of each weather station, using robust regression for each hour of July 2015. For the neighborhoods under investigation, increases in roof albedo are associated with decreases in air temperature, with the strongest sensitivities occurring in the afternoon. Air temperatures at 14:00–15:00 local daylight time are reduced by 0.31 °C and 0.49 °C per 1 MW increase in daily average solar power reflected from roofs per neighborhood in SFV and Central Los Angeles, respectively. Per 0.10 increase in neighborhood average albedo, daily average air temperatures were reduced by 0.25 °C and 1.84 °C. While roof albedo effects on air temperature seem to exceed tree fraction effects during the day in these two regions, increases in tree fraction are associated with reduced air temperatures at night.

scholarly journals The Street Air Warming Phenomenon in a High-Rise Compact City

Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 402 ◽  
Author(s):  
Xiaoxue Wang ◽  
Yuguo Li ◽  
Xinyan Yang ◽  
Pak Chan ◽  
Janet Nichol ◽  
...  
Keyword(s):  
Thermal Comfort ◽  
Air Temperature ◽  
Thermal Environment ◽  
Urban Climate ◽  
Pollutant Dispersion ◽  
Urban Morphology ◽  
Air Temperatures ◽  
Significant Difference ◽  
Sensitivity Studies ◽  
Weather Stations

The street thermal environment is important for thermal comfort, urban climate and pollutant dispersion. A 24-h vehicle traverse study was conducted over the Kowloon Peninsula of Hong Kong in summer, with each measurement period consisting of 2–3 full days. The data covered a total of 158 loops in 198 h along the route on sunny days. The measured data were averaged by three methods (direct average, FFT filter and interpolated by the piecewise cubic Hermite interpolation). The average street air temperatures were found to be 1–3 °C higher than those recorded at nearby fixed weather stations. The street warming phenomenon observed in the study has substantial implications as usually urban heat island (UHI) intensity is estimated from measurement at fixed weather stations, and therefore the UHI intensity in the built areas of the city may have been underestimated. This significant difference is of interest for studies on outdoor air temperature, thermal comfort, urban environment and pollutant dispersion. The differences were simulated by an improved one-dimensional temperature model (ZERO-CAT) using different urban morphology parameters. The model can correct the underestimation of street air temperature. Further sensitivity studies show that the building arrangement in the daytime and nighttime plays different roles for air temperature in the street. City designers can choose different parameters based on their purpose.

A weighted coefficient model for estimation of Australian daily soil temperature at depths of 5cm to 100cm based on air temperature and rainfall

Soil Research ◽  
2011 ◽  
Vol 49 (4) ◽  
pp. 305 ◽  
Author(s):  
Brian Horton ◽  
Ross Corkrey
Keyword(s):  
Soil Temperature ◽  
Air Temperature ◽  
Cross Validation ◽  
Soil Depth ◽  
Mean Square ◽  
Air Temperatures ◽  
Proposed Model ◽  
Soil Temperatures ◽  
Weather Stations ◽  
Fold Cross Validation

Soil temperatures are related to air temperature and rainfall on the current day and preceding days, and this can be expressed in a non-linear relationship to provide a weighted value for the effect of air temperature or rainfall based on days lag and soil depth. The weighted minimum and maximum air temperatures and weighted rainfall can then be combined with latitude and a seasonal function to estimate soil temperature at any depth in the range 5–100 cm. The model had a root mean square deviation of 1.21–1.85°C for minimum, average, and maximum soil temperature for all weather stations in Australia (mainland and Tasmania), except for maximum soil temperature at 5 and 10 cm, where the model was less precise (3.39° and 2.52°, respectively). Data for this analysis were obtained from 32–40 Bureau of Meteorology weather stations throughout Australia and the proposed model was validated using 5-fold cross-validation.

scholarly journals Regional Climate Change (Karelia, Russia)

2015 ◽  
Vol 2 ◽  
pp. 356
Author(s):  
Larisa Nazarova
Keyword(s):  
Air Temperature ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Climatic Conditions ◽  
Temperature And Precipitation ◽  
The Mean ◽  
Weather Stations ◽  
Meteorological Observations ◽  
Mean Annual Air Temperature

The overview of climatic conditions in Karelia is based on the data from meteorological observations carried out in 1951-2009 at Roskomgidromet weather stations situated in the study area. Taking the period in question into account, the mean annual air temperature norm has increased by 0.2-0.3°C. The greatest deviation from multiyear averages of mean monthly air temperature is observed in January and March. The investigation of the changes the basic regional climate characteristics is very important in present time because the global climate is changed. The analysis the data about air temperature and precipitation, that were obtained for the different meteorological stations in the investigated region, shows that the regional climate is changed and the main tendencies are directly proportional to the change of the global characteristics.

scholarly journals Leftover Spaces for the Mitigation of Urban Overheating in Municipal Beirut

Climate ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 68 ◽  
Author(s):  
Noushig Kaloustian ◽  
David Aouad ◽  
Gabriele Battista ◽  
Michele Zinzi
Keyword(s):  
Air Temperature ◽  
Natural Ventilation ◽  
Integrated Approach ◽  
Urban Vegetation ◽  
Reference Case ◽  
Air Temperatures ◽  
Urban Intervention ◽  
Urban Heat ◽  
Neighborhood Scale ◽  
Typical Summer

The Urban Heat Island phenomenon and urban overheating are serious consequences of urbanization resulting in impacts on thermal comfort levels, heat stress and even mortality. This paper builds on previous findings on the topic of non-constructible parcels, small vacant or built spaces in Municipal Beirut, some of which belong to the municipality while others are privately owned and which might be used for different functional purposes. This paper further examines the possibility of implementing cool surface or paving materials and urban vegetation to reduce air urban temperature, especially during the summer period and with the view to project the positive findings of this case study to the entire Municipal Beirut area. A numerical analysis using ENVI-met 4.0 investigates the thermal performance of these non-constructibles further to implementation of high reflective surfaces and urban vegetation on a broad neighborhood scale, taking the Bachoura District as a reference case for a typical summer day. The best air temperature reductions correspond to the use of cool material in areas that are far from buildings where there are no shadow effects. In some cases, the introduction of trees leads to an increase of the air temperature near the ground because they became an obstacle of the natural ventilation. Results show a maximum mitigation effect with the use of cool materials that lead to reductions in air temperatures up to 0.42 °C if used alone and up to 0.77 °C if used in combination with trees. Within the framework of an integrated approach to planning, this form of urban intervention aims for substantial overheating reduction.

scholarly journals Thermal growing season in Poland calculated by two different methods

2015 ◽  
Vol 47 (3) ◽  
pp. 261-273 ◽  
Author(s):  
Małgorzata Kępińska-Kasprzak ◽  
Przemysław Mager
Keyword(s):  
Air Temperature ◽  
Graphical Method ◽  
Growing Season ◽  
Threshold Value ◽  
Mean Values ◽  
Temperature Changes ◽  
Growing Seasons ◽  
Air Temperatures ◽  
Weather Stations ◽  
Comparative Results

Abstract Methods of identifying dates of passing determined threshold value are of significant importance in the study of thermal growing seasons. The difficulty to determine dates of beginning and end of growing season in a given year stems from the fact that daily mean air temperature changes irregularly on a day-to-day basis often crossing the threshold value (i.e. 5°C) multiple times. The most frequently used method to identify dates of threshold value crossing is the mathematical or graphical method proposed by Gumiński in 1950 which based on monthly mean air temperature values. In the 1970s, Huculak and Makowiec presented a method using daily mean values of air temperature. It is assumed that both methods give comparative results although calculations of daily mean air temperature render more accurate results. This paper presents the comparison of these two methods. Air temperatures measurements from 1966–2005 taken at 38 weather stations located in various physiographic conditions in Poland were used.

scholarly journals Trend Analysis of Air Temperature in the Federal District of Brazil: 1980–2010

Climate ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 89 ◽  
Author(s):  
Valdir Adilson Steinke ◽  
Luis Alberto Martins Palhares de Melo ◽  
Mamedes Luiz Melo ◽  
Rafael Rodrigues da Franca ◽  
Rebecca Luna Lucena ◽  
...  
Keyword(s):  
Air Temperature ◽  
Negative Impact ◽  
Statistical Tests ◽  
Federal District ◽  
Data Series ◽  
Public Administrators ◽  
Temperature Trends ◽  
Air Temperatures ◽  
Weather Stations ◽  
Maximum Minimum

This study was designed to identify trends in maximum, minimum, and average air temperatures in the Federal District of Brazil from 1980 to 2010, measured at five weather stations. Three statistical tests (Wald–Wolfowitz, Cox–Stuart, and Mann–Kendall) were tested for their applicability for this purpose, and the ones found to be most suitable for the data series were validated. For this data sample, it was observed that the application of the Wald–Wolfowitz test and its validation by the Cox–Stuart and Mann–Kendall tests was the best solution for analyzing the air temperature trends. The results showed an upward trend in average and maximum air temperature at three weather stations, a downward trend at one, and the absence of any trend at two. If the trend of increasing air temperature in the Federal District persists, it could have a negative impact on various sectors of society, mainly on the health of the population, especially during the dry season when more cases of respiratory diseases are registered. These results could serve as inputs for public administrators involved in the planning and formulation of public policies.

scholarly journals Mozingo Studies I. Ice phenology and limnological legacies in a mid-continental reservoir

2016 ◽  
Author(s):  
Kurt A. Haberyan
Keyword(s):  
Air Temperature ◽  
Ice Thickness ◽  
Physical Parameters ◽  
Mild Winter ◽  
Winter Conditions ◽  
Air Temperatures ◽  
Central United States ◽  
Meteorological Observations ◽  
Lake Record

<p>Long-term, integrated records of limnology are rare in the central United States.  Mozingo Lake is a reservoir in northwestern Missouri that was sampled regularly since its creation in 1994.  Physical data were collected during 121 visits and compared to meteorological observations. July hypolimnetic temperatures have risen rapidly (2.4°C / decade: P=0.037), suggesting weakened summer stratification in the future.  Winter conditions were rarely correlated with lake conditions in the following July; the exception is July epilimnion temperature, which correlated with ice-over date, January hypolimnion temperature, and ice duration (P=0.006, 0.010, and 0.024).  In contrast, winter ice-over date was best correlated with air temperature in the preceding July (P=0.006); other factors were not significantly correlated, including fall air temperatures, July epilimnion temperatures, and October water column temperatures. Analysis of air temperatures preceding ice-over revealed that the strongest correlation was with a 68-day average air temperature of 4.8°C. July air temperatures, along with ice-over date, correlated with January ice thickness and ice duration (P=0.014 and 0.001, respectively). This suggests that a warm July is associated with a mild winter, a relationship confirmed by a significant correlation (P=0.011). Ice thickness, ice duration, and ice-out date also correlated with winter air temperature (P≤0.003 for each). It therefore appears that summer conditions influence winter conditions which, in turn, influence certain lake conditions in the following summer; this observation indicates that winter conditions may not reset physical parameters in lakes.  Legacies thus may span various intervals, ranging from a week to a year or more.  Although the Mozingo Lake record is brief (20 years), it suggests directions for longer-term studies.  Multi-year legacy effects have rarely been documented, but in Mozingo Lake they suggest that a single strong climatic anomaly may affect the lake for several years.  </p>

scholarly journals Experiences in using low-cost sensors to observe road weather

2021 ◽  
Author(s):  
Virve Karsisto ◽  
Lasse Latva ◽  
Janne Miettinen ◽  
Marjo Hippi ◽  
Kari Mäenpää ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Explanatory Variable ◽  
Low Cost ◽  
Temperature Measurements ◽  
Sensor Technology ◽  
Spatial Density ◽  
Weather Station ◽  
Weather Stations ◽  
Temperature Observations

&lt;p&gt;Road weather information is essential for keeping the roads well maintained and safe during wintertime. Main source of road weather observations are road weather stations, but IoT (Internet of things) sensor technology provides new ways to observe road weather. Finnish Meteorological Institute (FMI) and Fintraffic Road are studying whether such IoT technology could help increase spatial density and/or improve coverage in the observation network and whether these additional observations could also be used to improve road weather forecasts. Around 100 autonomous battery-operated low-cost IoT sensors based on LoRaWAN communication technology were installed into the roadside area of a motorway in southern Finland and at the Sodankyl&amp;#228; airport test track during winter 2020. Most of the sensors were of the types UC11-T1 from Ursalink and ELT-2 from ELSYS AB, but there were a few MCF-LW12TERWP sensors from MCF88 as well. All sensors measure air temperature and humidity and the MCF sensors also measure air pressure. Some of the sensors were installed at a weather station and some at road weather stations to enable data comparison with reference stations. During wintertime the IoT sensors&amp;#8217; air temperature measurements correspond rather well to the reference measurements. However, during other times of the year the solar radiation often causes warm bias to the measurements. The bias is reduced when the sensors are installed inside radiation shields. However, the reliability of the IoT devices needs improvement, as several sensors stopped working during the measurement campaign. This was probably caused by a firmware bug, that led to excess power consumption and emptying of batteries in some of the devices.&lt;/p&gt;&lt;p&gt;The FMI road weather model uses surface temperature observations in the model initialization to improve the forecasts. As the model surface temperature is forced to the observed surface temperature, the air temperature measurements don&amp;#8217;t have that much effect in the initialization. When there are no surface temperature observations available at the forecast location, the model uses values interpolated from road weather station observations. The interpolation is done with the universal kriging method, where elevation is used as an explanatory variable. In this project we studied whether air temperature observations from IoT sensors could be used as explanatory variable as well. The results thus far show that use of air temperature observations from road weather stations improves the interpolated surface temperature values at least in some situations. However, this is rather location dependent. Initial results suggest that IoT observations would be useful this way as well. According to the results, IoT observations show potential to improve road weather monitoring and forecasting, but more studies are still needed.&lt;/p&gt;

scholarly journals Intercomparison of Surface Temperatures from AIRS, MERRA, and MERRA-2 with NOAA and GC-Net Weather Stations at Summit, Greenland

2018 ◽  
Vol 57 (5) ◽  
pp. 1231-1245 ◽  
Author(s):  
Thomas J. Hearty ◽  
Jae N. Lee ◽  
Dong L. Wu ◽  
Richard Cullather ◽  
John M. Blaisdell ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Cold Season ◽  
Near Surface ◽  
Surface Temperatures ◽  
Air Temperatures ◽  
Weather Stations ◽  
The Difference ◽  
Temperature Inversions

AbstractThe surface skin and air temperatures reported by the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU-A), the Modern-Era Retrospective Analysis for Research and Applications (MERRA), and MERRA-2 at Summit, Greenland, are compared with near-surface air temperatures measured at National Oceanic and Atmospheric Administration (NOAA) and Greenland Climate Network (GC-Net) weather stations. The AIRS/AMSU-A surface skin temperature (TS) is best correlated with the NOAA 2-m air temperature (T2M) but tends to be colder than the station measurements. The difference may be the result of the frequent near-surface temperature inversions in the region. The AIRS/AMSU-A surface air temperature (SAT) is also correlated with the NOAA T2M but has a warm bias during the cold season and a larger standard error than the surface temperature. The extrapolation of the temperature profile to calculate the AIRS SAT may not be valid for the strongest inversions. The GC-Net temperature sensors are not held at fixed heights throughout the year; however, they are typically closer to the surface than the NOAA station sensors. Comparing the lapse rates at the two stations shows that it is larger closer to the surface. The difference between the AIRS/AMSU-A SAT and TS is sensitive to near-surface inversions and tends to measure stronger inversions than both stations. The AIRS/AMSU-A may be sampling a thicker layer than either station. The MERRA-2 surface and near-surface temperatures show improvements over MERRA but little sensitivity to near-surface temperature inversions.

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