scholarly journals Analyses of the Zagreb Grič observatory air temperatures indices for the period 1881 to 2017

2018 ◽  
pp. 67-85 ◽  
Author(s):  
Ognjen Bonacci ◽  
Tanja Roje Bonacci
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Partial Sums ◽  
Daily Maximum ◽  
Absolute Maximum ◽  
Absolute Minimum ◽  
Air Temperatures ◽  
Temperature Regimes ◽  
Urban Heat ◽  
Maximum Temperatures

The paper studies time series of characteristic (minimum, mean, and maximum) daily, monthly, and yearly air temperatures measured at the Zagreb Grič Observatory in the period from 1 Jan. 1881 to 31 Dec. 2017. The following five air temperatures indices (ATI) are analysed: (1) absolute minimum yearly, monthly, and daily; (2) mean yearly, monthly, and daily minimum; (3) average mean yearly, monthly, and daily; (4) mean yearly, monthly, and daily maximum; (5) absolute maximum yearly, monthly, and daily. Methods of Rescaled Adjusted Partial Sums (RAPS), regression and correlation analyses, F-tests, and t-tests are used in order to describe changes in air temperature regimes over 137 years. Using the RAPS method the five analysed yearly ATI time series durations of 137 years were divided into two sub-periods. The analyses made in this paper showed that warming of minimum air temperatures started in 1970, mean air temperatures in 1988, and maximum air temperatures in 1998. Results of t-tests show an extreme statistically significant jump in the average air-temperature values in the second (recent time) sub-periods. Results of the t-tests of monthly temperatures show statistically significant differences between practically all five pairs (except in two cases) of analysed monthly ATI subseries for the period from January to August. From September to December the differences for most of pairs (except in six cases) of the analysed monthly ATI subseries are not statistically significant. It can be concluded that the urban heat island influenced the increase in recent temperatures more strongly than global warming. It seems that urbanisation firstly and chiefly influenced the minimum temperatures, as well as that Zagreb’s urbanisation had a bigger impact on minimum temperatures than on maximums. Increasing trend in time series of maximum temperatures started 20 years later.

scholarly journals Heatwaves and Summer Urban Heat Islands: A Daily Cycle Approach to Unveil the Urban Thermal Signal Changes in Lisbon, Portugal

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 292 ◽  
Author(s):  
Ana Oliveira ◽  
António Lopes ◽  
Ezequiel Correia ◽  
Samuel Niza ◽  
Amílcar Soares
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Wind Direction ◽  
Urban Heat Islands ◽  
Daily Cycle ◽  
Local Climate ◽  
Thermal Signal ◽  
Air Temperatures ◽  
Local Climate Change ◽  
Urban Heat

Lisbon is a European Mediterranean city, greatly exposed to heatwaves (HW), according to recent trends and climate change prospects. Considering the Atlantic influence, air temperature observations from Lisbon’s mesoscale network are used to investigate the interactions between background weather and the urban thermal signal (UTS) in summer. Days are classified according to the prevailing regional wind direction, and hourly UTS is compared between HW and non-HW conditions. Northern-wind days predominate, revealing greater maximum air temperatures (up to 40 °C) and greater thermal amplitudes (approximately 10 °C), and account for 37 out of 49 HW days; southern-wind days have milder temperatures, and no HWs occur. Results show that the wind direction groups are significantly different. While southern-wind days have minor UTS variations, northern-wind days have a consistent UTS daily cycle: a diurnal urban cooling island (UCI) (often lower than –1.0 °C), a late afternoon peak urban heat island (UHI) (occasionally surpassing 4.0 °C), and a stable nocturnal UHI (1.5 °C median intensity). UHI/UCI intensities are not significantly different between HW and non-HW conditions, although the synoptic influence is noted. Results indicate that, in Lisbon, the UHI intensity does not increase during HW events, although it is significantly affected by wind. As such, local climate change adaptation strategies must be based on scenarios that account for the synergies between potential changes in regional air temperature and wind.

scholarly journals Extreme Temperature Events in Serbia in Relation to Atmospheric Circulation

Atmosphere ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 1584
Author(s):  
Ivana Tošić ◽  
Suzana Putniković ◽  
Milica Tošić ◽  
Irida Lazić
Keyword(s):  
Atmospheric Circulation ◽  
Heat Waves ◽  
Extreme Temperature ◽  
Daily Maximum ◽  
Absolute Maximum ◽  
Extreme Temperature Events ◽  
Atmospheric Circulation Patterns ◽  
Circulation Patterns ◽  
Maximum Temperatures ◽  
The Relationship

In this study, extremely warm and cold temperature events were examined based on daily maximum (Tx) and minimum (Tn) temperatures observed at 11 stations in Serbia during the period 1949–2018. Summer days (SU), warm days (Tx90), and heat waves (HWs) were calculated based on daily maximum temperatures, while frost days (FD) and cold nights (Tn10) were derived from daily minimum temperatures. Absolute maximum and minimum temperatures in Serbia rose but were statistically significant only for Tx in winter. Positive trends of summer and warm days, and negative trends of frost days and cold nights were found. A high number of warm events (SU, Tx90, and HWs) were recorded over the last 20 years. Multiple linear regression (MLR) models were applied to find the relationship between extreme temperature events and atmospheric circulation. Typical atmospheric circulation patterns, previously determined for Serbia, were used as predictor variables. It was found that MLR models gave the best results for Tx90, FD, and Tn10 in winter.

scholarly journals Winter Protection of Tree Ferns at the Royal Botanic Garden Edinburgh

2007 ◽  
pp. 141-154
Author(s):  
Andrew Ensoll ◽  
Louise Galloway ◽  
Alastair Wardlaw
Keyword(s):  
Air Temperature ◽  
Royal Botanic Garden ◽  
Botanic Garden ◽  
Tree Fern ◽  
Additional Specimen ◽  
Air Temperatures ◽  
Tree Ferns ◽  
Insulation Effect ◽  
Maximum Temperatures ◽  
Heated Glass

Ten plants of six species of tree fern were trialled for frost hardiness during the winter of 2005/06 when they were planted outdoors in the ground of an interior courtyard at the Royal Botanic Garden Edinburgh. The species were Culcita macrocarpa, Cyathea dealbata, Cyathea dregei,Cyathea smithii, Dicksonia antarctica and Thyrsopteris elegans. An additional specimen of C. dregei was planted in the main garden. The apex region of each tree fern was fitted with an electric thermometer probe to record weekly minimum and maximum temperatures. These were compared with the air temperatures of the courtyard. For thermal insulation, the trunks and crowns of the three Cyathea species were encased in straw. The prostrate rhizomes of C. macrocarpa and T. elegans were covered respectively with leaf litter, straw and a polystyrene tile. As comparators, three trunked specimens of D. antarctica were given no winter wrapping, since previous experience had shown it to be unnecessary. All ten plants survived the winter of 2005/06 which was colder than average, and put out new growth the following spring. Fronds of D. antarctica and C. macrocarpa stayed green; the fronds of the other species were withered by the coldest exposures when the air temperature reached 4.7°C.Compared with the main botanic garden, the courtyard provided a relatively mild microclimate. It was on average 2.5 °C warmer than the air temperature measured in the screen of the main garden weather station, and 7.7°C warmer than the ‘grass’ temperature in the main garden, which went down to –13°C at its lowest. All tree fern apices registered sub-zero temperatures, the range in different plants being from –0.3 to –3.4°C. The apex regions did not get as cold as the surrounding air temperature, which ranged between 0.5 and 2.3°C. The three D. antarctica (without added insulation) had minimum apical temperatures in the same range as the species that were wrapped for the winter. The insulation effect in the apex regions was also shown by the weekly maximum temperatures, which on average were lower than those of the courtyard air maxima.In conclusion, the combination of the locally favourable microclimate of the courtyard, plus appropriate trunk and crown insulation provided for some species, allowed the planting outdoors, of tree ferns normally grown in Edinburgh under heated glass.

scholarly journals Long-term Effect of Temperature and Triadimefon on Proliferation of Uncinula necator: Implications for Fungicide Resistance and Disease Risk Assessment

Plant Disease ◽  
1997 ◽  
Vol 81 (10) ◽  
pp. 1187-1192 ◽  
Author(s):  
H. L. Ypema ◽  
W. D. Gubler
Keyword(s):  
Risk Assessment ◽  
Disease Risk ◽  
Resistant Isolate ◽  
Effect Of Temperature ◽  
Daily Maximum ◽  
Uncinula Necator ◽  
Risk Assessment Models ◽  
Temperature Regimes ◽  
Entire Duration ◽  
Maximum Temperatures

Triadimefon has been used in California to control Uncinula necator, causal agent of grape powdery mildew, since 1982. Instances of unsatisfactory control have occurred mainly in the cooler coastal areas of California. The effect of temperature and application of triadimefon was investigated over a 53-day-period on two U. necator isolates, sensitive and resistant to triadimefon. At 15°C, 25°C, or temperatures fluctuating between 15 and 25°C, in absence of triadimefon, the isolates continued to produce high numbers of conidia for the entire duration of the experiment. Sporulation declined at daily maximum temperatures of 32°C for 6 h, 36°C for 3 h, and 40°C for 1 h, but was detectable when the experiment was terminated. At these temperature regimes, sporulation of the triadimefon-treated sensitive isolate ceased after 23 days. When treated with triadimefon, sporulation of the resistant isolate was comparable to that of the water-treated control. At daily maximum temperatures of 32°C for 11 h, 36°C for 6 h, and 40°C for 3 h, sporulation of both isolates generally ceased after 23 days, regardless of triadimefon application. Triadimefon resistance is most likely to manifest itself under high disease pressure, which is in part a function of temperature. The duration of daily maximum temperatures may be a valuable addition to disease risk assessment models.

scholarly journals Identifying the influence of dams and ponds on the thermal regime at regional scale: The case of Loire catchment

2020 ◽  
Author(s):  
Hanieh Seyedhashemi ◽  
Florentina Moatar ◽  
Jean-Philippe Vidal ◽  
Aurélien Beaufort ◽  
André Chandesris ◽  
...  
Keyword(s):  
Time Series ◽  
Air Temperature ◽  
Temperature Regime ◽  
Thermal Regime ◽  
Regional Scale ◽  
Stream Temperature ◽  
Annual Peak ◽  
Air Temperatures ◽  
Catchment Areas ◽  
Anthropogenic Structures

<p>Human activities and natural processes are the main drivers of the spatio-temporal variability of thermal regime. Despite a few local studies on the thermal regime variability, regional assessments are scarce in the scientific literature. However, regional assessments allow tracing systematic human-induced changes emerging from some types of anthropogenic structures like dams or ponds and identifying the locations of highly influenced reaches.</p><p>In the current study, we propose a framework to detect the influence of dams and ponds on stream temperature. We use observational data from 526 evenly distributed hourly stream temperature stations in the Loire River catchment, France (110,000 km<sup>2</sup>). The data consist of unbalanced time series of natural and altered thermal regimes that contain at least 80 summer days from 2000–2018. By comparing time series of observed stream temperature and air temperature, we define five indicators to distinguish different patterns of thermal regime. Three of them are based on weekly stream-air temperature linear regressions (slope; intercept; and coefficient of determination). The remaining two indicators compare monthly air and stream temperature regime: 1) the proportion of times stream temperature is greater than air temperature from March–October (“frequency”), and 2) the lag time between the annual peak in air temperature and annual peak in stream temperature (“shift”).</p><p>K-means clustering partitioned stations into three clusters: 1) pond-like, 2) dam-like 3) and natural, with 164, 37, and 316 stations, respectively. Supporting this cluster analysis, 93% of stations in pond-like cluster have upstream ponds, and 55% of stations in dam-like cluster have upstream large dams. Pond-like stations have the greatest slope between weekly stream and air temperatures (slope = 0.4) and have stream temperatures greater than air temperatures more frequently (68%) than other clusters. In contrast, dam-like stations have the lowest correlations between weekly stream and air temperatures (mean R<sup>2</sup>=0.3, compared to 0.7 for the other two clusters). Dam-like stations also exhibit the largest shifts in stream thermal regime relative to air temperature (mean shift = 30 days). Impounded runoff index (IRI), the ratio of reservoir volume to annual discharge, best explaines variability within the dam-like cluster. For pond-like stations, catchment areas and mean upstream ponded surface area best explain the within-cluster variability, particularly for the frequency indicator, although this relationship is sensitive to interannual air temperature regime.</p><p>These findings support modelers in quantifying the downstream impacts of different types of anthropogenic structures and managers in surveying and monitoring stream networks through identification of critical reaches.</p>

scholarly journals Cool Pavement Strategies for Urban Heat Island Mitigation in Suburban Phoenix, Arizona

2019 ◽  
Vol 11 (16) ◽  
pp. 4452 ◽  
Author(s):  
Sushobhan Sen ◽  
Jeffery Roesler ◽  
Benjamin Ruddell ◽  
Ariane Middel
Keyword(s):  
Urban Heat Island ◽  
Air Temperature ◽  
Urban Areas ◽  
Meteorological Data ◽  
Heat Island ◽  
Land Use Patterns ◽  
Reflective Coating ◽  
Air Temperatures ◽  
Artificial Surfaces ◽  
Urban Heat

Urban areas are characterized by a large proportion of artificial surfaces, such as concrete and asphalt, which absorb and store more heat than natural vegetation, leading to the Urban Heat Island (UHI) effect. Cool pavements, walls, and roofs have been suggested as a solution to mitigate UHI, but their effectiveness depends on local land-use patterns and surrounding urban forms. Meteorological data was collected using a mobile platform in the Power Ranch community of Gilbert, Arizona in the Phoenix Metropolitan Area, a region that experiences harsh summer temperatures. The warmest hour recorded during data collection was 13 August 2015 at 5:00 p.m., with a far-field air temperature of about 42 ∘ C and a low wind speed of 0.45 m/s from East-Southeast (ESE). An uncoupled pavement-urban canyon Computational Fluid Dynamics (CFD) model was developed and validated to study the microclimate of the area. Five scenarios were studied to investigate the effects of different pavements on UHI, replacing all pavements with surfaces of progressively higher albedo: New asphalt concrete, typical concrete, reflective concrete, making only roofs and walls reflective, and finally replacing all artificial surfaces with a reflective coating. While new asphalt surfaces increased the surrounding 2 m air temperatures by up to 0.5 ∘ C, replacing aged asphalt with typical concrete with higher albedo did not significantly decrease it. Reflective concrete pavements decreased air temperature by 0.2–0.4 ∘ C and reflective roofs and walls by 0.4–0.7 ∘ C, while replacing all roofs, walls, and pavements with a reflective coating led to a more significant decrease, of up to 0.8–1.0 ∘ C. Residences downstream of major collector roads experienced a decreased air temperature at the higher end of these ranges. However, large areas of natural surfaces for this community had a significant effect on downstream air temperatures, which limits the UHI mitigation potential of these strategies.

scholarly journals Long-Term Winter Inversion Properties in a Mountain Valley of the Western United States and Implications on Air Quality

2015 ◽  
Vol 54 (12) ◽  
pp. 2339-2352 ◽  
Author(s):  
S.-Y. Simon Wang ◽  
Lawrence E. Hipps ◽  
Oi-Yu Chung ◽  
Robert R. Gillies ◽  
Randal Martin
Keyword(s):  
Air Quality ◽  
Air Temperature ◽  
Daily Maximum ◽  
Horizontal Distance ◽  
Climate Conditions ◽  
Air Temperatures ◽  
Narrow Valley ◽  
Northern Utah ◽  
Temperature Inversions

AbstractBecause of the geography of a narrow valley and surrounding tall mountains, Cache Valley (located in northern Utah and southern Idaho) experiences frequent shallow temperature inversions that are both intense and persistent. Such temperature inversions have resulted in the worst air quality in the nation. In this paper, the historical properties of Cache Valley’s winter inversions are examined by using two meteorological stations with a difference in elevation of approximately 100 m and a horizontal distance apart of ~4.5 km. Differences in daily maximum air temperature between two stations were used to define the frequency and intensity of inversions. Despite the lack of a long-term trend in inversion intensity from 1956 to present, the inversion frequency increased in the early 1980s and extending into the early 1990s but thereafter decreased by about 30% through 2013. Daily mean air temperatures and inversion intensity were categorized further using a mosaic plot. Of relevance was the discovery that after 1990 there was an increase in the probability of inversions during cold days and that under conditions in which the daily mean air temperature was below −15°C an inversion became a certainty. A regression model was developed to estimate the concentration of past particulate matter of aerodynamic diameter ≤ 2.5 μm (PM2.5). The model indicated past episodes of increased PM2.5 concentrations that went into decline after 1990; this was especially so in the coldest of climate conditions.

Automated detection of urban heat islands based on satellite imagery, digital surface models, and a low-cost sensor network                                     

2021 ◽  
Author(s):  
Sebastian Schlögl ◽  
Nico Bader ◽  
Julien Gérard Anet ◽  
Martin Frey ◽  
Curdin Spirig ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Rural Areas ◽  
Urban Areas ◽  
Low Cost ◽  
Urban Heat Islands ◽  
Heat Islands ◽  
Micro Scale ◽  
Air Temperatures ◽  
Urban Heat

<p>Today, more than half of the world’s population lives in urban areas and the proportion is projected to increase further in the near future. The increased number of heatwaves worldwide caused by the anthropogenic climate change may lead to heat stress and significant economic and ecological damages. Therefore, the growth of urban areas in combination with climate change can increase future mortality rates in cities, given that cities are more vulnerable to heatwaves due to the greater heat storage capacity of artificial surfaces towards higher longwave radiation fluxes.</p><p>To detect urban heat islands and resolve the micro-scale air temperature field in an urban environment, a low-cost air temperature network, including 450 sensors, was installed in the Swiss cities of Zurich and Basel in 2019 and 2020. These air temperature data, complemented with further official measurement stations, force a statistical air temperature downscaling model for urban environments, which is used operationally to calculate hourly micro-scale air temperatures in 10 m horizontal resolution. In addition to air temperature measurements from the low-cost sensor network, the model is further forced by albedo, NDVI, and NDBI values generated from the polar-orbiting satellite Sentinel-2, land surface temperatures estimated from Landsat-8, and high-resolution digital surface and elevation models.</p><p>Urban heat islands (UHI) are processed averaging hourly air temperatures over an entire year for each grid point, and comparing this average to the overall average in rural areas. UHI effects can then be correlated to high-resolution local climate zone maps and other local factors.</p><p>Between 60-80 % of the urban area is modeled with an accuracy below 1 K for an hourly time step indicating that the approach may work well in different cities. However, the outcome may depend on the complexity of the cities. The model error decreases rapidly by increasing the number of spatially distributed sensor data used to train the model, from 0 to 70 sensors, and then plateaus with further increases. An accuracy below 1 K can be expected for more than 50 air temperature measurements within the investigated cities and the surrounding rural areas. </p><p>A strong statistical air temperature model coupled with atmospheric boundary layer models (e.g. PALM-4U, MUKLIMO, FITNAH) will aid to generate highly resolved urban heat island prediction maps that help decision-makers to identify local heat islands easier. This will ensure that financial resources will be invested as efficiently as possible in mitigation actions.</p>

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