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One of information needed in weather forecast is air temperature. This value might change any time. Prediction of air temperature is very valuable for some communities and occasions. Therefore, high accuracy prediction is needed. Since the information about air temperature might vary over time, it is necessary to implement methods that can adapt to this situation. The use of neural network methods such as long short term memory (LSTM), nowadays, becomes popular in facing big data including unexpected fluctuation on the data. Thus, the model is used in this paper which provides long series data on air temperature. In addition, recently, Facebook announced an accurate method of forecasting, called Prophet model's, for data which have trend, seasonality, holidays, missing data, not to mention outliers. Hence, the forecast of five-year daily air temperatures in Bandung on this paper is modeled by LSTM and Facebook Prophet. The result shows that, for minimum temperature, Prophet performs better on maximum air temperature while LSTM performs better on minimum air temperature. However, the difference on the value of RMSE is not too large significant. [ABSTRACT FROM AUTHOR]

Remote sensing techniques are a useful tool for continuous observation of the Earth at global scale. However, products derived from remote sensing data require a rigorous validation using in situ data. Moderate Resolution Imaging Spectroradiometer (MODIS) is not really a sounding instrument, but it does have 16 infrared bands (bands 20–36 covering the spectral range from 3 µm to 14 µm) that allow the retrieval of temperature and moisture profiles as well as total column integrated magnitudes. In this paper we show the results obtained in the evaluation of MOD07 daytime and nighttime products over the Iberian Peninsula during the decade from 2000 to 2010 using nine radiosonde stations. Although MODIS limitations in comparison with other sounding instruments, the validation provided satisfactory results, with bias (MOD07 minus radiosonde) < 0.3 cm and a standard deviation of 0.5 cm for the total column water vapor, and bias around 1 K on average with standard deviations between 2 K and 3 K for air temperature at different pressure levels. On average, bias was positive and below 2 K with standard deviations around 5 K for the dew point temperature case. Large errors were found in this case for pressure levels higher than 50 hPa. [ABSTRACT FROM AUTHOR]

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Pear fruit are subject to sun damage from high fruit surface temperature (FST). Threshold FST for the occurrence of sunburn are currently unknown and basic relationships between FST of pears and weather parameters have not been reported. Such knowledge is needed to aid implementation of management practices and improve orchard design to minimise sunburn. This paper reports relationships between pear FST and weather conditions. Continuous monitoring of FST and observations of sunburn damage enabled determination of threshold FST for the development of sunburn. Threshold FST for sunburn damage on ‘ANP-0131’ (Deliza®) pears was estimated to be 47.1 °C. Use of FST thresholds to improve mitigation of sunburn is discussed. [ABSTRACT FROM AUTHOR]

Precisely forecasting air temperature as a significant meteorological parameter has a critical role in environment quality management. Hence, this study employs a hybrid intelligent model for accurately monthly temperature forecasting for one to three times ahead in the hottest and coldest regions of the world. The hybrid model contains the artificial neural network (ANN) hybridized with the powerful hetaeristic Honey Badger Algorithm (HBA-ANN). The average mutual information (AMI) technique is employed to find the optimal time delay values for the temperature variable for different time horizons. Finally, the performance of the developed hybrid model is compared with the classical ANN and the Gene Expression Programming (GEP) using some statistical criteria, and the Taylor and scatter diagrams. Results indicated that in each time horizon, the HBA-ANN model with the lowest distance from observation points based on Taylor diagram, high values for NSE and R², and low values for RMSE, MAE, and RSR outperformed the ANN and GEP models in both training and testing phases. Hence, using the Honey Badger Algorithm could increase the accuracy of the model. This model's precise performance supports the case for it to be employed to forecast other environmental parameters. [ABSTRACT FROM AUTHOR]

The London Olympic Parkland represents a substantial area of redevelopment with the potential to significantly modify urban temperatures. This paper illustrates a neighbourhood-scale model of the type that can be used to analyse the impact of large developments on the urban heat island, using the London Olympic Parkland as an example. Using theAtmospheric Dispersion Modelling System Temperature and Humiditymodel, the impact of the urban surfaces for the Parkland area (∼16 km2) is modelled at a 400 m2grid resolution for the pre-Olympic, Olympic and Legacy periods. Temperature perturbations from upwind values are simulated for the periods to estimate the contribution the Parkland has on local air temperatures. The results illustrate the impact that large impermeable features such as the concourse might have on increased air temperatures during Olympic period design conditions. In comparison, a Legacy scenario shows temperature reductions from the pre-Olympic period due to an increase in vegetation coverage. [ABSTRACT FROM AUTHOR]

Public health professionals are increasingly concerned about the potential impact that climate variability and change can have on infectious disease. The International Research Institute for Climate and Society (IRI) is developing new products to increase the public health community’s capacity to understand, use and demand the appropriate climate data and climate information to mitigate the public health impacts of climate on infectious disease, in particular meningitis and malaria. In this paper, we present the new and improved products that have been developed for: (i) estimating dust aerosol for forecasting risks of meningitis and (ii) for monitoring temperature and rainfall and integrating them into a vectorial capacity model for forecasting risks of malaria epidemics. We also present how the products have been integrated into a knowledge system (IRI Data Library Map Room, SERVIR) to support the use of climate and environmental information in climate-sensitive health decision-making. [ABSTRACT FROM PUBLISHER]

During 826, 1-h sessions 107 participants (33 women, 74 men, 18-51 years of age) were exposed to defined draughts where air velocity (0.1≤V[sub a]≤0.4 m s[sup -1]), turbulence intensity (<30, ≈50, >70%), draught direction (horizontal, vertical, diagonal), air temperature (11≤t[sub a]≤23°C), and metabolic rate (≈60≤M≤156 W m[sup -2]) were varied but kept constant during single sessions. Perception and evaluation (annoyance due to draught and local cold) were registered using a list of prescribed body parts. Annoyance due to draught increased with the increase in mean air velocity and in turbulence intensity, as well as with the decrease in air temperature and in metabolic rate. The direction of air flow had no influence. As these responses were neither sufficiently predicted by the draught-rating model proposed in ISO 7730 (1994), nor by its extension developed by Toftum (1994a), the latter was modified according to the data registered in this paper. Using the modified model the accordingly predicted percentage of people annoyed by draught agreed highly with the percentage actually observed (r=0.726, p<0.001). As the resulting model covers larger ranges of air temperature and metabolic rate it is suggested that it should substitute the model proposed in ISO 7730 [1994]. [ABSTRACT FROM AUTHOR]

Establishing green roofs has been used as a method to mitigate urban environmental quality problems. In this study, the effect of Tehran Nature Bridge green roof as a sustainable structure on its surrounding microclimate is investigated using urban microclimate model, ENVI-met, on a hot summer day in July 2015. For this purpose, two simulation scenarios were generated to assess the impact of extensive and intensive green roofs on some climate variables. A comparison was made between the scenarios at two different heights, 1.5 and 40.5 m and two times including 10 am and 4 pm. Based on the predicted results, the second scenario showed a 10.47% increase in relative humidity (RH) compared to the first scenario on bridge level at 10 am. In the second scenario, air temperature dropped by 0.8°C at 10 am compared with the first scenario, which is equivalent to 2.87%. The presence of intensive green roof caused a decrease in wind velocity on bridge level by 1.75 m/s and changed its direction. Furthermore, green roof also influenced velocity and direction of the wind, RH, and air temperature in different ways at ground level. Overall, green roof altered climatic parameters such as air temperature, RH, and wind velocity and direction at both bridge and ground level. [ABSTRACT FROM AUTHOR]

Measurements of air temperature, mean radiant temperature, air velocity and humidity are necessary for the evaluation of the thermal environment at a place of work and it's influence on man. In the present paper methods and transducers for measuring the physical parameters of the thermal environment are described and compared. [ABSTRACT FROM PUBLISHER]

The invasive tiger mosquito Aedes albopictus is a serious nuisance for people due to its biting and potential for disease transmission, even in Italian mountain regions. In this work, we examined its occurrence dynamic from the first invasion in two Alpine cities, Rovereto and Trento, only 25 km apart. Mosquito's distribution was assessed using ovitraps, from mid-May to end-October, from its first reported occurrence, i.e. 2001 in Rovereto and 2010 in Trento. In both cities, ovitraps were located in seven habitat types: gathering places, residential areas, urban parks, car parks, near watercourses, industrial areas and croplands. The annual average temperature and precipitation were similar in the two cities from 2001 to 2020. We had hypothesized that the seasonal and annual differences in egg number between both cities would be limited. Significant linear and positive relationship was found between the average number of eggs and air temperature in both the cities, but with a steeper slope in Trento. In addition, the average number of eggs per ovitrap was higher in Trento than in Rovereto (average 50.3 vs 14.2). None of the considered risk factors (climate, habitat type) explained such difference in abundance between cities. Indeed, based on the temperature, the expectation was to find fewer eggs in Trento being cooler than Rovereto during 2010–2020 (the average in the period of activated traps was, respectively, 19.2 vs 19.7°C). Thus, we argue that other anthropogenic factors, such as different control activities (adulticide treatments were carried out solely in Rovereto), might explain the difference in egg abundance found between cities. A specific experimental design to evaluate treatment effect might validate our hypothesis (e.g. apply adulticides during the surveillance period, with treatments applied at regular distances from the ovitraps and with a specific periodicity to compare adult and egg abundance). Ae. albopictus invaded two alpine cities 25 km apart with a lag of 12 yrs Temporal trend of egg abundance was positively correlated with temperature in both cities Ae. albopictus was more abundant in gathering places in urban areas The colder city (Trento) was the more infested Control activities carried out in Rovereto might explain difference in abundance between the two cities [ABSTRACT FROM AUTHOR]

In this study, soil temperature of Sivas province was estimated by the artificial neural networks (ANNs) method using data obtained from five different meteorological measurement stations situated in provincial borders. Nineteen years of (2000–2018) monthly mean air temperature data obtained from five different soil depths (5, 10, 20, 50 and 100 cm) was used for ANN analysis. Predicted and measured soil temperatures were strongly correlated with determination coefficient (R2) values ranging between 0.9767 and 0.9941. Mean Absolute Error (MAE) ranged from 0.532°C to 1.381°C, while Mean Absolute Percentage Error (MAPE) ranged from 5.692% to 16.263% and Root Mean Squared Error (RMSE) ranged between 0.694°C and 1.666°C. It was found that the predicted values are in good agreement with the measured data. However, there was a tendency to underestimate the soil temperature. [ABSTRACT FROM AUTHOR]

Green and cool roofs retrofit technologies, aim to mitigate the urban heat island effect and cooling energy demands from buildings. This study reports on parametric energy modelling of energy saving loads and indoor air temperature, as well as microclimate modelling of outdoor air temperature. The work adds new knowledge by evaluating roof retrofit technologies at the building and neighbourhood scale, and the results should guide strategic decisions for building envelope retrofitting. The simulations respectively predicted a 10% and 7.5% reduction in the cooling load for cool and green roofs versus a conventional roof. In summer, the indoor air temperature was similar for these roofs, but in winter the cool roof's indoor air temperature was 0.5°C lower than the green. In the microclimate simulation, average roof surface temperatures were 31.5°C (cool) and 31.3°C (green), versus 40.2°C (conventional); the air temperature difference was −0.8°C (cool) and −0.6°C (green) against the conventional roof. [ABSTRACT FROM AUTHOR]

Sea surface temperature (SST) is an important indicator of marine system. In this study, the hybrid physically-statistically based air2water model was modified for the forecasting of SST. The hybrid model combines empiricism and theory, and balances the complexity and accuracy between the process-based physical models and statistical models. Daily observed SST data (2009–2019) from six stations in the Baltic Sea were used for the evaluation of model performance. Two metrics including the root mean squared error (RMSE) and the Nash-Sutcliffe efficiency coefficient (NSE) were used for model assessment. With the increase of air temperature, SST presents a clear warming trend (0.133°C/year–0.166°C/year), and air temperature warms faster than SST in the studied stations. The modelling results indicated that the model performs well for SST forecasting (in the validation period, mean value of RMSE is 1.245°C, and mean value of NSE is 0.961). Cross-validation results showed that the model is transferable in unknown stations. However, the model works a little bit worse in the warm period due to the impact of the upwelling phenomenon. Overall, the model is a promising tool for the prediction of SST. [ABSTRACT FROM AUTHOR]

Air temperature (Tair) is a fundamental variable in climate research and climate impact management. Conventional field observations do not accurately capture its spatial distribution due to the sparse and uneven distribution of weather stations, especially in remote areas where the local variability is high. To circumvent this problem, in this study, remote sensing and weather station data were used to estimate Tair in the Souss watershed in Morocco. Two statistical methods, including linear regression and partial least squares (PLS), and four machine learning algorithms, namely k-nearest neighbors, random forest (RF), extreme gradient boost, and Cubist, were used for modeling and predicting Tair and its performance were evaluated using random subsets and cross-validation. Moderate resolution imaging spectroradiometer predictors, including Terra band 32 emissivity, Terra nighttime land surface temperature, Terra local time of night observation, Aqua band 31 emissivity, Aqua daytime land surface temperature, and Aqua nighttime land surface temperature (ALSTN), and auxiliary inputs, including sky-view, elevation, slope, and hillshade, were used as inputs for modeling. The results showed that the Cubist and RF were the most accurate models (RMSE = 2.09°C and 2.13°C, R2 = 0.91 and 0.90, respectively), while PLS had the lowest predictive power (RMSE = 2.71°C; R2 = 0.83). The overall performance of the models for estimating Tair in the study area was generally satisfactory, with RMSE limited to less than 3°C for all models. Nevertheless, the station data reliability was still an issue, with only four of the seven stations marked by complete meteorological data. [ABSTRACT FROM AUTHOR]

Spatially distributed air temperature (Ta) data are essential for environmental studies. Ta data are collected from meteorological stations of sparse distribution. This problem can be overcome by using remotely sensed datasets at different scales. This study used land-based temperature measurements and satellite data for estimating Ta distribution over the United Arab Emirates. Land-based Ta data from 11 weather stations during 2003 to 2019 were used with MODIS Aqua LST for both daytime (LSTd) and nighttime (LSTn) data. The results indicate a significant correlation between LST and Ta with regression coefficients R2 > 0.94/0.96 and Root Mean Square Error about 1.75/0.97 °C of LSTd/Tmax and LSTn/Tmin, respectively. Large variability was observed between the daytime and nighttime mean temperature distribution indicating the importance of MODIS LST as a proxy for Ta. These countrywide Ta grids provide vital tools for the planning of environmental and economic developments in the era of global climate change. [ABSTRACT FROM AUTHOR]

How do we explain the way that climate affects plant distribution, such as arctic or alpine treelines? Faced with predictions of significant human-caused climate changes such questions are of huge applied, as well as academic, interest. Recently in this journal Christian Korner (2008) provocatively argued that data on winter crop growth may provide important insights into the factors that govern treelines - a surprising, and perhaps inspired choice of data for thinking about trees. Here I consider Korner's views in the wider context of temperature regulation in plants and their geological history. [ABSTRACT FROM AUTHOR]

Junglerice (Echinochloa colona) is one of the most important annual weeds affecting crops in Argentina. A predictive seedling emergence model based on thermal time was developed and validated. Monitoring of seedling emergence was performed weekly during the growing season in a soybean field over four years. Cumulative thermal time, expressed in growing degree days (GDD), was used as the independent variable for predicting cumulative emergence. The variations in mean air temperature between late August and early September have determined a period with a conserved pattern over the years. That period had a close linear relationship (r2 = 0.99) with the beginning of seedling emergence. A double-logistic model fitted junglerice seedling emergence better than Gompertz, Logistic or Weibull functions. Model validation showed a good performance in predicting the seedling emergence (r2 = 0.99). Based on findings of this study it is possible to predict junglerice emergence by air temperature and, thus, to contribute reliably to the rational management of this weed. [ABSTRACT FROM AUTHOR]

Sea ice conditions and navigability along four typical routes of the Northeast Passage (NEP) are analysed using remote-sensing data from 1979 to 2019. The influence of air temperature (Tair) and surface wind on the sea ice concentration (SIC) and the navigability of routes is determined. It is found that the annually averaged SICs of the different routes have decreased over the past 41 years. The fastest rate of decrease occurred in the Kara Sea (∼−1% per year), while the slowest rates of decrease occurred in the Laptev/East Siberian Sea (∼−0.42% per year). The number of navigable days for the Kara Sea has become ∼1–2 months longer than the Laptev/East Siberian Sea route as a result. The effect of Tair on SIC, quantified by ΔSIC/ΔTair in the routes through the eastern Kara Sea and Laptev/East Siberian Sea in 2010s was ∼−0.04/°C, two to three times that seen during the 1980s. Air temperature is becoming a significant driving force of melting ice in these routes. Surface winds are also a crucial factor for the navigability of the Vilkitsky Strait and Long Strait, as they drive ice drift, and affect the navigability of the Kara Strait by introducing warm air. [ABSTRACT FROM AUTHOR]

This study investigates the ability of support vector machine (SVM), random forest (RF) and geo-statistical (GS) methods in simulating long-term monthly air temperatures. Data of 30 locations in Iran were utilized and data scanning procedure was employed in the applications. Geographical coordinates, e.g. latitude, longitude and altitude as well as the periodicity component (month of the year), were utilized as inputs to the applied models. SVM and RF models obtained using k-fold testing were also compared with artificial neural networks (NNs) and neuro fuzzy (NF) methods employed in a previous study. Comparisons demonstrated the superiority of SVM and RF models over the NN and NF models in the present study. In all stations, the RF model with average scatter index of 0.111, average mean absolute error of 1.456 and average variance account for of 0.968 provided better estimates than the SVM model with corresponding values of 0.142, 1.855 and 0.945, respectively. Nonetheless, the obtained results revealed that the geo-statistics-based kriging method is able to spatially simulate air temperature. [ABSTRACT FROM AUTHOR]

Previously, it was shown that annual rhythm of human reproduction is associated with photoperiod and air temperature. However, insufficient information exists regarding the association between climatic factors in the Far North and human reproductive function. We tested significance of associations of air temperature, day length and the level of geomagnetic activity with the length of pregnancy and anthropometric characteristics of newborns. Using cross-correlation and covariance analyses, the Kp-index during the period of conception was shown to have negative associations with pregnancy duration and newborn weight. Day length and air temperature did not have significant associations with characteristics of reproductive function of the inhabitants of the Far North. [ABSTRACT FROM AUTHOR]

This paper presents a theoretical analysis of a thermal storage unit, which consists of parallel rectangular channels for the air flow each separated by a phase change material (PCM). The purpose of the storage unit is to absorb night coolness and to provide cooled air at comfort temperatures during daytime in the summer season. A MATLAB simulation tool has been used to compute the air temperature variation with location as well as time, charging and discharging times of the storage unit. Effect of PCM mass, air flow rate and different inlet temperatures are considered for daytime and nighttime operations of the storage unit. Maximum daytime and minimum nighttime ambient temperatures for the selected location are 40°C and 24°C, respectively, for the month of June. Results show that air temperature at the exit increases and discharging time decreases on increasing the air flow rates during the daytime operation. [ABSTRACT FROM PUBLISHER]

Copyright of Ostrich: The Journal of African Ornithology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Different satellite-based radiation (Makkink) and temperature (Hargreaves-Samani, Penman-Monteith temperature, PMT) reference evapotranspiration (ETo) models were compared with the FAO56-PM method over the Cauvery basin, India. Maximum air temperature (Tmax) required in the ETo models was estimated using the temperature-vegetation index (TVX) and an advanced statistical approach (ASA), and evaluated with observed Tmax obtained from automatic weather stations. Minimum air temperature (Tmin) was estimated using ASA. Land surface temperature was employed in the ETo models in place of air temperature (Ta) to check the potency of its applicability. The results suggest that the PMT model with Ta as input performed better than the other ETo models, with correlation coefficient (r), averaged root mean square error (RMSE) and mean bias error (MBE) of 0.77, 0.80 mm d−1 and −0.69 for all land cover classes. The ASA yielded better Tmax and Tmin values (r and RMSE of 0.87 and 2.17°C, and 0.87 and 2.27°C, respectively). [ABSTRACT FROM AUTHOR]

This study aims to develop effective methods for the damage diagnosis of cable-stayed bridges based on the variation of cable forces. The air temperature is firstly adopted to eliminate the environmental temperature effects from the cable force variation. The instant damage scenario caused by earthquake is investigated using a methodology recently proposed by the authors. The other two damage scenarios regarding the unequal settlement and the asphalt pavement overlay are also considered. For these two types of long-term damages, a new approach by taking the moving average is established to remove the daily variations. A transfer coefficient is subsequently obtained to take out the long-term temperature effect from the averaged variation history of cable force. According to the data collected from Ai-Lan Bridge, the thresholds for diagnosing the long-term damages are determined. The FE models for Chi-Lu Bridge and Ai-Lan Bridge are then constructed to simulate various damage scenarios and assess the diagnosis methodology. It is demonstrated that mild seismic damages can be effectively detected. The identification of an unequal settlement reaching 9 mm or more is also found to be feasible. Moreover, the asphalt pavement overlay with a thickness of 3.2 cm can be distinctly detected. [ABSTRACT FROM AUTHOR]

Before its establishment in Estonia at the beginning of the twenty-first century, the Colorado potato beetleLeptinotarsa decemlineataSay was a notifiable quarantine pest for many years. In high-latitude environments it encounters strong evolutionary pressure to adapt to low temperatures due to high overwintering mortality and periodic influx of new individuals from more southern populations. Our study focused on gathering evidence for such a range shift leading to the formation of a permanent local population. The phenology and overwintering success of beetles was investigated from 2008 to 2015. Depending on weather conditions in the different years, the overwintered beetles emerged from the soil from the beginning of May to mid-June. Over 700 degree days accumulated in 2010, 2011, 2013 and 2014 exceeding the limit needed for development of two generations. However, food supply and temperature distribution in the growing period enabled development of the second complete generation only in 2010 and 2013. Survival of overwintering beetles in field conditions varied between 18% and 47% in the different years. Winter mortality was not associated with low air temperature in any year as snow cover provided the necessary protection and winter soil temperatures at the depth of 30 cm remained at around 0°C for the duration of the whole observation period, with only some records as low as −3.5°C. The survival of overwintering beetles is more likely defined by factors other than low temperature. As a result of periodic invasions of beetles with naturally lower cold resistance originating from southern regions, the structure of the overwintering population in Nordic temperate conditions is not homogeneous. Moreover, this may also be derived from cultural practices, as commercial producers regularly apply agrochemicals while organic growers avoid them. [ABSTRACT FROM PUBLISHER]

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The analysis of hair cortisol concentrations (HCC) is a promising new biomarker for retrospective measurement of chronic stress. The effect of basic military training (BMT) on chronic stress has not yet been reported. The aim of this study was to investigate the effect of 10-week BMT on HCC, while further exploring the role of known and novel covariates. Young healthy male recruits of the Swiss Army participated twice, 10 weeks apart, in data collection (1st examination: n = 177; 2nd examination: n = 105). On two occasions, we assessed HCC, perceived stress and different candidate variables that may affect HCC (e.g. socioeconomic status, meteorological data). Military training increased perceived stress from the first to the second examination, but did not affect HCC. In line with this, there was no correlation between HCC and perceived stress ratings. This could be interpreted as a missing influence of mainly physical stress (e.g. exercise) on HCC. In contrast, significant correlations were found between HCC and ambient temperature, humidity and education. Future studies should control for meteorological data and educational status when examining HCC. [ABSTRACT FROM AUTHOR]

Larger and longer lived flowers receive more pollinators, but may also involve increased water maintenance costs under hot, dry environments. Hence, smaller and/or short-lived flowers may buffer such costs. We surveyed floral longevity in three large-flowered MediterraneanCistusspecies. We hypothesize that: (1) inCistus, floral longevity decreases with increasing air temperature and flower size; (2) inC. ladanifer, flower size and longevity increase along an altitudinal gradient; (3) floral longevity is differentially affected by temperature rather than flower size along the gradient; (4) under similar temperature, floral longevity decreases with flower size. For each species, we evaluated the effects of flower size and air temperature on floral longevity. Specifically, floral longevity was surveyed along an altitudinal gradient in the largest flowered speciesCistusladanifer. Floral longevity inCistusspecies lasted < 1 d and was affected by air temperature, independently of flower size. InC. ladanifer, flower size increased along the gradient but floral longevity decreased. Still, floral longevity decreased with increasing air temperature and, to a lesser extent, with flower size. Together, our findings show a triangular relationship among air temperature, flower size and floral longevity with margins for plasticity to accommodate pollinator attraction with the costs of large-flowered Mediterranean plants. [ABSTRACT FROM AUTHOR]

Underground air has been gaining popularity for space heating and cooling on Jeju volcanic island, Korea, because there are many geological and societal limitations in the application of conventional ground source heat pump systems. The underground air temperature on the Jeju Island is very stable, at 15°C–19°C (median 17°C), throughout the year, while the ambient air temperature varies widely. In addition, vesicular basalts widespread in the island facilitate the extraction of underground air. As of 2007, there were 63 underground air facilities used, which were mostly greenhouses for growing fruits, vegetables, flowers, and ornamental shrubs. Practical operations and agricultural studies have revealed that the supply of underground air to greenhouses growing plants saved energy costs and enhanced crop production due to the high CO2 content in the underground air. Despite these advantageous features, there are still some problems that need to be resolved including public grievance relating to potential groundwater contamination due to the drilling of boreholes and lack of technical experiences in optimal system design. Regulations have not been tailored to the use of underground air systems, which is still not officially acknowledged as a renewable energy source and these factors will need to be resolved prior to the sustainable use of underground air. [ABSTRACT FROM AUTHOR]

In grassland areas where herbage production has no economic value, the cut grass is often left on the sward surface where its decomposition is influenced by weather conditions. Although the influence of temperature and humidity on decomposition has been investigated under controlled lab conditions, experimentation has generally been under ideal moisture conditions that have not tested the combinations of climatic limitations that might occur in the field. The decomposition of mown turfgrass clippings deposited at different times of vegetation period was studied in situ using nylon bags during the first 8 weeks after deposition to investigate the effect of weather conditions (the air temperature, relative humidity, precipitation) on decomposition. Decomposition is the highest in the case of high air humidity and temperature of 10°C. Limiting factors for decomposition at temperatures above 10°C is the air humidity and below 10°C the air temperature. The general tendency was that the rate of decomposition increased with increasing air temperature up to 10°C, but with further increases of air temperature the decomposition rate slowed down. Relative air humidity had a variable impact (at the beginning of the decomposition process (weeks 1–2) the influence was negative, during weeks 3–8 of the decomposition process the effect was positive), and hence had no generalized relationship with decomposition over the studied decomposition period (weeks 1–8). The most significant influence of weather conditions on the decomposition rate was recorded directly after cutting. If the cutting was done during hot weather conditions, the material was drying fast and therefore decomposed slowly. Our results indicate that for fast decomposition of clippings it is important to maintain the freshness of material. Lower decomposition rates occurred during conditions of hot and dry weather, and also cooler (temperature near to 0°C) weather, and can be compensated as soon as favourable weather arrives. [ABSTRACT FROM AUTHOR]

The impact of meteorological conditions on in vitro pollen germination and pollen tube growth during the initial phases of the development of male flowers in the Pedunculate Oak, Quercus robur, is studied. Phenological observations of male flowers and pollen sampling were performed on the field trial established with grafted Pedunculate Oak clones. During the investigation, weather conditions (absolute minimum and maximum daily air temperature, minimum absolute relative humidity of air and amount of precipitation) were recorded by an automatic meteorological station installed at the field trial. Influence of meteorological conditions on pollen germination and pollen tube growth was studied in the following stages of male flower: (I) during the last ten days of flower bud dormancy, (II) during swelling of the buds, (III) during bud burst and beginning of male catkins elongation, (IV) during the final stage of male flower catkins elongation. High temperatures and low relative air humidity during the bud burst and beginning of the male catkins elongation reduced pollen germination and pollen tube growth. Weather conditions did not significantly affect pollen germination and pollen tube growth during the swelling of flower buds, or in the final stage of male catkins elongation. [ABSTRACT FROM AUTHOR]

The physical environmental parameters affecting water vapor transfer properties of fabrics include air temperature, relative humidity, and wind speed. The effects of air temperature, relative humidity, and wind speed on water vapor diffusion resistance have been investigated. The air temperatures varied from 10°C to 30°C in an interval of 5°C. The relative humidities ranged from 0% to 50%. The wind speed was from 0.1 m/s to 0.4 m/s. A new testing apparatus was utilized for evaluating the water vapor transfer properties of four typical fabrics exposed under 120 environmental conditions. The test results indicated that the water vapor diffusion resistances of four representative fabrics varied little with air temperatures. The microporous membrane laminated fabrics and air permeable fabrics showed a gradual increase in water vapor diffusion resistance with an increase in the relative humidity, whereas the water vapor diffusion resistance of hydrophilic membrane laminated fabrics and hybrid laminated fabrics were a function of relative humidity. These two types of fabrics exhibited low resistance to water vapor diffusion when the relative humidity was high. Finally, low wind speed resulted in high water vapor diffusion resistance of four typical fabrics. [ABSTRACT FROM AUTHOR]

As a case study for application in climate change studies, daily air temperature records in Lisbon are analysed by applying advanced statistical methodologies that take into account the dynamic nature of climate. A trend analysis based on two non-parametric tests (Spearman and Mann-Kendall) revealed the presence of statistically significant upward trends in the maximum temperatures, mainly during March. The minimum temperatures do not present significant trends, with the exception of March where a relatively weak positive trend is detected. A singular spectral analysis combined with a maximum entropy spectral analysis enables the detection of regularities in the annual mean time series of the maximum and minimum temperatures. A quasi-periodic oscillation with a peak period of about 50 years is superimposed in the linear trends. At the maximum temperature, a secondary oscillation with a peak period of nearly 20 years is also identified. No other regularities are isolated in these time series. The study is enhanced by applying an extreme value analysis to the extreme winter and summer temperatures. The generalized extreme value distribution family is shown to provide high-quality adjustments to the distributions, and a description of the temperatures related to different return periods and risks is given. [ABSTRACT FROM AUTHOR]

Row covers and colored plastic mulch are used routinely throughout the United States to grow vegetables but are rarely used in conjunction to produce a crop. Summer squash (Cucurbita pepo L.), cv. Prelude II, was grown on an Orangeburg sandy loam soil in Shorter, AL. The summer squash was direct seeded in single rows. The experiment consisted of 12 treatments including: (1) black plastic mulch (BPM)+spunbonded row cover (RC), (2) BPM alone, (3) white plastic mulch (WPM)+RC, (4) WPM alone, (5) red plastic mulch (RPM)+RC, (6) RPM alone, (7) bare soil (BS)+RC, (8) BS alone, (9) silver plastic mulch (SPM)+RC, (10) SPM alone, (11) blue plastic mulch (BLUPM)+RC, and (12) BLUPM alone. Year and mulch color affected all variables, row cover affected plant height and stem diameter, and the mulch color × row cover interaction affected yield variables. Mulch color and year significantly affected air and soil temperatures and row cover significantly affected air temperature. Soil temperatures were more than 5°C lower than air temperatures in all treatments and air temperatures were 2-5°C higher with row covers than without. Increased soil and air temperatures did not always result in yield increases. Colored plastic mulch with or without row covers did not increase early fruit yield in squash. Lack of a mulch/row cover induced temperature effect on yield was attributed to the relatively high mean air temperatures that may have masked treatment temperature effects. [ABSTRACT FROM AUTHOR]