scholarly journals Elevation Effects on Air Temperature in a Topographically Complex Mountain Valley in the Spanish Pyrenees

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 656
Author(s):  
Francisco Navarro-Serrano ◽  
Juan Ignacio López-Moreno ◽  
Cesar Azorin-Molina ◽  
Esteban Alonso-González ◽  
Marina Aznarez-Balta ◽  
...  
Keyword(s):  
Air Temperature ◽  
Weather Conditions ◽  
Time Lapse ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Night Time ◽  
Air Temperatures ◽  
Spanish Pyrenees ◽  
Lapse Rates

Air temperature changes as a function of elevation were analyzed in a valley of the Spanish Pyrenees. We analyzed insolation, topography and meteorological conditions in order to understand how complex topoclimatic environments develop. Clustering techniques were used to define vertical patterns of air temperature covering more than 1000 m of vertical elevation change. Ten locations from the bottom of the valley to the summits were monitored from September 2016 to June 2019. The results show that (i) night-time lapse rates were between −4 and −2 °C km−1, while in the daytime they were from −6 to −4 °C km−1, due to temperature inversions and topography. Daily maximum temperature lapse rates were steeper from March to July, and daily minimum temperatures were weaker from June to August, and in December. (ii) Different insolation exposure within and between the two analyzed slopes strongly influenced diurnal air temperatures, creating deviations from the general lapse rates. (iii) Usually, two cluster patterns were found (i.e., weak and steep), which were associated with stable and unstable weather conditions, respectively, in addition to high-low atmospheric pressure and low-high relative humidity. The results will have direct applications in disciplines that depend on air temperature estimations (e.g., snow studies, water resources and sky tourism, among others).

The differing impact of air stagnation on near-surface ozone across Europe

2020 ◽  
Author(s):  
José M. Garrido-Pérez ◽  
Carlos Ordóñez ◽  
Ricardo García-Herrera ◽  
Jordan L. Schnell
Keyword(s):  
Climate Model ◽  
Surface Ozone ◽  
Weather Conditions ◽  
Ozone Production ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Southern Europe ◽  
Near Surface ◽  
Photochemical Production

<p>Daily maximum temperature is known to be the meteorological variable that mostly controls the afternoon near-surface ozone concentrations during summer. Air stagnation situations, characterised by stable weather conditions and poor ventilation, also lead to the accumulation of pollutants and regional ozone production close to the surface. This work evaluates the joint effect of daily maximum temperature and a simplified air stagnation index on surface ozone observations in eight regions of Europe during summer 1998-2015.</p><p>As expected, the correlations of MDA8 O<sub>3</sub> (maximum daily 8-h running average ozone) with temperature are higher than with stagnation for most regions. Nevertheless, stagnation can also be considered as a good predictor of ozone, especially in the regions of central/southern Europe, where the correlation coefficients between MDA8 O<sub>3</sub> and the percentage of stagnant area are within the range 0.50–0.70. MDA8 O<sub>3</sub> consistently increases over central/southern Europe under stagnant conditions, but this is not always the case in the north. Under non-stagnant conditions and daily maximum temperatures within 20-25 ºC (typical temperatures of fair weather conditions that allow photochemical production), northern Europe is affected by southerly advection that often brings aged air masses from more polluted areas, increasing the MDA8 O<sub>3</sub> mixing ratios.</p><p>We have also found that the ozone diurnal cycles in the central/southern regions exhibit large amplitudes, with above-average daytime and below-average night-time concentrations, when stagnation occurs. Stagnant nights are often associated with stable shallow planetary boundary layer and, presumably, enhanced dry deposition and chemical destruction of ozone. After sunrise, mixing with air from air from the residual layer, accumulation of ozone and precursors, and photochemical production seem to be the main mechanisms involved in the build-up of daytime ozone.</p><p>According to previous studies, some of the central/southern European regions where stagnation has a clear impact on ozone have undergone significant upward trends in air stagnation in the past and are also likely to experience increases in the future. However, our study has identified other regions with unclear responses of summer ozone to the occurrence of stagnation. This indicates that climate model projections of increases in stagnation should not directly be translated into enhanced summer ozone pollution if the sensitivity of this pollutant to stagnation has not been proved for a particular region.</p>

scholarly journals Relationship beetwen the phenological features of pear cultivars and the main meteorological parameters in a gene bank with 555 pear

2009 ◽  
Vol 15 (1-2) ◽  
Author(s):  
L. Lakatos ◽  
S. Musacchi ◽  
T. Szabó ◽  
G. Kocsisné Molnár ◽  
Z. Szabó ◽  
...  
Keyword(s):  
Gene Bank ◽  
Meteorological Variables ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Night Time ◽  
Correlation And Regression Analysis ◽  
Fruit Growing ◽  
Autumn And Winter ◽  
The Relationship

The trees observed are grown at Ujfehert6, Eastern Hungary in a gene bank with 555 pear cultivars. Each of the cultivars was monitored for its dates of: the beginning of bloom, main bloom and the end of bloom and ripe phenophasis separately between I 984 and 2002. We analyzed the statistical features, frequency, distribution of these phenophasis and its' correlation the meteorological variables bet ween the interval. During this period the meteorological database recorded the following variables: daily mean temperature (°C), daily maximum temperature (0C), daily mini m um temperature (0C), daily precipitation (mm), daily hours of bright sunshine, daily means or the differences between the day-time and night-time temperatures (0C). For the analysis of data the cultivars have been grouped according to dates of maturity, blooming period as well as types of the seasons. Groups of maturity dates: summer ripe, autumnal ripening, winter ripe cultivars. Groups of blooming dates: early blooming, intermediate blooming, late blooming cultivars. At all the separated groups we analyzed the relationship between phenophasis and meteorological variables. During the 18 years of observation , the early blooming cultivars started blooming on 10-21 April, those of intermediate bloom date started flowering bet ween 20 April and 3 May, whereas the late blooming group started on 2- 10 May. Among the meteorological variables of the former autumn and winter periods, the winter maxima were the most active factor influencing the start dates of bloom in the subsequent spring. For the research of fruit growing-weather relationships we used simple, well known statistical methods, correlation and regression analysis. We used the SPSS 1 1.0 software for the linear regression fitting and for calculation of dispersions as well. The 1ables made by Excel programme.

Seasonal analysis of warm extreme events in Serbia from 1949 to 2017

2020 ◽  
Author(s):  
Ivana Tosic ◽  
Suzana Putniković ◽  
Milica Tošić
Keyword(s):  
Extreme Events ◽  
Heat Waves ◽  
Extreme Temperature ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Extreme Temperature Events ◽  
Air Temperatures ◽  
Seasonal Analysis ◽  
Novi Sad

<p>Worldwide studies revealed a general increase in frequency and severity of warm extreme temperature events. In this study, extreme temperature events including Heat waves (HWs) are examined. Extreme indices are calculated based on daily maximum temperature (Tx). The following definitions are employed: SU - number of days with Tx > 25 °C, umber of days with Tx > 90<sup>th</sup> percentile, and WSDI - number of days in intervals of at least six consecutive days for which Tx is higher than the calendar day 90<sup>th</sup> percentile. Daily values of air temperatures from 11 meteorological stations distributed across Serbia were used for the period 1949–2017.</p><p>Trends of extreme temperature events and their frequencies are examined. The period 1949–2017 are characterised by a warming of extreme temperature indices (SU, Tx90, HWs). It is found that maximum air temperatures increased at all stations, but statistically significant at 6 stations in winter, 4 stations in summer and two stations in spring. The average number of SU per station was between 63.1 in Novi Sad to 73.5 in Negotin during the summer season. Significant increase of SU is recorded in summer for 10 out of 11 stations. Positive trends of SU and Tx90 are observed for all stations and seasons, except in Novi Sad. The average number of Tx90 is about 9 for all stations in all seasons. The longest heat waves prevailed in 2012, but the most severe are recorded in 2007. Increasing of warm extreme events in Serbia are in agreement with studies for different regions of the world.</p>

scholarly journals Modeling and projecting health-relevant combined ozone and temperature events in present and future Central European climate

2020 ◽  
Author(s):  
Sally Jahn ◽  
Elke Hertig
Keyword(s):  
Large Scale ◽  
Time Windows ◽  
Coupled Model ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Pollution Levels ◽  
European Climate ◽  
Air Temperatures ◽  
Meridional Winds

Abstract Statistical models to evaluate the relationships between large-scale meteorological conditions, prevailing air pollution levels and combined ozone and temperature events, were developed during the 1993–2012 period with Central Europe as regional focus. Combined ozone and temperature events were defined based on the high frequency of coinciding, health-relevant elevated levels of daily maximum tropospheric ozone concentrations (based on running 8-h means) and daily maximum temperature values in the peak ozone and temperature season from April to September. By applying two different modeling approaches based on lasso, logistic regression, and multiple linear regression mean air temperatures at 850 hPa, ozone persistence, surface thermal radiation, geopotential heights at 850 hPa, meridional winds at 500 hPa, and relative humidity at 500 hPa were identified as main drivers of combined ozone and temperature events. Statistical downscaling projections until the end of the twenty-first century were assessed by using the output of seven models of the Coupled Model Intercomparison Project Phase 5 (CMIP5). Potential frequency shifts were evaluated by comparing the mid- (2031–2050) and late-century (2081–2100) time windows to the base period (1993–2012). A sharp increase of ozone-temperature events was projected under RCP4.5 and RCP8.5 scenario assumptions with respective multi-model mean changes of 8.94% and 16.84% as well as 13.33% and 37.52% for mid- and late-century European climate.

Prediction of temperatures in cattle dung for estimating development times of coprophilous organisms

1988 ◽  
Vol 78 (2) ◽  
pp. 235-240 ◽  
Author(s):  
J. N. Matthiessen ◽  
M. J. Palmer
Keyword(s):  
Air Temperature ◽  
Meteorological Data ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Threshold Temperature ◽  
Cattle Dung ◽  
Daily Maximum ◽  
Daily Minimum ◽  
Maximum Temperatures ◽  
Minimum Air Temperature

AbstractIn studies in Western Australia, temperatures in air and one- and two-litre pads of cattle dung set out weekly and ranging from one to 20 days old were measured hourly for 438 days over all seasons, producing 1437 day x dung-pad observations. Daily maximum temperatures (and hence thermal accumulation) in cattle dung pads could not be accurately predicted using meteorological data alone. An accurate predictor of daily maximum dung temperature, using multiple regression analysis, required measurement of the following factors: maximum air temperature, hours of sunshine, rainfall, a seasonal factor (the day number derived from a linear interpolation of day number from day 0 at the winter solstice to day 182 at the preceding and following summer solstices) and a dung-pad age-specific intercept term, giving an equation that explained a 91·4% of the variation in maximum dung temperature. Daily maximum temperature in two-litre dung pads was 0·6°C cooler than in one-litre pads. Daily minimum dung temperature equalled minimum air temperature, and daily minimum dung temperatures occurred at 05.00 h and maximum temperatures at 14.00 h for one-litre and 14.30 h for two-litre pads. Thus, thermal summation in a dung pad above any threshold temperature can be computed using a skewed sine curve fitted to daily minimum air temperature and the calculated maximum dung temperature.

Influence of High-Temperatures on the Survival of Rhopalosiphum-Padi (L) (Hemiptera, Aphididae) in Irrigated Perennial Grass Pastures in South-Australia

1993 ◽  
Vol 41 (2) ◽  
pp. 123 ◽  
Author(s):  
PJ Debarro ◽  
DA Maelzer
Keyword(s):  
Field Experiment ◽  
Rhopalosiphum Padi ◽  
Perennial Grass ◽  
South Australia ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Air Temperatures ◽  
Exposure Temperature ◽  
C 32

A field experiment in a perennial grass pasture showed that the survival of Rhopalosiphum padi (L.) (Hemiptera: Aphididae) was reduced when aphids were exposed to air temperatures of at least 36-degrees-C (32-degrees-C at the base of the sward). The longevity, rate of reproduction and fecundity of individuals also declined as the exposure temperature and duration of exposure increased. The results of the field experiment were later corroborated by sampling an aphid population every 4-6 days over summer and regressing aphid numbers on daily maximum temperature and duration of exposure to temperature. A model is proposed to estimate the numbers of aphids that survive in refuge areas over summer in relation to temperature-induced mortality.

scholarly journals Relationship between several meteorological factors and phenological features of apple cultivars

2008 ◽  
Vol 14 (1-2.) ◽  
Author(s):  
L. Lakatos ◽  
T. Szabó ◽  
S. Zhongfu ◽  
Y. Wang ◽  
J. Racskó ◽  
...  
Keyword(s):  
Daily Precipitation ◽  
Meteorological Factors ◽  
Meteorological Data ◽  
Gene Bank ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Night Time ◽  
Apple Cultivars

The trees observed are grown at Ofeherto, Eastern Hungary in the plantation of an assortment (gene bank) with 586 apple cultivars. Each of the cultivars were observed as for their dates of subsequent phenophases, the beginning of bloom, main bloom and the end of bloom over a period between 1984 and 2001. during this period the meteorological data-base keeps the following variables: daily means of temperature (°C), daily maximum temperature (°C), daily minimum temperature (°C), daily precipitation sums (mm), daily sums of sunny hours, daily means of the differences between the day-time and night-time temperatures (°C), average differences between temperatures of successive daily means (°C). Between the 90th and 147th day of the year over the 18 years of observation. The early blooming cultivars start blooming at 10-21April. The cultivars of intermediate bloom start at the interval 20 April to 3 May, whereas the late blooming group start at 2-10 May. Among the meteorological variables of the former autumnal and hibernal periods, the hibernal maxima were the most active factor influencing the start of bloom in the subsequent spring.

A TECHNIQUE FOR ESTIMATING HATCHING OF NATURAL EGG POPULATIONS OF MELANOPLUS SANGUINIPES (ORTHOPTERA: ACRIDIDAE)

1974 ◽  
Vol 106 (8) ◽  
pp. 801-812 ◽  
Author(s):  
R. L. Randell ◽  
M. K. Mukerji
Keyword(s):  
Embryonic Development ◽  
Control Measures ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Melanoplus Sanguinipes ◽  
Average Effect ◽  
Spring Temperature ◽  
Hatching Time ◽  
Air Temperatures

AbstractThe earliness or lateness of the hatching period in Melanoplus sanguinipes (Fabr.) affects the type and amount of damage to the crop and the timing of control measures. An empirical model for prediction of hatching at each decile of egg populations was developed by multiple regression using daily maximum air temperatures for a unit interval of 5 days from 2 March to 29 June and embryonic development in the preceding fall. The model accounted for a maximum of 96% of the variance in hatching date. It showed the average effect of a unit change of 1° of daily maximum temperature for each of the 24 5-day intervals on the number of days to hatch. The time and pattern of hatching of the major bulk of egg population was dependent mainly on spring temperature; however, fall embryonic development accounted for considerable variation in hatching time especially of the less developed eggs. The implications for population growth and certain assumptions made during the analyses in this study are discussed.

scholarly journals Effect of weather conditions on light-trap catches of Trichoptera in Hungary (Central Europe)

2014 ◽  
Vol 83 (4) ◽  
pp. 269-280
Author(s):  
László Nowinszky ◽  
Ottó Kiss ◽  
János Puskás
Keyword(s):  
Central Europe ◽  
Strong Influence ◽  
Light Trap ◽  
Weather Conditions ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Temperature Minimum ◽  
Trap Catch ◽  
Trap Catches

ABSTRACT The study deals with the effect of weather conditions on the light trap catch of 2 caddisflies (Trichoptera) species: Hydropsyche bulgaromanorum and Setodes punctatus. We found that the light trap catch of both species increased when the daily maximum temperature, minimum and average values of temperature was higher. The results can be written down with second- or third-degree polynomials. The fluctuation in temperature had no clear influence on the catch. The hydrothermal quotient has a strong influence on the catch of both species. Precipitation has no significant influence on the catch of the tested species.

Diurnal Cycle of Surface Air Temperature within China in Current Reanalyses: Evaluation and Diagnostics

2018 ◽  
Vol 31 (11) ◽  
pp. 4585-4603 ◽  
Author(s):  
Jizeng Du ◽  
Kaicun Wang ◽  
Jiankai Wang ◽  
Shaojing Jiang ◽  
Chunlüe Zhou
Keyword(s):  
Air Temperature ◽  
Diurnal Cycle ◽  
Surface Air Temperature ◽  
Warming Trend ◽  
Maximum Temperature ◽  
Daily Minimum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Positive Trend ◽  
Southeastern China

Abstract Diurnal cycle of surface air temperature T is an important metric indicating the feedback of land–atmospheric interaction to global warming, whereas the ability of current reanalyses to reproduce its variation had not been assessed adequately. Here, we evaluate the daily maximum temperature Tmax, daily minimum temperature Tmin, and diurnal temperature range (DTR) in five reanalyses based on observations collected at 2253 weather stations over China. Our results show that the reanalyses reproduce Tmin very well; however, except for Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), they substantially underestimate Tmax and DTR by 1.21°–6.84°C over China during the period of 1980–2014. MERRA-2 overestimates Tmax and DTR by 0.35° and 0.81°C, which are closest with observation. The reanalyses are skillful in reproducing the interannual variability of Tmax and Tmin but relatively poor for DTR. All reanalyses underestimate the warming trend of Tmin by 0.13°–0.17°C (10 yr)−1 throughout China during 1980–2014, and underestimate the warming trend of Tmax by 0.24°–0.40°C (10 yr)−1 in northwestern China while overestimating this quantity by 0.18°–0.33°C (10 yr)−1 in southeastern China. These trend biases in Tmax and Tmin introduce a positive trend bias in DTR of 0.01°–0.26°C (10 yr)−1 within China, especially in the north China plain and southeastern China. In the five reanalyses, owing to the sensitivity discrepancies and trend biases, the surface solar radiation Rs and precipitation frequency (PF) are notable deviation sources of the diurnal cycle of air temperature, which explain 31.0%–38.7% (31.9%–37.8%) and 9.8%–22.2% (7.4%–15.3%) of the trend bias in Tmax (DTR) over China, respectively.

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