scholarly journals Solar coronal rotation according to soft X-ray solar radiation during the 22nd, 23rd, and 24th solar cycles

2021 ◽  
Vol 2103 (1) ◽  
pp. 012040
Author(s):  
P B Dmitriev
Keyword(s):  
Time Window ◽  
Weighted Average ◽  
Average Lifetime ◽  
Data Series ◽  
Solar Cycles ◽  
A Value ◽  
Daily Data ◽  
Activity Cycles ◽  
Sidereal Rotation ◽  
Value Changes

Abstract Using the developed method of combining numerous scattered time series of the same type of measurements into a single weighted average series, according to the data of the GOES series satellites, a single series of daily data was synthesized during the 22nd, 23rd and 24th solar cycles (1986 – 2019 years). The flare and background components were distinguished from this data series, which were investigated by means the method of constructing a composite spectral periodogram for the presence of quasiperiodic oscillations at various solar cycles. Some of these found quasiperiods may be explained by both synodic and sidereal rotation of the Sun, while others coincide with the average lifetime of the solar atmosphere active formations such as the sunspot groups and the facular plages. Special attention was paid to the study of the change over time the revealed quasiperiodic values over the course of solar cycles by calculating the sample normalized spectral density of the analyzed data in a sliding time window with a value of up to two years. Based on the revealed quasiperiodic value changes presented on the dynamic diagrams, it can be concluded that the differential rotation of the solar corona is unstable and manifests itself only at certain stages of the development and existence of solar activity cycles.

scholarly journals Aplikasi Pengambilan Keputusan dengan Metode Tsukamoto pada Penentuan Tingkat Kepuasan pelanggan

CAUCHY ◽  
2015 ◽  
Vol 4 (1) ◽  
pp. 10 ◽  
Author(s):  
Venny Riana Riana Agustin ◽  
Wahyu Henky Irawan
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Fuzzy Inference ◽  
Weighted Average ◽  
Fuzzy Rules ◽  
Quality Of Services ◽  
Inference System ◽  
A Value ◽  
Fuzzy Logic Analysis

Tsukamoto method is one method of fuzzy inference system on fuzzy logic for decision making. Steps of the decision making in this method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules, fuzzy logic analysis, defuzzyfication (affirmation), as well as the conclusion and interpretation of the results. The results from this research are steps of the decision making in Tsukamoto method, namely fuzzyfication (process changing the input into kabur), the establishment of fuzzy rules by the general form IF a is A THEN B is B, fuzzy logic analysis to get alpha in every rule, defuzzyfication (affirmation) by weighted average method, as well as the conclusion and interpretation of the results. On customers at the case, in value of 16 the quality of services, the value of 17 the quality of goods, and value of 16 a price, a value of the results is 45,29063 and the level is low satisfaction

scholarly journals Advanced Chemophenetic Analysis of Essential Oil from Leaves of Piper gaudichaudianum Kunth (Piperaceae) Using a New Reduction-Oxidation Index to Explore Seasonal and Circadian Rhythms

Plants ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2116
Author(s):  
Ygor Jessé Ramos ◽  
Claudete da Costa-Oliveira ◽  
Irene Candido-Fonseca ◽  
George Azevedo de Queiroz ◽  
Elsie Franklin Guimarães ◽  
...  
Keyword(s):  
Essential Oils ◽  
Weighted Average ◽  
Chemical Diversity ◽  
Terpene Biosynthesis ◽  
Phenological Stages ◽  
Compound C ◽  
A Value ◽  
Chemical Profiles ◽  
Aromatic Species ◽  
Piper Gaudichaudianum

The aromatic species Piper gaudichaudianum Kunth (Piperaceae) is widely used in Brazil for medicinal and ritualistic applications. In the current study, chemophenetic patterns were realized across season and circadian rhythm based on the chemical profile of essential oils (EOs) from leaves. Hydrodistilled essential oils were analyzed by GC-MS and GC-FID, and a new calculation of metabolite oxidation level, averaged for each individual molecule component of the EO, was used to explore the patterns of metabolism/biosynthesis. This new index used an intermediate calculation, the ‘weighted average redox standard’ (SRO), to enable a value for mixtures of metabolites to be generated, the ‘general mixture redox index’ (GMOR). The indices were subjected to a proof-of-concept approach by making comparison to outcomes from multivariate analyses, i.e., PCA and HCA. Chemical analysis demonstrated that the essential oils were dominated by sesquiterpenes, constructed of 15 classes of compound (C-skeletons), and 4 C-skeletons were recognized in the monoterpene group, giving a total of 19. The variation of chemical profiles was distinct at different phenological stages, but stronger chemical variation was evident between day and night as compared to season. Furthermore, due to comprehensive sampling across different regions, nine chemotypes were recognized, including those previously reported. The SRO and GMRO indices demonstrate that phenological variation of chemistry is mainly an outcome of redox fluctuations in terpene biosynthesis, changing from day to night. These indices also corroborate that chemical diversity is increased with oxidative metabolism. Lastly, the current study demonstrates pronounced phenotypic plasticity in P. gaudichaudianum, which makes it a suitable candidate to help further our understanding of chemophenetics and chemical ecology.

Creation of a representative climatological database for Hungary from 1870 to 2020

2021 ◽  
Author(s):  
Beatrix Izsák ◽  
Mónika Lakatos ◽  
Rita Pongrácz ◽  
Tamás Szentimrey ◽  
Olivér Szentes
Keyword(s):  
Time Series ◽  
Data Series ◽  
Data Sets ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
Innovation Fund ◽  
Daily Data ◽  
Observation Network ◽  
Meteorological Elements ◽  
Climate Studies

<p>Climate studies, in particular those related to climate change, require long, high-quality, controlled data sets that are representative both spatially and temporally. Changing the conditions in which the measurements were taken, for example relocating the station, or a change in the frequency and time of measurements, or in the instruments used may result in an fractured time series. To avoid these problems, data errors and inhomogeneities are eliminated for Hungary and data gaps are filled in by using the MASH (Multiple Analysis of Series for Homogenization, Szentimrey) homogenization procedure. Homogenization of the data series raises the problem that how to homogenize long and short data series together within the same process, since the meteorological observation network was upgraded significantly in the last decades. It is possible to solve these problems with the method MASH due to its adequate mathematical principles for such purposes. The solution includes the synchronization of the common parts’ inhomogeneities within three (or more) different MASH processing of the three (or more) datasets with different lengths. Then, the homogenized station data series are interpolated to the whole area of Hungary, to a 0.1 degree regular grid. For this purpose, the MISH (Meteorological Interpolation based on Surface Homogenized Data Basis; Szentimrey and Bihari) program system is used. The MISH procedure was developed specifically for the interpolation of various meteorological elements. Hungarian time series of daily average temperature and precipitation sum for the period 1870-2020 were used in this study, thus providing the longest homogenized, gridded daily data sets in the region with up-to-date information already included.</p><p><em>Supported by the ÚNKP-20-3 New National Excellence Program of the Ministry for Innovation andTechnology from the source of the National Research, Development and Innovation Fund.</em></p>

scholarly journals Delimitation of Agricultural Areas with Natural Constraints in Greece: Assessment of the Dryness Climatic Criterion Using Geostatistics

Agronomy ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. 161 ◽  
Author(s):  
Konstantinos Soulis ◽  
Dionissios Kalivas ◽  
Costas Apostolopoulos
Keyword(s):  
Climate Variability ◽  
Spatial Variability ◽  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Data Series ◽  
Eu Member States ◽  
Daily Data ◽  
Agricultural Areas ◽  
Soil Climate ◽  
The Eu

The Less Favored Areas (LFAs) scheme has existed in various forms since 1975 and it is a broad mechanism supporting rural development in agricultural areas with natural constraints (ANC). Within the programme period 2014–2020, the European Commission developed a common set of biophysical criteria (soil, climate, and terrain) to meet the requirement for a robust and harmonized approach of delimiting ANC throughout the EU Member States. Soil and terrain criteria can be derived directly from soil maps using geospatial analysis techniques based on the provided guidelines. However, the assessment of climatic criteria can be challenging especially in regions characterized by increased spatial variability and data scarcity. In this paper, the assessment of the dryness climatic criterion in a data-scarce region (Greece) as well as the challenges, limitations, and solutions are presented. Daily data-series from 140 meteorological stations for a 30-year reference period were analyzed and the spatial distribution of the precipitation and the potential evapotranspiration for each year were estimated in order to make the final assessment of the dryness criterion. Climate variability and the presence of trends were investigated as well. The obtained results indicated that most of the utilized agricultural area is affected by dryness due to a combination of low precipitation and high evapotranspiration rates. The extreme spatial variability especially in precipitation was also highlighted. An important temporal variability was observed as well, including indications of decreasing trends in precipitation and aridity index. Climate variability and possible trends should be investigated in more detail using longer time series in order to evaluate their impact in agricultural production.

scholarly journals Global evolution of solar magnetic fields and prediction of activity cycles

2019 ◽  
Vol 15 (S354) ◽  
pp. 147-156
Author(s):  
Irina N. Kitiashvili
Keyword(s):  
Solar Activity ◽  
Magnetic Fields ◽  
Activity Cycle ◽  
Dynamo Model ◽  
Solar Magnetic Fields ◽  
Solar Cycles ◽  
Multiscale Dynamics ◽  
Activity Cycles ◽  
Solar Dynamics ◽  
Solar Activity Cycles

AbstractPrediction of solar activity cycles is challenging because physical processes inside the Sun involve a broad range of multiscale dynamics that no model can reproduce and because the available observations are highly limited and cover mostly surface layers. Helioseismology makes it possible to probe solar dynamics in the convective zone, but variations in differential rotation and meridional circulation are currently available for only two solar activity cycles. It has been demonstrated that sunspot observations, which cover over 400 years, can be used to calibrate the Parker-Kleeorin-Ruzmaikin dynamo model, and that the Ensemble Kalman Filter (EnKF) method can be used to link the modeled magnetic fields to sunspot observations and make reliable predictions of a following activity cycle. However, for more accurate predictions, it is necessary to use actual observations of the solar magnetic fields, which are available only for the last four solar cycles. In this paper I briefly discuss the influence of the limited number of available observations on the accuracy of EnKF estimates of solar cycle parameters, the criteria to evaluate the predictions, and application of synoptic magnetograms to the prediction of solar activity.

EXCHANGE BROADENING OF SPIN–SPIN TRIPLETS IN NUCLEAR MAGNETIC RESONANCE SPECTRA. APPLICATION TO THE SYSTEM ETHANOL–WATER

1963 ◽  
Vol 41 (3) ◽  
pp. 714-720 ◽  
Author(s):  
W. G. Paterson
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Proton Exchange ◽  
Average Lifetime ◽  
Hydroxyl Proton ◽  
A Value ◽  
Nuclear Magnetic Resonance Spectra ◽  
Spin Triplets ◽  
Exchange Broadening ◽  
Nuclear Magnetic

Using an extension of the method of McConnell (1), an expression is derived for the nuclear magnetic resonance spectrum of a hydroxyl proton in a —CH2OH group which is undergoing intermolecular exchange. A graphical method is presented which enables a rapid evaluation of τ, the average lifetime of a hydroxyl proton between exchange events. Measurements of line widths and multiplet spacings in the n.m.r. spectra of ethanol—water solutions are interpreted in terms of the proton exchange reaction[Formula: see text]for which a value of 2.7 1. mole−1 sec−1 at 42 ± 1 °C is suggested as an upper limit to the rate constant.

scholarly journals Surface Radio Refractivity of Akure and Ondo town, Southwest Nigeria

2021 ◽  
Vol 4 (1) ◽  
pp. 212-219
Author(s):  
IP Onujagbe ◽  
F Ahmed-Ade ◽  
M Mopah ◽  
AJ David
Keyword(s):  
Meteorological Parameters ◽  
Ground Surface ◽  
Mean Value ◽  
Strongly Correlated ◽  
K Value ◽  
Earth Radius ◽  
A Value ◽  
Daily Data ◽  
Southwest Nigeria ◽  
The Mean

The surface radio refractivity, refractivity gradient at 1km above ground surface and the effective earth radius factor, K over Akure and Ondo town of South west Nigeria has been investigated using Ten (10) years daily data of the meteorological parameters of Pressure, air temperature and humidity. The result showed that the mean monthly value of the surface refractivity at the Ondo station is generally slightly higher than that of Akure. The monthly mean value of refractivity at the two stations was found to be strongly correlated with a value of 0.915. The most negative refractive gradient value observed at Ondo and Akure are of -46.48N-units/km and -45.64N-units/km respectively and the least effective earth radius factor, k value of 1.421 and 1.410 were observed at the station respectively. These results showed that the Ondo and Akure station were generally super-refractive. The Ondo station was however found to be slightly more super-refractive than the Akure station.

scholarly journals Filling Gaps in Hourly Air Temperature Data Using Debiased ERA5 Data

Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 13 ◽  
Author(s):  
Miloš Lompar ◽  
Branislava Lalić ◽  
Ljiljana Dekić ◽  
Mina Petrić
Keyword(s):  
Global Climate ◽  
Reanalysis Data ◽  
Temperature Data ◽  
Weather Data ◽  
Data Series ◽  
Measured Temperature ◽  
Weather Forecasts ◽  
Environmental Models ◽  
Fifth Generation ◽  
Daily Data

Missing data in hourly and daily temperature data series is a common problem in long-term data series and many observational networks. Agricultural and environmental models and climate-related tools can be used only if weather data series are complete. To support user communities, a technique for gap filling is developed based on the debiasing of ERA5 reanalysis data, the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses of the global climate. The debiasing procedure includes in situ measured temperature. The methodology is tested for different landscapes, latitudes, and altitudes, including tropical and midlatitudes. An evaluation of results in terms of root mean square error (RMSE) obtained using hourly and daily data is provided. The study shows very low average RMSE for all gap lengths ranging from 1.1 °C (Montecristo, Italy) to 1.9 °C (Gumpenstein, Austria).

Ocean Circulation from the synergy of altimeter-derived and oceanic tracers observations

2021 ◽  
Author(s):  
Daniele Ciani ◽  
Marie-Hélène Rio ◽  
Bruno Buongiorno Nardelli ◽  
Stéphanie Guinehut ◽  
Elodie Charles ◽  
...  
Keyword(s):  
Ocean Circulation ◽  
Time Window ◽  
Ocean Surface ◽  
Global Scale ◽  
Surface Currents ◽  
Sensitivity Experiment ◽  
Daily Data ◽  
Basin Scale ◽  
Ocean Surface Currents ◽  
Spatio Temporal

<p>Measuring the ocean surface currents at high spatio-temporal resolutions is crucial for scientific and socio-economic applications. Since the early 1990s, the synoptic and global-scale monitoring of the ocean surface currents has been provided by constellations of Radar Altimeters. The Altimeter observations enable to derive the geostrophic component of the surface currents with effective spatial-temporal resolutions O(100 km) and O(10 days), respectively. Therefore, only the largest mesoscale oceanic features can be accurately resolved. In order to enhance the altimeter system capabilities, we propose a synergistic use of high resolution, satellite-derived Sea Surface Temperature (SST), Chlorophyll concentrations (Chl) and Altimeter-derived currents. Our approach is tested in both global-scale and regional contexts.<br>At global scale, relying on past numerical studies, we perform a sensitivity experiment based on several gap-free SST datasets, emphasizing strengths and weaknesses in ocean currents applications. Overall, the comparison with in-situ measured currents shows that our synergistic method can improve the altimeter estimates up to 30% locally.<br>Then, our method is also implemented with Chl data in the  Mediterranean Sea, where the most energetic variable signals are found at spatio-temporal scales up to 10 km and few days. We test the method feasibility in an Observing System Simulation Experiment relying on model outputs of the European Copernicus Marine Service. Statistical analyses based on the 2017 daily data show that our approach can improve the altimeter-derived currents accuracy up to 50% at the basin scale, also enhancing the effective spatial-temporal resolutions up to 30 km and less than 10 days, respectively. The method efficiency decreases when the surface Chl patterns are dominated by the biological activity rather than the currents advection, which mostly occurs in the mid-February to mid-March time window. Preliminary tests on the method applicability to satellite-derived data are also presented and discussed.</p>

scholarly journals Event-adjusted evaluation of weather and climate extremes

2014 ◽  
Vol 14 (2) ◽  
pp. 473-483 ◽  
Author(s):  
M. Müller ◽  
M. Kaspar
Keyword(s):  
Time Window ◽  
Heat Waves ◽  
Time Windows ◽  
Geometric Mean ◽  
Climate Extremes ◽  
Data Series ◽  
Return Periods ◽  
Time Duration ◽  
Weather And Climate ◽  
The One

Abstract. After an overview of existing methods, we present a novel method of "event-adjusted" evaluation of extremeness of weather and climate events. It is based on optimization of both the considered area and the time duration for every event. The method consists of three steps: (i) estimation of return periods of a representative variable at individual sites, performed separately for various time windows; (ii) spatial interpolation of the point return period data; and (iii) searching the area and the time window in which the extremeness of the event was maximum. The extremeness is quantified as the common logarithm of the spatial geometric mean of the return periods multiplied by the radius of a circle of the same area as the one over which the geometric mean is taken. The maximum product is referred to as the weather extremity index (WEI). Two precipitation events, which affected the Czech Republic in May and in August 2010, were evaluated by the WEI for illustration. Validation of the method on sufficiently long data series is still needed. Moreover, the WEI is generally applicable regardless of the studied phenomenon (heavy rains, heat waves, windstorms, etc.). This makes it possible to study various weather and climate extremes from the viewpoint of possible recent and future changes in their frequency, seasonal distribution, and circulation conditions accompanying them.

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