Combination of Using Pairwise Comparisons and Composite Reference Series: A New Approach in the Homogenization of Climatic Time Series with ACMANT

The removal of non-climatic biases, so-called inhomogeneities, from long climatic records needs sophistically developed statistical methods. One principle is that the differences between a candidate series and its neighbor series are usually analyzed instead of the candidate series directly, in order to neutralize the possible impacts of regionally common natural climate variation on the detection of inhomogeneities. In most homogenization methods, two main kinds of time series comparisons are applied, i.e., composite reference series or pairwise comparisons. In composite reference series, the inhomogeneities of neighbor series are attenuated by averaging the individual series, and the accuracy of homogenization can be improved by the iterative improvement of composite reference series. By contrast, pairwise comparisons have the advantage that coincidental inhomogeneities affecting several station series in a similar way can be identified with higher certainty than with composite reference series. In addition, homogenization with pairwise comparisons tends to facilitate the most accurate regional trend estimations. A new time series comparison method is presented here, which combines the use of pairwise comparisons and composite reference series in a way that their advantages are unified. This time series comparison method is embedded into the Applied Caussinus-Mestre Algorithm for homogenizing Networks of climatic Time series (ACMANT) homogenization method, and tested in large, commonly available monthly temperature test datasets. Further favorable characteristics of ACMANT are also discussed.

Possibilities of Using Pumice Concrete as Thermal Insulation Lining of Industrial Chimneys

This paper deals with the possibility of using pumice concrete as thermal insulation lining of industrial chimneys. Two formulas were prepared, the first from sulphate resistant cement and the second as a reference mixture from Cem I 42.5R. The thermal insulating properties of the prepared recipes will be evaluated as well as the resistance to the action of sulphates in 5 % sodium sulphate solution. No significant decrease in strength was observed when samples were stored in 5% sodium sulfate solution for 60 days. Only the reference series reported a significant unexpected decrease in strength.

Assessment of meteorological drought in agricultural locations from Venezuela under future projections of climate change

Drought is a phenomenon that is difficult to detect and predict, and with devastating consequences for natural, agricultural and human ecosystems. In order to know the future effects that climate change could have on this phenomenon in eight agricultural localities of Venezuela, the changes in the magnitude and duration of meteorological drought events were evaluated, for the reference series and for future series (period 2050s), projected by NCAR-CCSM4, GISS-E2-R, NIMR-HADGEM2-AO and MPI-ESM-LR models, for RCP 2.6 and RCP 8.5 scenarios. Drought events were estimated using the Standardized Precipitation Index (SPI) for the monthly scale and keeping the shape and scale parameters of the reference period. The results reveal a high variability of drought events among stations, models and scenarios; but with a common increase of the magnitude and duration of drought events for all models, mainly under the RCP 8.5 scenario. For the NCAR-CCSM4 model, there would be the greatest increase in the analyzed characteristics, in contrast to the NIMR-HADGEM2-AO model. The localities with droughts of greater magnitude and duration would be Barinitas and Pariaguán.

Combination of Using Pairwise Comparisons and Composite Reference Series: A New Approach in the Homogenization of Climatic Time Series

The removal of non-climatic biases, so-called inhomogeneities, from long climatic records needs sophistically developed statistical methods. One principle is that usually the differences between a candidate series and its neighbour series are analysed instead of directly the candidate series, in order to neutralize the possible impacts of regionally common natural climate variation on the detection of inhomogeneities. In most homogenization methods, two main kinds of time series comparisons are applied, i.e. composite reference series or pairwise comparisons. In composite reference series the inhomogeneities of neighbour series are attenuated by averaging the individual series, and the accuracy of homogenization can be improved by the iterative improvement of composite reference series. By contrast, pairwise comparisons have the advantage that coincidental inhomogeneities affecting several station series in a similar way can be identified with higher certainty than with composite reference series. In addition, homogenization with pairwise comparisons tends to facilitate the most accurate regional trend estimations. A new time series comparison method is presented here, which combines the use of pairwise comparisons and composite reference series in a way that their advantages are unified. This time series comparison method is embedded into the ACMANT homogenization method, and tested in large, commonly available monthly temperature test datasets.

Time series homogenization with the ACMANT software

<p>The development of ACMANT homogenization software started during the European COST HOME project, around 2010. Due to its excellent results in method comparison tests, the development of ACMANT has been being continuous since then. While its first version was applicable only to the homogenization of monthly temperature series, the later versions are applicable to a wide range of climatic variables and either for monthly or daily time series.</p><p>The operation of ACMANT is fast and automatic, and it is easy to use that even for large size datasets. The method can homogenize together time series of varied lengths, well tolerate data gaps, includes outlier filtering and infilling of data gaps (optional). ACMANT includes modern and effective statistical tools for the detection and removal of inhomogenities, such as step function fitting, bivariate detection for breaks of annual means and seasonal amplitudes (where applicable), ANOVA correction method and ensemble homogenization with varied pre-homogenization of neighbour series. For these properties, ACMANTv4 was the most accurate homogenization method in most method comparison tests of the Spanish MULTITEST project (https://doi.org/10.1175/JCLI-D-20-0611.1). In these tests, one important exception occurred, namely network mean trend errors were removed with significantly higher certainty by the Pairwise Homogenization Algorithm when approximately a half of the time series were affected with quasi synchronous breaks imitating concerted technical changes in the performance of climate observations. The most recent developments aiming the release of ACMANTv5 include the elimination of this drawback of ACMANT.</p><p>For ACMANTv5, a new break detection method has been developed, in which the combination of two time series comparison methods is applied. The new method contains both the use of composite reference series and pairwise comparisons, and in the detection with composite reference series the step function fitting is forced to include the breaks detected by pairwise comparisons. Another novelty of ACMANTv5 is that it gives options to use metadata in the homogenization procedure. The default operation mode of ACMANTv5 is still fully automatic, with or without the automatic use of a prepared metadata table. ACMANTv5 uses every date of the metadata list as a break indicator, and they are evaluated together with other indicators obtained by pairwise comparisons. Optionally, ACMANTv5 gives access to users to edit the list of detected breaks based on the pairwise detections of the first homogenization round. In the later steps of ACMANTv5 user intervention is not possible, but metadata may be considered by the automatic procedure also in the final estimation of break positions.     </p>

Deciphering the Global Private Financial Flows

Cross border and inter country financial recourse is like a civilization hold. It is fundamentally important phenomenon to study. Purpose of this study is to investigate inter country global private financial flows in context of current financial regimes. Design of the study is quantitative based on a secondary data taken from website of World Development Indicators (WDI) 2020. A literature review of relevant studies extracted from renowned research databases is also integral part of the overall design of the study. For the purpose of analysis and investigation the study uses Grey Relational Analysis (GRA). GRA is a mathematical technique capable of handling a multitude of alternatives with plenty of criteria simultaneously. It is a ranking technique that generates the reference series, normalizes the data and compares the weighted average grey coefficients with reference series. GRA is a popular methodology espoused in grey systems theory. It is the study of eighty-three countries on the basis of five different criteria. The countries have been ranked according to Grey relational grades by using rank function of excel and are divided into seven different categories on the basis of intensity of financial flows. The categories have been made on the basis of ordinal scale e.g. exceptionally high level of private global financial flows, excellent, very good, good, fair, poor and very poor. Results show that China, Niger, Brazil, Mozambique, Mongolia, St. Vincent and the Grenadines, Cambodia, Grenada, Thailand, Indonesia, Argentina and Maldives have exceptionally high private financial flows, whereas, countries namely Lesotho, Kazakhstan, Uzbekistan, Botswana, Guatemala, Solomon Islands, Afghanistan, Bolivia, Bhutan, Angola and Russian Federation have poor financial flows. Majorly, Arabian Countries (AC), Organization for Economic Co-operation and Development (OECD) and Union of South American Nations (UNASUR) countries fall under exceptionally high ensign, whereas, member countries of Economic Cooperation Organization (ECO) and Southern Africa Development Community (SADC) countries fall under very poor ensign. This study is useful for political governments, international agencies, researchers and academia (students and teachers of international finance). It also provides new information and deeper insights by way of assigning grey relational grades to countries and classifies them into seven groups. It also extends discussion to enlighten upon bloc level position.

SURFACE OCEAN RADIOCARBON FROM A PORITES CORAL RECORD IN THE GREAT BARRIER REEF: 1945–2017

ABSTRACT We present a high-resolution seawater radiocarbon (Δ14C) record from a Porites coral collected from Masthead Island in the southern Great Barrier Reef (GBR) covering the years 1945–2017. The Δ14C values from 1945–1953 (pre-bomb era) averaged –49‰. As a result of bomb-produced 14C in the atmosphere, Δ14C values started to rise rapidly from 1959, levelled off at ∼131‰ in the late 1970s and gradually decreased to ∼40.3‰ by 2017 due to the decrease in the air-sea 14C gradient and the overturning of the 14C ocean reservoir (i.e., surface ocean to subsurface ocean; atmosphere to surface ocean). The Masthead Island record is in agreement with previous 14C coral records from the southern GBR. A comparison between surface ocean and atmospheric Δ14C suggests that, since 2010, the main reservoir of bomb-derived 14C has shifted from the atmosphere to the surface ocean, potentially resulting in reversed 14C flux in regions where the CO2 gradient is favorable. The high-resolution Masthead coral Δ14C sheds light on long-term variability in air-sea exchange and GBR regional ocean dynamics associated with climate change and in conjunction with the previous records provides a robust seawater 14C reference series to date other carbonate samples.

Analysing the Return on Asset to Construct Foretelling Indicator for Bangladeshi Banking Sector

Financial institutions and banks are required to follow mechanisms to monitor the positions and create stimulas for sensible risk-taking by divisions a well as individuals. Risk measurement comprises of the quantification of risk exposures, whereas risk management demonstrates to the overall procedures by which managers fulfill these needs to identify the risks and recognise the category of the risks it faces. This research targerts on the economic instability faced by banks in financial arena in terms of the crises affairs in regard of economic distress. Here, the methodology followed is based on the CAMELS framework variables. CAMELS is a short form stands for: capital adequacy (C), asset (A), management (M), earnings (E), liquidity (L) and sensitivity to market risk (S). Based on these nomenclature, a couple of variables should be selected, such as capital asset ratio, cost income ratio, non-performing loan, non-interest income as component series and return on asset (ROA) as the reference series to identify turning points of economic volatility in banking sector of Bangladesh. Thus, by forecasting the directional deviations it could make financial policymakers aware of the changes at early stage in financial markets and banking industry and privilege them to undertake precautionary steps for preventive purposes. The constructed MPI should have a incredible lead time of about 5 to 7 months on an average in case of prediction against leading for the reference series. By renovating financial efficacy of venture banks, Bangladesh also should recover their subsequent banking system to execute these suggestions.

Creep Assessment of the Cement Matrix of Self-Compacting Concrete Modified with the Addition of Nanoparticles Using the Indentation Method

In recent years, there has been an increased interest in the modification of cement composites with finer materials, including nanoparticles. Multi-scale studies are needed to fully assess the effect of nanoparticles and provide a complete overview of their impact on both the structure of an obtained material and its important mechanical parameters, such as creep. Therefore, the purpose of this paper is to fill the knowledge gap in the literature concerning the assessment of the creep of a cement matrix of self-compacting concrete modified with the addition of SiO2, TiO2, and Al2O3 nanoparticles using the indentation method. Depending on the type of used nanoparticles, we found an increase or decrease of the creep coefficient CIT in comparison to the reference series. The obtained results were scrupulously analyzed in terms of statistics, which enabled the conclusion that the addition of nanoparticles does not significantly affect the creep of the cement matrix of self-compacting concrete. The methodology used in this paper allowed us to shorten the time needed to assess the creep phenomenon compared to traditional methods and fill the corresponding knowledge gap in the literature.