Relevant bibliographies by topics / Monthly Anomalies

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Monthly Anomalies'

Author: Grafiati
Published: 25 June 2021
Last updated: 13 February 2022

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Journal articles on the topic "Monthly Anomalies"

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Betts, Alan K., Ahmed B. Tawfik, and Raymond L. Desjardins. "Revisiting Hydrometeorology Using Cloud and Climate Observations." Journal of Hydrometeorology 18, no. 4 (March 16, 2017): 939–55. http://dx.doi.org/10.1175/jhm-d-16-0203.1.

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Abstract This paper uses 620 station years of hourly Canadian Prairie climate data to analyze the coupling of monthly near-surface climate with opaque cloud, a surrogate for radiation, and precipitation anomalies. While the cloud–climate coupling is strong, precipitation anomalies impact monthly climate for as long as 5 months. The April climate has memory of precipitation anomalies back to freeze-up in November, mostly stored in the snowpack. The summer climate has memory of precipitation anomalies back to the beginning of snowmelt in March. In the warm season, mean temperature is strongly correlated to opaque cloud anomalies, but only weakly to precipitation anomalies. Mixing ratio anomalies are correlated to precipitation, but only weakly to cloud. The diurnal cycle of mixing ratio shifts upward with increasing precipitation anomalies. Positive precipitation anomalies are coupled to a lower afternoon lifting condensation level and a higher afternoon equivalent potential temperature; both favor increased convection and precipitation. Regression coefficients on precipitation increase from wet to dry conditions. This is consistent with increased uptake of soil water when monthly precipitation is low, until drought conditions are reached, and also consistent with gravity satellite observations. Regression analysis shows monthly opaque cloud cover is tightly correlated to three climate variables that are routinely observed: diurnal temperature range, mean temperature, and mean relative humidity. The set of correlation coefficients, derived from cloud and climate observations, could be used to evaluate the representation of the land–cloud–atmosphere system in both forecast and climate models.
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Plastun, Alex, Xolani Sibande, Rangan Gupta, and Mark E. Wohar. "Historical evolution of monthly anomalies in international stock markets." Research in International Business and Finance 52 (April 2020): 101127. http://dx.doi.org/10.1016/j.ribaf.2019.101127.

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Klein, William H., and Runhua Yang. "Specification of monthly mean surface temperature anomalies in Europe and Asia from concurrent 700 mb monthly mean height anomalies over the Northern Hemisphere." Journal of Climatology 6, no. 5 (1986): 463–84. http://dx.doi.org/10.1002/joc.3370060503.

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Taylor, Patrick C. "Variability of Monthly Diurnal Cycle Composites of TOA Radiative Fluxes in the Tropics." Journal of the Atmospheric Sciences 71, no. 2 (February 1, 2013): 754–66. http://dx.doi.org/10.1175/jas-d-13-0112.1.

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Abstract Earth system variability is generated by a number of different sources and time scales. Understanding sources of atmospheric variability is critical to reducing the uncertainty in climate models and to understanding the impacts of sampling on observational datasets. The diurnal cycle is a fundamental variability evident in many geophysical variables—including top-of-the-atmosphere (TOA) radiative fluxes. This study considers aspects of the TOA flux diurnal cycle not previously analyzed: namely, deseasonalized variations in the monthly diurnal cycle composites, termed monthly diurnal cycle variability. Significant variability in the monthly diurnal cycle composites is found in both outgoing longwave radiation (OLR) and reflected shortwave (RSW). OLR and RSW monthly diurnal cycle variability exhibits a regional structure that follows traditional, climatological diurnal cycle categorization by prevailing cloud and surface types. The results attribute monthly TOA flux diurnal cycle variability to variations in the diurnal cloud evolution, which is sensitive to monthly atmospheric dynamic- and thermodynamic-state anomalies. The results also suggest that monthly diurnal cycle variability can amplify or buffer monthly TOA flux anomalies, depending on the region. Considering the impact of monthly diurnal cycle variability on monthly TOA flux anomalies, the results suggest that monthly TOA flux diurnal cycle variability must be considered when constructing a TOA flux dataset from sun-synchronous orbit. The magnitude of monthly diurnal composite variability in OLR and RSW is regionally dependent—1–7 W m−2 and 10%–80% relative to interannual TOA flux variability. The largest (4–7 W m−2; 40%–80%) and smallest (1–3 W m−2; 10%–30%) TOA flux uncertainties occur in convective and nonconvective regions, respectively, over both land and ocean.
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Borges, A. V., B. Tilbrook, N. Metzl, A. Lenton, and B. Delille. "Inter-annual variability of the carbon dioxide oceanic sink south of Tasmania." Biogeosciences 5, no. 1 (February 6, 2008): 141–55. http://dx.doi.org/10.5194/bg-5-141-2008.

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Abstract. We compiled a large data-set from 22 cruises spanning from 1991 to 2003, of the partial pressure of CO2 (pCO2) in surface waters over the continental shelf (CS) and adjacent open ocean (43° to 46° S; 145° to 150° E), south of Tasmania. Climatological seasonal cycles of pCO2 in the CS, the subtropical zone (STZ) and the subAntarctic zone (SAZ) are described and used to determine monthly pCO2 anomalies. These are used in combination with monthly anomalies of sea surface temperature (SST) to investigate inter-annual variations of SST and pCO2. Monthly anomalies of SST (as intense as 2°C) are apparent in the CS, STZ and SAZ, and are indicative of strong inter-annual variability that seems to be related to large-scale coupled atmosphere-ocean oscillations. Anomalies of pCO2 normalized to a constant temperature are negatively related to SST anomalies. A reduced winter-time vertical input of dissolved inorganic carbon (DIC) during phases of positive SST anomalies, related to a poleward shift of westerly winds, and a concomitant local decrease in wind stress is the likely cause of the negative relationship between pCO2 and SST anomalies. The observed pattern is an increase of the sink for atmospheric CO2 associated with positive SST anomalies, although strongly modulated by inter-annual variability of wind speed. Assuming that phases of positive SST anomalies are indicative of the future evolution of regional ocean biogeochemistry under global warming, we show using a purely observational based approach that some provinces of the Southern Ocean could provide a potential negative feedback on increasing atmospheric CO2.
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Lagos, P., Y. Silva, E. Nickl, and K. Mosquera. "El Niño – related precipitation variability in Perú." Advances in Geosciences 14 (April 10, 2008): 231–37. http://dx.doi.org/10.5194/adgeo-14-231-2008.

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Abstract. The relationship between monthly mean sea surface temperature (SST) anomalies in the commonly used El Niño regions and precipitation for 44 stations in Perú is documented for 1950–2002. Linear lag correlation analysis is employed to establish the potential for statistical precipitation forecasts from SSTs. Useful monthly mean precipitation anomaly forecasts are possible for several locations and calendar months if SST anomalies in El Niño 1+2, Niño 3.4, and Niño 4 regions are available. Prediction of SST anomalies in El Niño regions is routinely available from Climate Prediction Center, NOAA, with reasonable skill in the El Niño 3.4 region, but the prediction in El Niño 1+2 region is less reliable. The feasibility of using predicted SST anomalies in the El Niño 3.4 region to predict SST anomalies in El Niño 1+2 region is discussed.
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Kossowska-Cezak, Urszula. "Monthly thermal and precipitation anomalies in Warsaw and their causes." Miscellanea Geographica 7, no. 1 (March 1, 1996): 71–76. http://dx.doi.org/10.2478/mgrsd-1996-070110.

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CASTILLA, EDUARDO E., IEDA M. ORIOLI, REGINA LUGARINHO, GRACA P. DUTRA, JORGE S. LOPEZ-CAMELO, HEBE E. CAMPANA, AMEDEO SPAGNOLO, and PIERPAOLO MASTROIACOVO. "Monthly and Seasonal Variations in the Frequency of Congenital Anomalies." International Journal of Epidemiology 19, no. 2 (1990): 399–404. http://dx.doi.org/10.1093/ije/19.2.399.

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Smith, Thomas M., Phillip A. Arkin, Mathew R. P. Sapiano, and Ching-Yee Chang. "Merged Statistical Analyses of Historical Monthly Precipitation Anomalies Beginning 1900." Journal of Climate 23, no. 21 (November 1, 2010): 5755–70. http://dx.doi.org/10.1175/2010jcli3530.1.

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Abstract A monthly reconstruction of precipitation beginning in 1900 is presented. The reconstruction resolves interannual and longer time scales and spatial scales larger than 5° over both land and oceans. Because of different land and ocean data availability, the reconstruction combines two separate historical reconstructions. One analyzes interannual variations directly by fitting gauge-based anomalies to large-scale spatial modes. This direct reconstruction is used for land anomalies and interannual oceanic anomalies. The other analyzes annual and longer variations indirectly from correlations with analyzed sea surface temperature and sea level pressure. This indirect reconstruction is used for oceanic variations with time scales longer than interannual. In addition, a method of estimating reconstruction errors is also presented. Over land the reconstruction is a filtered representation of the gauge data with data gaps filled. Over oceans the reconstruction gives an estimate of the atmospheric response to changing temperature and pressure, combined with interannual variations. The reconstruction makes it possible to evaluate global precipitation variations for periods much longer than the satellite period, which begins in 1979. Evaluations show some large-scale similarities with coupled model precipitation variations over the twentieth century, including an increasing tendency over the century. The reconstructed land and sea trends tend to be out of phase at low latitudes, similar to the out-of-phase relationship for interannual variations. This reconstruction may be used for climate monitoring, for statistical climate studies of the twentieth century, and for helping to evaluate dynamic climate models. In the future the possibility of improving the reconstruction will be explored by further improving the analysis methods and including additional data.
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Krokhin, V. V., and W. M. J. Luxemburg. "Temperatures and precipitation totals over the Russian Far East and Eastern Siberia: long-term variability and its links to teleconnection indices." Hydrology and Earth System Sciences 11, no. 6 (November 27, 2007): 1831–41. http://dx.doi.org/10.5194/hess-11-1831-2007.

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Abstract. The present study examines the spatial-temporal regime of the mean monthly temperature (MMT) and monthly precipitation (MPT) anomalies over the Russian Far East and Eastern Siberia for the period 1949–2003. The original data were analyzed spatially by means of complex principal component analysis and temporally by means of the maximum entropy method and traditional Fourier spectral analysis. The interannual variability in these anomalies can be represented by the single dominant modes. These dominant modes oscillate with periods of about 2–3 yr and 6–8 yr that are accompanied by statistically significant changes in such monthly teleconnection indices, as the Arctic and North Pacific Oscillations.
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Dissertations / Theses on the topic "Monthly Anomalies"

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Edberg, Christopher, and Oliver Kjellander. "Calendar Anomalies in the Nordic Stock Markets : A quantitative study of the Sell in May effect, January effect & Monthly Anomalies." Thesis, Linnéuniversitetet, Institutionen för ekonomistyrning och logistik (ELO), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-105272.

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This study has applied a geographical perspective with the ambition of evaluating the presence of the Sell in May effect, January effect and monthly anomalies in the Nordic stock markets. In extension the study examines the relationship between corporate size and the returns of calendar anomalies. The study has conducted statistical tests based on Newey-West regressions as well as a Generalized Auto-Regressive Conditional Heteroscedasticity model. The findings suggest that the Sell in May and January are present in the Nordic region and partially abide by theory and results of previous research. The findings suggest that the Sell in May and January effect are independent, however, tendencies when the January effect has a considerable influence on the Sell in May effect are also evident. Additionally, the “April Effect” is an unexpected outlier with positive excess returns that was identified through this study.
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Halari, Anwar. "An analysis of monthly calendar anomalies in the Pakistani stock market : a study of the Gregorian and Islamic calendars." Thesis, University of Dundee, 2013. https://discovery.dundee.ac.uk/en/studentTheses/ef1d3ef3-4cda-4a39-83eb-aa3ba3d46689.

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Most of the prior research in the area of monthly regularities has been based on the Gregorian calendar; by contrast, little attention has been given to other calendars based on different religions or cultures. This thesis examines monthly calendar anomalies in the Pakistani stock market for both the Gregorian calendar and its Islamic counterpart. This is one of the first studies to investigate both calendars for monthly seasonality in one investigation on the same dataset. Empirical studies of the Pakistani stock market that have examined monthly calendar anomalies are relatively sparse when compared with investigations from other emerging markets throughout the world. Even the findings from the small number of Pakistani investigations that have examined for the presence of monthly calendar anomalies have arrived at different conclusions about the predictability of equity returns at different times within a year. Since the conclusions of these findings have been mixed, the current study undertakes further work on this topic to offer some clarity in this area; this thesis arrives at a firm conclusion about the monthly calendar anomaly. For the purpose of this thesis, both qualitative and quantitative research methods were employed. Firstly, 19 face-to-face interviews were conducted with brokers, regulators and individual investors to ascertain their views about share price regularities with regards to monthly calendar anomalies and to gain some insights about the role of investor sentiment in the Pakistani stock markets. Secondly, share returns for a sample of 106 companies listed on the KSE over the 17 year period from 1995 to 2011 were analysed to determine whether Pakistani stock markets are weak-form efficient or whether security price changes can be predicted from knowledge of the month when the return is earned; it also investigates whether there is a change in the risk (volatility) of shares in different months which might explain any pattern in returns. To answer these questions various research methods were employed. The results of the interviews suggest that most respondents believed that share prices exhibit patterns in certain months of the year. The most common pattern highlighted by the interviewees related to the month of January for the Gregorian calendar and Ramadan for the Islamic calendar. Interviewees also argued that volatility declined during the religious month of Ramadan; they attributed these changes to investor sentiment and religious duties. Overall, the results suggested that monthly calendar anomalies may be present in the market and that these are studied by investors in an attempt to earn profit. The results from the quantitative analyses supported the findings from the interviews. Initial analyses suggested that returns varied significantly during certain months which indicate that the market might not be efficient. Further, investigations for seasonality in both the mean and volatility of returns offered conflicting evidence; very little statistical evidence of monthly seasonal anomalies was identified in average returns. However, monthly patterns were present in the variance of equity price changes in Pakistan. Overall, the results confirm that whatever monthly seasonality may be present in the equity prices of Pakistani companies, it is more pronounced in the volatility data than in the mean return numbers. These findings may have useful implications for trading strategies and investment decisions; investors may look to gain from managing the risk of their portfolios due to time varying volatility documented in the findings of this thesis. Further, the results of this thesis have interesting implications for our understanding of the dynamics of equity volatility in the Pakistani stock market.
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Jean, Dominic. "A full century of monthly Canadian stock price index returns : a review of the Fisher hypothesis and some anomalies." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ64050.pdf.

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Ficik, Jozef. "Are Financial Market Anomalies Real? Evidence from Stock Markets in Five Countries." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-198627.

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The financial market anomaly can be characterized as the event when observed stock returns differentiate from those expected by concrete pricing model. Many anomalies have been detected so far, and some of them vanished, while other persisted, after they had been published by academics and researchers. The aim of this thesis is to investigate the potential presence of selected types of anomalies in the financial markets and to provide relevant empirical evidence. The theoretical section will supply the reader with the descriptions of several types of financial market anomalies and the results of past studies documenting the existence of these anomalies, with possible reasons justifying the presence of this phenomenon. The analytical section will focus on the few selected anomalies and test whether they are still present in the selected financial markets.
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Halldestam, Markus, and Katarina Karlsson. "Trading Opportunities You Missed on the Swedish Equity Market : An Analysis of the Persistence of Calendar Anomalies." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-354678.

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This Study uses a period between 1939-2017 to analyse calendar anomalies on the Swedish equity market. We test whether calendar anomalies’ return deviates from the return of ordinary trading days. Our result shows that the day of the week effect, weekend effect, turn of the year, turn of the month and holiday effect have had an impact on the daily rate of return, both domestic and abroad. Similar to international markets the calendar anomalies in Sweden start to be less prominent during 1980’s. Also, our result displays that, since the 1970’s, UK holidays have had a negative impact on the daily return in Sweden. In contrast, American holidays have since the 2010’s had a positive impact. Turn of the year and turn of the month in Sweden have been more clustered around the first trading day of the year and month, compared to studies on other equity markets. Negative returns on Tuesdays, rather than Mondays, do also distinguish Sweden’s equity market relative to other markets.
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Hetting, Oscar, Joakim Hellman, and Maryam Tarighi. "Capitalizing on seasonalities in the Singapore Straits Times Index." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Företagsekonomi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-18167.

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Purpose: The purpose of this thesis is to study the possible existence of day-of-the-week effects and month-of-the-year effects in the Singapore stock market over the period January 1st 1993 to December 31st 2011. The findings are analysed with the intention of developing investment strategies and to investigate if behavioural finance can help to explain the existence of seasonal anomalies.  Background: A number of previous studies have found evidence of seasonal anomalies in global stock markets, and by challenging the core assumptions of market efficiency, such anomalies may make it possible to predict the movement of stock prices at certain periods during the year. Consequently, there may be substantial profit-making opportunities that clever investors can benefit from, raising two important questions: (1) can such anomalies be strategically used to outperform the market and (2) why do such cyclical return patterns exist? Method: Daily closing prices from the Singapore Straits Times Index (STI) are used to compute average daily and monthly returns, which are further analysed through the use of statistical significance analysis and hypothesis testing to identify the possible existence of day-of-the-week effects and month-of-the-year effects in the Singapore stock market.  The results of the statistical investigation are used to develop investment strategies that are designed to take advantage of both positive and negative effects, and the theories of behavioural finance are applied to help explain why seasonalities occur at certain points in time. Conclusions: This study finds evidence of several seasonal anomalies in the Singapore stock market. Both day-of-the-week effects and month-of-the-year effects are present in the STI over the full sample period. Many of these effects can be explained by behavioural finance, and used to develop investment strategies that outperform the market.
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Books on the topic "Monthly Anomalies"

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Cayan, Daniel R. An atlas of United States monthly and seasonal temperature anomalies, December 1930 - November 1984. [La Jolla, Calif: Scripps Institution of Oceanography, Climate Research Group, 1986.

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1940-, Gruber Arnold, and United States. National Environmental Satellite, Data, and Information Service., eds. Monthly and seasonal mean outgoing longwave radiation and anomalies. Washington, D.C: U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1986.

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Hutton, Kim. Disorders of the kidney and upper urinary tract in children. Edited by David F. M. Thomas. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199659579.003.0116.

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The majority of clinically significant congenital disorders of the upper urinary tract are now detected prenatally. Commonly identified abnormalities include pelviureteric junction obstruction (PUJO), vesicoureteric junction obstruction (VUJO), duplication anomalies, multicystic dysplastic kidney (MCDK), high grade vesicoureteric reflux (VUR) and anomalies of renal migration and/or fusion. Most affected infants are asymptomatic at birth and further investigation can usually be undertaken on a non-urgent basis in the first few weeks or months of life. Long-term natural history studies have shown that many of these conditions can be managed non-operatively. In most cases, standardized procedures such as pyeloplasty and ureteric reimplantation give predictably satisfactory results. Long-term outcome data for surgical and conservative management of upper tract disorders in children is sparse and research in this area is still required.
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Giacovazzo, Carmelo. Phasing in Crystallography. Oxford University Press, 2013. http://dx.doi.org/10.1093/oso/9780199686995.001.0001.

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Modern crystallographic methods originate from the synergy of two main research streams, the small-molecule and the macro-molecular streams. The first stream was able to definitively solve the phase problem for molecules up to 200 atoms in the asymmetric unit. The achievements obtained by the macromolecular stream are also impressive. A huge number of protein structures have been deposited in the Protein Data Bank. The solution of them is no longer reserved to an elite group of scientists, but may be attained in a large number of laboratories around the world, even by young scientists. New probabilistic approaches have been tailored to deal with larger structures, errors in the experimental data, and modest data resolution. Traditional phasing techniques like ab initio, molecular replacement, isomorphous replacement, and anomalous dispersion techniques have been revisited. The new approaches have been implemented in robust phasing programs, which have been organized in automatic pipelines usable even by non-experts. Protein structures, which 50 years ago could take months or even years to solve, can now be solved in a matter of hours, partly also due to technological advances in computer science. This book describes all modern crystallographic phasing methods, and introduces a new rational classification of them. A didactic approach is used, with the techniques described simply and logically in the main text, and further mathematical details confined to the Appendices for motivated readers. Numerous figures and applicative details illustrate the text.
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Book chapters on the topic "Monthly Anomalies"

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Mattarocci, Gianluca. "Monthly Calendar Anomalies." In Anomalies in the European REITs Market, 60–70. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137390929_6.

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Rao, T. Subba, and E. P. Tsolaki. "Nonstationary Time Series Analysis of Monthly Global Temperature Anomalies." In Time Series Analysis and Applications to Geophysical Systems, 73–103. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4684-9386-3_5.

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Subba Rao, T., and E. P. Tsolaki. "Nonstationary Time Series Analysis of Monthly Global Temperature Anomalies." In Time Series Analysis and Applications to Geophysical Systems, 73–103. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4612-2962-9_5.

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Bolduc, P. A., and T. S. Murty. "Monthly Mean Sea Level Anomalies for the North and Tropical Atlantic Ocean." In Sea Level Changes: Determination and Effects, 1–22. Washington, D. C.: American Geophysical Union, 2013. http://dx.doi.org/10.1029/gm069p0001.

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Selvam, Amujuri Mary. "Signatures of Universal Characteristics of Fractal Fluctuations in Global Mean Monthly Temperature Anomalies." In Springer Atmospheric Sciences, 121–35. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54546-2_5.

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Amoo, Oseni Taiwo, Hammed Olabode Ojugbele, Abdultaofeek Abayomi, and Pushpendra Kumar Singh. "Hydrological Dynamics Assessment of Basin Upstream–Downstream Linkages Under Seasonal Climate Variability." In African Handbook of Climate Change Adaptation, 2005–24. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-45106-6_116.

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AbstractThe impacts of climate change are already being felt, not only in terms of increase in temperature but also in respect of inadequate water availability. The Mkomazi River Basins (MRB) of the KwaZulu-Natal region, South Africa serves as major source of water and thus a mainstay of livelihood for millions of people living downstream. It is in this context that the study investigates water flows abstraction from headwaters to floodplains and how the water resources are been impacted by seasonal climate variability. Artificial Neural Network (ANN) pattern classifier was utilized for the seasonal classification and subsequence hydrological flow regime prediction between the upstream–downstream anomalies. The ANN input hydroclimatic data analysis results covering the period 2008–2015 provides a likelihood forecast of high, near-median, or low streamflow. The results show that monthly mean water yield range is 28.6–36.0 m3/s over the Basin with a coefficient of correlation (CC) values of 0.75 at the validation stage. The yearly flow regime exhibits considerable changes with different magnitudes and patterns of increase and decrease in the climatic variables. No doubt, added activities and processes such as land-use change and managerial policies in upstream areas affect the spatial and temporal distribution of available water resources to downstream regions. The study has evolved an artificial neuron system thinking from conjunctive streamflow prediction toward sustainable water allocation planning for medium- and long-term purposes.
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Mattarocci, Gianluca. "The Time of the Month Effect for European REIT Investors." In Anomalies in the European REITs Market, 91–101. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137390929_8.

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Mattarocci, Gianluca. "The Impact of the Turn of the Month on European REIT Markets." In Anomalies in the European REITs Market, 71–90. London: Palgrave Macmillan UK, 2014. http://dx.doi.org/10.1057/9781137390929_7.

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Jacobeit, Jucundus, Heinz Wanner, Gerhard Koslowski, and Martin Gudd. "European Surface Pressure Patterns for Months with Outstanding Climatic Anomalies During the Sixteenth Century." In Climatic Variability in Sixteenth-Century Europe and Its Social Dimension, 201–21. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-015-9259-8_7.

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Ziemba, William T. "Japanese security market regularities Monthly, turn-of-the-month and year, holiday and golden week effects." In Calendar Anomalies and Arbitrage, 263–90. WORLD SCIENTIFIC, 2012. http://dx.doi.org/10.1142/9789814405461_0011.

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Conference papers on the topic "Monthly Anomalies"

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Li, Weigang, Leonardo D. Sa, G. S. Prasad, A. G. Nowosad, Mauricio Bolzan, and E. S. M. Chiang. "Neural networks adaptive wavelets for predictions of the northeastern Brazil monthly rainfall anomalies time series." In Aerospace/Defense Sensing and Controls, edited by Steven K. Rogers and Dennis W. Ruck. SPIE, 1996. http://dx.doi.org/10.1117/12.235908.

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McGuinness, Sarah A., and Richard H. Becker. "ASSESSING GROUNDWATER-SURFACE WATER INTERACTIONS OF THE SUDD WETLAND, SOUTH SUDAN, USING NDVI/NDWI TIME SERIES AND MONTHLY GRACE ANOMALIES." In GSA Annual Meeting in Phoenix, Arizona, USA - 2019. Geological Society of America, 2019. http://dx.doi.org/10.1130/abs/2019am-336986.

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Pajak, Katarzyna. "Seasonal Baltic Sea level change from altimetry data." In Environmental Engineering. VGTU Technika, 2017. http://dx.doi.org/10.3846/enviro.2017.223.

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Regional sea level changes occur at different time scales. Global warming of the oceans, glacial and polar ice melting and meteorological or hydrological factors are major contributors to long-term sea level rise. In the recent years, a lot of attention has been paid to research concerning sea level change and seasonal fluctuations. The main objective of this paper was to determine the seasonal variability in the Baltic Sea level using satellite altimetry data for the period 1 January 2010 – 31 December 2014. The ANOVA analysis of variance was used in the research in order to estimate seasonal fluctuations. This study focused on investigate the monthly and annual amplitude in sea level anomalies over a given time period. The results from research showed that the amplitudes of fluctuations are the highest in winter and the smallest in summer in three analyzed points of the Baltic Sea. The results can bring valuable information about ongoing aspects in sea level changes, as a way of tracking climate change.
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MAGYARI-SÁSKA, Zsolt, and Ștefan DOMBAY. "Preferential Attachment in Modeling Climate Changes. Test Location: Miercurea-Ciuc, Romania." In Air and Water – Components of the Environment 2021 Conference Proceedings. Casa Cărţii de Ştiinţă, 2021. http://dx.doi.org/10.24193/awc2021_15.

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Climate change is a fact that we face year after year. Although is a common syntagma its manifestation is different for various region of the planet producing not just global, but local anomalies and changes. In order to track these changes, we propose a network model with preferential attachment, vertices representing successive time periods. The test location for our research was Miercurea Ciuc, one of the coldest locations of Romania. We have developed a similarity index including different meteorological parameters such as air temperature, ground temperature, precipitation amount, snow depth and sunshine hours. Using this similarity index for preferential attachment and considering the appearance order of nodes representing periods on time scale we have created a network model which shows the similarities between these periods as they appear in time. Clustering the obtained graph model, we could observe that the created network model at monthly scale clearly shows up some of experienced characteristic at the study location.
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Navia, Diaz Juan, Diaz Juan Navia, Bolaños Nancy Villegas, Bolaños Nancy Villegas, Igor Malikov, and Igor Malikov. "EXTREME VALUES OF SEA SURFACE TEMPERATURE ASSOCIATED WITH LONG-PERIOD PHENOMENA OCCURRED DURING 1960-2015 IN THE COLOMBIAN PACIFIC OCEAN." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.21610/conferencearticle_58b431547291f.

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Sea Surface Temperature Anomalies (SSTA), in four coastal hydrographic stations of Colombian Pacific Ocean, were analyzed. The selected hydrographic stations were: Tumaco (1°48'N-78°45'W), Gorgona island (2°58'N-78°11'W), Solano Bay (6°13'N-77°24'W) and Malpelo island (4°0'N-81°36'W). SSTA time series for 1960-2015 were calculated from monthly Sea Surface Temperature obtained from International Comprehensive Ocean Atmosphere Data Set (ICOADS). SSTA time series, Oceanic Nino Index (ONI), Pacific Decadal Oscillation index (PDO), Arctic Oscillation index (AO) and sunspots number (associated to solar activity), were compared. It was found that the SSTA absolute minimum has occurred in Tumaco (-3.93°C) in March 2009, in Gorgona (-3.71°C) in October 2007, in Solano Bay (-4.23°C) in April 2014 and Malpelo (-4.21°C) in December 2005. The SSTA absolute maximum was observed in Tumaco (3.45°C) in January 2002, in Gorgona (5.01°C) in July 1978, in Solano Bay (5.27°C) in March 1998 and Malpelo (3.64°C) in July 2015. A high correlation between SST and ONI in large part of study period, followed by a good correlation with PDO, was identified. The AO and SSTA have showed an inverse relationship in some periods. Solar Cycle has showed to be a modulator of behavior of SSTA in the selected stations. It was determined that extreme values of SST are related to the analyzed large scale oscillations.
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Navia, Diaz Juan, Diaz Juan Navia, Bolaños Nancy Villegas, Bolaños Nancy Villegas, Igor Malikov, and Igor Malikov. "EXTREME VALUES OF SEA SURFACE TEMPERATURE ASSOCIATED WITH LONG-PERIOD PHENOMENA OCCURRED DURING 1960-2015 IN THE COLOMBIAN PACIFIC OCEAN." In Managing risks to coastal regions and communities in a changing world. Academus Publishing, 2017. http://dx.doi.org/10.31519/conferencearticle_5b1b943a9e4336.75393991.

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Abstract:
Sea Surface Temperature Anomalies (SSTA), in four coastal hydrographic stations of Colombian Pacific Ocean, were analyzed. The selected hydrographic stations were: Tumaco (1°48'N-78°45'W), Gorgona island (2°58'N-78°11'W), Solano Bay (6°13'N-77°24'W) and Malpelo island (4°0'N-81°36'W). SSTA time series for 1960-2015 were calculated from monthly Sea Surface Temperature obtained from International Comprehensive Ocean Atmosphere Data Set (ICOADS). SSTA time series, Oceanic Nino Index (ONI), Pacific Decadal Oscillation index (PDO), Arctic Oscillation index (AO) and sunspots number (associated to solar activity), were compared. It was found that the SSTA absolute minimum has occurred in Tumaco (-3.93°C) in March 2009, in Gorgona (-3.71°C) in October 2007, in Solano Bay (-4.23°C) in April 2014 and Malpelo (-4.21°C) in December 2005. The SSTA absolute maximum was observed in Tumaco (3.45°C) in January 2002, in Gorgona (5.01°C) in July 1978, in Solano Bay (5.27°C) in March 1998 and Malpelo (3.64°C) in July 2015. A high correlation between SST and ONI in large part of study period, followed by a good correlation with PDO, was identified. The AO and SSTA have showed an inverse relationship in some periods. Solar Cycle has showed to be a modulator of behavior of SSTA in the selected stations. It was determined that extreme values of SST are related to the analyzed large scale oscillations.
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Menezes, Cinderella, Bindu Radha, Soraya Shirzad, and Ahmed Abdelgadir. "321 Antenatally diagnosed renal anomalies and the six-month post-natal outcome of renal pelvic dilatation at a district general hospital in South East England." In RCPCH Conference Singapore. BMJ Publishing Group Ltd, 2021. http://dx.doi.org/10.1136/bmjpo-2021-rcpch.177.

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Viveiros, Victor Hugo, Rayanne Lima, Fernando Lucas Martins, Alessandra Coelho, and Matheus Baffa. "Fully-Connected Neural Network for COVID-19 Chest X-Ray Imaging Classification Using Hybrid Features." In Workshop de Visão Computacional. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/wvc.2020.13498.

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Discovered on 31st December of 2019, the new Coronavirus has a high transmission capacity and was considered pandemic by the World Health Organization. In only six months is was able to spread all over the world and cause more than 600 thousand deaths. Early diagnosis is essential for governments to take public policies, such as social isolation, commerce control, and contact tracking. In order to make these actions, massive tests are required. On the other hand, diagnosis kits are expensive and not accessible to everyone. Medical imaging, such as thoracic x-ray and Computational Tomography (CT) has been used to visualize the lung and to verify at the first moment the presence of viral pneumonia. However, some countries have few radiologists specializing in chest x-ray analysis. The findings in the image are generally not so easy to see and can easily be confused with traditional pneumonia findings. For this reason, studies in Computer Vision are necessary, both to detect anomalies in imaging and to differentiate the other types of pneumonia. This paper addresses the initial results of a research, which developed an image classification methodology to differentiate x-ray images from sick patients, infected with Coronavirus, and healthy patients. The proposed method, based on the extraction and detection of patterns in texture and color features through a Deep Neural Network, obtained an average accuracy of 95% following a k-fold cross-validation experiment.
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Morrison, James, David Christie, Charles Greenwood, Ruairi Maciver, and Arne Vogler. "Software Analysis Tools for Wave Sensors." In ASME 2015 34th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/omae2015-41852.

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This paper presents a set of software tools for interrogating and processing time series data. The functionality of this toolset will be demonstrated using data from a specific deployment involving multiple sensors deployed for a specific time period. The approach was developed initially for Datawell Waverider MKII/MKII buoys [1] and expanded to include data from acoustic devices in this case Nortek AWACs. Tools of this nature are important to address a specific lack of features in the sensor manufacturers own tools. It also helps to develop standard approaches for dealing with anomalous data from sensors. These software tools build upon an effective modern interpreted programming language in this case Python which has access to high performance low level libraries. This paper demonstrates the use of these tools applied to a sensor network based on the North West coast of Scotland as described in [2,3]. Examples can be seen of computationally complex data being easily calculated for monthly averages. Analysis down to a wave by wave basis will also be demonstrated form the same source dataset. The tools make use of a flexible data structure called a DataFrame which supports mixed data types, hierarchical and time indexing and is also integrated with modern plotting libraries. This allows sub second querying and the ability for dynamic plotting of large datasets. By using modern compression techniques and file formats it is possible to process datasets which are larger than memory datasets without the need for a traditional relational database. The software library shall be of use to a wide variety of industry involved in offshore engineering along with any scientists interested in the coastal environment.
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Seto, Laura, Thomas Hennig, and Thorsten Sickinger. "Development and Validation of a Combined UM/UC In-Line Inspection Tool for a 36/48″ Pipeline System." In 2014 10th International Pipeline Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/ipc2014-33296.

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Within the global integrity program of Enbridge a 36/48″ dual diameter pipeline with a total length of approximately1800 km needs to be inspected for wall thickness and axial cracking in a single run. The line consists of 29 sections, each of an approximate length of 60 km. A challenging characteristic of the line is the 36″ launcher and 48″ receiver in 28 of the sections. Thus, the resulting outer diameter change is about 305mm or 33%. From an intelligent inspection perspective additional boundary conditions had to be taken into account, e.g. tight 1.5D bends and a medium with high attenuation — which is especially important for the crack inspection technology. Pipeline operator and in-line inspection (ILI) vendor agreed on an extensive testing and qualification program including small scale tests (200 anomalies) and field verifications. Therefore, the operator witnessed pull tests of the 36/48″ UCM tool at the test facility in Stutensee, Germany during the development phase in 2012. The first inspection in an operating pipeline system, as part of the validation process, was made in July 2012 after only 12 months of development and construction. Some shortcomings of the tool concept were observed within the first inspection, which led to an unsuccessful run. Both parties worked closely together to implement some modifications to the tool. In 2012 and 2013 the modified tool was run a total of 29 times, with further runs planned for 2014. The first excavations have been completed, and show an excellent correlation between tool performance and specification. Further excavations are scheduled for early 2014 that will provide additional feedback to assess and validate the tool. At the time of writing, the 36/48″ tool is fully validated for metal loss defects, and validated for cracks only up to 2.5mm in depth. The authors will present in detail the development of the tool and the definition of the validation process. Mechanical and operational conditions are discussed. The predefined validation process of the tool is briefly presented and the test results are discussed in detail. Furthermore, field verification results are presented.
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