Evaluation of Performance of Different Methods in Detecting Abrupt Climate Changes

We compared and evaluated the performance of five methods for detecting abrupt climate changes using a time series with artificially generated abrupt characteristics. Next, we analyzed these methods using annual mean surface air temperature records from the Shenyang meteorological station. Our results show that the movingt-test (MTT), Yamamoto (YAMA), and LePage (LP) methods can correctly and effectively detect abrupt changes in means, trends, and dynamic structure; however, they cannot detect changes in variability. We note that the sample size of the subseries used in these tests can affect their results. When the sample size of the subseries ranges from one-quarter to three-quarters of the jump scale, these methods can effectively detect abrupt changes; they perform best when the sample size is one-half of the jump scale. The Cramer method can detect abrupt changes in the mean and trend of a series but not changes in variability or dynamic structure. Finally, we found that the Mann-Kendall test could not detect any type of abrupt change. We found no difference in the results of any of the methods following removal of the mean, creation of an anomaly series, or normalization. However, detrending and study period selection affected the results of the Cramer and Mann-Kendall methods; in the latter case, they could lead to a completely different result.

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Holocene temperature and environmental reconstruction from lake sediments in the Søndre Strømfjord region, southern West Greenland

Geological Survey of Denmark and Greenland Bulletin ◽

10.34194/ggub.v189.5157 ◽

2001 ◽

pp. 59-64 ◽

Cited By ~ 5

Author(s):

Klaus P. Brodersen ◽

Claus Lindegaard ◽

N. John Anderson

Keyword(s):

Lake Sediments ◽

Surface Air Temperature ◽

Environmental Reconstruction ◽

Considerable Influence ◽

Arctic Ecosystems ◽

West Greenland ◽

The Earth ◽

The Mean ◽

Temperature Records ◽

Instrumental Temperature

NOTE: This article was published in a former series of GEUS Bulletin. Please use the original series name when citing this article, for example: Brodersen, K. P., Lindegaard, C., & Anderson, N. J. (2001). Holocene temperature and environmental reconstruction from lake sediments in the Søndre Strømfjord region, southern West Greenland. Geology of Greenland Survey Bulletin, 189, 59-64. https://doi.org/10.34194/ggub.v189.5157 _______________ Instrumental temperature records indicate that the mean annual surface-air temperature of the Earth has risen approximately 0.6°C since 1860 (IPCC 2001). Increased global warming can have considerable influence at high latitudes, and among the major concerns are the effects on the sensitive arctic ecosystems and the possible reduction in the diversity of regional flora and fauna. Arctic organisms are highly adapted to extreme environmental conditions and have difficulties coping with any additional stresses or disturbances.

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Abrupt Change Detection Method Based on Features of Lorenz Trajectories

Atmosphere ◽

10.3390/atmos12060781 ◽

2021 ◽

Vol 12 (6) ◽

pp. 781

Author(s):

Chaojiu Da ◽

Binglu Shen ◽

Jian Song ◽

Cairang Xaiwu ◽

Guolin Feng

Keyword(s):

Time Series ◽

Climate Changes ◽

Abrupt Change ◽

Atmospheric Model ◽

Original Method ◽

Lorenz Equation ◽

Dynamical Characteristics ◽

Abrupt Changes ◽

The Times ◽

The Right

This paper presents a definition of bifurcation-type abrupt changes based on the bifurcation features of Lorenz trajectories. These abrupt changes are the result of the transition behavior of dynamical system trajectories among different equilibrium regions. We demonstrate that these bifurcation-type jumps can better reflect the nature of abrupt change. In analyzing the features of Lorenz equation trajectories, a dynamical method for detecting bifurcation-type abrupt changes is presented. A numerical solution of the Lorenz equation is adopted, using a curve integral or vector product to construct a time series of positive and negative values. Changes in the sign of this time series accurately determine whether the trajectory is in the right or left equilibrium region, and the points at which the time series is equal to zero are the times at which the trajectory jumps between different equilibrium regions, that is, the occurrence times of bifurcation-type abrupt changes. This method is completely dependent on the dynamical characteristics of the system. A theoretical approach for detecting abrupt climate changes based on the dynamical characteristics of the atmospheric model is described. Compared with the original method of identifying abrupt climate changes, this method has dynamic significance and can detect abrupt changes in multi-dimensional time series. Although this method can be applied theoretically, applications to real atmospheric data first require the data to be smoothed.

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The anatomy of past abrupt warmings recorded in Greenland ice

Nature Communications ◽

10.1038/s41467-021-22241-w ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

E. Capron ◽

S. O. Rasmussen ◽

T. J. Popp ◽

T. Erhardt ◽

H. Fischer ◽

...

Keyword(s):

Climate Changes ◽

Ice Core ◽

Ice Cores ◽

Climate System ◽

Data Availability ◽

Tight Coupling ◽

Decadal Scale ◽

Abrupt Changes ◽

Systematic Pattern ◽

The Last Glacial

AbstractData availability and temporal resolution make it challenging to unravel the anatomy (duration and temporal phasing) of the Last Glacial abrupt climate changes. Here, we address these limitations by investigating the anatomy of abrupt changes using sub-decadal-scale records from Greenland ice cores. We highlight the absence of a systematic pattern in the anatomy of abrupt changes as recorded in different ice parameters. This diversity in the sequence of changes seen in ice-core data is also observed in climate parameters derived from numerical simulations which exhibit self-sustained abrupt variability arising from internal atmosphere-ice-ocean interactions. Our analysis of two ice cores shows that the diversity of abrupt warming transitions represents variability inherent to the climate system and not archive-specific noise. Our results hint that during these abrupt events, it may not be possible to infer statistically-robust leads and lags between the different components of the climate system because of their tight coupling.

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Future Extreme Climates Projection over Huang-Huai-Hai Region of China

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.955-959.3887 ◽

2014 ◽

Vol 955-959 ◽

pp. 3887-3892 ◽

Cited By ~ 1

Author(s):

Huang He Gu ◽

Zhong Bo Yu ◽

Ji Gan Wang

Keyword(s):

Climate Changes ◽

Climate Model ◽

Regional Climate ◽

Surface Air Temperature ◽

Daily Rainfall ◽

Heavy Rain ◽

Near Surface ◽

Temperature And Precipitation ◽

Huai River ◽

The Future

This study projects the future extreme climate changes over Huang-Huai-Hai (3H) region in China using a regional climate model (RegCM4). The RegCM4 performs well in “current” climate (1970-1999) simulations by compared with the available surface station data, focusing on near-surface air temperature and precipitation. Future climate changes are evaluated based on experiments driven by European-Hamburg general climate model (ECHAM5) in A1B future scenario (2070-2099). The results show that the annual temperature increase about 3.4 °C-4.2 °C and the annual precipitation increase about 5-15% in most of 3H region at the end of 21st century. The model predicts a generally less frost days, longer growing season, more hot days, no obvious change in heat wave duration index, larger maximum five-day rainfall, more heavy rain days, and larger daily rainfall intensity. The results indicate a higher risk of floods in the future warmer climate. In addition, the consecutive dry days in Huai River Basin will increase, indicating more serve drought and floods conditions in this region.

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370: Sample Size Determination for the Regression Estimate of the Mean

Biometrics ◽

10.2307/2529236 ◽

1974 ◽

Vol 30 (4) ◽

pp. 709 ◽

Cited By ~ 2

Author(s):

Aaron Tenenbein

Keyword(s):

Sample Size ◽

Sample Size Determination ◽

Size Determination ◽

Regression Estimate ◽

The Mean

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The Probability That a Measurement Falls within a Range of Standard Deviations from an Estimate of the Mean

ISRN Applied Mathematics ◽

10.5402/2012/710806 ◽

2012 ◽

Vol 2012 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

Louis M. Houston

Keyword(s):

Confidence Interval ◽

Sample Size ◽

General Equation ◽

Sample Sizes ◽

The Mean ◽

Standard Deviations ◽

Intermediate Value ◽

Theoretical Results

We derive a general equation for the probability that a measurement falls within a range of n standard deviations from an estimate of the mean. So, we provide a format that is compatible with a confidence interval centered about the mean that is naturally independent of the sample size. The equation is derived by interpolating theoretical results for extreme sample sizes. The intermediate value of the equation is confirmed with a computational test.

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Stillbirth Rate and Weight at Birth of Quintuplets in Japan

Acta geneticae medicae et gemellologiae twin research ◽

10.1017/s0001566000002841 ◽

1989 ◽

Vol 38 (1-2) ◽

pp. 65-69 ◽

Cited By ~ 6

Author(s):

Yoko Imaizumi

Keyword(s):

Sample Size ◽

Birth Order ◽

Gestational Age ◽

Size Effects ◽

Maternal Age ◽

Small Sample Size ◽

Small Sample ◽

Stillbirth Rate ◽

The Mean

AbstractNation-wide data in Japan on births and prenatal deaths of 16 sets of quintuplets during 1974-1985 were analysed. Among the 16 sets, 3 sets were liveborn, 8 were stillborn, and 5 were mixed, with a stillbirth rate of 0.64 (51/80). Effects of sex, maternal age and birth order on the stillbirth rate were not considered because of the small sample size. Effects of gestational age and birthweight on stillbirth rate were also examined. The mean weight of the 40 quintuplet individuals was 1,048 g.

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A Pro-Environmental Method of Sample Size Determination to Predict the Quality Level of Products Considering Current Customers’ Expectations

Sustainability ◽

10.3390/su13105542 ◽

2021 ◽

Vol 13 (10) ◽

pp. 5542

Author(s):

Dominika Siwiec ◽

Andrzej Pacana

Keyword(s):

Sample Size ◽

Population Based ◽

Mean Value ◽

Sample Size Determination ◽

Quality Level ◽

High Quality ◽

Test Power ◽

The Mean ◽

Potential Customers ◽

Main Factor

The main factor that conditions the success of organizations is the development of products oriented toward customer satisfaction. An additional attribute of organizations is the use of sustainable development rules. The use of these rules and the simultaneous desire to create high-quality products encourage organizations to apply different methods to, for example, eliminate waste. This study aimed to develop a method to determine the research sample size required to predict a product’s quality level, taking into account current customers’ expectations. This method was developed by modifying a procedure to determine the research sample size as part of the calculated estimator of the mean value in the general population. Based on the concept of product sustainability development, the goal of the developed method was to determine the number of potential customers (respondents) needed to provide product requirements, which were then processed and used to predict the quality level of the product. This method was applied to simultaneously test a number of hypotheses, determine the test power, and detect statistically significant differences for several relationships of the sample sizes and the test power. This was achieved using universal hypotheses and the popular alternative-punctual (MAP) method. Testing of the proposed method showed that it was able to predict the quality level of products based on current expectations of customers.

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Sample size for postharvest quality traits of ‘Palmer’ mangoes

Revista Brasileira de Fruticultura ◽

10.1590/0100-29452021014 ◽

2021 ◽

Vol 43 (5) ◽

Author(s):

João Claudio Vilvert ◽

Sérgio Tonetto de Freitas ◽

Maria Aparecida Rodrigues Ferreira ◽

Eleonora Barbosa Santiago da Costa ◽

Edna Maria Mendes Aroucha

Keyword(s):

Sample Size ◽

Estimation Error ◽

Titratable Acidity ◽

Soluble Solids ◽

Postharvest Quality ◽

Maturity Stage ◽

Transverse Diameter ◽

Quality Traits ◽

Growing Seasons ◽

The Mean

Abstract The objective of this study was to determine the most efficient sample size required to estimate the mean of postharvest quality traits of ‘Palmer’ mangoes harvested in two growing seasons. A total of 50 mangoes were harvested at maturity stage 2, in winter (June 2020) and spring (October 2020), and evaluated for weight, length, ventral and transverse diameter, skin and pulp L*, C* and hº, dry matter, firmness, soluble solids (SS), titratable acidity (TA) and the SS/TA ratio. According to the results, the coefficient of variation (CV) of fruit quality traits ranged from 2.1% to 18.1%. The highest CV in both harvests was observed for the SS/TA ratio, while the lowest was reported for pulp hº. In order to estimate the mean of physicochemical traits of ‘Palmer’ mangoes, 12 fruits are needed in the winter and 14 in the spring, considering an estimation error of 10% and a confidence interval of 95%. TA and the SS/TA ratio required the highest sample size, while L* and hº required the lowest sample size. In conclusion, the variability was different among physicochemical traits and seasons, implying that different sample sizes are required to estimate the mean of different quality traits in different growing seasons.

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On double stage minimax-shrinkage estimator for generalized Rayleigh model

International Journal of Applied Mathematical Research ◽

10.14419/ijamr.v5i1.5553 ◽

2016 ◽

Vol 5 (1) ◽

pp. 39 ◽

Cited By ~ 1

Author(s):

Abbas Najim Salman ◽

Maymona Ameen

Keyword(s):

Sample Size ◽

Shape Parameter ◽

Mean Squared Error ◽

Scale Parameter ◽

Rayleigh Distribution ◽

Shrinkage Estimator ◽

Squared Error ◽

Expected Sample Size ◽

Generalized Rayleigh Distribution ◽

The Mean

This paper is concerned with minimax shrinkage estimator using double stage shrinkage technique for lowering the mean squared error, intended for estimate the shape parameter (a) of Generalized Rayleigh distribution in a region (R) around available prior knowledge (a0) about the actual value (a) as initial estimate in case when the scale parameter (l) is known .In situation where the experimentations are time consuming or very costly, a double stage procedure can be used to reduce the expected sample size needed to obtain the estimator.The proposed estimator is shown to have smaller mean squared error for certain choice of the shrinkage weight factor y(×) and suitable region R.Expressions for Bias, Mean squared error (MSE), Expected sample size [E (n/a, R)], Expected sample size proportion [E(n/a,R)/n], probability for avoiding the second sample and percentage of overall sample saved for the proposed estimator are derived.Numerical results and conclusions for the expressions mentioned above were displayed when the consider estimator are testimator of level of significanceD.Comparisons with the minimax estimator and with the most recent studies were made to shown the effectiveness of the proposed estimator.

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