Theil–Sen Estimator vs. Ordinary Least Squares — Trend Analysis for Selected ETCCDI Climate Indices

Chervenkov, Hristo; Slavov, Kiril

doi:10.7546/crabs.2019.01.06

Cited by 30 publications

(20 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our working group has previous, partially project-driven, experience with CIsbased analysis [4][5][6]. The present study is a natural continuation of our recent efforts, documented in [7,8].…”

Section: Introductionmentioning

confidence: 85%

“… , meaning that it can tolerate arbitrary corruption of up to 29.3 % of the input data-points without degradation of its accuracy [23]. The performance of both regression methods, LSE and TSE, for trend estimation of meteorological data is assessed in [4]. Among other findings, it is revealed that in certain cases the LSE could produce trend slope even with wrong sign.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Trend Analysis of CMIP5 Ensemble of Climate Indices over Southeast Europe with Focus on Agricultural Impacts

Chervenkov

Gadzhev

Ivanov

et al. 2020

Cybernetics and Information Technologies

Self Cite

View full text Add to dashboard Cite

Nowadays there is a strong degree of agreement that the climate change is the defining challenge of our time, which will exert influence on the ecosystems, on all branches of the international economy and on the quality of life. The analysis based on climate indices is widely used non-parametric approach for quantification of the mean state as well as extreme climate events. This study, which is continuation of our previous efforts, is dedicated to the assessment of the trend magnitude and the trend statistical significance of six temperature-based and three precipitation-based indices in projected future climate over Southeast Europe up to the end of the 21st century. The indices are computed from the bias-corrected output of five CMIP5 global models, reinforced with all four RCP emission scenarios. The model output is accessed from the section of the Inter Sectoral Impact Model Intercomparison Project in the Copernicus Data Store. The multi model ensemble medians of the temperature-based indices shows considerable increase which is consistent with the warming of the mean temperatures. These changes are statistically significant in most cases and intensify with the radiative forcing. The revealed tendencies of the precipitation-based indices are more complex when compared with temperature tendencies.

show abstract

Section: Introductionmentioning

confidence: 85%

Section: Methodsmentioning

confidence: 99%

Trend Analysis of CMIP5 Ensemble of Climate Indices over Southeast Europe with Focus on Agricultural Impacts

Chervenkov

Gadzhev

Ivanov

et al. 2020

Cybernetics and Information Technologies

Self Cite

View full text Add to dashboard Cite

show abstract

“…TS is used to compute the magnitude of the trend. It is more robust than the linear regression since it limits the influence of outliers and performs better even for the case of normally distributed data (Gujarati, 2009;Chervenkov and Slavov, 2019). According to TS method, the overall slope S Ã is the median of N values of slope S and is given by…”

Section: Theil Sen's Slope (Ts)mentioning

confidence: 99%

The impact of climate indices on precipitation variability in Baluchistan, Pakistan

Aamir

Hassan

2020

Tellus A: Dynamic Meteorology and Oceanography

View full text Add to dashboard Cite

“…The magnitude of the trend is estimated by the Theil-Sen Estimator (TSE), which is preferably used in many geophysical and engineering branches as a superior alternative of the ordinary least squares [8]. The statistical significance is analysed with the Mann-Kendall (MK) test.…”

Section: Trend Analysismentioning

confidence: 99%

Degree-Day Climatology over Central and Southeast Europe for the Period 1961-2018 – Evaluation in High Resolution

Chervenkov

Ivanov

Gadzhev

et al. 2020

Cybernetics and Information Technologies

Self Cite

View full text Add to dashboard Cite

The ongoing climate change over Central and Southeast Europe has a great potential to affect significantly the public energy demands and in particular the energy consumption in the residential heating and cooling sector. The linkage of the ambient daily extreme and mean temperatures and the energy needs for condition or heat buildings can be quantified as numerical indicators as the heating and cooling degree-days. In the present study, these indicators are calculated according the UK Met Office methodology from the daily mean and extreme temperatures, which, in turn, are computed from the output of the MESCAN-SURFEX system in the frame the FP7 UERRA project. The study, which is performed in a very high resolution, is dedicated on the analysis of the spatial patterns as well as assessment of the magnitude and statistical significance of the temporal evolution of the heating and cooling degree-days. It reveals general tendencies which are coherent with the regional climate warming, but with high spatial heterogeneities. The study confirms the essential impact of the ongoing climate change on the heating, ventilating and air-conditioning industry over Central and Southeast Europe.

show abstract

Theil–Sen Estimator vs. Ordinary Least Squares — Trend Analysis for Selected ETCCDI Climate Indices

Cited by 30 publications

References 0 publications

Trend Analysis of CMIP5 Ensemble of Climate Indices over Southeast Europe with Focus on Agricultural Impacts

Trend Analysis of CMIP5 Ensemble of Climate Indices over Southeast Europe with Focus on Agricultural Impacts

The impact of climate indices on precipitation variability in Baluchistan, Pakistan

Degree-Day Climatology over Central and Southeast Europe for the Period 1961-2018 – Evaluation in High Resolution

Contact Info

Product

Resources

About