scholarly journals Long Term Rainfall Trend Analysis of Different Time Series in Solapur District of Maharashtra, India

2019 ◽  
Vol 8 (12) ◽  
pp. 2359-2367
Author(s):  
J. K. Joshi ◽  
S. K. Upadhye ◽  
D. D. More
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Rainfall Trend

scholarly journals Comparison of Statistical Methods to Graphical Methods in Rainfall Trend Analysis: Case Studies from Tropical Catchments

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Upaka Rathnayake
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Climatic Factors ◽  
Data Series ◽  
Graphical Methods ◽  
Rainfall Trend ◽  
Comparison Analysis ◽  
Analysis Techniques ◽  
Rainfall Trends ◽  
Time Series Analyses

Time series analyses for climatic factors are important in climate predictions. Rainfall is being one of the most important climatic factors in today’s concern for future predictions; thus, many researchers analyze the data series for identifying potential rainfall trends. The literature shows several methods in identifying rainfall trends. However, statistical trend analysis using Mann–Kendall equation and graphical trend analysis are the two widely used and simplest tests in trend analysis. Nevertheless, there are few studies in comparing various methods in the trend analysis to suggest the simplest methods in analyzing rainfall trends. Therefore, this paper presents a comparison analysis of statistical and graphical trend analysis techniques for two tropical catchments in Sri Lanka. Results reveal that, in general, both trend analysis techniques produce comparable results in identifying rainfall trends for different time steps including annual, seasonal, and monthly rainfalls.

Long-term prediction of karst water recovery process based on two different approaches in a former mining area, Transdanubian Range, Hungary

2020 ◽  
Author(s):  
Kamilla Modrovits ◽  
András Csepregi ◽  
József Kovács
Keyword(s):  
Time Series ◽  
Water Level ◽  
Trend Analysis ◽  
Recovery Process ◽  
Karst Water ◽  
Deterministic Approach ◽  
Term Prediction ◽  
Transdanubian Range ◽  
Long Term Prediction

<p>The Transdanubian Range is located in the mid-western part of Hungary and contains Mesozoic, mainly Triassic formations with the total thickness of 1.5-2 km. From 1950 to 1990 coal and bauxite mining took place with different centres in this area, therefor large amount of karst water was extracted for preventative purpose. Thus, the water levels decreased from ten to more than a hundred of meters. Since the mining was stopped in the beginning of the 1990s, the natural recharge exceeded the amount of extraction and the recovery of the karst water began. Since then the system is on the way to return to its original – undisturbed – state. Because of the rising water level, economic and technical engineering problems have occurred, which requires the better understanding of the process.</p><p>Water level changes are often predicted with a deterministic approach using different modelling software (e.g. MODFLOW, FEFLOW, etc.). However, stochastic approaches (e.g. trend estimation), which have so far been little used in forecast of groundwater, can also be applied for certain hydrogeological problems. The aims of the research were (i) to find the most accurate trend function describing the recovery process (ii) in order to make a long-term prediction, (iii) and compare the results with the results deterministic modelling. For this purpose, decades of time series from 107 monitoring wells were investigated.</p><p>As a result of the research, it was identified that the karst water time series from the Transdanubian Range can be properly estimated (R<sup>2</sup> > 0.9 in the 82.24% of the cases) by growth and logistic curves, especially by the so-called Richards and “63%” ones. These curves gave the best fit in 57.95% of the cases based on the R<sup>2</sup> value obtained by fitting the 10 examined models. Both the deterministic approach modelling (MODFLOW) and the stochastic approach trend analysis are suitable for estimating and predicting the water level rise in the karst aquifer, but the results are slightly different. Modelling with the MODFLOW software can be affected by the accuracy of input parameters (infiltration, yield of springs, etc.) and the realness of the conceptual model. First and foremost, more and better-quality water level data series are needed for trend analysis, and based on our prior knowledge, it is essential to provide an accurate expected maximum water level (upper limit). The comparison of the two methods unveiled, that growth and logistic curves can also be successfully used in the prediction of groundwater levels. As a conclusion, the number of methods which may be used for such research can be expanded.</p><p>This research is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 810980.</p>

scholarly journals Multidecadal trend analysis of aerosol radiative properties at a global scale

2020 ◽  
Author(s):  
Martine Collaud Coen ◽  
Elisabeth Andrews ◽  
Cathrine Lund Myhre ◽  
Jenny Hand ◽  
Marco Pandolfi ◽  
...  
Keyword(s):  
Time Series ◽  
North America ◽  
Trend Analysis ◽  
Single Scattering ◽  
Single Scattering Albedo ◽  
Radiative Properties ◽  
Least Mean Square ◽  
Long Term Trend ◽  
Aerosol Radiative

<p>In order to assess the global evolution of aerosol parameters affecting climate change, a long-term trend analyses of aerosol optical properties were performed on time series from 52 stations situated across five continents. The time series of measured scattering, backscattering and absorption coefficients as well as the derived single scattering albedo, backscattering fraction, scattering and absorption Ångström exponents covered at least 10 years and up to 40 years for some stations. The non-parametric seasonal Mann-Kendall (MK) statistical test associated with several prewhitening methods and with the Sen’s slope were used as main trend analysis methods. Comparisons with General Least Mean Square associated with Autoregressive Bootstrap (GLS/ARB) and with standard Least Mean Square analysis (LMS) enabled confirmation of the detected MK statistically significant trends and the assessment of advantages and limitations of each method. Currently, scattering and backscattering coefficients trends are mostly decreasing in Europe and North America and are not statistically significant in Asia, while polar stations exhibit a mix of increasing and decreasing trends. A few increasing trends are also found at some stations in North America and Australia. Absorption coefficients time series also exhibit primarily decreasing trends. For single scattering albedo, 52% of the sites exhibit statistically significant positive trends, mostly in Asia, Eastern/Northern Europe and Arctic, 18% of sites exhibit statistically significant negative trends, mostly in central Europe and central North America, while the remaining 30% of sites have trends, which are not statistically significant. In addition to evaluating trends for the overall time series, the evolution of the trends in sequential 10 year segments was also analyzed. For scattering and backscattering, statistically significant increasing 10 year trends are primarily found for earlier periods (10 year trends ending in 2010-2015) for polar stations and Mauna Loa. For most of the stations, the present-day statistically significant decreasing 10 year trends of the single scattering albedo were preceded by not statistically significant and statistically significant increasing 10 year trends. The effect of air pollution abatement policies in continental North America is very obvious in the 10 year trends of the scattering coefficient – there is a shift to statistically significant negative trends in 2010-2011 for all stations in the eastern and central US. This long-term trend analysis of aerosol radiative properties with a broad spatial coverage enables a better global view of potential aerosol effects on climate changes.</p>

scholarly journals Multidecadal trend analysis of aerosol radiative properties at a global scale

2020 ◽  
Author(s):  
Martine Collaud Coen ◽  
Elisabeth Andrews ◽  
Andrés Alastuey ◽  
Todor Petkov Arsov ◽  
John Backman ◽  
...  
Keyword(s):  
Time Series ◽  
North America ◽  
Trend Analysis ◽  
Single Scattering ◽  
Single Scattering Albedo ◽  
Radiative Properties ◽  
Least Mean Square ◽  
Long Term Trend ◽  
Aerosol Radiative

Abstract. In order to assess the global evolution of aerosol parameters affecting climate change, a long-term trend analyses of aerosol optical properties were performed on time series from 52 stations situated across five continents. The time series of measured scattering, backscattering and absorption coefficients as well as the derived single scattering albedo, backscattering fraction, scattering and absorption Ångström exponents covered at least 10 years and up to 40 years for some stations. The non-parametric seasonal Mann–Kendall (MK) statistical test associated with several prewhitening methods and with the Sen's slope were used as main trend analysis methods. Comparisons with General Least Mean Square associated with Autoregressive Bootstrap (GLS/ARB) and with standard Least Mean Square analysis (LMS) enabled confirmation of the detected MK statistically significant trends and the assessment of advantages and limitations of each method. Currently, scattering and backscattering coefficients trends are mostly decreasing in Europe and North America and are not statistically significant in Asia, while polar stations exhibit a mix of increasing and decreasing trends. A few increasing trends are also found at some stations in North America and Australia. Absorption coefficients time series also exhibit primarily decreasing trends. For single scattering albedo, 52 % of the sites exhibit statistically significant positive trends, mostly in Asia, Eastern/Northern Europe and Arctic, 18 % of sites exhibit statistically significant negative trends, mostly in central Europe and central North America, while the remaining 30 % of sites have trends, which are not statistically significant. In addition to evaluating trends for the overall time series, the evolution of the trends in sequential 10 year segments was also analyzed. For scattering and backscattering, statistically significant increasing 10 year trends are primarily found for earlier periods (10 year trends ending in 2010–2015) for polar stations and Mauna Loa. For most of the stations, the present-day statistically significant decreasing 10 year trends of the single scattering albedo were preceded by not statistically significant and statistically significant increasing 10 year trends. The effect of air pollution abatement policies in continental North America is very obvious in the 10 year trends of the scattering coefficient – there is a shift to statistically significant negative trends in 2010–2011 for all stations in the eastern and central US. This long-term trend analysis of aerosol radiative properties with a broad spatial coverage enables a better global view of potential aerosol effects on climate changes.

scholarly journals Long-term trend analysis of rainfall using hybrid Discrete Wavelet Transform (DWT) based Mann-Kendall tests in central Gujarat region, India

MAUSAM ◽  
2021 ◽  
Vol 71 (2) ◽  
pp. 209-224
Author(s):  
RAJANI NIRAV V ◽  
TIWARI MUKESH K ◽  
CHINCHORKAR S S
Keyword(s):  
Time Series ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Trend Analysis ◽  
Time Scales ◽  
Series Data ◽  
Trend Test ◽  
Discrete Wavelet ◽  
Rainfall Time Series

Trend analysis has become one of the most important issues in hydro-meteorological variables study due to climate change and the focus given to it in the recent past from the scientific community. In this study, long-term trends of rainfall are analyzed in eight stations located in semi-arid central Gujarat region, India by considering time series data of 116 years (1901-2016). Discrete wavelet transform (DWT) as a dyadic arrangement of continuous wavelet transformation combined with the widely applied and acknowledged Mann-Kendall (MK) trend analysis method were applied for analysis of trend and dominant periodicities in rainfall time series at monthly, annual and monsoonal time scales. Initially, rainfall time series applied in this study were decomposed using DWT to generate sub-time series at high and low frequencies, before applying the MK trend test. Further, the Sequential Mann-Kendall (SQMK) test was also applied to find out the trend changing points. The result showed that at the monthly annual and monsoon time scales, the trends in rainfall were significantly decreasing in most of the station. The 4-month and 8-month components were found as dominant at the monthly time series and the 2-year and 4-year component were found as dominant at the monsoon time series, whereas the 2-year components were observed as dominant in the annual time scale.

scholarly journals Trend analysis of the 20 years time series of stratospheric ozone profiles observed by the GROMOS microwave radiometer at Bern

2015 ◽  
Vol 15 (12) ◽  
pp. 16371-16400
Author(s):  
L. Moreira ◽  
K. Hocke ◽  
E. Eckert ◽  
T. von Clarmann ◽  
N. Kämpfer
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Southern Oscillation ◽  
Stratospheric Ozone ◽  
Microwave Radiometer ◽  
Atmospheric Composition ◽  
Quasi Biennial Oscillation ◽  
Ozone Trend ◽  
Long Term Trend

Abstract. The ozone radiometer GROMOS (GROund-based Millimeterwave Ozone Spectrometer) performs continuous observations of stratospheric ozone profiles since 1994 above Bern, Switzerland. GROMOS is part of the Network for the Detection of Atmospheric Composition Change (NDACC). From November 1994 to October 2011, the ozone line spectra were measured by a filter bench (FB). In July 2009, a Fast-Fourier-Transform spectrometer (FFTS) has been added as backend to GROMOS. The new FFTS and the original FB measured in parallel for over two years. The ozone profiles retrieved separately from the ozone line spectra of FB and FFTS agree within 5 % at pressure levels from 30 to 0.5 hPa, from October 2009 to August 2011. A careful harmonisation of both time series has been carried out by taking the FFTS as the reference instrument for the FB. This enables us to assess the long-term trend derived from more than 20 years of stratospheric ozone observations at Bern. The trend analysis has been performed by using a robust multilinear parametric trend model which includes a linear term, the solar variability, the El Niño–Southern Oscillation (ENSO) index, the quasi-biennial oscillation (QBO), the annual and semi-annual oscillation and several harmonics with period lengths between 3 and 24 months. Over the last years, some experimental and modelling trend studies have shown that the stratospheric ozone trend is levelling off or even turning positive. With our observed ozone profiles, we are able to support this statement by reporting a statistically significant trend of +3.14 % decade-1 at 4.36 hPa, covering the period from January 1997 to January 2015, above Bern. Additionally, we have estimated a negative trend over this period of −3.94 % decade-1 at 0.2 hPa.

scholarly journals Diurnal cycle and multi-decadal trend of formaldehyde in the remote atmosphere near 46° N

2016 ◽  
Vol 16 (6) ◽  
pp. 4171-4189 ◽  
Author(s):  
Bruno Franco ◽  
Eloise A. Marais ◽  
Benoît Bovy ◽  
Whitney Bader ◽  
Bernard Lejeune ◽  
...  
Keyword(s):  
Time Series ◽  
Trend Analysis ◽  
Diurnal Cycle ◽  
Transport Model ◽  
Parametric Model ◽  
Swiss Alps ◽  
Chemical Transport Model ◽  
Ch4 Oxidation ◽  
Short Term

Abstract. Only very few long-term records of formaldehyde (HCHO) exist that are suitable for trend analysis. Furthermore, many uncertainties remain as to its diurnal cycle, representing a large short-term variability superimposed on seasonal and inter-annual variations that should be accounted for when comparing ground-based observations to, e.g., model results. In this study, we derive a multi-decadal time series (January 1988–June 2015) of HCHO total columns from ground-based high-resolution Fourier transform infrared (FTIR) solar spectra recorded at the high-altitude station of Jungfraujoch (Swiss Alps, 46.5° N, 8.0° E, 3580 m a. s. l. ), allowing for the characterization of the mid-latitudinal atmosphere for background conditions. First we investigate the HCHO diurnal variation, peaking around noontime and mainly driven by the intra-day insolation modulation and methane (CH4) oxidation. We also characterize quantitatively the diurnal cycles by adjusting a parametric model to the observations, which links the daytime to the HCHO columns according to the monthly intra-day regimes. It is then employed to scale all the individual FTIR measurements on a given daytime in order to remove the effect of the intra-day modulation for improving the trend determination and the comparison with HCHO columns simulated by the state-of-the-art GEOS-Chem v9-02 chemical transport model. Such a parametric model will be useful to scale the Jungfraujoch HCHO columns on satellite overpass times in the framework of future calibration/validation efforts of space-borne sensors. GEOS-Chem sensitivity tests suggest then that the seasonal and inter-annual HCHO column variations above Jungfraujoch are predominantly led by the atmospheric CH4 oxidation, with a maximum contribution of 25 % from the anthropogenic non-methane volatile organic compound precursors during wintertime. Finally, trend analysis of the so-scaled 27-year FTIR time series reveals a long-term evolution of the HCHO columns in the remote troposphere to be related to the atmospheric CH4 fluctuations and the short-term OH variability: +2.9 % year−1 between 1988 and 1995, −3.7 % year−1 over 1996–2002 and +0.8 % year−1 from 2003 onwards.

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