The structure of climate variability across scales

CLE Franzke, S Barbosa, R Blender… - Reviews of …, 2020 - Wiley Online Library
One of the most intriguing facets of the climate system is that it exhibits variability across all
temporal and spatial scales; pronounced examples are temperature and precipitation. The …

[PDF][PDF] Forecasting daily meteorological time series using ARIMA and regression models

M Murat, I Malinowska, M Gos… - International …, 2018 - archive.sciendo.com
The daily air temperature and precipitation time series recorded between January 1, 1980
and December 31, 2010 in four European sites (Jokioinen, Dikopshof, Lleida and Lublin) …

DFNet: Decomposition fusion model for long sequence time-series forecasting

F Zhang, T Guo, H Wang - Knowledge-Based Systems, 2023 - Elsevier
The study of time series forecasting is of great significance, particularly as accurate
forecasting under long time-series is critical to data-driven decision-making. Although …

Impact of spatial soil and climate input data aggregation on regional yield simulations

H Hoffmann, G Zhao, S Asseng, M Bindi, C Biernath… - PloS one, 2016 - journals.plos.org
We show the error in water-limited yields simulated by crop models which is associated with
spatially aggregated soil and climate input data. Crop simulations at large scales (regional …

A modified multifractal detrended fluctuation analysis (MFDFA) approach for multifractal analysis of precipitation

JLM Martínez, I Segovia-Domínguez… - Physica A: Statistical …, 2021 - Elsevier
Abstract Multifractal Detrended Fluctuation Analysis (MFDFA) is an efficient method to
investigate the long-term correlations of the power law of non-stationary time series, in which …

A modified multifractal detrended fluctuation analysis (MFDFA) approach for multifractal analysis of precipitation in dongting lake basin, China

X Zhang, G Zhang, L Qiu, B Zhang, Y Sun, Z Gui… - Water, 2019 - mdpi.com
Multifractal detrended fluctuation analysis (MFDFA) method can examine higher-
dimensional fractal and multifractal characteristics hidden in time series. However, removal …

Nonlinear dynamics and multifractal analysis of minimum–maximum temperature and solar radiation over Lagos State, Nigeria

J Akinsusi, S Ogunjo, I Fuwape - Acta Geophysica, 2022 - Springer
This study focuses on investigating the chaotic and multifractal behavior of atmospheric time
series of solar radiation (solar), maximum temperature (Tmax), and minimum temperature …

Multifractal characterization and comparison of meteorological time series from two climatic zones

J Krzyszczak, P Baranowski, M Zubik… - Theoretical and Applied …, 2019 - Springer
The results of the multifractal analysis performed for meteorological time series coming from
four stations in Poland and Bulgaria located in varying climatic zones are presented. To …

[HTML][HTML] Multifractal fluctuations of the precipitation in Spain (1960–2019)

J Gómez-Gómez, R Carmona-Cabezas… - Chaos, Solitons & …, 2022 - Elsevier
In this work, an analysis of multifractal parameters of daily precipitation series over the
Iberian Peninsula was performed in two 30-year periods to explore whether these properties …

Multifractal characterization of meteorological drought in India using detrended fluctuation analysis

S Adarsh, DN Kumar, B Deepthi… - International Journal …, 2019 - Wiley Online Library
This study presents multifractal detrended fluctuation analysis (MF‐DFA) to describe the
multifractality of Standardized Precipitation Index (SPI) series from 30 meteorological …