Statistical Methods for Estimating Yield Changes Attributable to Climate Change

2019 ◽  
pp. 131-150
Author(s):  
S. Niggol Seo
Keyword(s):  
Climate Change ◽  
Statistical Methods

scholarly journals Inferences on weather extremes and weather-related disasters: a review of statistical methods

2012 ◽  
Vol 8 (1) ◽  
pp. 265-286 ◽  
Author(s):  
H. Visser ◽  
A. C. Petersen
Keyword(s):  
Climate Change ◽  
Statistical Methods ◽  
Human Impacts ◽  
Gumbel Distribution ◽  
Weather Extremes ◽  
Trend Model ◽  
Climate Reconstructions ◽  
Log Normal ◽  
Uncertainty Information ◽  
Modelling Approach

Abstract. The study of weather extremes and their impacts, such as weather-related disasters, plays an important role in research of climate change. Due to the great societal consequences of extremes – historically, now and in the future – the peer-reviewed literature on this theme has been growing enormously since the 1980s. Data sources have a wide origin, from century-long climate reconstructions from tree rings to relatively short (30 to 60 yr) databases with disaster statistics and human impacts. When scanning peer-reviewed literature on weather extremes and its impacts, it is noticeable that many different methods are used to make inferences. However, discussions on these methods are rare. Such discussions are important since a particular methodological choice might substantially influence the inferences made. A calculation of a return period of once in 500 yr, based on a normal distribution will deviate from that based on a Gumbel distribution. And the particular choice between a linear or a flexible trend model might influence inferences as well. In this article, a concise overview of statistical methods applied in the field of weather extremes and weather-related disasters is given. Methods have been evaluated as to stationarity assumptions, the choice for specific probability density functions (PDFs) and the availability of uncertainty information. As for stationarity assumptions, the outcome was that good testing is essential. Inferences on extremes may be wrong if data are assumed stationary while they are not. The same holds for the block-stationarity assumption. As for PDF choices it was found that often more than one PDF shape fits to the same data. From a simulation study the conclusion can be drawn that both the generalized extreme value (GEV) distribution and the log-normal PDF fit very well to a variety of indicators. The application of the normal and Gumbel distributions is more limited. As for uncertainty, it is advisable to test conclusions on extremes for assumptions underlying the modelling approach. Finally, it can be concluded that the coupling of individual extremes or disasters to climate change should be avoided.

Data Construction and Spatiotemporal Trend Attribution of Runoff over the African Continent (1981–2016)

2021 ◽  
Author(s):  
Fidele Karamage ◽  
Yongwei Liu ◽  
Yuanbo Liu
Keyword(s):  
Climate Change ◽  
Statistical Methods ◽  
Human Activities ◽  
Water Resource Management ◽  
Agricultural Land ◽  
Curve Number ◽  
Discharge Data ◽  
Resource Managers ◽  
Runoff Change ◽  
Natural Resource Managers

AbstractThe availability of streamflow records in Africa has been declining since the 1980s due to malfunctioning gauging stations and data collection failures. Africa also has insufficient hydrological information owing to the allocation of few resources to research efforts. Unreliable runoff datasets and large uncertainties in runoff trends due to climate change patterns and human activities are major challenges to water resource management in Africa. Therefore, this study aimed to improve runoff estimates and to assess runoff trend responses to climate change and human activities in Africa during 1981–2016. Using statistical methods, monthly gridded runoff datasets were generated for the period of 1981–2016 from a modified runoff curve number method calibrated with river discharge data from 535 gauging stations. According to the cross-validation results, the constructed runoff datasets comprised the Nash and Sutcliffe coefficients ranging from 0.5 to 1, coefficients of determination ranging from 0.5 to 1 and percent biases between ±25% for a large number of stations up to 73%, 80% and 91% of the 535 gauged catchments used as references. Analysis of runoff trend responses to climate change and human activities revealed that land cover change contributed more (72%) to the observed net runoff change (0.30%•a−1) than continental climate changes (28%). These contributions were results of cropland expansion rate of 0.46%•a−1 and a precipitation increase of 0.07%•a−1. The performance and simplicity of the statistical methods used in this study could be useful for improving runoff estimations in other regions with limited streamflow data data. The results of the current study could be important to natural resource managers and decision makers in terms of raising awareness of climate change adaptation strategies and agricultural land-use policies in Africa.

scholarly journals Inferences on weather extremes and weather-related disasters: a review of statistical methods

2011 ◽  
Vol 7 (5) ◽  
pp. 2893-2935 ◽  
Author(s):  
H. Visser ◽  
A. C. Petersen
Keyword(s):  
Climate Change ◽  
Statistical Methods ◽  
Human Impacts ◽  
Gumbel Distribution ◽  
Weather Extremes ◽  
Climate Change Research ◽  
Trend Model ◽  
Climate Reconstructions ◽  
Log Normal ◽  
Uncertainty Information

Abstract. The study of weather extremes and their impacts, such as weather-related disasters, plays an important role in climate-change research. Due to the great societal consequences of extremes – historically, now and in the future – the peer-reviewed literature on this theme has been growing enormously since the 1980s. Data sources have a wide origin, from century-long climate reconstructions from tree rings to short databases with disaster statistics and human impacts (30 to 60 yr). In scanning the peer-reviewed literature on weather extremes and impacts thereof we noticed that many different methods are used to make inferences. However, discussions on methods are rare. Such discussions are important since a particular methodological choice might substantially influence the inferences made. A calculation of a return period of once in 500 yr, based on a normal distribution will deviate from that based on a Gumbel distribution. And the particular choice between a linear or a flexible trend model might influence inferences as well. In this article we give a concise overview of statistical methods applied in the field of weather extremes and weather-related disasters. Methods have been evaluated as to stationarity assumptions, the choice for specific probability density functions (PDFs) and the availability of uncertainty information. As for stationarity we found that good testing is essential. Inferences on extremes may be wrong if data are assumed stationary while they are not. The same holds for the block-stationarity assumption. As for PDF choices we found that often more than one PDF shape fits to the same data. From a simulation study we conclude that both the generalized extreme value (GEV) distribution and the log-normal PDF fit very well to a variety of indicators. The application of the normal and Gumbel distributions is more limited. As for uncertainty it is advised to test conclusions on extremes for assumptions underlying the modeling approach. Finally, we conclude that the coupling of individual extremes or disasters to climate change should be avoided.

scholarly journals Analysis of the Hydrological Behavior of Watersheds in the Context of Climate Change (Northwestern Algeria)

2021 ◽  
pp. 143-179
Author(s):  
Halima Belarbi ◽  
Bénina Touaibia ◽  
Nadir Boumechra ◽  
Chérifa Abdelbaki ◽  
Sakina Amiar
Keyword(s):  
Climate Change ◽  
Statistical Methods ◽  
Simulation Method ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Calibration And Validation ◽  
The Cross ◽  
Monthly Runoff ◽  
Hydroclimatic Variables ◽  
Rainfall Deficits

AbstractThe aim of this work is to study the temporal evolution of the rainfall-runoff relations of four basins in northwestern Algeria: the Tafna Maritime, Isser Sikkak, downstream Mouilah and Upper Tafna basins. The adopted approach consists of analyzing hydroclimatic variables using statistical methods and testing the nonstationarity of the rainfall-runoff relation by the cross-simulation method using the GR2M model. The results of the different statistical methods applied to the series of rainfall and hydrometric variables show a decrease due to a break in stationarity detected since the mid-1970s and the beginning of the 1980s. The annual rainfall deficits reached average values of 34.6% during the period of 1941–2006 and 29.1% during the period of 1970–2010. The average annual wadi flows showed average deficits of 61.1% between 1912 and 2000 and 53.1% between 1973 and 2009. The GR2M conceptual model simulated the observed hydrographs in an acceptable manner by providing calculated runoff values in the calibration and validation periods greater or less than the observed runoff values. The application of the cross-simulation method highlighted the nonstationarity of the rainfall-runoff relations in three of the four studied basins, indicating downward trends of monthly runoff.

scholarly journals DINÂMICA CLIMATOLÓGICA E IMPACTOS DAS PRECIPITAÇÕES NO MUNICÍPIO DE PIRAPORA – NORTE DE MINAS GERAIS (1990-2016)

2020 ◽  
Vol 18 (01) ◽  
pp. 66-82
Author(s):  
Álvaro Henrique Gomes da Costa ◽  
Luis Ricardo Fernandes da Costa
Keyword(s):  
Climate Change ◽  
Environmental Management ◽  
Statistical Methods ◽  
Minas Gerais ◽  
Rainfall Data ◽  
The Other ◽  
Precipitation Trend ◽  
Water Crisis ◽  
The Past ◽  
Palabras Clave

O estudo da dinâmica climatológica se torna cada dia mais importante para entender as transformações do ambiente, pois o conhecimento pretérito permite planejar ações relacionadas à gestão e ao planejamento ambiental. Fatores como crise hídrica, mudanças climáticas, degradação em bacias hidrográficas e impactos em reservatórios de água é tema recorrente nas discussões em geografia. O presente trabalho procura analisar a dinâmica climatológica no município de Pirapora no período de 1990 a 2016. Para a efetivação da análise foram realizadas análises pluviométricas e térmicas, utilizando métodos estatísticos para a análise em climatologia. Para a pluviosidade foram coletados dados referentes à precipitação, onde se obteve a totalização das precipitações em cada ano. Após a análise foram elaborados um gráfico e um pluviograma para melhor compreensão e leitura dos dados coletados. Os resultados indicam que após aferir e correlacionar às informações de temperatura e pluviosidade é perceptível a interação no comportamento de ambos, tal como também é notável a diminuição na tendência das precipitações. Em contrapartida, há a tendência do aumento na temperatura durante o período analisado.   Palavras-chave: Climatologia. Precipitações. Minas Gerais. Pirapora.   SUMMARY The study of climatological dynamics becomes increasingly important to understand the transformations of the environment, because the past knowledge allows planning actions related to environmental management and planning. Factors such as water crisis, climate change, degradation in watersheds and impacts on water reservoirs are a recurring theme in discussions in geography. The present work seeks to analyze the climatological dynamics in the municipality of Pirapora from 1990 to 2016. For the analysis, rainfall and thermal analyzes were performed using statistical methods for the climatological analysis. For rainfall data were collected regarding precipitation, where precipitation totals were obtained each year. After the analysis, a graph and a rain chart were prepared to better understand and read the collected data. The results indicate that after gauging and correlating the temperature and rainfall information, it is noticeable the interaction in the behavior of both, as well as the decrease in precipitation trend. On the other hand, there is a tendency to increase in temperature during the analyzed period. Keywords: Climatology. Rainfall. Minas Gerais. Pirapora.   RESUMEN El estudio de la dinámica climatológica se vuelve cada vez más importante para comprender las transformaciones del medio ambiente, porque el conocimiento pasado permite acciones de planificación relacionadas con la gestión y planificación ambiental. Factores como la crisis del agua, el cambio climático, la degradación de las cuencas hidrográficas y los impactos en los reservorios de agua son un tema recurrente en las discusiones en geografía. El presente trabajo busca analizar la dinámica climatológica en el municipio de Pirapora de 1990 a 2016. Para el análisis, se realizaron análisis térmicos y de lluvia utilizando métodos estadísticos para el análisis climatológico. Para la precipitación, se recopilaron datos sobre precipitación, donde se obtuvieron totales de precipitación cada año. Después del análisis, se prepararon un gráfico y un gráfico de lluvia para comprender y leer mejor los datos recopilados. Los resultados indican que después de medir y correlacionar la información de temperatura y lluvia, se nota la interacción en el comportamiento de ambos, así como la disminución en la tendencia de precipitación. Por otro lado, hay una tendencia a aumentar la temperatura durante el período analizado. Palabras clave: Climatología. Lluvia Minas Gerais. Pirapora

scholarly journals Development of an Interface in MATLAB for Trend Analysis of Hydro-Meteorological Data

2019 ◽  
Author(s):  
J. P. Patil ◽  
A. Sarangi ◽  
D. K. Singh
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Statistical Methods ◽  
Meteorological Data ◽  
Rainfed Agriculture ◽  
Analysis Process ◽  
Mk Test ◽  
Rainfall Trends ◽  
Change Trend ◽  
Slope Estimator

This study presents an interface, ‘Climate Change Trend Analysis (CCTA)’, developed in MATLAB® environment to analyze the trends using non-parametric statistical methods, Mann-Kendall (MK) test and modified Mann-Kendall (MMK) test with Sen’s slope estimator. The interface was used to determine trend in annual and seasonal (kharif) rainfall depths in Pune district acquired from 13 observatories. The developed interface automates the trend analysis process, which can further use for detecting variability and trends in the meteorological as well as other hydrological and agricultural parameters. The observed rainfall trends during monsoon would play a significant role for rainfed agriculture in Pune district.

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