Trends and Interannual Variability of Extreme Rainfall Indices over Cameroon

Central African citizens are highly vulnerable to extreme hydroclimatic events due to excess precipitation or to dry spells. This study makes use of CHIRPS precipitation data gridded at 0.05° × 0.05° resolution and extended from 1981 to 2019 to analyze spatial variabilities and trends of six extreme precipitation indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) over Cameroon. They are the number of wet days (RR1), the simple daily intensity index (SDII), the annual total precipitation from days greater than the 95th percentile (R95ptot), the maximum number of consecutive wet days (CWD), the maximum number of consecutive dry days (CDD), the number of very heavy rainfall (RR20). The standard precipitation index (SPI) time series were also examined in the five agro-climatic regions of the domain. The pattern of annual precipitation was first checked over the entire domain. We obtain a well-known pattern showing a decreased precipitation northward with the highest values around the Atlantic Ocean coast. The analysis shows that all indices represent patterns approximately similar to that of annual rainfall except CDD where the spatial south-north gradient is reversed. RR20 shows the lowest spatial variability. Trend study of RR1 indicates negative values south of the domain and predominated positive values in the northern part, where CDD, on the contrary, shows a decreased trend. The highest trends are observed in the northernmost area for CWD and around the coast for SDII and R95ptot. SPI time series indicate an alternative dry and wet period and the years between 1990 and 2000 witnessed more annual wet conditions. Such a study is very important in this domain where variabilities of climatic components are very high due to climate change impact and diversified relief. The results can serve as a reference for agricultural activity, hydropower management, civil engineering, planning of economic activities and can contribute to the understanding of the climate system in Cameroon.

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Tendências em índices extremos de precipitação em Cabaceiras (PB) para períodos distintos

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v13.1.p271-285 ◽

2020 ◽

Vol 13 (1) ◽

pp. 271

Author(s):

Rafaela Lisboa Costa ◽

Heliofábio Barros Gomes ◽

Fabrício Daniel Dos Santos Silva ◽

Rodrigo Lins Da Rocha Júnior ◽

Giuliene Carla Dos Santos Silva ◽

...

Keyword(s):

Climate Change ◽

Time Series ◽

Change Detection ◽

Annual Rainfall ◽

Positive Trend ◽

Total Period ◽

Significant Positive Trend ◽

Total Length ◽

Expert Team ◽

Climate Change Detection

Este trabalho teve como objetivo aplicar e estudar 11 índices de extremos de precipitação formulados pelo ETCCDI (Expert Team on Climate Change Detection and Indices, www.clivar.org/organization/etccdi), para a cidade de Cabaceiras-PB, utilizando dados diários de precipitação contínuos de 90 anos. Os índices foram calculados para o comprimento total da série, 1928 a 2017, assim como para três segmentos de 30 anos (1928-1957, 1958-1987 e 1988-2017). Os resultados evidenciaram que para muitos índices, tendências opostas e estatisticamente significativas podem ser observadas a depender do subperíodo estudado, assim como haver diferença entre estas tendências e as obtidas ao analisar-se o período total dos dados. Exemplos disso aconteceram para os índices R1mm, R10mm, R20mm, CWD e PRCPTOT. Trends in extreme precipitation indexes in Cabaceiras (PB) for different periods A B S T R A C TThis work aimed to apply and analyze 11 precipitation extremes indexes formulated by ETCCDI (Expert Team on Climate Change Detection and Indices, www.clivar.org/organization/etccdi), for the city of Cabaceiras, located in the Borborema mesoregion and microregion of Paraíba Oriental Cariri. A municipality in the semiarid region, it has the title of municipality where it rains less in Brazil, with an annual average of just over 300mm. Daily 90-year continuous precipitation data were used for the extreme indices, with the time series analyzed for four distinct periods, the total length of the series, 1928 to 2017, as well as three 30-year segments (1928-1957, 1958- 1987 and 1988-2017). The results showed that for many indices, opposite and significant trends can be observed depending on the sub period studied, as well as differences between these trends and those obtained by analyzing the total data period. The R1, R10 and R20mm indices show significant negative trends in the 1928-1957 sub period, but positive in the following two sub periods, reflecting a significant positive trend in the total period from 1928 to 2017. Other interesting examples are CDD indices for consecutive dry days, and PRCPTOT, for total annual rainfall with rainfall greater than 1mm. The CDD showed significant positive trend only in the 1928-1957 sub period, but non-significant negative trends in the subsequent sub periods, reflecting non-significant negative trends in the total length of the series. The PRCPTOT index shows behavior opposite to the CDD index, with a significant negative trend in the 1928-1957 sub period, positive in 1958-1987 and negative again in 1988-2017, but for the total length of the series the trend is positive and significant. These results show that the analysis of extreme trends is noticeably sensitive to the sample of the analyzed period, and may not reflect the reality of the time series the longer the total length of the time series, and need to be used with caution.Keywords: climate variability, dry and wet periods, semiarid.

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Interannual Variability and Trends of Extreme Rainfall Indices over Benin

Climate ◽

10.3390/cli9110160 ◽

2021 ◽

Vol 9 (11) ◽

pp. 160

Author(s):

Ezéchiel Obada ◽

Eric Adechina Alamou ◽

Eliezer Iboukoun Biao ◽

Esdras B. Josué Zandagba

Keyword(s):

Human Life ◽

Extreme Rainfall ◽

Adaptive Strategies ◽

Waterborne Diseases ◽

Intensity Index ◽

Expert Team ◽

Annual Total ◽

Extreme Precipitation Indices ◽

Precipitation Indices ◽

Simple Daily Intensity Index

Observed rainfall data (1961–2016) were used to analyze variability, trends and changes of extreme precipitation indices over Benin. Nine indices out of the ones developed by the Expert Team on Climate Change Detection and Indices (ETCCDI) were used. The results indicate a mix of downward and upward trends for maximum 1-day precipitation (RX1day) and maximum 5-days precipitation (RX5day). Decrease trends are observed for annual total precipitation of wet days (P), while significant increases are found for the simple daily intensity index (SDII). The number of wet days (RR1) and maximum consecutive dry days (CDD) show a mix of increase/decrease trends. However, the number of heavy (R10) and very heavy (R20) wet days and maximum consecutive wet days (CWD) show decreased trends. All wet indices increased over 1991–2010 in relation to 1971–1990. The increase in all wet indices over Benin could explain the intensification of hydrology, and the increase in the frequency and the intensity of floods. It caused damages such as soil erosion, crop destruction, livestock destruction, displacement of populations, proliferation of waterborne diseases and loss of human life. Some adaptive strategies are suggested to mitigate the impacts of changes in extreme rainfall.

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Are Soybean Yields Getting a Free Ride From Climate Change? Evidence From Argentine Time Series

10.20944/preprints201811.0387.v1 ◽

2018 ◽

Author(s):

Hildegart Ahumada ◽

Magdalena Cornejo

Keyword(s):

Climate Change ◽

Time Series ◽

Extreme Rainfall ◽

Co2 Concentration ◽

Interesting Case ◽

Extreme Rainfall Events ◽

Beneficial Effects ◽

Positive Effects ◽

Long Run ◽

Equilibrium Correction

Soybean yields are often indicated as an interesting case of climate change mitigation due to the beneficial effects of CO2 fertilization. In this paper we econometrically study this effect using a time series model of yields in a multivariate framework for a main producer and exporter of this commodity, Argentina. We have to deal with the upward behavior of soybean yields trying to identify which variables are the long-run determinants responsible of its observed trend. With this aim we adopt a partial system approach to estimate subsets of long-run relationships due to climate, technological and economic factors. Using an automatic selection algorithm we evaluate encompassing of the different obtained equilibrium correction models. We found that only technological innovations due to new crop practices and the use of modified seeds explain soybean yield in the long run. Regarding short run determinants we found positive effects associated with the use of standard fertilizers and also from changes in atmospheric CO2 concentration which would suggest a mitigation effect from global warming. However, we also found negative climate effects from periods of droughts associated with La Niña episodes, high temperatures and extreme rainfall events during the growing season of the plant.

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An Evaluation of the Statistics of Rainfall Extremes in Rain Gauge Observations, and Satellite-Based and Reanalysis Products Using Universal Multifractals

Journal of Hydrometeorology ◽

10.1175/2009jhm1142.1 ◽

2010 ◽

Vol 11 (2) ◽

pp. 388-404 ◽

Cited By ~ 29

Author(s):

Xiaoming Sun ◽

Ana P. Barros

Keyword(s):

Time Series ◽

Extreme Rainfall ◽

Global Precipitation Climatology Project ◽

Rain Gauge ◽

Climatic Data ◽

Statistics Of Extremes ◽

Maximum Rainfall ◽

Climatic Regions ◽

National Climatic Data Center ◽

Rainfall Extremes

Abstract Confidence in the estimation of variations in the frequency of extreme events, and specifically extreme precipitation, in response to climate variability and change is key to the development of adaptation strategies. One challenge to establishing a statistical baseline of rainfall extremes is the disparity among the types of datasets (observations versus model simulations) and their specific spatial and temporal resolutions. In this context, a multifractal framework was applied to three distinct types of rainfall data to assess the statistical differences among time series corresponding to individual rain gauge measurements alone—National Climatic Data Center (NCDC), model-based reanalysis [North America Regional Reanalysis (NARR) grid points], and satellite-based precipitation products [Global Precipitation Climatology Project (GPCP) pixels]—for the western United States (west of 105°W). Multifractal analysis provides general objective metrics that are especially adept at describing the statistics of extremes of time series. This study shows that, as expected, multifractal parameters estimated from the NCDC rain gauge dataset map the geography of known hydrometeorological phenomena in the major climatic regions, including the strong orographic gradients from west to east; whereas the NARR parameters reproduce the spatial patterns of NCDC parameters, but the frequency of large rainfall events, the magnitude of maximum rainfall, and the mean intermittency are underestimated. That is, the statistics of the NARR climatology suggest milder extremes than those derived from rain gauge measurements. The spatial distributions of GPCP parameters closely match the NCDC parameters over arid and semiarid regions (i.e., the Southwest), but there are large discrepancies in all parameters in the midlatitudes above 40°N because of reduced sampling. This study provides an alternative independent backdrop to benchmark the use of reanalysis products and satellite datasets to assess the effect of climate change on extreme rainfall.

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Describing the interannual variability of precipitation with the derived distribution approach: effects of record length and resolution

Hydrology and Earth System Sciences ◽

10.5194/hess-20-4177-2016 ◽

2016 ◽

Vol 20 (10) ◽

pp. 4177-4190 ◽

Cited By ~ 2

Author(s):

Claudio I. Meier ◽

Jorge Sebastián Moraga ◽

Geri Pranzini ◽

Peter Molnar

Keyword(s):

Time Series ◽

Interannual Variability ◽

Lognormal Distribution ◽

Traditional Approach ◽

Probability Model ◽

Extreme Rainfall ◽

Annual Precipitation ◽

Annual Rainfall ◽

Precipitation Data ◽

Record Length

Abstract. Interannual variability of precipitation is traditionally described by fitting a probability model to yearly precipitation totals. There are three potential problems with this approach: a long record (at least 25–30 years) is required in order to fit the model, years with missing rainfall data cannot be used, and the data need to be homogeneous, i.e., one has to assume stationarity. To overcome some of these limitations, we test an alternative methodology proposed by Eagleson (1978), based on the derived distribution (DD) approach. It allows estimation of the probability density function (pdf) of annual rainfall without requiring long records, provided that continuously gauged precipitation data are available to derive external storm properties. The DD approach combines marginal pdfs for storm depths and inter-arrival times to obtain an analytical formulation of the distribution of annual precipitation, under the simplifying assumptions of independence between events and independence between storm depth and time to the next storm. Because it is based on information about storms and not on annual totals, the DD can make use of information from years with incomplete data; more importantly, only a few years of rainfall measurements should suffice to estimate the parameters of the marginal pdfs, at least at locations where it rains with some regularity. For two temperate locations in different climates (Concepción, Chile, and Lugano, Switzerland), we randomly resample shortened time series to evaluate in detail the effects of record length on the DD, comparing the results with the traditional approach of fitting a normal (or lognormal) distribution. Then, at the same two stations, we assess the biases introduced in the DD when using daily totalized rainfall, instead of continuously gauged data. Finally, for randomly selected periods between 3 and 15 years in length, we conduct full blind tests at 52 high-quality gauging stations in Switzerland, analyzing the ability of the DD to estimate the long-term standard deviation of annual rainfall, as compared to direct computation from the sample of annual totals. Our results show that, as compared to the fitting of a normal or lognormal distribution (or equivalently, direct estimation of the sample moments), the DD approach reduces the uncertainty in annual precipitation estimates (especially interannual variability) when only short records (below 6–8 years) are available. In such cases, it also reduces the bias in annual precipitation quantiles with high return periods. We demonstrate that using precipitation data aggregated every 24 h, as commonly available at most weather stations, introduces a noticeable bias in the DD. These results point to the tangible benefits of installing high-resolution (hourly, at least) precipitation gauges, next to the customary, manual rain-measuring instrument, at previously ungauged locations. We propose that the DD approach is a suitable tool for the statistical description and study of annual rainfall, not only when short records are available, but also when dealing with nonstationary time series of precipitation. Finally, to avert any misinterpretation of the presented method, we should like to emphasize that it only applies for climatic analyses of annual precipitation totals; even though storm data are used, there is no relation to the study of extreme rainfall intensities needed for engineering design.

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Analýza vybraných indikátorov hodnotenia zmeny klímy na území SR (pre účely podpory rozvoja záchranných služieb)

Krízový manažment ◽

10.26552/krm.c.2021.2.16-24 ◽

2021 ◽

Vol 20 (2) ◽

pp. 16-24

Author(s):

Iveta Marková ◽

◽

Mikuláš Monoši

Keyword(s):

Climate Change ◽

Time Series ◽

Air Temperature ◽

Drought Index ◽

Slovak Republic ◽

Atmospheric Precipitation ◽

Annual Total ◽

State Of The Environment ◽

Climatic Elements

The development of climate change is evaluated based on trends in long-term time series (1951 - 2018) of individual climatic elements, comparing values of individual years with the standard period in climatology 1961 - 1990 (SAŽP, 2019). The aim of the article is to evaluate climate elements, namely the production of greenhouse gases, average annual air temperature, annual total atmospheric precipitation, drought index and annual soil temperature (soil index). Data presented in the article are obtained from public reports on the state of the environment in the Slovak Republic and other related documents. In 1881 - 2018, Slovakia underwent significant changes in all monitored climatic elements. The most crucial changes occurred in 2017 and 2018.

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Spatio-temporal Variability and Trends of Mean and Extreme Rainfall Events in the Sudano-sahelian Region of Cameroon

10.21203/rs.3.rs-848441/v1 ◽

2021 ◽

Author(s):

Ibrahim NJOUENWET ◽

Lucie A. Djiotang Tchotchou ◽

Brian Odhiambo Ayugi ◽

Guy Merlin Guenang ◽

Derbetini A. Vondou ◽

...

Keyword(s):

Climate Change ◽

Extreme Rainfall ◽

Temporal Variations ◽

Annual Rainfall ◽

Drought Risk ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Precipitation Concentration ◽

Spatio Temporal ◽

The Impact

Abstract The Sudano-Sahelian region of Cameroon is mainly drained by the Benue, Chari and Logone rivers, which are very useful for water resources, especially for irrigation, hydropower generation, and navigation. Long-term changes in mean and extreme rainfall events in the region may be of crucial importance in understanding the impact of climate change. Daily and monthly rainfall data from twenty-five synoptic stations in the study area from 1980 to 2019 and extreme indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) measurements were estimated using the non-parametric Modified Mann-Kendall test and the Sen slope estimator. The precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP) were used to explore the spatio-temporal variations in the characteristics of rainfall concentrations. An increase in extreme rainfall events was observed, leading to an upward trend in mean annual. Trends in consecutive dry days (CDD) are significantly increasing in most parts of the study area. This could mean that the prevalence of drought risk is higher in the study area. Overall, the increase in annual rainfall could benefit the hydro-power sector, agricultural irrigation, the availability of potable water sources, and food security.

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Spatio-Temporal Trend Analysis of Rainfall and Temperature Extremes in the Vea Catchment, Ghana

Climate ◽

10.3390/cli6040087 ◽

2018 ◽

Vol 6 (4) ◽

pp. 87 ◽

Cited By ~ 7

Author(s):

Isaac Larbi ◽

Fabien Hountondji ◽

Thompson Annor ◽

Wilson Agyare ◽

John Mwangi Gathenya ◽

...

Keyword(s):

Climate Change ◽

Extreme Rainfall ◽

Warming Trend ◽

Trend Detection ◽

Annual Rainfall ◽

Annual Number ◽

Temperature Extremes ◽

Distribution Analysis ◽

Mk Test ◽

Seasonal Correlation

This study examined the trends in annual rainfall and temperature extremes over the Vea catchment for the period 1985–2016, using quality-controlled stations and a high resolution (5 km) Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data. The CHIRPS gridded precipitation data’s ability in reproducing the climatology of the catchment was evaluated. The extreme rainfall and temperature indices were computed using a RClimdex package by considering seventeen (17) climate change indices from the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). Trend detection and quantification in the rainfall (frequency and intensity) and temperature extreme indices were analyzed using the non-parametric Mann–Kendall (MK) test and Sen’s slope estimator. The results show a very high seasonal correlation coefficient (r = 0.99), Nash–Sutcliff efficiency (0.98) and percentage bias (4.4% and −8.1%) between the stations and the gridded data. An investigation of dry and wet years using Standardized Anomaly Index shows 45.5% frequency of drier than normal periods compared to 54.5% wetter than normal periods in the catchment with 1999 and 2003 been extremely wet years while the year 1990 and 2013 were extremely dry. The intensity and magnitude of extreme rainfall indices show a decreasing trend for more than 78% of the rainfall locations while positive trends were observed in the frequency of extreme rainfall indices (R10mm, R20mm, and CDD) with the exception of consecutive wet days (CWD) that shows a decreasing trend. A general warming trend over the catchment was observed through the increase in the annual number of warm days (TX90p), warm nights (TN90p) and warm spells (WSDI). The spatial distribution analysis shows a high frequency and intensity of extremes rainfall indices in the south of the catchment compared to the middle and northern of part of the catchment, while temperature extremes were uniformly distributed over the catchment.

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Detecção de Mudanças Climáticas Através de Índices Pluviométricos Diários no Estado de Pernambuco (Detection of Climate Change Through Daily rainfall in the State of Pernambuco)

Revista Brasileira de Geografia Física ◽

10.26848/rbgf.v6i4.233064 ◽

2013 ◽

Vol 6 (4) ◽

pp. 713 ◽

Cited By ~ 1

Author(s):

Priscila V. dos Santos ◽

Rosaline Dos Santos ◽

Maytê D. L. Coutinho

Keyword(s):

Climate Change ◽

Equatorial Pacific ◽

The State ◽

Total Precipitation ◽

Tropical Atlantic ◽

Intensity Index ◽

Annual Total ◽

Simple Daily Intensity Index ◽

Consecutive Dry Days ◽

Sst Anomalies

O objetivo do presente trabalho é estimar e analisar índices de detecção e monitoramento de mudanças climáticas, decorrentes da precipitação diária, para o Estado de Pernambuco, verificar sua possível dependência das anomalias de temperatura da superfície do mar e examinar suas influências sobre a dinâmica da vegetação, medida pelo Índice de Vegetação por Diferenças Normalizadas (IVDN), e variabilidade do clima, estimada pelo Índice Inverso de Aridez de Budyko (IIAB) anual. Para isso utilizou-se dados de precipitação totais diários de 26 localidades, anomalias de TSM para o período de 1964 a 2006, IVDN mensais de 1982 a 2001 e estimativa de temperaturas do ar média, máxima e mínima. Observou-se um decaimento da precipitação total anual, da intensidade simples diária da precipitação, dos dias consecutivos úmidos, dos dias com chuva superior a 20mm/dia e inferior a 50mm/dia, e aumento dos dias consecutivos secos. Verificou-se que, além do total anual de precipitação, o número de dias consecutivos secos, número de dias no ano com chuvas acima de 10mm/dia e intensidade simples diária de precipitação são dependentes dos padrões de anomalias de TSM nos Oceanos Pacífico Equatorial e Atlântico Tropical. O IVDN é influenciado pela precipitação total e pelo número de dias com chuvas superiores a 10mm/dia, principalmente no Alto Sertão do Estado. O índice inverso de aridez de Budyko é dependente das configurações das anomalias de TSM dos Oceanos Pacífico Equatorial e Atlântico Tropical Norte, e exerce influência sobre o IVDN. A B S T R A C T The objectives of the present work are: to compute and to analyze climate extreme indexes for monitoring and detecting climate change, for the state of Pernambuco; to verify the possible dependence of the extreme indexes of the anomalies of the sea surface temperature and to examine the influences of the extreme indexes on the dynamics of the vegetation, measured by NDVI (Normalized Difference Vegetation Index), and climate variability, evaluated for IIAB (Aridity Inverse Index of Budyko) annual. It was used precipitation diaries data from 26 meteorological stations, anomalies of SST for the period from 1964 to 2006, monthly NDVI from 1982 to 2001 and the mean, maxima and minima air temperature. It was observed a decline of the annual total precipitation, precipitation simple daily intensity index, consecutive wet days and days with superior rains to 20mm/day and inferior to 50mm/day. And it was verified an increase of the consecutive dry days. It was verified that the annual total of precipitation, number of consecutive dry days, number of days in the year with rains above 10mm/day and precipitation simple daily intensity index are dependent of the SST anomalies patterns on the Equatorial Pacific and Tropical Atlantic Oceans. NDVI is influenced by the total precipitation and for the number of days with superior rains to 10mm/day, mainly on the Sertão of the State. Aridity inverse index of Budyko is dependent of the SST anomalies configurations on the Equatorial Pacific and Northern Tropical Atlantic Oceans, and it exercises influence on NDVI. Keywords: climate, climatic changes, semiarid, coast.

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Effect of Climate Variables on Yield of Major Crop in Samastipur District of Bihar: A time Series Analysis

Economic Affairs ◽

10.46852/0424-2513.4.2020.21 ◽

2020 ◽

Vol 65 (4) ◽

Author(s):

Meera Kumari

Keyword(s):

Climate Change ◽

Time Series ◽

Crop Yield ◽

Minimum Temperature ◽

Time Series Data ◽

Annual Rainfall ◽

Series Data ◽

Climate Variables ◽

Climatic Variable ◽

Climate Variable

Climate change influences crop yield vis-a-vis crop production to a greater extent in Bihar. Climate change and its impacts are well recognizing today and it will affect both physical and biological system. Therefore, this study has been planned to assess the effect of climate variables on yield of major crops, adaptation measures undertaken in Samastipur district of Bihar. Secondary data on yield of maize and wheat crops were collected for the period from 1999-2019 to describe the effects of climate variable namely rainfall, maximum and minimum temperature on yield of maize and wheat. Analysis of time series data on climate variables indicated that annual rainfall was positively related to yields while maximum and minimum temperature had a negative but significant impact on maize and wheat yields. It actually revealed that other factors, such as; type of soil, soil fertility and method of farming may also be responsible for crop yield. Trend in cost as well as income of farmers indicated that income and cost of cultivation has no significant relationship with climate variable. On the basis of above observation it may be concluded that level of income of farmers changed due to change in the other factors rather than change in climatic variable over the period under study as cost of cultivation increases with increased in the price of input over the period but not due to change in climatic variable.

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